Background: Missing data in electronic health records (EHRs) presents significant challenges in medical studies. Many methods have been proposed, but uncertainty exists regarding the current state of missing data addressing methods applied for EHR and which strategy performs better within specific contexts. Methods: All studies referencing EHR and missing data methods published from their inception until 2024 March 30 were searched via the MEDLINE, EMBASE, and Digital Bibliography and Library Project databases. The characteristics of the included studies were extracted. We also compared the performance of various methods under different missingness scenarios. Results: After screening, 46 studies published between 2010 and 2024 were included. Three missingness mechanisms were simulated when evaluating the missing data methods: missing completely at random (29/46), missing at random (20/46), and missing not at random (21/46). Multiple imputation by chained equations (MICE) was the most popular statistical method, whereas generative adversarial network-based methods and the k nearest neighbor (KNN) classification were the common deep-learning-based or traditional machine-learning-based methods, respectively. Among the 26 articles comparing the performance among medical statistical and machine learning approaches, traditional machine learning or deep learning methods generally outperformed statistical methods. Med.KNN and context-aware time-series imputation performed better for longitudinal datasets, whereas probabilistic principal component analysis and MICE-based methods were optimal for cross-sectional datasets. Conclusions: Machine learning methods show significant promise for addressing missing data in EHRs. However, no single approach provides a universally generalizable solution. Standardized benchmarking analyses are essential to evaluate these methods across different missingness scenarios.

Background and aim: Hepatitis C virus infection can lead to an enormous health burden worldwide. Investigating the changes in HCV-related burden between different countries could provide inferences for disease management. Hence, we aim to explore the temporal tendency of the disease burden associated with HCV infection in China, India, the United States, and the world.Methods: Detailed data on the total burden of disease related to HCV infection were collected from the Global Burden of Disease (GBD) 2019 database. Joinpoint regression models were used to simulate the optimal joinpoints of annual percent changes (APCs). Further analysis of the age composition of each index over time and the relationship between ASRs and the socio-demographic Index (SDI) were explored. Finally, three factors (population growth, population aging, and age-specific changes) were deconstructed for the changes in the number of incidences, deaths, and DALYs.Results: It was estimated that 6.2 million new HCV infections, 0.54 million HCV-related deaths, and 15.3 million DALYs worldwide in 2019, with an increase of 25.4, 59.1, and 43.6%, respectively, from 1990, are mainly due to population growth and aging. China experienced a sharp drop in age-standardized rates in 2019, the United States showed an upward trend, and India exhibited a fluctuating tendency in the burden of disease. The incidence was increasing in all locations recently.Conclusion: HCV remains a global health concern despite tremendous progress being made. The disease burden in China improved significantly, while the burden in the United States was deteriorating, with new infections increasing recently, suggesting more targeted interventions to be established to realize the 2030 elimination goals.

Background: There is a risk of pelvic floor dysfunction (PFD) from baby delivery. Many clinical guidelines recommend pelvic floor muscle training (PFMT) as the conservative treatment for PFD because pelvic floor muscles (PFMs) play a crucial role in development of PFD. However, there is disagreement about the method and intensity of PFM training and the relevant measurements. To pilot the study in PFM training, we designed a Pelvic Floor Workout (PEFLOW) for women to train their pelvic through entire body exercises, and we planned a trial to evaluate its effectiveness through comparing the outcomes from a group of postpartum women who perform PELFLOW at home under professional guidance online with the control group. Methods/design: The randomized controlled trial was projected to be conducted from November 2021 to March 2023. A total of 260 postpartum women would be recruited from the obstetrics departments of the study hospital and women would be eligible for participation randomized into experimental or control groups (EG/CG) if their PFM strength are scaled by less than Modified Oxford grading Scale (MOS) to be less than grade 3. Women in EG would perform a 12-week PEFLOW online under the supervision and guidance of a physiotherapist, while women in CG would have no interventions. Assessments would be conducted at enrollment, post intervention (for EG) or 18th to 24th week postpartum (for CG), and 1 year postpartum. Assessment would be performed in terms of pelvic floor symptoms, including MOS, cough stress test, urinary leakage symptoms, pelvic organ prolapse quantitation (POP-Q), and vaginal relaxation, clinic examinations including Pelvic floor electrophysiological test, Pelvic floor ultrasound and Spine X-ray, overall body test including trunk endurance test, handgrip test, body composition test, and questionnaires including International Physical Activity Questionnaire Score-Short Form(IPAQ-SF), Pelvic Floor Distress Inventory Questionnaire-20 (PFDI-20), Pelvic Floor Impact Questionnaire-7 (PFIQ-7), the 6-item Female Sexual Function Index (FSFI-6), and the Pittsburgh Sleep Quality Index (PSQI). Primary analysis will be performed to test our main hypothesis that PEFLOW is effective with respect to strengthen PFM strength. Discussion: This trial will demonstrate that pelvic floor-care is accessible to most women and clinical practice on PFD may change relevantly should this study find that Online PEFLOW approach is effective to improve PFMs. Trial registration: ClinicalTrials.gov, NCT05218239.

