Selection of the mode of delivery in a twin pregnancy is always challenging for obstetricians, although vaginal delivery is theoretically feasible for diamniotic twins if the first twin is in cephalic presentation.1 In the past 15 years, two cohort studies2 3 and a multicentre randomised trial4 concluded that when the first twin was in cephalic presentation, planned caesarean delivery did not significantly decrease or increase the risk of fetal/neonatal death or serious neonatal morbidity, compared with planned vaginal delivery. These findings suggest that vaginal delivery of twins is a safe and reasonable mode of delivery. However, attempts to deliver vaginally are not always successful, and the intrapartum risks of adverse outcomes for second twins should be carefully considered.

In a study of factors that were predictive of successful vaginal delivery, Easter et al5 found that the vaginal delivery rates of second twins in non-vertex presentation were comparable with the vaginal delivery rates of second twins in vertex presentation. Successful vaginal delivery was associated with higher parity. In the subgroup of second twins in non-vertex presentation, successful vaginal delivery was associated with the presence of more experienced birth attendants. The rates of neonatal morbidity and mortality were low in both groups, and they did not differ between groups. However, that study only included twins with gestational ages of ≥32 weeks.

In a study that examined caesarean delivery of the second twin after successful vaginal delivery of the first twin, Breathnach et al6 found that the most common indication for caesarean delivery of the second twin was malpresentation (transverse/shoulder/brow) or compound presentation. Second twins who were delivered by emergency caesarean section after vaginal delivery of the first twin had a perinatal morbidity rate of 29%, but there were only 14 such twins; thus, the sample size was insufficient for robust statistical analysis.

There is a need for additional information concerning factors predictive of successful vaginal delivery of the second twin, which will allow better case selection and avoid combined vaginal-caesarean delivery (ie, failed vaginal delivery of the second twin). To our knowledge, there have been few studies of these factors in Asian populations. Here, we examined the medical records of second twins born to mothers who had attempted vaginal delivery of twins in Hong Kong; we sought to identify factors that could affect the perinatal outcomes and predict failure of vaginal delivery in a predominantly Asian population. We also included deliveries of preterm gestations (23-32 weeks), which were not extensively investigated in previous studies.

This retrospective study focused on twin pregnancies that were delivered between 1 January 2006 and 31 December 2015 in Princess Margaret Hospital, a regional public hospital in Kowloon, Hong Kong. Inclusion criteria were vaginal delivery of the first twin at gestational viability or beyond. Exclusion criteria were miscarriage (delivery before gestational viability) or delivery of the first twin by elective or emergency caesarean section. Under Hong Kong law, 24 full weeks of gestation is generally regarded as the threshold of gestational viability. In exceptional cases, the threshold may be reduced to 23 weeks if, after full discussion with the obstetric and neonatal care teams, the parents demonstrate a strong preference for earlier initiation of active neonatal management.

Eligible cases were identified from the Obstetric Clinical Information System (OBSCIS); for each case, the mother’s demographic and clinical data were retrieved. The OBSCIS is a territory-wide electronic database that contains the prenatal, intrapartum, and postpartum information of all mothers who receive care in public hospitals in Hong Kong. Clinical information in the system is updated in a timely manner by each patient’s midwives and physicians before the patient is discharged from the hospital. Data entry integrity is continuously monitored by a dedicated information technology team within the Hospital Authority, and each obstetrics unit is asked to provide missing data promptly. Each infant’s clinical information was retrieved from the Electronic Patient Record, a comprehensive system that contains all health information (except obstetric records) of patients from birth to death and is shared by all public hospitals and out-patient clinics under the Hong Kong Hospital Authority.

The following maternal data were retrieved: age, parity, gestational age at delivery, chorionicity, and mode of delivery of the second twin. The following infant data were retrieved: birth weight, Apgar score, cord blood pH, delivery time, inter-twin delivery interval, presentation at delivery, and neonatal intensive care unit (NICU) admission status.

The primary outcome of the study was a composite adverse perinatal outcome that included any of the following: Apgar score <6 at 5 minutes after birth, cord blood pH <7, NICU admission, birth trauma, and presence of neonatal complications. For infants with a hospital stay of >28 days, complications until hospital discharge were included. The following complications were considered: respiratory morbidity, intracranial haemorrhage, hypoxic ischaemic encephalopathy, sepsis, metabolic disturbance, birth defects, and neonatal death. The secondary outcome was mode of delivery. Gestational age was established by the patient’s last menstrual period and verified by ultrasound in the first or early second trimester. Chorionicity was established by prenatal ultrasound and confirmed by placental histology after delivery. The likelihood of vaginal delivery may be adversely impacted by considerably larger second twin size, compared with the first twin. Breathnach et al6 found that the rate of caesarean section was higher if the first twin had ≥20% lower weight than the second twin. Therefore, clinically significant weight discordance was regarded as ≥20% in the present study, where weight discordance was defined as the weight difference between the second and first twin divided by the weight of first twin.

Vaginal deliveries of twins were managed in accordance with our labour ward protocol, which does not regard estimated fetal weight discordance as a contra-indication to vaginal delivery. All deliveries were attended by two physicians (as described below) and assisted by ≥2 midwives. Specialist supervision was recommended. In this context, a specialist is an obstetrician who has completed ≥6 years of postgraduate residency training and received accreditation as a Fellow of the Hong Kong College of Obstetricians and Gynaecologists (FHKCOG). Membership in the Royal College of Obstetricians and Gynaecologists (MRCOG) is a prerequisite for FHKCOG accreditation. When a specialist was unavailable (particularly at night), deliveries were conducted or supervised by an MRCOG-qualified physician. Paediatricians were present for all deliveries of second twins. Prenatal steroids (either betamethasone or dexamethasone depending on pharmacy availability and initial treatment at the referral unit) were administered in cases of delivery before 34 weeks of gestation. If necessary, oral nifedipine was used as a first-line tocolytic. Intravenous salbutamol was used as a second-line tocolytic until 2012; since 2013, atosiban has been used as a second-line tocolytic.

Statistical analysis was carried out using SPSS software (Windows version 17.0; SPSS Inc., Chicago [IL], United States). Categorical data were analysed by the Chi squared test or Fisher’s exact test, as appropriate. Among the factors that showed statistical significance in univariate analysis, binary logistic regression was used to identify factors that were independently predictive of vaginal delivery and adverse perinatal outcomes. P values <0.05 were considered statistically significant.

During the 10-year study period, 47 595 deliveries were performed in Princess Margaret Hospital; 718 twin pairs were delivered. Among these twin pairs, 182 and 305 were delivered by elective and emergency caesarean section, respectively; they were excluded from the study. In the remaining 231 cases, the mothers delivered the first twin vaginally and intended to deliver the second twin vaginally. The second twins in this group of patients were included for analysis.

Table 1 shows the demographic and obstetric characteristics of the 231 cases, stratified according to the mode of delivery of the second twin. Emergency caesarean delivery was required in 10 cases (4.3%). Among the three second twins in vertex presentation, two were delivered by caesarean section because of second twin retention; the remaining twin was delivered by caesarean section because of fetal distress. Among the seven second twins in non-vertex presentation, the indications for caesarean delivery were second twin retention (two cases), fetal distress (four cases), and transverse lie (one case). Of the factors shown in Table 1, only an inter-twin delivery interval of >30 minutes and non-vertex presentation of the second twin at delivery were associated with the mode of delivery of the second twin. Logistic regression analysis showed that an inter-twin delivery interval of >30 minutes (odds ratio [OR]=26.952, 95% confidence interval [CI]=5.924-122.619) and non-vertex presentation of the second twin at delivery (OR=5.003, 95% CI=1.101-22.743) were independently associated with caesarean delivery of the second twin.

In subgroup analyses, we examined the relationships of the demographic and obstetric factors in Table 1 to determine their relationships with the mode of delivery for second twins in breech presentation. Univariate analysis revealed that only an inter-twin delivery interval >30 minutes and the presence of less experienced birth attendants were significantly associated with the mode of delivery. Logistic regression showed that an inter-twin delivery interval >30 minutes (OR=36.492, 95% CI=3.035-438.712) and the presence of less experienced birth attendants (OR=10.252, 95% CI=1.001-104.956) were independently associated with caesarean delivery of second twins in breech presentation.

Perinatal outcomes of second twins are shown in Table 2. Univariate analysis revealed that the composite adverse perinatal outcome was only associated with gestational age <32 weeks (P<0.001; OR=12.1, 95% CI=2.738-53.481) [Table 3]. Similarly, gestational age <32 weeks was the only factor significantly associated with NICU admission (P<0.001; OR=6.420, 95% CI=2.073-19.878) [Table 4].

Among the 47 cases with delivery before 34 weeks of gestation, 27 completed steroid treatment before delivery. In 17 cases, delivery occurred before the completion of steroid treatment because of rapid labour that did not respond to tocolytics. Steroid treatment was not administered in three cases; two of these cases involved delivery before 24 weeks of gestation, which is the threshold for beginning steroid treatment in our hospital. In the third case, the mother was admitted in advanced labour. Completion or non-completion of steroid treatment was not associated with the composite adverse perinatal outcome (25/27 vs 18/20, P=0.753).

To our knowledge, this is the first study in Hong Kong concerning the short-term composite adverse perinatal outcomes of second twins in cases where vaginal delivery was attempted. Our approach enabled simultaneous consideration of multiple outcome parameters. The inclusion of additional clinical information until hospital discharge for infants with prolonged hospital stay (>28 days) allowed a more comprehensive assessment of outcomes. Notably, cases of gestation <32 weeks were included; there are minimal published data for this group of infants because they have been excluded from many large trials. Additionally, we examined the effects of birth attendant experience and birth timing.

Prior to this study, there were two analyses of twin deliveries in a predominantly Asia population, both from Hong Kong. The first analysis mainly focused on patient preference regarding the mode of delivery; it also included few vaginal deliveries (35 cases).7 The second analysis, reported by Tang et al,8 was performed in the same obstetric unit as the first analysis; it reviewed neonatal and maternal outcomes after an increase in the rate of vaginal delivery of twins. The authors did not find any significant differences in neonatal morbidities between the vaginal delivery group and the elective caesarean delivery group. However, there were fewer successful vaginal deliveries of ≥1 twin (72 cases) and the effect of inter-twin delivery interval was not evaluated.

In this study, the main factor that affected the composite adverse perinatal outcome was gestational age; complications were mainly related to prematurity. Similarly, NICU admission was mainly related to complications of prematurity, rather than complications of vaginal delivery. There were no statistically significant differences in adverse perinatal outcomes, even for twins who were not delivered in cephalic presentation. Thus, non-cephalic presentation alone should not be considered sufficient to recommend caesarean delivery for twin pregnancies.

A study in Hong Kong by Leung et al,9 published in 2002, showed that all umbilical cord blood gas parameters in the second twin were significantly associated with the inter-twin delivery interval. The risk of severe fetal acidosis was 27% if the second twin was not delivered ≤30 minutes after delivery of the first twin, but the outcomes of second twins were not analysed. In our study, an inter-twin delivery interval of >30 minutes alone did not increase the risk of short-term adverse perinatal outcomes, although it increased the risk of caesarean delivery of the second twin. Schneuber et al10 also reported similar findings in their series, which suggested that an increased inter-twin delivery interval was not associated with adverse fetal outcomes. If monitoring of the second twin is possible and the findings are reassuring, obstetricians may thus consider a conservative approach, even 30 minutes after delivery of the first twin; however, emergency caesarean delivery should be readily available if necessary.

