In recent years, accumulating evidence has supported the hypothesis that lower vitamin D status is associated with several known risk factors of stroke. However, the relationship between vitamin D and stroke is still uncertain. To explore if there was an association between vitamin D status and the risk of stroke, a systematic review and a meta-analysis were conducted by searching three databases: Pubmed, Embase, and the Cochrane Library. Following the application of inclusion and exclusion criteria, the relative risk estimates of all the included studies were pooled together to compare the risk of stroke between the lowest and the highest category of vitamin D. The Newcastle–Ottawa Scale (NOS) and the Cochrane Risk of Bias Tool were used to assess the risk of bias, and the publication bias was detected by using a funnel plot and Egger’s test. Nineteen studies were included and the pooled relative risk was 1.62 (95% CI: 1.34–1.96). Further analysis found that vitamin D status was associated with ischemic stroke (relative risk = 2.45, 95% CI: 1.56–3.86), but not with hemorrhagic stroke (relative risk = 2.50, 95% CI: 0.87–7.15). In conclusion, our meta-analysis supported the hypothesis that lower vitamin D status was associated with an increased risk of ischemic stroke. Further studies are required to confirm this association and to explore the association among different subtypes.

The effects of ambient particulate matter (PM) pollution on pneumonia in adults are inconclusive, and few scientific data on a national scale have been generated in low- or middle-income countries, despite their much higher PM concentrations. We aimed to examine the association between PM levels and hospital admissions for pneumonia in Chinese adults. A nationwide time series study was conducted in China between 2014 and 2017. Information on daily hospital admissions for pneumonia for 2014–2017 was collected from the database of Urban Employee Basic Medical Insurance (UEBMI), which covers 282.93 million adults. Associations of PM concentrations and hospital admissions for pneumonia were estimated for each city using a quasi-Poisson regression model controlling for time trend, temperature, relative humidity, day of the week, and public holiday and then pooled by random-effects meta-analysis. Meta-regression models were used to investigate potential effect modifiers, including cities’ annual-average air pollutants concentrations, temperature, relative humidity, gross domestic product (GDP) per capita, and coverage rates by the UEBMI. More than 4.2 million pneumonia admissions were identified in 184 Chinese cities during the study period. Short-term elevations in PM concentrations were associated with increased pneumonia admissions. At the national level, a 10-μg/m³ increase in 3-day moving average (lag 0–2) concentrations of PM_2.5 (PM ≤2.5 μm in aerodynamic diameter) and PM₁₀ (PM ≤10 μm in aerodynamic diameter) was associated with 0.31% (95% confidence interval [CI] 0.15%–0.46%, P < 0.001) and 0.19% (0.11%–0.30%, P < 0.001) increases in hospital admissions for pneumonia, respectively. The effects of PM₁₀ were stronger in cities with higher temperatures (percentage increase, 0.031%; 95% CI 0.003%–0.058%; P = 0.026) and relative humidity (percentage increase, 0.011%; 95% CI 0%–0.022%; P = 0.045), as well as in the elderly (percentage increase, 0.10% [95% CI 0.02%–0.19%] for people aged 18–64 years versus 0.32% [95% CI 0.22%–0.39%] for people aged ≥75 years; P < 0.001). The main limitation of the present study was the unavailability of data on individual exposure to PM pollution. Our findings suggest that there are significant short-term associations between ambient PM levels and increased hospital admissions for pneumonia in Chinese adults. These findings support the rationale that further limiting PM concentrations in China may be an effective strategy to reduce pneumonia-related hospital admissions.

Background: Knee osteoarthritis (KOA) provides many challenges on the healthcare system. However, few studies have reported the epidemiology, particularly in a large population. Our study aimed to estimate the prevalence, incidence, trends, and patterns of diagnosed KOA in China. Methods: This was a longitudinal study. We used health insurance claims of 17.7 million adults from 2008–2017 to identify people with KOA. Trends in prevalence and incidence were analyzed using joinpoint regression. Results: We identified 2,447,990 people with KOA in Beijing, 60% of which were women. The 10-year average age-standardized prevalence and incidence of KOA was, respectively, 4.6% and 25.2 per 1000 person-years. Prevalence increased with age, surging after 55 years old. The average crude prevalence was 13.2% for people over 55 years old. The prevalence showed an increasing trend from 2008 to 2017, including a period of rapid rise from 2008 to 2011 (p < 0.05); the increase in prevalence was greatest in people under 35 years old (p < 0.05). Conclusion: Our analyses showed that the annual prevalence rate of KOA increased significantly from 2008 to 2017 in China. We need to increase our attention to women and the elderly over 55 years old, and also be alert to the younger trend of incidence of KOA.

