Objective To systematically review the predictive model of stroke-related pneumonia risk. Methods The CNKI, WanFang Data, CBM, PubMed, Web of Science, Embase, MEDLINE and Cochrane Library databases were electronically searched to collect studies on risk prediction models for stroke-associated pneumonia from inception to February 15, 2023. Two researchers independently screened the literature and extracted data. The risk of bias and applicability of the models were assessed using PROBAST. Results A total of 18 studies and 27 SAP risk prediction models were included. The AUC values for inclusion in the model ranged from 0.67 to 0.96, and the number of candidate predictors ranged from 4 to 25, with the most common predictors being age, NIHSS score, dysphagia, mRS score, and impaired consciousness (GCS score). Conclusion The overall predictive performance of SAP risk prediction models is good, but their predictive performance cannot be directly compared because of the differences in study type, study population, and SAP diagnostic criteria. Moreover, 72.3% of the models are not externally validated, and most of the studies have a high risk of bias.
ObjectiveTo systematically review the research status of competency evaluation systems of residents in China. MethodsThe CNKI, VIP, WanFang Data, PubMed, Embase and Web of Science databases were electronically searched to collect relevant literature on competency evaluation systems for residents in China from inception to December 2023. Two reviewers independently screened literature, extracted data and assessed the risk of bias of the included studies. The descriptive analysis was then performed. ResultsA total of 15 studies were included. There were 9 index construction methods involved in the included studies, the Delphi method was the most widely used (7 papers, 46.7%), followed by the questionnaire method (3 papers, 20%) and the expert consultation method (2 papers, 13.3%). The most common reference model was the ACGME Milestones (10 articles, 66.7%). According to the construction of index systems, the number of first-level indicators was at least 4 and at most 8. The minimum number of entries (number of final grading indicators) was 15 and the maximum number was 116. The index systems included in the research had a wide range of contents, covering all aspects of resident competencies. The expert teams consisted of clinical experts, nurses, administrators, college teachers, patients, residents, etc. ConclusionThere are various research methods for the competency evaluation systems of residents in China, and the research content is in line with international standards.