Our study also showed no increase in adverse perinatal outcomes for infants who were delivered after midnight. In general, delivery of twins in daytime or early evening is preferable because additional staff are present, and those staff are often more experienced. Therefore, when there are no indications for urgent delivery, the usual practice in our unit is to begin labour induction for twin pregnancies in the early morning. Deliveries after midnight usually follow spontaneous labour and are thus unplanned. However, such deliveries are supervised by the most senior on-call obstetrician (MRCOG-qualified or FHKCOG-accredited) during the intrapartum period.

The vaginal delivery of second twins in non-cephalic presentation is challenging. Our findings showed a higher rate of caesarean delivery for second twins in non-cephalic presentation (9.0% vs 2.0%, P=0.03). In a large cohort study using the World Health Organization Global Survey dataset, Vogel et al11 showed that caesarean rates were 6.2% and 0.9% for second twins in non-cephalic and cephalic presentation, respectively. Another study by Kong et al12 revealed the caesarean delivery rates of second twins were 4.7% in cephalic presentation, 11.1% in breech presentation, and up to 90% in transverse lie. In both of these studies, analyses were conducted based on the presentation of the second twin at the onset of labour; their findings were consistent with our results. The presence of more experienced obstetricians who are able to perform artful manoeuvres (ie, internal podalic version and external cephalic version) can increase the likelihood of successful vaginal delivery of the second twin. Regular training and rehearsal of the vaginal delivery of twins is important for obstetricians to maintain their skills.

In our study, caesarean delivery of the second twin was necessary in 4.3% of cases, which is similar to or lower than the proportions in other series.6 8 13 14 Regardless of whether the second twin was delivered by caesarean section, there were no significant increases in short-term adverse perinatal outcomes; however, this mode of delivery is less favourable for mothers. These results are contrary to the findings by Breathnach et al,6 in which the perinatal morbidity rate was 29% among second twins delivered by emergency caesarean section after vaginal delivery of the first twin. A systematic review by Rossi et al15 also showed a higher rate of morbidity in second twins after caesarean delivery (19.8% vs 9.5% after vaginal delivery). Thus, combined vaginal-caesarean delivery of twins should be avoided whenever possible.

In the present study, the presence of a larger second twin (≥20% weight discordance) did not significantly increase the risk of caesarean delivery. The second twin was larger in only 12 cases (5.2%). We suspect that many other cases with a larger second twin were scheduled for caesarean delivery without a trial of vaginal delivery. Decisions concerning the mode of delivery are affected by the estimated fetal weight, fetal presentation, and whether the mother has a history of successful vaginal delivery. Various factors must be carefully considered in each case.

There were some limitations in this study. First, the retrospective design may have resulted in missing data or incomplete data collection. This is not a large problem because clinical information in the OBSCIS and the Electronic Patient Record is required to be updated when each patient is discharged from the hospital; therefore, these systems are reliable sources of patient data. Nevertheless, some information was not retrievable, such as the presentation of the second twin at the time of first twin delivery and whether birth attendant manoeuvres were necessary to deliver the second twin. Second, the non-randomised analysis might have led to selection bias concerning the mode of delivery, such that low-risk cases were over-represented in the study. The number of second twins delivered by caesarean section was small; a larger trial is needed to more comprehensively evaluate such cases.

Among second twins born to mothers who had attempted vaginal delivery, we found that adverse perinatal outcomes were mainly related to prematurity, rather than actual mode of delivery. For all second twins, an inter-twin delivery interval <30 minutes was associated with a higher rate of vaginal delivery; for second twins in breech presentation, the presence of more experienced birth attendants was also associated with a higher rate of vaginal delivery. Overall, the risk of caesarean delivery of the second twin was low. Our findings in a predominantly Asian population in Hong Kong support vaginal delivery of the second twin when the first twin is delivered in cephalic presentation.

This study was planned and designed by both authors. Both authors also jointly performed the data analysis. TK Lo provided leadership and supervision, while SL Mok wrote and managed the manuscript. Both authors had full access to the data, contributed to the study, approved the final version for publication, and take responsibility for its accuracy and integrity.

Both authors have disclosed no conflicts of interest.

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

This study was approved by the Kowloon West Cluster Research Ethics Committee (Ref KW/EX-17-154 (118-02)). The requirement for patient informed consent was waived because this was a retrospective review of medical records that did not involve patient participation.

1. Monson M, Silver RM. Multifetal gestation: mode of delivery. Clin Obstet Gynecol 2015;58:690-702. Crossref

2. Peaceman AM, Kuo L, Feinglass J. Infant morbidity and mortality associated with vaginal delivery in twin gestations. Am J Obstet Gynecol 2009;200:462.e1-6. Crossref

3. Fox NS, Silverstein M, Bender S, Klauser CK, Saltzman DH, Rebarber A. Active second-stage management in twin pregnancies undergoing planned vaginal delivery in a U.S. population. Obstet Gynecol 2010;115:229-33. Crossref

4. Barrett JF, Hannah ME, Hutton EK, et al. A randomized trial of planned cesarean or vaginal delivery for twin pregnancy. N Engl J Med 2013;369:1295-305.Crossref

5. Easter SR, Lieberman E, Carusi D. Fetal presentation and successful twin vaginal delivery. Am J Obstet Gynecol 2016;214:116.e1-10.Crossref

6. Breathnach FM, McAuliffe FM, Geary M, et al. Prediction of safe and successful vaginal twin birth. Am J Obsetet Gynecol 2011;205:237.e1-7. Crossref

7. Liu AL, Yung WK, Yeung HN, et al. Factors influencing the mode of delivery and associated pregnancy outcomes for twins: a retrospective cohort study in a public hospital. Hong Kong Med J 2012:18:99-107.

8. Tang HT, Liu AL, Chan SY, et al. Twin pregnancy outcomes after increasing the rate of vagina twin delivery: retrospective cohort study in a Hong Kong regional obstetrics unit. J Maternal Fetal Neonatal Med 2016;29:1094-100. Crossref

9. Leung TY, Tam WH, Leung TN, Lok IH, Lau TK. Effect of twin-to-twin delivery interval on umbilical cord blood gas in the second twins. BJOG 2002;109:63-7. Crossref

10. Schneuber S, Magnet E, Haas J, et al. Twin-to-twin delivery time: neonatal outcome of second twin. Twin Res Hum Genet 2011;14:573-9. Crossref

11. Vogel JP, Holloway E, Cuesta C, Carroli G, Souza JP, Barrett J. Outcomes of non-vertex second twins, following vertex vaginal delivery of first twin: a secondary analysis of the WHO Global Survey on maternal and perinatal health. BMC Pregnancy Childbirth 2014;14:55. Crossref

12. Kong CW, To WW. The predicting factors and outcomes of caesarean section of the second twin. J Obstet Gynaecol 2017;37:709-13. Crossref

13. Yang Q, Wen SW, Chen Y, Krewski D, Fung KF, Walker M. Neonatal death and morbidity in vertex-nonvertex second twins according to mode of deliverya and birth weight. Am J Obstet Gynecol 2005;192:840-7. Crossref

14. Persad VL, Baskett TF, O’Connell CM, Scott HM. Combined vaginal-cesarean delivery of twin pregnancies. Obstet Gynecol 2001;98:1032-7. Crossref

15. Rossi AC, Mullin PM, Chmait RH. Neonatal outcomes of twins according to birth order, presentation and mode of delivery: a systematic review and meta-analysis. BJOG 2011;118:523-32. Crossref

Heart failure is a major public health problem that has been shown to increase with age, such that incidence rates rapidly increase after 80 years of age.1 Among older patients with heart failure, 18% to 54% show signs of frailty, a state of reduced physical and cognitive function that results in weakness.2 There are some overlapping symptoms between heart failure and frailty; they interact to accelerate the vicious cycle of frailty.3 One study showed that frail patients with cardiovascular disease had a 7-year survival rate of 12%, which was much lower than the survival rate in non-frail patients with cardiovascular disease (43%).4 Moreover, frailty among patients with heart failure has been associated with poor prognosis5 and reduced cardiac output capacity.6 Pre-frailty is the first step towards frailty; approximately 34.6% to 46.1% of individuals with pre-frailty progress to frailty in Japan.7 Therefore, improvements in frailty and pre-frailty are important considerations in the care of older patients with heart failure.

Age,8 nutrition,9 walking speed,9 heart function,8 and grip strength10 have been shown to influence frailty improvement among older patients with heart failure. However, the predictive accuracies of such factors remain unknown. Moreover, a combination of the predictors has been suggested to increase their predictive accuracy,11 although this hypothesis has not yet been tested. Additionally, nutrition,12 physical function,12 and quality of life12 have been reported to influence pre-frailty improvement among community-dwelling older individuals. To our knowledge, there are no reports of factors that influence pre-frailty improvement among patients with heart failure.

In this study, we used the classification and regression tree (CART) method,13 which facilitates the establishment of clinical prediction models that can identify the best combinations of medical signs, symptoms, and other findings to predict prognoses or treatment outcomes.13 Several clinical prediction models have been developed using the CART method to predict mortality in patients with heart failure.14 15 However, no clinical prediction models have been established to predict the prognosis of patients with heart failure complicated by pre-frailty and frailty.

Here, we aimed to use the CART method to develop models that could predict the prognosis of older patients with heart failure complicated by pre-frailty and frailty, then confirm the predictive accuracies of those models.

This pilot prospective cohort study followed the STROBE reporting guidelines. All included patients provided written informed consent to participate in the study. Identifying information was not collected to protect each patient’s privacy. This study was performed in accordance with the Declaration of Helsinki.

Recruitment, follow-up, and data collection were performed at two acute hospitals (Saiseikai Kure Hospital, Kure, Japan; Kure Kyosai Hospital, Kure, Japan) between July 2018 and December 2019. Potential participants were recruited by therapists at the rehabilitation department.

This study included patients who met the following inclusion criteria: age ≥65 years; hospitalisation for the treatment of heart failure; and presence of pre-frailty or frailty. The exclusion criteria were complications during hospitalisation and/or severe dementia (defined as a revised Hasegawa’s Dementia Scale score ≤9).

Cardiac rehabilitation was performed by physical or occupational therapists to improve physical condition, restore walking ability during hospitalisation, and expand the activities of daily living. Rehabilitation programmes were established by physical or occupational therapists in accordance with physicians’ orders. Initially, aerobic exercises and resistance training programmes were provided according to each patient’s physical condition. Exercise intensity was determined using multiple indices, including target heart rate (convenient method: resting heart rate + 20 bpm), talk test, and Borg scale (11-13) for the chest and lower limbs. The type of exercise was modified (ie, duration extended and load increased) with consideration of each patient’s symptoms and haemodynamics. If necessary, functional exercises (eg, neuromuscular facilitation, joint range of motion, and muscle strengthening exercises), exercises for activities of daily living, and psychological support were implemented for patients and their families. Exercises for activities of daily living were customised according to the functions that each patient needed for discharge. Overall, the duration and frequency of intervention were 30 minutes to 1 hour per day and 5 days per week, respectively.

Variables included demographic and clinical characteristics, frailty assessment results, and physical function. Demographic characteristics included age, sex, body mass index, living arrangement (with family members or alone), New York Heart Association class, medical history (eg, heart failure, coronary artery disease, valvular disease, hypertension, diabetes mellitus, dyslipidaemia, atrial fibrillation, chronic renal dysfunction, and/or stroke), cognitive function assessed using the revised Hasegawa’s Dementia Scale, Life-Space Assessment score, interval from admission to initiation of cardiac rehabilitation, interval from admission to rehabilitation room entry, and length of hospital stay. Hasegawa’s Dementia Scale scores of 21-30, 15-20, 10-14, and ≤9 were regarded as normal, suspected dementia, mild to moderate dementia, and severe dementia, respectively.16 The Life-Space Assessment developed by Baker et al17 was used to evaluate life-space mobility. Up to 120 points were assigned based on the degree of independence in each life-space level during the month prior to the assessment; higher scores were considered indicative of broader life-space and/or greater independence.