Background: The COVID-19 epidemic affected the career choice of healthcare professionals and students. Career choice regret of healthcare professionals and students during COVID-19 outbreak and its affected factors are largely unexplored.Methods: Convenience sample of nurses, doctors, and medical students were recruited from hospitals and universities nationwide. The data collected including demographic information, professional value before and after the COVID-19 outbreak, the Connor-Davidson Resilience Scale, and career choice regret level by an online questionnaire. Multinominal logistic regression was employed to explore the factors associated with career choice regret.Results: In total, 9322 participants of convenience sampling were enrolled in, including 5786 nurses, 1664 doctors, and 1872 medical students. 6.7% participants had career choice regret. Multinominal logistic regression analysis showed, compared to participants with no regret, that as levels of psychological resilience increased, the odds of experiencing career choice regret decreased (OR = 0.95, 95% CI 0.94–0.96), while participants with lower professional value evaluation after the COVID-19 outbreak had higher probability to experience career choice regret (OR = 1.55,95% CI 1.50–1.61). Medical students were more likely to regret than nurses (OR = 1.65,95% CI 1.20–2.28), participants whose career/major choice was not their personal ideal had higher risk of experience career choice regret (OR = 1.59,95% CI 1.29–1.96), while participants who were very afraid of the coronavirus had higher risk to experience career choice regret then participants with no fear at all (OR = 2.00,95% CI 1.24–3.21).As for the medical students, results indicated that medical students major in nursing and undergraduates had higher risk to experience career choice regret compared to medical students major in clinical medicine and postgraduate (Master or PhD), with an odds ratios of 2.65(95% CI 1.56–4.49) and 6.85 (95% CI 2.48–18.91)respectively.Conclusions: A minority of healthcare professionals and medical students regretted their career choices during the COVID-19 outbreak. Enhance personal psychological resilience and professional value would helpful to reduce career choice regret among healthcare professionals and students during pandemic.

Aim: To assess the burden of liver complications related to non‐alcoholic fatty liver disease (LC‐NAFLD) from 2005 to 2019 in China. Materials and Methods: We used data from the Global Burden of Disease, Injuries, and Risk Factors Study, 2019, to present contemporary and varying profiles of China's LC‐NAFLD burden. The Joinpoint Regression model and Gaussian process regression were, respectively, used to estimate the annual percentage change in prevalence rates and disability‐adjusted life‐year (DALY) rates, and the relationship between the sociodemographic index (SDI) and age‐standardized rates of LC‐NAFLD. Results: In 2019, China had 293.42 million (95% uncertainty interval [UI]: 263.69‐328.44) LC‐NAFLD cases with a prevalence rate and DALYs of 20.63 (95% UI: 23.09‐18.54) per 1000 people and 591.03 thousand (95% UI: 451.25‐737.33), respectively. North China had the highest prevalence but the lowest DALYs of LC‐NAFLD, whereas Southwest China had the lowest prevalence but the highest DALYs. LC‐NAFLD were more common in men than in women (male: female ratio, 1.27) in 2019. From 2005 to 2019, the prevalence of NAFLD cases increased by 68.32% (from 174.32 million in 2005 to 293.42 million in 2019), mainly because of an age‐specific prevalence rate increase. Conclusion: The LC‐NAFLD burden in China is substantial and has increased markedly over the past 15 years. Effective measures for low SDI regions and men are needed to address the rapidly increasing NAFLD burden.

Background: Breast cancer and reproductive system cancers remain significant public health threats for Chinese women. This study aimed to evaluate the latest epidemiological patterns and trends of four female‐specific cancers in China.Methods: The year‐ and age‐specific estimates of the incidence, mortality, and disability‐adjusted life‐years (DALYs) associated with breast, cervical, ovarian, and uterine cancers in China from 1990 to 2021 were generated from the Global Burden of Disease, Injuries, and Risk Factors 2021 study. The epidemiological characteristics were analyzed with age–period–cohort models. A Bayesian age–period–cohort model was applied to forecast disease burden from 2022 to 2050.Results: In 2021, China reported 385.84 thousand (95% uncertainty interval [UI], 294.10–489.01 thousand) incident cases of female breast cancer, followed by cervical cancer (132.79 thousand [95% UI, 95.96–172.60 thousand]), uterine cancer (72.02 thousand [95% UI, 53.31–100.00 thousand]), and ovarian cancer (41.24 thousand [95% UI, 30.30–54.55 thousand]). Breast cancer ranked as the primary cause of cancer‐related deaths, followed by cervical cancer. The age‐specific incidence rate for breast, cervical, ovarian, and uterine cancers are projected to occur in the age groups 60–64 years, 55–59 years, 65–69 years, and 60–64 years, respectively. Breast, ovarian, and uterine cancer cases are projected to rise by 2050, which will exceed those recorded in 2021.Conclusions: Various inequities have been identified across four types of cancers affecting women, which underscores the need for tailored national cancer control strategies. Emphasis should be placed on primary prevention and screening for breast and cervical cancers, whereas efforts for uterine and ovarian cancers should focus on implementing early diagnosis and treatment measures.Plain language summary: This study examines the burdens and trends of breast, cervical, ovarian, and uterine cancers among Chinese women from 1990 to 2021. In 2021, breast cancer emerged as the most prevalent, followed by cervical, uterine, and ovarian cancers, with breast cancer also exhibiting the highest mortality rate. The age groups projected to exhibit the highest incidence rates for breast, cervical, ovarian, and uterine cancers are 60–64 years, 55–59 years, 65–69 years, and 60–64 years, respectively. Projections indicate that by 2050, the incidence of breast, ovarian, and uterine cancers will surpass 2021 levels, which underscores the necessity for targeted prevention, early detection, and treatment strategies.