Journal of Evidence‐Based Medicine最新文献

Objective: This study compares the safety and efficacy of general anesthesia (GA) and nongeneral anesthesia (non-GA) on functional outcomes in patients receiving endovascular therapy for ischemic stroke.

Methods: All available studies on the anesthetic management of patients with acute ischemic stroke in PubMed, the Cochrane Central Register of Controlled Trials, and Embase were included. We also compared the clinical outcomes in the studies with subgroup analyses of the occlusion site (anterior vs. posterior circulation) and preretriever group versus retriever group. Functional independence, mortality, successful recanalization, hemodynamic instability, intracerebral hemorrhage, and respiratory complications were considered primary or secondary outcomes.

Results: A total of 24,606 patients in 60 studies were included. GA had a lower risk of 90-day functional independence (OR = 0.67, 95% CI 0.58 to 0.77), higher risk of 90-day mortality (OR = 1.29; 95% CI 1.15 to 1.45), and successful reperfusion (OR = 1.18; 95% CI 1.94 to 6.82). However, there were no differences in functional independence and mortality between GA and non-GA at 90 days after the procedure.

Conclusion: The study shows poorer results in the GA group, which may be due to the inclusion of nonrandomized studies. However, analysis of the RCTs suggested that the outcomes do not differ between the two groups (GA vs. non-GA). Thus, general anesthesia is as safe as nongeneral anesthesia under standardized management.

Objective: Post-traumatic stress disorder (PTSD) is a prevalent condition characterized by prolonged psychological distress following traumatic events encompassing serious health threats, domestic abuse, and natural disasters. The onset and persistence of PTSD can be attributed to advanced age. This study aimed to explore the occurrence and influencing factors of enduring post-traumatic stress disorder (PTSD) in survivors aged 60 years and over in the main area of the 2008 Wenchuan earthquake 10 years after the disaster.

Methods: Data were collected using a multistage sampling method from individuals aged 60 years and older living in the main impacted areas of Wenchuan 10 years after the Wenchuan earthquake. The PTSD Checklist-Civilian Version (PCL-C) was used to evaluate PTSD symptoms. We evaluated participants based on their PTSD symptoms: those exhibiting and those without. The latter group was four times the size of the former and was matched based on gender and age (within ± 2 years). Conditional logistic regression was used to discern the risk factors.

Results: Out of the total, 56 participants were recognized as having probable PTSD as per the PCL-C checklist, leading to a rate of 9.4% (56/588). The univariate conditional logistic regression values showed that playing Mahjong/poker (odds ratio (OR) = 0.394, 95% confidence interval (CI) = 0.171-0.911) and displacement (OR = 0.446, 95% CI = 0.220-0.907) were protective factors for the long-term mental health of survivors in the hard-hit areas, while the presence of a 2-week illness (OR = 3.605, 95% CI = 1.751-7.424), possessing insurance (OR = 0.250, 95% CI = 0.072-0.864), suffering from a chronic ailment (OR = 3.132, 95% CI = 1.2-8.174), and having an injured family member (OR = 2.26, 95% CI = 1.136-4.496) emerged as risk factors for PTSD symptoms. Multivariate analysis indicated that the absence of insurance and prevalence of 2-week illness correlated with increased PTSD symptoms.

Conclusions: Ten years after the Wenchuan earthquake, the prevalence of probable PTSD remained significantly high in the elderly population. The major risk factors were the absence of insurance and the occurrence of a 2-week illness. Policymakers should incorporate these findings when devising strategies for aging societies.

Aim: To formulate the guideline for the development of diagnostic criteria for Chinese medicine syndromes, which can contribute to standardization of development of Chinese medicine syndrome diagnostic standards.

Methods: We embark into account on the development of Guideline on Establishing Diagnostic Criteria for Chinese Medicine Syndromes through Delphi method with reference to the existing technical system of diagnostic criteria for Chinese medicine syndromes and relevant criteria.

Results: Our guideline specifies principles, methods, and procedures for the formulation of diagnostic criteria for Chinese medicine syndromes.

Conclusions: It is a comprehensive and systematic evidence-based guideline, and we hope this guideline can be applied as a reference in developing diagnostic criteria for Chinese medicine syndromes in other disciplines. It is also applicable to the formulation of diagnostic criteria for relevant clinical, educational, and scientific research by hospitals, institutes, and academies.

Objective: Striking innovations and advancements have been achieved with the use of artificial intelligence and healthcare information technology being integrated into clinical real-world data. The current scoping review aimed to provide an overview of the current status of artificial intelligence-/information technology-based clinical decision support tools in China.

Methods: PubMed/MEDLINE, Embase, China National Knowledge Internet, and Wanfang data were searched for both English and Chinese literature. The gray literature search was conducted for commercially available tools. Original studies that focused on clinical decision support tools driven by artificial intelligence or information technology in China and were published between 2010 and February 2022 were included. Information extracted from each article was further synthesized by themes based on three types of clinical decision-making.

Results: A total of 37 peer-reviewed publications and 13 commercially available tools were included in the final analysis. Among them, 32.0% were developed for disease diagnosis, 54.0% for risk prediction and classification, and 14.0% for disease management. Chronic diseases were the most popular therapeutic areas of exploration, with particular emphasis on cardiovascular and cerebrovascular diseases. Single-center electronic medical records were the mainstream data sources leveraged to inform clinical decision-making, with internal validation being predominately used for model evaluation.

Conclusions: To effectively promote the extensive use of real-world data and drive a paradigm shift in clinical decision-making in China, multidisciplinary collaboration of key stakeholders is urgently needed.

Aim: To assess the performance of validated prediction models for acute respiratory distress syndrome (ARDS) by systematic review and meta-analysis.

Methods: Eight databases (Medline, CINAHL, Embase, The Cochrane Library, CNKI, WanFang Data, Sinomed, and VIP) were searched up to March 26, 2023. Studies developed and validated a prediction model for ARDS in adult patients were included. Items on study design, incidence, derivation methods, predictors, discrimination, and calibration were collected. The risk of bias was assessed by the Prediction model Risk of Bias Assessment Tool. Models with a reported area under the curve of the receiver operating characteristic (AUC) metric were analyzed.

Results: A total of 25 studies were retrieved, including 48 unique prediction models. Discrimination was reported in all studies, with AUC ranging from 0.701 to 0.95. Emerged AUC value of the logistic regression model was 0.837 (95% CI: 0.814 to 0.859). Besides, the value in the ICU group was 0.856 (95% CI: 0.812 to 0.899), the acute pancreatitis group was 0.863 (95% CI: 0.844 to 0.882), and the postoperation group was 0.835 (95% CI: 0.808 to 0.861). In total, 24 of the included studies had a high risk of bias, which was mostly due to the improper methods in predictor screening (13/24), model calibration assessment (9/24), and dichotomization of continuous predictors (6/24).

Conclusions: This study shows that most prediction models for ARDS are at high risk of bias, and the discrimination ability of the model is excellent. Adherence to standardized guidelines for model development is necessary to derive a prediction model of value to clinicians.