Clinical characteristics included blood data, cardiac function, and pharmacotherapy. Blood data included the Geriatric Nutritional Risk Index, brain natriuretic peptide level, estimated glomerular filtration rate (eGFR), and haemoglobin (Hb) level. Cardiac function was evaluated using left ventricular ejection fraction (LVEF), as determined by echocardiography. Pharmacotherapy data included whether patients were receiving dopamine, dobutamine, noradrenaline, phosphodiesterase III inhibitor, or diuretics.

Frailty was assessed using the following five conditions based on the Cardiovascular Health Study (CHS) Index: slow gait speed, weakness, exhaustion, low activity, and weight loss.18 Slow gait speed was defined as <1.0 m/s. Weakness was assessed using maximum grip strength according to sex-specific cut-offs (<26 and <18 kg for men and women, respectively). Exhaustion was assessed using the question “During the past 2 weeks, have you felt tired without a specific reason?” A positive response to this question (ie, “yes”) was considered indicative of exhaustion. Physical activity was evaluated using the question “Do you engage in low levels of physical activity to improve your health?” A negative response to this question (ie, “no”) was considered indicative of a low activity level. Weight loss was assessed using the question “Have you lost 2 kg or more in the past 6 months?” A positive answer to this question was considered indicative of weight loss. There are various criteria for assessing frailty; Fried’s frailty phenotype model18 and the accumulated deficit model established by Mitnitski et al19 are well known. The CHS criteria and the Frailty Index were developed based on the above frailty phenotype model and accumulated deficit model, respectively. Furthermore, a Japanese version of the CHS criteria (J-CHS) has been established,20 and its validity has been confirmed.21 Thus, we selected the J-CHS to assess frailty. Patients with none of the above conditions were considered non-frail (robust), patients with one to two conditions were considered pre-frail, and patients with three conditions or more were considered frail.22

Physical function was assessed using the Short Physical Performance Battery score, 10-metre walk time, single-leg standing time, and hand grip strength. Patients performed the Short Physical Performance Battery test in the following sequence, in accordance with the National Institute on Aging protocol: standing balance tests, gait test (4 m), and chair stand test (five repetitions). The sum of the three test components comprised the final Short Physical Performance Battery score, which ranged from 0 to 12; a score of 12 indicated optimal lower extremity function.23 24 Moreover, 10-m walk time was measured at a comfortable walking speed to assess walking ability. The 10-m walk test has demonstrated high validity and reliability in multiple populations, including healthy older individuals and patients with stroke, neurological disorders, or orthopaedic dysfunction.25 26 Measurements were performed twice at an interval of 30 s; the smaller value was used to indicate walking ability. Standing balance was evaluated by measuring single-leg standing time, which reflects the ability to maintain the body’s centre of gravity within its base of support. A stopwatch was used to measure the duration that a patient could stand on one leg with their eyes open and hands on their waist, without any assistance or falling. A second trial was performed if the result of the first trial was <60 s.27 Hand grip strength (kg) was measured using a digital hand grip strength dynamometer (TKK-5101; Takei Scientific Instruments, Tokyo, Japan or 12B3X00030; Tsutsumi Works, Chiba, Japan). Accordingly, patients were asked to squeeze the dynamometer with maximum effort during two trials for each hand. The maximum value (rounded to the nearest 0.1 kg) for either the left or right hand was used for subsequent analyses.28

Demographic and clinical characteristics were assessed upon admission or each time, whereas cognitive function and Life-Space Assessment were assessed during the first physical therapy session. Frailty and physical function were assessed upon initial entry into the rehabilitation room and at discharge. The amount of change in physical function (discharge−initial) was calculated.

To reduce selection bias, outcomes were selected based on the methods of previous studies.16 17 18 19 20 21 22 23 24 25 26 27 28 To reduce measurement bias, the first author (T Umehara) was not involved in participant enrolment or data collection. Patients received explanations about the purpose of the study but did not receive information concerning the hypothesis tested.

Classification and regression tree analysis29 was used to predict the primary outcomes. Patients with pre-frailty at admission were categorised into an improved group and a non-improved group: patients who were non-frail at discharge were assigned to the improved group, whereas patients who were pre-frail or frail were assigned to the non-improved group. Similarly, patients with frailty at admission were categorised into an improved group and a non-improved group: patients who were non-frail or pre-frail at discharge were assigned to the improved group, whereas patients who were frail were assigned to the non-improved group. Binary trees were used to recursively split predictor variables based on answers to yes/no questions for each variable. All statistical distributions were considered without limitation to linear relationships between outcome variables and predictor variables. These algorithms have been used to develop prediction models in various fields.30 31 32 The CART method with the Gini index was used for the following models: A, which predicted the presence or absence of pre-frailty improvement during hospitalisation; and B, which predicted the presence or absence of frailty improvement during hospitalisation. Pre-frailty or frailty improvement was the dependent variable, whereas demographic and clinical characteristics, pharmacotherapy, and amount of change in physical function were the independent variables. The accuracies of the CART models were evaluated using the area under the receiver operating characteristic curve (AUROC). The method proposed by Delong et al33 was used to identify optimal cut-off points. Subsequently, the sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were calculated. To assess model validity, cross-validation was performed as follows: the sample was divided into 10 subgroups and the model developed from nine subgroups was used to test the 10th subgroup; this was repeated for all 10 combinations and the rates of misclassification were averaged. Model validity was considered high when the misclassification rates were similar before and after cross-validation. The accuracies of the CART models were evaluated using the AUROC developed from each method. The maximum Youden index (sensitivity + specificity − 1) was defined as the optimal cut-off point. All statistical analyses were performed using SPSS (Windows version 23.0; IBM Corp, Armonk [NY], United States) and the significance level was set at 5%.

Sample size calculations were conducted using MedCalc statistical software, version 19.2 (MedCalc Software bvba, Ostend, Belgium). Before plotting an AUROC, the following values were established: statistical significance (P<0.05), alpha (0.05), statistical power (0.80), and the AUROC value to be included in the null hypothesis (0.5). The AUROC could distinguish between non-predictive (AUROC<0.5), less predictive (0.5<AUROC^lt;0.7), moderately predictive (0.7<AUROC<0.9), highly predictive (0.9<AUROC<1), and perfectly predictive (AUROC=1).34 In this study, an AUROC value of 0.7 was considered indicative of superior statistical discrimination. The frailty improvement ratio (ie, positive/negative ratio) considerably varied among previous studies.35 36 37 Therefore, the positive/negative ratio used here was set at 1:1-5. Moreover, a large sample size was needed to allow for the possibility of stratified analysis. Thus, 62 to 120 patients with frailty were required: 20-31 and 31-100 in the improved and non-improved groups, respectively.

Figure 1 shows the flowchart of patient recruitment. Among the 30 patients with pre-frailty, two with severe dementia were excluded; 28 patients were included in the analysis. Among the 161 patients with frailty, five with severe dementia were excluded; 156 patients were included in the analysis. The patient characteristics are summarised in Tables 1 and 2 (patients with pre-frailty and patients with frailty, respectively).

Figure 2 shows CART model A, which predicted the presence or absence of pre-frailty improvement during hospitalisation. Among the 28 patients with pre-frailty, seven experienced improvements. Single-leg standing time at admission was identified as the best single discriminator for pre-frailty improvement (≤4.4 or >4.4 s). Among patients with single-leg standing time of >4.4 s at admission, the next predictor was LVEF (≤36.8% or >36.8%). Our CART analysis resulted in the establishment of three terminal nodes. The terminal node with the highest probability of a favourable outcome (pre-frailty improvement) was defined as rank 1, whereas the terminal node with the lowest probability of a favourable outcome was defined as rank 3. Based on the AUROC (95% confidence interval [CI]), this CART model had an accuracy of 0.96 (95% CI=0.89-1.00), with an optimal cut-off point of rank 1 (sensitivity: 85.7%, specificity: 95.2%, PLR: 18.0, and NLR: 0.15). The misclassification rates before and after cross-validation were 7.1% and 28.6%, respectively.

Figure 3 shows CART model B, which predicted the presence or absence of frailty improvement during hospitalisation. Among the 156 patients with frailty, 57 experienced improvements. Hand grip strength at admission was identified as the best single discriminator for frailty improvement (≤16.8 or >16.8 kg). Among patients with hand grip strength of >16.8 kg at admission, the next predictor was eGFR (≤27.0 or >27.0 mL/min/1.73 m²). Among patients with hand grip strength of ≤16.8 kg at admission, the next predictor was eGFR (≤83.5 or >83.5 mL/min/1.73 m²). Among patients with eGFR ≤83.5 mL/min/1.73 m², the next predictor was Hb level (≤14.3 or >14.3 g/dL). Among patients with Hb level ≤14.3 g/dL, the next predictor was change in single-leg standing time (≤4.9 or >4.9 s). Our CART analysis resulted in the establishment of six terminal nodes. The terminal node with the highest probability of a favourable outcome (frailty improvement) was defined as rank 1, whereas the terminal node with the lowest probability of a favourable outcome was defined as rank 6. Based on the AUROC (95% CI), this CART model had an accuracy of 0.84 (95% CI=0.78-0.91), with an optimal cut-off point of rank 4 (sensitivity: 70.1%, specificity: 86.9%, PLR: 5.3, and NLR: 0.3). The misclassification rates before and after cross-validation were 19.2% and 35.3%, respectively.

Model A predicted pre-frailty improvement with high accuracy; it identified single-leg standing time at admission as the best predictor, followed by LVEF. Notably, changes in physical function during hospitalisation were not identified as predictors. These results suggest that conditions at admission strongly influence pre-frailty improvement during hospitalisation; moreover, improvement can be expected among patients with good physical function (single-leg standing time >4.4 s) and cardiac function (LVEF >36.8%) at admission. To our knowledge, no study has examined the factors that influence pre-frailty improvement among patients with heart failure. However, one study found that physical function, nutrition, and quality of life were factors that influenced pre-frailty improvement among community-dwelling older individuals.12 The above findings suggest that although physical function is a common factor that influences pre-frailty improvement among older patients with heart failure and community-dwelling older individuals, cardiac function specifically influences pre-frailty improvement among patients with heart failure.

Model B predicted frailty improvement with moderate accuracy; it identified hand grip strength at admission as the best predictor, followed by eGFR, Hb level, and change in single-leg standing time during hospitalisation. Thus, frailty improvement can be expected among patients with good hand grip strength and/or renal function at admission. However, the cut-off values for eGFR, an index of renal function, considerably differed between patients with good (>16.8 kg) and poor (≤16.8 kg) hand grip strength (27 and 83.5 mL/min/1.73 m², respectively). A previous study also showed that older patients with heart failure who had higher hand grip strength were more likely to experience frailty improvement.10 Although no association has been identified between renal function and frailty, renal function is known to influence improvements in exercise capacity among patients with heart failure.38 Moreover, our results showed that, despite the presence of poor physical and renal function at admission, patients with a high Hb level (>14.3 g/dL) were likely to improve from frailty. Although there is no published literature concerning an association between Hb level and frailty, a low Hb level has been shown to cause fatigability,39 40 which is one of the criteria for assessing frailty using the CHS. Furthermore, the Hb level reportedly influences improvements in exercise capacity among patients with heart failure.38

Despite poor hand grip strength, weak renal function, and a low Hb level at admission, frailty improvement was observed in most patients whose single-leg standing time during hospitalisation was >4.9 s. In previous studies that sought to predict frailty improvement among older patients with heart failure, investigators mostly focused on conditions at admission without considering changes during hospitalisation.41 The present results indicate that, despite the presence of poor conditions at admission, patients can recover from frailty by improving physical function during hospitalisation; therefore, rehabilitation is essential during hospitalisation. Resistance training is known to improve single-leg standing time among older individuals.42 Thus, we recommend cardiac rehabilitation, including resistance training, to improve frailty among older patients with heart failure.