To explore the multimorbidity prevalence and patterns among middle-aged and older adults from China. Data on thirteen chronic diseases were collected from 2,097,150 participants aged over 45 years between January 1st 2011 and December 31st 2015 from Beijing Medical Claim Data for Employees. Association rule mining and hierarchical cluster analysis were applied to assess multimorbidity patterns. Multimorbidity prevalence was 51.6% and 81.3% in the middle-aged and older groups, respectively. The most prevalent disease pair was that of osteoarthritis and rheumatoid arthritis (OARA) with hypertension (HT) (middle-aged: 22.5%; older: 41.8%). Ischaemic heart disease (IHD), HT, and OARA constituted the most common triad combination (middle-aged: 11.0%; older: 31.2%). Among the middle-aged group, the strongest associations were found in a combination of cerebrovascular disease (CBD), OARA, and HT with IHD in males (lift = 3.49), and CBD, OARA, and COPD with IHD in females (lift = 3.24). Among older patients, glaucoma and cataracts in females (lift = 2.95), and IHD, OARA, and glaucoma combined with cataracts in males (lift = 2.45) were observed. Visual impairment clusters, a mixed cluster of OARA, IHD, COPD, and cardiometabolic clusters were detected. Multimorbidity is prevalent among middle-aged and older Chinese individuals. The observations of multimorbidity patterns have implications for improving preventive care and developing appropriate guidelines for morbidity treatment.

Background: Modernizing medical education by using artificial intelligence and other new technologies to improve the clinical thinking ability of medical students is an important research topic in recent years. Prominent medical universities are actively conducting research and exploration in this area. In particular, given the shortage of human resources, the need to maintain social distancing to prevent the spread of the epidemics, and the increase in the cost of medical education, it is critical to harness online learning to promote medical education. A virtual case learning system that uses natural language processing technology to process and present a hospital’s real medical records and evaluate student responses can effectively improve medical students’ clinical thinking abilities. Objective: The purpose of this study is to develop a virtual case system, AIteach, based on actual complete hospital medical records and natural language processing technology, and achieve clinical thinking ability improvement through a contactless, self-service, trial-and-error system application. Methods: Case extraction is performed on a hospital’s case data center and the best-matching cases are produced through natural language processing, word segmentation, synonym conversion, and sorting. A standard clinical questioning data module, virtual case data module, and student learning difficulty module are established to achieve simulation. Students can view the objective examination and inspection data of actual cases, including details of the consultation and physical examination, and automatically provide their learning response via a multi-dimensional evaluation system. In order to assess the changes in students’ clinical thinking after using AIteach, 15 medical graduate students were subjected to two simulation tests before and after learning through the virtual case system. The tests, which included the full-process case examination of cases having the same difficulty level, examined core clinical thinking test points such as consultation, physical examination, and disposal, and generated multi-dimensional evaluation indicators (rigor, logic, system, agility, and knowledge expansion). Thus, a complete and credible evaluation system is developed. Results: The AIteach system used an internal and external double-cycle learning model. Students collect case information through online inquiries, physical examinations, and other means, analyze the information for feedback verification, and generate their detailed multi-dimensional clinical thinking after learning. The feedback report can be evaluated and its knowledge gaps analyzed. Such learning based on real cases is in line with traditional methods of disease diagnosis and treatment, and addresses the practical difficulties in reflecting actual disease progression while keeping pace with recent research. Test results regarding short-term learning showed that the average score (P < 0.01) increased from 69.87 to 85.6, the five indicators of clinical thinking evaluation improved, and there was obvious logical improvement, reaching 47%. Conclusion: By combining real cases and natural language processing technology, AIteach can provide medical students (including undergraduates and postgraduates) with an online learning tool for clinical thinking training. Virtual case learning helps students to cultivate clinical thinking abilities even in the absence of clinical tutor, such as during pandemics or natural disasters.