Effect of active warming on perioperative cardiovascular outcomes: a systematic review and meta-analysis of randomized controlled trials.

PURPOSE: The objective of this study was to provide an updated review on the active warming effects on major adverse cardiac events, 30-day all-cause mortality, and myocardial injury after noncardiac surgery. METHOD: We systematically searched MEDLINE, EMBASE, CINAHL, Cochrane CENTRAL, Web of Science, and Chinese BioMedical Literature Database. We included randomized controlled trials of adult population undergoing noncardiac surgeries that concentrate on the comparison of active warming methods and passive thermal management. Cochrane Collaboration's tool was applied for risk-of-bias assessment. We used trial sequential analysis to evaluate the possibility of false positive or negative results. RESULTS: A total of 13,316 unique records were identified, of which only 19 with reported perioperative cardiovascular outcomes were included in the systematic review and nine of them were included in final meta-analysis. No statistically significant difference between active warming methods and routine care was found in major adverse cardiac events (RR 0.56, 95% confidence interval (CI) 0.14-2.21, I2 = 71%, number of events 59 vs. 70), 30-day all-cause mortality (RR 0.81, 95% CI 0.43-1.54, I2 = 0%, number of events 17 vs. 21), and myocardial injury after noncardiac surgery (RR 0.61, 95% CI 0.17-2.22, I2 = 79%, number of events 236 vs. 234). Trial sequential analysis suggests that current trials did not reach the minimum information size regarding the major cardiovascular events. CONCLUSIONS: Compared to routine perioperative care, we found that active warming methods are not necessary for cardiovascular prevention in patients undergoing noncardiac surgery.

Relationship between the duration of smoking and blood pressure in Han and ethnic minority populations: a cross-sectional study in China.

BACKGROUND: Evidence for correlation between the cigarette use and blood pressure change remains ambiguous. This study modelled relationship between the duration of smoking and systolic blood pressure in a large national multi-ethnic cross-sectional survey in China. METHODS: Participants were selected through a multi-stage probability sampling procedure from 2012 to 2017. Former or current smokers were included in this study, whose smoking behaviour, blood pressure, and other demographic information were collected and measured through a face-to-face interview. Linear and non-linear relationships between the duration of smoking and systolic blood pressure were analysed and differences of the association between Han and minority populations were specially checked. RESULTS: A total of 8801 participants were enrolled in this study. Prevalence of hypertension was 41.3 and 77.8% were current smokers. For every additional year of smoking duration, systolic blood pressure raised by 0.325 mmHg (95% CI 0.296 to 0.354 mmHg, P <  0.001). The Chinese minority populations may suffer more from the elevated blood pressure in long-term smoking than Han populations (0.283 mmHg (95% CI 0.252 to 0.314 mmHg, P <  0.001) versus 0.450 mmHg (95% CI 0.380 to 0.520 mmHg, P <  0.001) raise in systolic blood pressure with each additional year of smoking in minority and Han populations). CONCLUSIONS: Smoking is associated with raised systolic blood pressure in Chinese population. This association is notedly stronger in Chinese minority populations.

[Nucleotide-binding Oligomerization Domain-like Receptor Family Pyrin Domain Containing 3 Inflammasome in Alzheimer's Disease].

Alzheimer's disease(AD)is a chronic neurodegenerative disease whose cause remains unclear.The ß-amyloid plaques in the brain are one of the major pathological features of AD.However,the drugs targeting extracellular ß-amyloid plaques have failed to cure the disease.Innate immunity and neuroinflammation play a role in the pathogenesis and progression of AD.As the macrophages existing in the central nervous system,microglia are related with extracellular ß-amyloid deposition,intracellular neurofibrillary tangle formation,and neuron injury.Accumulating evidence demonstrates that the activation of nucleotide-binding oligomerization domain-like receptor family pyrin domain containing 3(NLRP3)inflammasome in microglia plays a role in AD,suggesting new therapeutic target for AD in this signaling pathway.This article reviewed the studies about the activation and regulation of NLRP3 inflammasome in the pathogenesis and progression of AD as well as the development of AD therapies targeting this pathway,aiming to provide reference for further studies in this field.