The clinical implications of our findings are as follows. Thus far, no algorithms have been established concerning pre-frailty and frailty improvements in older patients with heart failure. Using the CART method, we developed models that could predict the prognosis of older patients with heart failure complicated by pre-frailty and frailty. These models will provide useful information for patients and caregivers. Many of the factors extracted in this study were only assessed at the time of initial rehabilitation. Thus, the prognoses of patients with pre-frailty and patients with frailty can be inferred (to some extent) at the time of initial rehabilitation. Additionally, an increase in single-leg standing time during hospitalisation was associated with frailty improvement. For older patients with heart failure who show signs of frailty, interventions to increase single-leg standing time may help to improve frailty. The PLR and NLR were used to assess the diagnostic performances of the CART models; these parameters revealed that both model A (pre-frailty) and model B (frailty) had good performance. However, our data should be interpreted cautiously because of the small number of patients with pre-frailty.

There were several notable weaknesses and limitations in this study. First, the sample size was limited; the numbers of patients with pre-frailty and frailty were 28 and 156, respectively. Therefore, this study should be regarded as a pilot prospective cohort study. Despite the moderate to high accuracies of models A and B, more large-scale studies are needed to enhance the generalisability of our results. Second, three aspects of frailty exist, namely physical, social, and mental frailty; mental frailty was not considered in this study. A previous study reported that patients with multifaceted frailty, including physical, mental, and social frailty, had worse prognoses compared with patients who had physical frailty alone.5 Therefore, additional studies are needed to develop models that predict improvements in multifaceted frailty, including mental frailty. Third, interventions were customised for each patient; they were not uniform. However, physical therapists in both study hospitals received 2 weeks of training in cardiac rehabilitation, and the methods of cardiac rehabilitation were standardised as much as possible. Fourth, we used the J-CHS to measure frailty; the use of this tool to assess patients with heart failure is potentially controversial. The J-CHS was developed for older adults and has been used in multiple studies.7 21 Additionally, the reliability and validity of this tool have been confirmed.21 We thus consider this use of the J-CHS to be appropriate. Fifth, this study was performed in an unblinded manner, and we could not completely rule out the potential for bias. However, to reduce the measurement bias, the first author (T Umehara) was not involved in participant enrolment or data collection. Sixth, a selection bias might have been present because patients were only recruited at two hospitals in Japan. Caution is needed when generalising our results, particularly to patients in other countries.

By using the CART method, we developed moderately to highly accurate prediction models for pre-frailty and frailty improvement among older patients with heart failure. Model A, which predicted pre-frailty improvement, showed that patients with good single-leg standing time and cardiac function at admission are likely to experience pre-frailty improvement. Furthermore, Model B, which predicted frailty improvement, showed that patients with good hand grip strength, excellent renal function, and/or a high Hb level at admission are likely to experience frailty improvement. Notably, despite the presence of poor conditions at admission, frailty improvement may occur in patients who show improvement in single-leg standing time during hospitalisation. Overall, our results suggest that cardiac rehabilitation to prolong single-leg standing time is necessary to improve frailty, particularly when conditions at admission are poor.

Concept or design: All authors.
Acquisition of data: T Umehara and N Katayama.
Analysis or interpretation of data: T Umehara, M Tsunematsu, M Kakehashi.
Drafting of the manuscript: T Umehara, A Kaneguchi and Y Iwamoto.
Critical revision of the manuscript for important intellectual content: T Umehara, A Kaneguchi, Y Iwamoto.

All authors had full access to the data, contributed to the study, approved the final version for publication, and take responsibility for its accuracy and integrity.

All authors have disclosed no conflicts of interest.

We thank Y Yamamoto, M Ota, Y Nakashima, W Kawakami, and M Iwanaga (Kure Kyosai Hospital, Kure, Japan), as well as S Nagao, Y Kawabata, and D Tomiyama (Saiseikai Kure Hospital, Kure, Japan) for their support in data collection.

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

The study was approved by the Ethics Committees of Saiseikai Kure Hospital (Ref 127) and Kure Kyosai Hospital (Ref 31-17). Patients provided written informed consent to participate.

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18. Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56:146-56. Crossref

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23. Bernabeu-Mora R, Medina-Mirapeix F, Llamazares-Herrán E, García-Guillamón G, Giménez-Giménez LM, Sánchez-Nieto JM. The Short Physical Performance Battery is a discriminative tool for identifying patients with COPD at risk of disability. Int J Chron Obstruct Pulmon Dis 2015;10:2619-26. Crossref

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For rural residents, who account for approximately 41% of China’s population, primary healthcare is the main source of medical care.1 To meet their healthcare needs, China promoted a tiered medical system in 2015 to encourage people to fully utilise primary healthcare.2 3 Nevertheless, while the government invests various resources, primary healthcare in rural areas remains underused.4 5 6 From 2015 to 2018, the total number of out-patient visits in rural primary healthcare institutions decreased from 2.90 billion to 2.70 billion, while the number of hospital visits increased from 3.10 billion to 3.60 billion.7

Disparity exists in the utilisation of primary healthcare across different regions of China. Compared with rural residents in eastern China, the utilisation of primary healthcare among those in western China is relatively low.8 9 The lack of medical resources and sparseness of the land in western China contributes to the inconvenience of accessing primary healthcare among rural residents.10 11 12 In addition to the difference between eastern and western China, differences in the utilisation of primary healthcare exists among the provinces in western China.11 Although many studies have reported on the utilisation of primary healthcare in Southwest China, most have focused on the perspective of rural residents while neglecting the importance of providers, who play important roles in primary healthcare.3 4 Therefore, research concerning village healthcare providers in Southwest China could be conducive to understanding the utilisation of primary healthcare.

Southwest China is home to more ethnic minority village healthcare providers than other areas in China.11 To investigate village healthcare providers in Southwest China, the ethnicity of providers, which may be linked to the utilisation of healthcare, is a factor that cannot be ignored. Previous studies have illustrated that ethnic minority providers are more likely to attract patients from the same ethnicity, and this finding has been attributed to the patients’ preference instead of the capability of minority providers.13 14 Existing studies were mainly conducted outside China or were related to providers who performed traditional Chinese medicine.13 14 15 Therefore, knowledge regarding whether differences exist in the utilisation of primary healthcare among Chinese ethnic minority providers and Han Chinese majority providers is limited.

Clinical competence may influence the utilisation of healthcare and serves as a practical way to measure a doctor’s working performance and quality.16 17 Some studies in China have shown that the ethnicity of medical students might be related to their future clinical competence.18 19 20 21 22 Studies conducted in Southwest China confirmed the underdeveloped clinical competence of village providers, but most studies failed to distinguish the ethnicity of the healthcare providers.23 24 25 26 Whether ethnic minority healthcare providers in rural areas of China have underdeveloped clinical competence remains unclear.

Considering the above, the purpose of the present study was to investigate the utilisation of primary healthcare in western China. In particular, the aims were to clarify whether the ethnicity of healthcare providers affects utilisation of primary healthcare; whether there are differences in clinical competence among different ethnic groups; and whether clinical competence of healthcare providers affects utilisation of primary healthcare.

This study was a cross-sectional survey conducted in three prefectures (ie, prefecture-level cities) in Yunnan Province, an economically developing area in Southwest China. In 2017, the per capita gross domestic product in Yunnan Province was US$5068, which is lower than the national average (US$8777).27 The total population in Yunnan Province was 47.71 million, and the proportion of the rural population in Yunnan Province was 53.31%, which is much higher than the overall proportion of rural population in China (41.48%).27 The three prefectures included in our study have a total rural population of 6.50 million, accounting for 20.00% of the total rural population in Yunnan Province.

To investigate the utilisation of primary healthcare in rural China, we conducted a cross-sectional study in 330 village clinics (VCs), representing the first tiers of China’s three-tiered rural health system.4 In summary, we selected a random sample of 330 healthcare providers from three prefectures in three steps (Fig). First, we selected 10 counties (in three prefectures) at random, after excluding three urban counties and 13 counties with a minority population greater than 20%. Second, we used probability proportional to size sampling to randomly select 330 VCs proportional to the number of VCs in each county. Finally, we asked each clinic to list all staff serving in the clinic and describe their responsibilities. Considering the measurement of different types of medical practitioners, we excluded healthcare providers other than Western medicine practitioners (ie, traditional Chinese medicine practitioners or those responsible for public health services only). Then, we randomly selected one of the remaining village healthcare providers as our sample.

The data collection was carried out in July 2017 by trained investigators. The survey consisted of a clinic form administered to the head of the VC and a clinician form administered to providers in each clinic verbally.

The clinic form (Supplementary Table 1) was used to collect basic information regarding the VCs, including the number of equipment per clinic, whether the drugs sold by the clinics met the zero price difference of medicine (a policy requires no mark-ups above the cost of drugs),6 the number of clinics within 5 km, the number of out-patient visits per clinic, and the number of providers per clinic.

The clinician form (Supplementary Table 2) consisted of two parts. The first part was used to obtain information regarding the provider’s demographics, working time allocation and income. This part included age, sex, ethnicity, basic salary, local residence (whether he/she was born and raised in the sample village), and time spent performing public health services. The second part was used to obtain detailed information on the providers’ in-service training participation in 2016 (the year before the survey year) and their clinical competence, including education level, certificate in rural medicine or higher, length of experience, and medical study.

The primary healthcare system provides generalist clinical care and basic public health services.1 China has promoted the three-tiered healthcare system to improve the use of primary healthcare. In rural China, the three-tiered healthcare system consists of VCs, township health centres, and county hospitals. Township health centres and VCs play a role in primary healthcare, and VCs mainly provide out-patient services under common clinical conditions. To assess the utilisation of VCs, the investigators asked the heads of the VCs to estimate (on average) the total number of out-patient visits during the previous month. The utilisation of the VCs was calculated using data related to the total number of out-patient visits, intramuscular injection visits, intravenous infusion visits, and number of healthcare providers in the clinics. Specifically, the utilisation of VCs in our research is measured on a per-provider basis. Thus, the utilisation of VCs equals the total number of out-patient visits divided by the number of healthcare providers.

Providers’ clinical competence is the quality of healthcare providers pertaining to medical knowledge, treatment quality, medical experience, medical study background, and medical training.28 In our study, we evaluated the providers’ clinical competence in the following dimensions: education above college level (measured medical knowledge); attainment of certificates in rural medicine or higher (measured treatment quality); length of experience (measured medical experience); participation in medical studies (measured medical study background); and completion of in-service training (measured medical training).

In clinical competence, multiple characteristics are often correlated; multicollinearity is a limitation of applying a multiple logistic regression analysis to measure clinical competence. A principal component analysis is often used to address this issue by transforming the data into one or two dimensions that serve as a summary of the characteristics, such as constructing an index.29 Therefore, we constructed the Clinical Competence Index to assess the overall clinical competence of the providers using a principal component analysis approach.

To explore the relationships between the healthcare providers and the utilisation of VCs, we used a multiple logistic regression. We conducted three types of regressions, and the outcome variable was out-patient visits per doctor. In the first regression, we measured the relationship between the village providers’ ethnicity and the utilisation of VCs. In the second regression, we included only the variables measuring the providers’ clinical competence. This relationship might vary across different ethnicities, and a heterogeneity analysis is needed. In the third regression, we performed a heterogeneity analysis by including the interaction term ‘Clinical Competence Index ethnic minority providers’ to measure the providers’ clinical competence and its relationship with the utilisation of VCs across different ethnicities.

In each regression mentioned above, we assessed the correlations with a fixed set of facility-level and provider-level characteristics. These characteristics included the number of equipment per clinic, whether the drugs sold by the clinics met the zero price difference of medicine, the number of clinics within 5 km, the percentage of minority residents in the town, the providers’ sex, salary, local residency, and time spent providing public health services. Notably, in all regressions, we also controlled for county-fixed effects.

All statistical analyses were performed using Stata version 15.0 statistical software (Stata Corp, College Station [TX], United States). The results with a P value <0.05 were considered statistically significant.

The questionnaire surveys were sent to 330 VCs and 330 healthcare providers, and valid results were obtained from all (participation rate 100%). There were no significant differences in terms of the amount of clinic equipment (P=0.395) and the implementation of the zero price difference of medicine (P=0.396) among the VCs (Table 1). However, the proportion of minority residents in the towns significantly differed with type of VCs (P<0.001). We also found that VCs where Han Chinese providers worked faced more competition, as the number of clinics within 5 km of these clinics was significantly higher than that for clinics where ethnic minority providers worked (P=0.002). The average number of healthcare providers in the VCs was 2.79. There was a significant difference in the number of providers across clinics (P=0.016), and this difference was mainly due to the number of providers who treat patients (P=0.044). Among the 330 VCs, mean number of out-patient visits per doctor was 146. The results indicate that the Han Chinese providers conducted a significantly higher average number of out-patient visits than the ethnic minority providers (151 vs 101; P=0.008) [Table 1]. In addition, we documented intramuscular injection visits and intravenous infusion visits. There was also a significant difference between the ethnic minority and Han Chinese majority providers in intravenous infusion visits (P=0.023), but no significant difference was found in intramuscular injection visits (P=0.834).

Most healthcare providers were male (64.5%), and 81.8% of providers were local residents (Table 2). The mean ± standard deviation annual salary of all providers was US$926±399, with no significant difference between the ethnic minority and Han Chinese majority providers (P=0.327). More than half of the healthcare providers devoted close to 60% of their work time to providing public health services (P=0.577).

Among the 330 providers, 26.4% had a college degree or higher, and the proportion among the Han Chinese providers was similar to that (26.4%) among the ethnic minority providers (25.7%, P=0.927) [Table 2]. In total, 91.9% of the Han Chinese providers were confirmed to have at least certificates in rural medicine; however, the proportion was 74.3% among the ethnic minority providers (P=0.001). In addition, the length of experience of the Han Chinese providers was significantly higher than that of the ethnic minority providers (P=0.013). The proportion of full-time medical studies conducted by all providers was 52.7%, and more ethnic minority providers than Han Chinese providers received in-service medical training (P=0.085).

The ethnicity of the providers was negatively associated with the utilisation of VCs (odds ratio [OR]=0.53, 95% confidence interval [CI]=0.29-0.96; P=0.037) [Table 3]; the providers’ clinical competence was positively associated with the utilisation of VCs (OR=1.49, 95% CI=1.12-2.00; P=0.007) [Table 3]. To better examine this relationship, we performed a heterogeneity analysis (Table 4). The results suggest that ethnic minority providers were likely to have underdeveloped clinical competence, which could further limit the utilisation of VCs (OR=0.45, 95% CI=0.23-0.89; P=0.022) [Table 4]. We also measured the determinants of intravenous infusion visits, and the results suggest that the providers’ clinical competence (OR=1.43, 95% CI=1.16-1.77; P=0.001) [Supplementary Table 4] was associated with the utilisation of VCs.

The data enabled an analysis of the utilisation of primary healthcare in rural areas in Southwest China. In general, there are three key findings in this study. First, we found significant differences between Han Chinese and ethnic minority providers in the utilisation of VCs. Second, compared with Han Chinese providers, ethnic minority providers in our sample had poorer clinical competence in two dimensions (possession of rural physician certificate or length of experience). Finally, our results indicate that underdeveloped clinical competence is a factor responsible for the lower utilisation of VCs among ethnic minority providers.

Our survey data show that the average number of out-patient visits in the sampling VCs is 146 per month per doctor, which is lower than the number of out-patient visits in eastern China (188 per month per doctor, 2017).9 Consistent with previous studies, we believe that the inconvenience of accessing primary healthcare among rural residents contributes to this difference.23 Compared with Yunnan Province (116 per month per doctor, 2017), the utilisation of VCs in the sampling area was higher.9 Based on our investigation, the high utilisation of VCs in the sampling area could be explained by both the population density and local economic development. According to the China Statistical Yearbook, the rural residents in the three prefectures we studied accounted for 20.00% of the total rural residents in Yunnan Province, which is quite large compared with the rate in other regions.30 The gross domestic product of the sampling area is also relatively high in Yunnan Province.27

However, the number of out-patient visits to VCs where the main providers are ethnic minorities is significantly lower than that of VCs where the main providers are Han Chinese individuals. Previous studies have shown that patients visiting providers of their own race were more satisfied and deliberately chose providers of their own race because of personal preference and language issues.13 14 In contrast to these studies, we excluded the preference and language issues of patients. First, their studies were generally conducted in large hospitals with many providers, but the average number of providers in our sampled VCs was approximately two, limiting the patients’ choices. Second, regarding language, most (81.8%) providers in our study were local residents who were fluent in the local dialect. These providers rarely have communication problems with their patients. After the above exclusions, an investigation of the characteristics of different ethnic providers was performed. Consistent with previous studies, there was no significant difference in provider characteristics and income, and the amount of clinic equipment and implementation of zero price difference of the medicine did not differ.19 20

Furthermore, we find significant differences between ethnic minority and Han Chinese village providers in their clinical competence. As a crucial aspect of primary healthcare services in rural China, village providers are obligated to provide qualified medical services, which require abundant clinical competence.31 32 However, based on our evidence, even if rural patients in Southwest China were asked to follow the instructions of policymakers and seek care primarily in VCs, they would visit higher-level facilities with a relatively high cost considering the local providers’ poor clinical competence. In fact, this type of situation is already very common in rural China.3 16 25

Under such circumstances, our findings imply that the difference in the utilisation of VCs might be related to ethnic minority providers’ underdeveloped clinical competence. Despite the small number of previous studies, the current evidence is consistent with the main findings.1 24 On the one hand, early studies suggested that the quality of health providers limited the utilisation of primary healthcare.3 4 16 On the other hand, ethnic minority providers usually experience less supportive learning environments during their medical studies, which might help explain the lag in their clinical competence.33 34 35 Therefore, we believe that uniformly improving the clinical competence of village providers, especially that of ethnic minority village providers, is conducive to improving the utilisation of primary healthcare.1 36

The Government of the People’s Republic of China understands the benefits of improving the clinical competence of village providers. A series of human resource policies for health launched in 2010 had a positive impact in rural China.37 Among these policies, the encouragement of external training for healthcare providers has been proven effective and necessary.36 38 39 In-service training for village providers could help these providers be informed of the latest knowledge and skills to manage diseases, which could significantly improve the quality of their medical services.36 The government has implemented actions to encourage the training of ethnic minorities since 2009.40 Thus, the appropriate introduction of re-education and more medical training should be adopted among ethnic minority providers.

Considering previous studies with analyses based mainly on the utilisation of healthcare from the patient perspective, our study might be the first investigation to examine healthcare providers’ ethnicity and clinical competence.10 11 32 In addition, our quantitative data include a rich set of detailed information of VCs regarding out-patient visits and providers’ clinical competence. We hope that our findings offer key insights into the utilisation of primary healthcare in rural China.

Our study has two main limitations. First, the participants in this study were recruited from rural Southwest China, so unavoidably, the nationwide validity of our findings is limited. Second, the results were limited by the cross-sectional nature of the study, and no causal effect between the providers’ clinical competence and the utilisation of primary healthcare was detected. Future research could investigate how different ethnic providers influence the utilisation of VCs and seek to adopt multiple measures to reduce bias in investigations.

In conclusion, this study reveals differences in the utilisation of primary healthcare between ethnic minority providers and Han Chinese providers at VCs in rural areas in Southwest China. Notably, the results indicate that higher clinical competence is more likely to drive the utilisation of VCs. We believe that the results of this study provide compelling evidence that ethnic minority healthcare providers in Southwest China require further enhancement with respect to their clinical competence.

Concept or design: All authors.
Acquisition of data: All authors.
Analysis or interpretation of data: All authors.
Drafting of the manuscript: All authors.
Critical revision of the manuscript for important intellectual content: All authors.

All authors had full access to the data, contributed to the study, approved the final version for publication, and take responsibility for its accuracy and integrity.

As an adviser of the journal, Y Shi was not involved in the peer review process. Other authors have disclosed no conflicts of interest.

H Yi received funding for this study from the Health and Hope Fund of the Business Development Center of the Red Cross Society of China and UCB of Belgium. Y Shi received funding from 111 Project (Grant number B16031), and Q Gao received funding from Innovation Capability Support Program of Shaanxi (Grant number 2022KRM007). The funders had no role in study design, data collection/analysis/interpretation, or manuscript preparation.

The study was approved by the Peking University Institutional Review Board (Ref IRB 00001052-17033). The board approved the verbal consent procedure. Informed consent from all respondents as a requirement for completing the survey.

1. Li X, Lu J, Hu S, et al. The primary health-care system in China. Lancet 2017;390:2584-94. Crossref

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3. Li YN, Nong D, Wei B, Feng QM, Luo HY. The impact of predisposing, enabling, and need factors in utilization of health services among rural residents in Guangxi, China. BMC Health Serv Res 2016;16:592. Crossref

4. Sylvia S, Xue H, Zhou C, et al. Tuberculosis detection and the challenges of integrated care in rural China: A cross-sectional standardized patient study. PLoS Med 2017;14:e1002405. Crossref

5. Dong X, Liu L, Cao S, et al. Focus on vulnerable populations and promoting equity in health service utilization—an analysis of visitor characteristics and service utilization of the Chinese community health service. BMC public health 2014;14:503. Crossref

6. Li Z. Healthcare reform and the development of China’s rural healthcare: a decade’s experience [in Chinese]. Chinese Rural Economy 2019;9:1-22.

7. National Bureau of Statistics of China, PRC Government. China Statistical Yearbook 2019. Available from: http://www.stats.gov.cn/tjsj/ndsj/2019/indexch.htm. Accessed 20 Oct 2020.

8. Sun J, Luo H. Evaluation on equality and efficiency of health resources allocation and health services utilization in China. Int J Equity Health 2017;16:127. Crossref

9. China Statisitcs Press. China Health Statistical Yearbook 2018. Available from: https://data.cnki.net/area/Yearbook/Single/N2019030282?z=D09. Accessed 9 May 2020.

10. Zhang X, Wu Q, Shao Y, Fu W, Liu G, Coyte PC. Socioeconomic inequities in health care utilization in China. Asia Pac J Public Health 2015;27:429-38. Crossref

11. Wang M, Fang H, Bishwajit G, Xiang Y, Fu H, Feng Z. Evaluation of rural primary health care in Western China: a cross-sectional study. Int J Environ Res Public Health 2015;12:13843-60. Crossref

12. Shi Y, Xue H, Wang H, Sylvia S, Medina A, Rozelle S. Measuring the quality of doctors’ health care in rural China: an empirical research using standardized patients [in Chinese]. Studies in Labor Econ 2016;4:48-71.