Global competence of medical students: An assessment scale and preliminary investigation in China.

INTRODUCTION: The importance of global competence has been acknowledged in medical care as well as medical education. This study aims to develop a scale assessing the global competence of medical students, determine the factor structure and internal consistency of the scale and explore the underlying factors influencing the global competence of Chinese medical students in 8-year programs. METHODS: A questionnaire (Global Competence Assessment Scale for Medical Students, MS-GCAS) was developed, and a cross-sectional multicenter survey was conducted in 1062 medical students from 10 medical schools in China. Questionnaire data were analyzed using exploratory factor analysis and multiple linear regression. RESULTS: The exploratory factor analysis revealed a three-factor scale. The MS-GCAS has good internal consistency (Cronbach's alpha = 0.79 to 0.87). In the multivariate regression analyses, medical education stage (p<0.05), the frequency of communicating with foreigners (p<0.001), multilingual ability (p<0.05) and grade level (p<0.05) are associated with the MS-GCAS scores. DISCUSSION: The MS-GCAS has the potential to serve as a tool to measure the global competence of medical students. This three-factor scale can be used by medical education researches to improve future versions. Medical schools should conduct further educational reforms to promote students' global competence.

Automated medical literature screening using artificial intelligence: a systematic review and meta-analysis.

OBJECTIVE: We aim to investigate the application and accuracy of artificial intelligence (AI) methods for automated medical literature screening for systematic reviews. MATERIALS AND METHODS: We systematically searched PubMed, Embase, and IEEE Xplore Digital Library to identify potentially relevant studies. We included studies in automated literature screening that reported study question, source of dataset, and developed algorithm models for literature screening. The literature screening results by human investigators were considered to be the reference standard. Quantitative synthesis of the accuracy was conducted using a bivariate model. RESULTS: Eighty-six studies were included in our systematic review and 17 studies were further included for meta-analysis. The combined recall, specificity, and precision were 0.928 [95% confidence interval (CI), 0.878-0.958], 0.647 (95% CI, 0.442-0.809), and 0.200 (95% CI, 0.135-0.287) when achieving maximized recall, but were 0.708 (95% CI, 0.570-0.816), 0.921 (95% CI, 0.824-0.967), and 0.461 (95% CI, 0.375-0.549) when achieving maximized precision in the AI models. No significant difference was found in recall among subgroup analyses including the algorithms, the number of screened literatures, and the fraction of included literatures. DISCUSSION AND CONCLUSION: This systematic review and meta-analysis study showed that the recall is more important than the specificity or precision in literature screening, and a recall over 0.95 should be prioritized. We recommend to report the effectiveness indices of automatic algorithms separately. At the current stage manual literature screening is still indispensable for medical systematic reviews.

Automation of literature screening using machine learning in medical evidence synthesis: a diagnostic test accuracy systematic review protocol.

BACKGROUND: Systematic review is an indispensable tool for optimal evidence collection and evaluation in evidence-based medicine. However, the explosive increase of the original literatures makes it difficult to accomplish critical appraisal and regular update. Artificial intelligence (AI) algorithms have been applied to automate the literature screening procedure in medical systematic reviews. In these studies, different algorithms were used and results with great variance were reported. It is therefore imperative to systematically review and analyse the developed automatic methods for literature screening and their effectiveness reported in current studies. METHODS: An electronic search will be conducted using PubMed, Embase, ACM Digital Library, and IEEE Xplore Digital Library databases, as well as literatures found through supplementary search in Google scholar, on automatic methods for literature screening in systematic reviews. Two reviewers will independently conduct the primary screening of the articles and data extraction, in which nonconformities will be solved by discussion with a methodologist. Data will be extracted from eligible studies, including the basic characteristics of study, the information of training set and validation set, and the function and performance of AI algorithms, and summarised in a table. The risk of bias and applicability of the eligible studies will be assessed by the two reviewers independently based on Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). Quantitative analyses, if appropriate, will also be performed. DISCUSSION: Automating systematic review process is of great help in reducing workload in evidence-based practice. Results from this systematic review will provide essential summary of the current development of AI algorithms for automatic literature screening in medical evidence synthesis and help to inspire further studies in this field. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020170815 (28 April 2020).