13. van Zanten M, Boulet JR, McKinley DW. The influence of ethnicity on patient satisfaction in a standardized patient assessment. Acad Med 2004;79(10 Suppl):S15-7. Crossref

14. LaVeist TA, Nuru-Jeter A, Jones KE. The association of doctor-patient race concordance with health services utilization. J Public Health Policy 2003;24:312-23. Crossref

15. Li Z, Li Y, Cui J. Development history of Chinese minority traditional medicine [in Chinese]. Med Philosophy (Humanistic & Soc Med Ed) 2011;32:78-81.

16. Wu D, Lam TP. Underuse of primary care in China: the scale, causes, and solutions. J Am Board Fam Med 2016;29:240-7. Crossref

17. Sandberg J. Understanding human competence at work: an interpretative approach. Acad Manage J 2000;43:9-25. Crossref

18. Liu W, Ding Y, Yang X. The determinants of rural labor migration in minority regions [in Chinese]. Population J 2015;37:102-12.

19. Shi L, Sai D. An empirical analysis of income inequality between a minority and the majority in urban China: the case of Ningxia Hui Autonomous Region. Rev Black Polit Econ 2013;40:341-55. Crossref

20. Li L, Li XG. Ethnicity, social capital and income gap: a comparative study of the Northwest ethnic group and the Western Han nationality [in Chinese]. J Sun Yat-sen University (Social Science Edition) 2016;56:161-71.

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22. China National Knowledge Infrastructure. BMJ; Why are ethnic minority doctors less successful than white doctors? Available from: https://schlr.cnki.net/en/Detail/index/SPQDLAST/SPQD48BA99708EE31C6710E1A02B2C34186A. Accessed 12 Jun 2020.

23. Li Y, Chi I, Zhang K, Guo P. Comparison of health services use by Chinese urban and rural older adults in Yunnan province. Geriatr Gerontol Int 2006;6:260-9. Crossref

24. Anand S, Fan VY, Zhang J, et al. China’s human resources for health: quantity, quality, and distribution. Lancet 2008;372:1774-81. Crossref

25. Meng Q, Liu X, Shi J. Comparing the services and quality of private and public clinics in rural China. Health Policy Plan 2000;15:349-56. Crossref

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27. Chinese Statistics Press. National Accounts. In: China Statistical Yearbook 2017. Available from: http://www.stats.gov.cn/tjsj/ndsj/2017/indexeh.htm. Accessed 6 Jun 2020.

28. Wass V, Van der Vleuten C, Shatzer J, Jones R. Assessment of clinical competence. Lancet 2001;357:945-9. Crossref

29. Lever J, Krzywinski M, Altman N. Principal component analysis. Nat Methods. 2017;14:641-2. Crossref

30. Chinese Statistics Press. Population. In: China Statistical Yearbook 2017. Available from: http://www.stats.gov.cn/tjsj/ndsj/2017/indexch.htm. Accessed 14 Jun 2020.

31. Li X, Liu J, Huang J, Qian Y, Che L. An analysis of the current educational status and future training needs of China’s rural doctors in 2011. Postgrad Med J 2013;89:202-8. Crossref

32. Dias SF, Severo M, Barros H. Determinants of health care utilization by immigrants in Portugal. BMC Health Serv Res 2008;8:207. Crossref

33. Myers SL, Xiaoyan G, Cruz BC. Ethnic minorities, race, and inequality in China: a new perspective on racial dynamics. Rev Black Polit Econ 2013;40:231-44. Crossref

34. Esmail A, Everington S. Racial discrimination against doctors from ethnic minorities. BMJ 1993;306:691-2. Crossref

35. Iacobucci G. Specialty training: ethnic minority doctors’ reduced chance of being appointed is “unacceptable”. BMJ 2020;368:m479. Crossref

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39. Yi H, Wu P, Zhang X, Teuwen DE, Sylvia S. Market competition and demand for skills in a credence goods market: evidence from face-to-face and web-based non-physician clinician training in rural China. PLoS One 2020;15:e0233955. Crossref

40. People Television. Training of ethnic minority grassroots doctors in the central and western regions launched [in Chinese]. Available from: http://tv.people.com.cn/n/2012/0915/c14645-19017341.html. Accessed 16 Jul 2020.

A substantial number of people infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain completely asymptomatic throughout the course of infection.1 In a recent prospective observational study of maternal and neonatal complications among 2130 pregnant women with and without SARS-CoV-2 infection, 44% of pregnant women diagnosed with coronavirus disease 2019 (COVID-19) were asymptomatic upon diagnosis. Despite this asymptomatic status, they exhibited increased risks of maternal morbidity (relative risk=1.24; 95% confidence interval=1.00-1.52) and pre-eclampsia (relative risk=1.63; 95% confidence interval=1.01-2.63), compared with pregnant women who had not been diagnosed with COVID-19.2 In a retrospective cohort study conducted in Spain, 3.1% of 759 pregnant women exhibited anti–SARS-CoV-2 antibodies and had been asymptomatic throughout pregnancy.3 Serological testing may serve as a useful tool to identify pregnant women who have recovered from a recent asymptomatic SARS-CoV-2 infection; this information can help guide the management of potential future complications.

Before the imposition of strict border control, a large number of people travelled between Hong Kong and the rest of the world each day. Pregnant women could have been infected without their knowledge because of asymptomatic or very mild disease. Furthermore, pregnancy symptoms can mask some COVID-19 symptoms, particularly if the COVID-19 symptoms are mild.4 In this study, we invited women who had undergone Down syndrome screening (DSS) since November 2019 to ascertain the seroprevalence of anti–SARS-CoV-2 antibodies in an unselected sample of pregnant women in Hong Kong. The findings were expected to provide insights concerning the asymptomatic infection rate among pregnant women.

This prospective cohort study included pregnant women who presented for routine DSS and underwent routine blood sample collection at 11 to 13 weeks of gestation between November 2019 and October 2020. All participants delivered at Kwong Wah Hospital or Prince of Wales Hospital, Hong Kong; the last delivery occurred in March 2021. Eligibility criteria included consent to serum storage for future research purposes and intention to deliver at the booking hospital. Eligible women who attended the booking hospital for delivery were invited to participate in the study. Women who delivered elsewhere, experienced pregnancy termination or miscarriage, or received a diagnosis of COVID-19 before the study were excluded. Women who agreed to participate in the study were asked to provide written informed consent for blood collection at delivery. Symptoms of COVID-19 throughout the pregnancy were evaluated at recruitment and at delivery.

Serum antibodies against SARS-CoV-2 were analysed using a qualitative serological assay. Qualitative detection of anti–SARS-CoV-2 antibodies (immunoglobulin G [IgG] and immunoglobulin M [IgM]) directed against the nucleocapsid protein (N-protein) of the virus was performed using the Elecsys Anti–SARS-CoV-2 assay (Roche, United States) on a Cobas^®e411 analyser. The result was provided as a cut-off index (COI). A positive anti–SARS-CoV-2 antibody result was defined as COI >=1.0. Individuals who had recovered from COVID-19 were recruited as positive control cases (COI >=1.0); individuals who had negative SARS-CoV-2 test results were recruited as negative control cases (COI <1.0) to ensure quality control in the anti–SARS-CoV-2 immunoassay.

Positive results based on qualitative detection of anti–SARS-CoV-2 antibodies were subsequently confirmed by quantitative measurements of IgG and IgM antibodies against the SARS-CoV-2 spike protein by using enzyme-linked immunosorbent assays (ImmunoDiagnostics Limited, Hong Kong). All tests were performed in duplicate, in accordance with the manufacturer’s instructions. Results were interpreted as negative when the optical density was <0.2 and as positive when the optical density was >=0.2. For samples with positive results, anti–spike protein concentrations (ng/mL) were calculated.

Continuous variables were expressed as medians (interquartile ranges or ranges). Categorical variables were summarised as counts and percentages. SPSS Statistics (Windows version 26.0; IBM Corp, Armonk [NY], United States) was used for data analyses.

The STROBE reporting guidelines were used during the preparation of this manuscript.

In total, 3219 consecutive pregnant women were approached; 306 declined participation and 1083 were excluded, including two with laboratory-confirmed SARS-CoV-2 infection, 69 who experienced miscarriage or pregnancy termination, and 1012 who planned delivery elsewhere. Thus, 1830 women were recruited to the study and provided written informed consent to participate. In total, 1810 (98.9%) women were Chinese, and 852 (46.6%) women were nulliparous. The median (interquartile range) maternal weight, height and age were 55.5 kg (50.3-62.5), 159 cm (155-163) and 33.0 years (30.2-36.4), respectively.

In total, six women (0.33%) were seropositive (COI >=1) at the DSS visit; this seropositivity persisted until delivery. Among these six women, one exhibited both anti–SARS-CoV-2 IgG and IgM antibodies; the IgM antibodies were undetectable at delivery. The remaining seropositive women exhibited only anti–SARS-CoV-2 IgG antibodies at both visits. All six of these women reported no relevant symptoms during pregnancy. Among the six women, one reported a travel history before her first DSS and one reported relevant contact history. The median COIs were 2.465 (interquartile range=1.430-3.178) and 1.680 (interquartile range=1.145-2.350) at DSS and delivery, respectively. The interval between sample collections was 177 days (range, 161-195). The COI at delivery was lower by a median of 31.8% (range, 12.0-35.1), compared with the COI at the DSS visit.

Characteristics of the study sample are presented in the Table. Fifty six women reported a travel history during pregnancy; one (1.79%) was seropositive at both visits. Two women reported relevant contact history during pregnancy; one (50.0%) was seropositive at both visits. Forty two women reported relevant symptoms during pregnancy; all were seronegative at both visits. Of the 1788 asymptomatic women, six (0.34%) were seropositive at both visits. In all, 259 women reported undergoing community SARS-CoV-2 testing during pregnancy; all tested negative. Among these 259 women, two (0.77%) were seropositive at both visits.

Our findings demonstrated a low seroprevalence (0.33%) of anti–SARS-CoV-2 antibodies in an unselected sample of pregnant women in Hong Kong. Among women with risk factors for SARS-CoV-2 infection, 1.79% and 50% with a travel history and relevant contact history, respectively, were seropositive. This finding suggests that targeted serological testing of pregnant women with a positive epidemiological link is useful for identifying women who have recovered from asymptomatic SARS-CoV-2 infection. A limitation of this study was that we relied on recruited individuals to recall COVID-19 symptoms throughout pregnancy, using only two recall time points: recruitment and delivery. This aspect may have introduced recall bias, particularly when COVID-19 symptoms could be non-specific and overlap with pregnancy symptoms. However, this limitation presumably did not have a large effect on the results because the seroprevalence of anti–SARS-CoV-2 antibody found in our unselected sample of pregnant women was very low. With a population of over 7 million, Hong Kong has largely been successful in controlling the transmission of SARS-CoV-2. Only 11 981 confirmed or probable cases have been recorded since the beginning of the epidemic.5 Thus, it is reasonable that the number of asymptomatic SARS-CoV-2 infections has also been low; this low number of asymptomatic infections has led to a low seroconversion rate in pregnant women.

Compared with other seroprevalence studies in pregnant women, the seroprevalence recorded in our study was substantially lower. The seroprevalence rates were 14% and 21% in Barcelona6 and southern Madrid3 (both in Spain), respectively. The low seroprevalence of anti–SARS-CoV-2 antibodies recorded in our study is presumably related to the implementation of a series of infection control strategies, including strict border control, mandatory quarantine for inbound travellers, mask wearing, and meticulous contact tracing. Hong Kong has learnt from its prior experience combating the SARS (severe acute respiratory syndrome) outbreak in 2003; accordingly, it implemented serious control measures early during the current epidemic. The Figure outlines the timeline of public health measures implemented during the first three waves of the epidemic in Hong Kong. By the end of March 2020, Hong Kong had closed its border to all incoming non-residents arriving from overseas and stopped transits through the city. All returning residents were subject to mandatory quarantine for 14 days; the quarantine period was extended to 21 days in December 2020. Locally, temporary closures of gyms, karaoke venues, clubs, and bars were periodically enforced, depending on the incidence of COVID-19. Dine-in service was forbidden from 6:00 pm to 5:00 am for several months, beginning in mid-July 2020. Mask wearing in public indoor areas and public transportation was also mandatory at that time. Notably, all seropositive cases in this study were first identified at the DSS visit between February 2020 and July 2020. This suggests that the seropositive cases acquired their infections during the first two waves of the epidemic; the implementation of stricter control measures by the local government during the third wave might have led to a lower transmission rate of asymptomatic infection among pregnant women, resulting in a lack of seroconversion during that period. Moreover, pregnant women are presumably more careful about social distancing and compliant with public health regulations. It would be useful to compare our seroprevalence results with the findings in other countries where strict measures were also implemented, such as Australia and New Zealand.

The humoral immune response is characterised by the production of virus-specific neutralising antibodies. Regardless of whether patients are symptomatic, IgG or IgM seroconversion has been observed in 65% to 100% of patients after infection with SARS-CoV-2.7 8 9 10 We previously demonstrated that 75% of pregnant women with laboratory-confirmed SARS-CoV-2 infection were seropositive at delivery.11 In addition to the strict control measures mentioned above, the low seroprevalence recorded in our study might have been related to undetectable antibody levels at the time of specimen collection—the timing of blood sample collection might not have been compatible with antibody detection. However, this is unlikely to have affected the findings among the large number of pregnant women in this study. A longitudinal study conducted in Wuhan, China, demonstrated that the median times from the first virus-positive test result to IgG or IgM seroconversion were 7 and 14 days in asymptomatic and symptomatic patients, respectively.12 In the asymptomatic cohort, all patients underwent seroconversion within 14 days from the first positive reverse transcriptase–polymerase chain reaction result.12 While waning immunity was observed at 5 months after infection,13 two studies showed that the antibody levels remained high and detectable at 8 months after infection.14 15 This finding is consistent with our results that the antibodies persisted until delivery in all women who had demonstrated seroconversion at the DSS visit. Because the two blood samples in this study were collected approximately 6 months apart, the timing of specimen collection was presumably adequate to identify most women who had contracted SARS-CoV-2 and developed detectable levels of antibodies.

Concerns regarding the usefulness of serological testing have been raised because of the uncertain onset and duration of humoral immunity; our study demonstrated a very low seroconversion yield in an unselected sample of pregnant women. Because of the ongoing vaccination programme, it is increasingly difficult to distinguish people who have acquired humoral immunity through natural infection from people who have acquired humoral immunity through vaccination. While the strict public health measures in Hong Kong have significantly reduced community transmission of SARS-CoV-2, these measures cannot be maintained indefinitely. The adverse effects of prolonged social distancing measures on the economy, education, mental health, and well-being of the population are immeasurable. There is increasing evidence that the COVID-19 mRNA vaccines are safe and effective; thus, pregnant women and women planning to become pregnant are encouraged to undergo vaccination at the earliest opportunity because pregnancy is a risk factor for severe COVID-19–related complications (eg, intensive care unit admission, invasive ventilation requirement, and death).16 17 The risk of preterm birth is also greater among pregnant women with COVID-19, compared with pregnant women who do not have COVID-19.18 19 20 Our study has demonstrated that anti–SARS-CoV-2 antibodies found at DSS persist until delivery. This result suggests that the presence of anti–SARS-CoV-2 antibodies in early pregnancy, preferably acquired through vaccination, would provide some protection for the pregnant woman and her baby during the remaining portion of the pregnancy.

Until a highly effective therapeutic drug targeting SARS-CoV-2 becomes readily available, mass vaccination remains the best solution to control the COVID-19 pandemic, avoid further lockdowns, and allow a return to “normal” pre–COVID-19 life, as well as saving lives. Our study highlights the importance of a successful vaccination campaign.

Concept or design: LCY Poon, DS Sahota.
Acquisition of data: HHY Leung, CYT Kwok, WC Leung, DS Sahota, MBW Leung, GCY Lui, SSS Ng.
Analysis or interpretation of data: HHY Leung, CYT Kwok, LCY Poon.
Drafting of the manuscript: HHY Leung, CYT Kwok, LCY Poon, DS Sahota.
Critical revision of the manuscript for important intellectual content: HHY Leung, CYT Kwok, LCY Poon, DS Sahota, SSS Ng, PKS Chan.

All authors had full access to the data, contributed to the study, approved the final version for publication, and take responsibility for its accuracy and integrity.

LCY Poon has received speaker fees and consultancy payments from Roche Diagnostics and Ferring Pharmaceuticals. She has also received in-kind contributions from Roche Diagnostics. Other authors have disclosed no conflict of interest.

We thank Lijia Chen, Tracy CY Ma, Maggie Mak, Ching-man Mak, Angela ST Tai, Jeffery Ip, Phyllis Ngai, Andrea Chan, and Lisa LS Chan for making substantial contributions by involving in study coordination and patient recruitment.

This work was supported by Roche Diagnostic, United States, which provided reagents for the qualitative detection of anti– SARS-CoV-2 antibodies.

Approval for the study was obtained from the Joint Chinese University of Hong Kong–New Territories East Cluster Clinical Research Ethics Committee (CREC Ref No. 2020.214). Patients provided written informed consent to participate in the study; this included consent for serum storage for research purposes.

The study is registered with ClinicalTrials.gov (Ref NCT04465474).

1. Byambasuren O, Cardona M, Bell K, Clark J, McLaws ML, Glasziou P. Estimating the extent of asymptomatic COVID-19 and its potential for community transmission: systematic review and meta-analysis. Off J Assoc Med Microbiol Infect Dis Can 2020;5:223-34. Crossref

2. Villar J, Ariff S, Gunier RB, et al. Maternal and neonatal morbidity and mortality among pregnant women with and without COVID-19 infection: the INTERCOVID multinational cohort study. JAMA Pediatr 2021;175:817-26. Crossref

3. Villala n C, Herraiz I, Luczkowiak J, et al. Seroprevalence analysis of SARS-CoV-2 in pregnant women along the first pandemic outbreak and perinatal outcome. PLoS One 2020;15:e0243029. Crossref

4. Afshar Y, Gaw SL, Flaherman VJ, el al. Clinical presentation of coronavirus disease 2019 (COVID-19) in pregnant and recently pregnant people. Obstet Gynecol 2020;136:1117-25. Crossref

5. Hong Kong SAR Government. Together, we fight the virus! Available from: https://www.coronavirus.gov.hk/eng/index.html. Accessed 28 Jul 2021.

6. Crovetto F, Crispi F, Llurba E, Figueras F, G mez-Roig MD, Gratac s E. Seroprevalence and presentation of SARS-CoV-2 in pregnancy. Lancet 2020;396:530-1. Crossref

7. W lfel R, Corman VM, Guggemos W, et al. Virological assessment of hospitalized patients with COVID-2019. Nature 2020;581:465-9. Crossref

8. Zhao J, Yuan Q, Wang H, et al. Antibody responses to SARS-CoV-2 in patients with novel coronavirus disease 2019. Clin Infect Dis 2020;71:2027-34. Crossref

9. Long QX, Liu BZ, Deng HJ, et al. Antibody responses to SARS-CoV-2 in patients with COVID-19. Nat Med 2020;26:845-8. Crossref

10. Qu J, Wu C, Li X, et al. Profile of immunoglobulin G and IgM antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Clin Infect Dis 2020;71:2255-8. Crossref

11. Poon LC, Leung BW, Ma T, et al. Relationship between viral load, infection-to-delivery interval and mother-to-child transfer of anti-SARS-CoV-2 antibodies. Ultrasound Obstet Gynecol 2021;57:974-8. Crossref

12. Jiang C, Wang Y, Hu M, et al. Antibody seroconversion in asymptomatic and symptomatic patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Clin Transl Immunology 2020;9:e1182. Crossref

13. Choe PG, Kang CK, Suh HJ, et al. Waning antibody responses in asymptomatic and symptomatic SARS-CoV-2 infection. Emerg Infect Dis 2021;27:327-9. Crossref

14. Hartley GE, Edwards ES, Aui PM, et al. Rapid generation of durable B cell memory to SARS-CoV-2 spike and nucleocapsid proteins in COVID-19 and convalescence. Sci Immunol 2020;5:eabf8891. Crossref

15. Choe PG, Kim KH, Kang CK, et al. Antibody responses 8 months after asymptomatic or mild SARS-CoV-2 infection. Emerg Infect Dis 2021;27:928-31. Crossref

16. UK Government. JCVI issues new advice on COVID-19 vaccination for pregnant women. Available from: https://www.gov.uk/government/news/jcvi-issues-new-advice-on-covid-19-vaccination-for-pregnant-women. Accessed 17 May 2021.

17. Hong Kong College of Obstetricians and Gynaecologists. HKCOG advice on Covid-19 vaccination in pregnant and lactating women (interim; updated on 21 April 2021). Available from: https://www.hkcog.org.hk/hkcog/Upload/EditorImage/20210423/20210423141055_6024.pdf. Accessed 17 May 2021.

18. Martinez-Portilla RJ, Smith ER, He S, et al. Young pregnant women are also at an increased risk of mortality and severe illness due to coronavirus disease 2019: analysis of the Mexican National Surveillance Program. Am J Obstet Gynecol 2021;224:404-7. Crossref

19. Martinez-Portilla R, Sotiriadis A, Chatzakis C, et al. Pregnant women with SARS-CoV-2 infection are at higher risk of death and pneumonia: propensity score matched analysis of a nationwide prospective cohort (COV19Mx). Ultrasound Obstet Gynecol 2021;57:224-31. Crossref

20. Allotey J, Stallings E, Bonet M, et al. Clinical manifestations, risk factors, and maternal and perinatal outcomes of coronavirus disease 2019 in pregnancy: living systematic review and meta-analysis. BMJ 2020;370:e3320. Crossref

Since the beginning of the human immunodeficiency virus (HIV) epidemic, stigma and discrimination have affected the provision of healthcare to patients with HIV. These factors have limited access to HIV testing and treatment; they have also prevented the uptake of interventions, such as pre-exposure prophylaxis.1 The global shift necessary in the biomedical response to acquired immunodeficiency syndrome (AIDS) thus heavily relies on reductions of both stigma and discrimination. The importance of stigma reduction has been recognised as a key priority in the Blueprint for Achieving an AIDS-Free Generation (established by The United States President’s Emergency Plan for AIDS Relief)2 and in the HIV investment framework (established by The Joint United Nations Programme on HIV/AIDS).3

For many years, stigma from healthcare professionals has remained a major barrier to access for HIV prevention and treatment services. According to aggregated data from the Stigma Index for 50 countries, healthcare has been denied to one in eight people living with HIV (PLHIV).4 Despite high antiretroviral therapy coverage, Hong Kong is no exception to this phenomenon. In the early and middle 2010s, 26.8% of PLHIV reported stigmatising experiences during treatment for non- HIV-related healthcare needs.5 Since the late 2000s, advances in HIV treatment have led to a decline in mortality.6 Increasing life expectancy among PLHIV has resulted in higher HIV prevalence.7 Thus, medical students have an increased likelihood of encountering patients with HIV in future clinical practice, irrespective of their specialties. Because HIV epidemiology has changed over the years, medical students’ attitudes towards the disease may also have changed. If attitudes have changed, the medical school curriculum should be adjusted to match such changes; this will ensure that future physicians can provide the best possible care. To our knowledge, no study has compared changes over time in medical students’ attitudes towards HIV. Thus, we performed a survey to compare medical students’ attitudes towards HIV/AIDS between the late 2000s (2007-2010) and middle 2010s (2014-2017).

This study was a descriptive cross-sectional survey to measure medical students’ attitudes towards HIV/AIDS, as well as their experiences within the HIV curriculum.

An assessment survey was administered to final-year medical students at the Chinese University of Hong Kong, one of the two medical schools in Hong Kong. Questionnaires were distributed to medical students at the end of their final-year attachment to an HIV specialist clinic. At the Chinese University of Hong Kong, HIV education is an integral part of the medical student curriculum. Over the course of 3 years, students attend microbiology and medicine lectures regarding HIV/AIDS, a community medicine module that includes the prevention and control of HIV infection, a half-day attachment to Hong Kong’s largest HIV specialist clinic, and hospital ward rounds that involve patients with HIV. The HIV curriculum was generally consistent between the late 2000s and middle 2010s. This study was based on the analysis of survey data collected from six cohorts of medical students: three from 2007 to 2010 and three from 2014 to 2017. All students were asked to complete the survey during their final teaching session. Hard copies of the self-administered structured questionnaire were distributed to the students and collected by the course instructors. All responses were anonymous and participation was voluntary.

The study questionnaire was originally developed as an assessment form by the HIV medicine teaching team at the Chinese University of Hong Kong; it was designed for completion by final-year medical students. The form was piloted in 2005 and became standardised in 2007, with minor modifications in subsequent years.8 The questionnaire was in English and consisted of 25 close-ended questions; all questions were completed by the students without assistance. The questionnaire contents slightly differed between the 2007-2010 and 2014-2017 survey periods. Seven questions that appeared in both questionnaires were selected for analysis. These questions focused on demographics, exposure to patients with HIV, and attitudes towards patients with HIV. Eight additional questions were analysed for cohorts from 2014 to 2017. These questions focused on a participant’s ability to recall various HIV learning experiences and their satisfaction with clinical exposure during attachment to an HIV clinic. We divided students into groups according to their willingness to provide HIV care in the future. An unwilling student chose “strongly agree” or “agree” (on a four-point scale for cohorts from 2007 to 2010 and a six-point scale for cohorts from 2014 to 2017) when asked whether they would refuse to perform treatment or surgical procedures for patients with HIV.

We calculated proportions of responses, along with exact binomial 95% confidence intervals (CIs). We used bivariable logistic regression to compare exposure and attitudes between participants in the 2007-2010 cohort (cohorts from 2007 to 2010) and the 2014-2017 cohort (cohorts from 2014 to 2017); each set of three cohorts was grouped together to maximise sample size. Factors associated with willingness to provide HIV care were analysed using bivariable logistic regression. SPSS software (Windows version 26; IBM Corp., Armonk [NY], United States) was used for data management and statistical analyses. Two-sided P values <0.05 were considered statistically significant.

In total, 1050 final-year students participated in the survey. Three cohorts of final-year medical students participated between 2007 and 2010 (n=546); three additional cohorts of final-year medical students participated between 2014 and 2017 (n=504). The response rates were 97% in the 2007-2010 cohort and 91% in the 2014-2017 cohort. Table 1 shows the detailed characteristics, exposure, and attitudes among the surveyed students. There was no difference in gender between the 2007-2010 and 2014-2017 cohorts (odds ratio [OR]=1.14; 95% CI=0.89-1.46).

Significantly fewer students (39.3%) in the mid-2010s initially encountered patients with HIV during attachment to an HIV clinic, compared with students in the late 2000s (72.1%; OR=0.25; 95% CI=0.18-0.34) [Table 1]. The proportion of students who personally knew HIV-positive friends or relatives remained low and did not significantly differ over time (OR=0.55; 95% CI=0.1-3.01). In the 2007-2010 and 2014-2017 cohorts, only four of 545 students (0.7%) and two of 495 students (0.4%), respectively, personally knew HIV-positive friends or relatives.

Student willingness to provide HIV care was similar between cohorts (Table 1). Approximately 78% of students were willing to provide care (OR=0.98; 95% CI=0.73-1.33). The proportion of students who preferred to avoid work in a field involving HIV/AIDS significantly decreased over time: 17.2% in the 2007-2010 cohort, compared with 10.6% in the 2014-2017 cohort (OR=0.57; 95% CI=0.4-0.83). An increasing number of students planned to specialise in clinical HIV treatment: 11 of 517 students (2.1%) in the 2007-2010 cohort, compared with 53 of 480 students (11%) in the 2014-2017 cohort (OR=5.71; 95% CI=2.95-11.07).

There was no difference in gender between willing and unwilling students (OR=1.24; 95% CI=0.92-1.68) [Table 2]. Unwilling students were more likely than willing students to have initially encountered patients with HIV during attachment to an HIV clinic (61.4% vs 50.9%) [OR=1.53; 95% CI=1.07-2.19]. Willingness was not associated with personally knowing HIV-positive friends or relatives. In the 2014-2017 cohort, most students (80.3%) recalled their attachment to an HIV clinic, whereas fewer than half could recall other components of the HIV curriculum (lectures and ward rounds; 14.5-48.7%). Notably, the ability to recall attachment to an HIV clinic was associated with willingness (OR=0.57; 95% CI=0.34-0.96) to provide HIV care. Ratings of the content and format of the attachment to an HIV clinic were not associated with willingness (OR=0.94; 95% CI=0.58-1.50 and OR=0.79; 95% CI=0.50-1.27, respectively). Overall, most students (97.5%) have encountered >1 patient with HIV during clinical attachment. Unwilling students (5/71, 7%) were less likely than willing students (4/295, 1.4%) to have encountered any patients with HIV during clinical attachment.

Human immunodeficiency virus prevalence has risen over time8 with advances in antiretroviral therapy that contribute to prolonged survival; this pattern has been observed in nearly all countries, irrespective of the initial HIV prevalence. Thus, it is unsurprising that exposure to patients with HIV/AIDS increased over time among medical students in our study. Nevertheless, Hong Kong remains a low prevalence setting for HIV/AIDS9; therefore, the number of students who personally knew HIV-positive friends or relatives has remained low. Despite predictable trends in exposure to patients with HIV since the late 2000s, some students maintained negative attitudes towards patients with HIV. Although exposure to patients with HIV has increased, the proportion of students unwilling to provide HIV care did not change between the late 2000s and middle 2010s. The proportion of unwilling students in our study is higher than that in a similar study conducted in 2011 in Malaysia, where 10% to 15% of students reported unwillingness to provide HIV care.10 Because medical students are future healthcare providers, their unwillingness to provide HIV care represents an extreme manifestation of stigma, which has been a problem since the HIV/AIDS epidemic began.11

Stigma can have subtle effects, which may influence career choices. A previous study found that these effects can diminish over time12; our results are consistent with that finding. While a large proportion of students did not plan to work in a field involving HIV, such plans may be related to personal preferences for medical disciplines that facilitate career development and job opportunities, although discrimination cannot be ruled out. However, the present study showed that, over time, fewer students have reported that they prefer to avoid working in a field involving HIV/AIDS. Encouragingly, increasing numbers of students are planning to specialise in clinical HIV treatment. “Interest” has been most frequently cited as the main reason for choosing a specialty; thus, interest in HIV/AIDS may be increasing among medical students.13 However, the proportion of students who intended to specialise in clinical HIV treatment was lower in our study than in a previous study in the United Kingdom, where 8% to 24% of students reported such an intention.14

Clinical attachment with patient exposure appears to be an effective learning experience. In the current system, some students may have overlooked and missed the opportunity to encounter a patient with HIV/AIDS. We found that, compared with willing students, a higher proportion of students unwilling to provide HIV/AIDS care had not encountered a patient with HIV/AIDS during their clinical attachment. This difference may be attributed to a lack of exposure to patients with HIV/AIDS during the medical school curriculum. Students may benefit from repeated exposure to patients with HIV/AIDS in different settings—willing students were more likely to have previously encountered a patient with HIV/AIDS. Further research is needed to determine whether students could be exposed to patients with HIV outside clinical settings (eg, through non-governmental organisations) and to understand the impacts of such exposure. Willing students were more likely to recall their attachment to an HIV clinic, compared with other teaching methods; this suggests that their emotions were aroused, which prompted recall.15

Previous research has shown that teaching methods with experiential, small group, or affective components and role models of positive attitudes can effectively change students’ attitudes.14 Such considerations may be useful in clinics where small numbers of students observe patient management by a specialist physician. If a student is emotionally affected by a patient or sees the clinician as a good role model, the clinical attachment may constitute a memorable experience. This may be more important than gaining technical knowledge and skills through the clinical attachment experience because content and format were not associated with willingness to provide HIV care. Our results are consistent with the findings of previous studies, which showed that frequent clinical exposure to patients with HIV/AIDS led to more positive attitudes.14 16 17 18 19 20 Furthermore, knowledge alone cannot effectively decrease HIV stigma21; similarly, we found that the ability to recall lectures was not associated with willingness to provide care for patients with HIV/AIDS. However, increased exposure alone may be insufficient to combat HIV stigma. Antibias information is also needed to reduceprejudice,22 such as homophobia, which has been associated with unwillingness to provide care for patients with AIDS.12 Medical training should address these issues that contribute to stigma towards patients with HIV/AIDS. Notably, medical students reportedly demonstrated increased willingness to provide care for patients with HIV/AIDS after they had attended an PLHIV sharing session or participated in experiential games that were designed to increase empathy towards PLHIV.23 In another study, HIV stigma levels decreased in medical students after exposure to an intervention that included discussion of HIV stigma and other pre-existing related stigmas (eg, homosexuality and illegal drug use).24

This study had some limitations. First, it was a comparison of cross-sectional surveys over a 10-year period and thus we were unable to assess potential changes in attitudes among medical students within a single cohort. Second, each cohort used in comparative analysis was composed of three annual cohorts; therefore, time intervals varied among cohorts (eg, the 2007 and 2017 cohort were separated by 10 years, whereas the 2010 and 2014 cohorts were separated by 4 years). Nevertheless, we grouped cohorts together to maximise sample size; our analysis clearly showed changes in attitudes among medical students over time.

Despite more positive attitudes towards HIV/AIDS in terms of career choices, the willingness of medical students to provide HIV care did not change between the late 2000s and middle 2010s.

Interventions to reduce stigmatising attitudes among towards PLHIV should be incorporated in medical training; however, the framework for medical school curriculum in Hong Kong makes no mention of such interventions, although it lists “attitudes and professionalism” as a core competency.25 The medical school curriculum could be updated to incorporate interventions that involve experiential and affective teaching components to adequately address HIV stigma; additional clinical attachments can ensure that medical students have adequate exposure to patients with HIV.

Concept or design: G Tam, SS Lee.
Acquisition of data: SS Lee.
Analysis or interpretation of data: NS Wong.
Drafting of the manuscript: All authors.
Critical revision of the manuscript for important intellectual content: All authors.

All authors had full access to the data, contributed to the study, approved the final version for publication, and take responsibility for its accuracy and integrity.

The authors declare that they have no competing interests.

This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

This study was approved by the Survey and Behavioural Research Ethics Committee, The Chinese University of Hong Kong (Ref 12-01-2011). Participation was voluntary and completion of the survey implied consent to participate in the study. All data were anonymised and confidential.

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