目的：比较肝胆手术后两种腹腔引流管的应用效果。方法：将我院2005年5月～2007年3月间行肝脏手术病人106例随机分为实验组(57例)和对照组（49例），实验组采用自制双套管持续负压冲洗引流，对照组采用传统的单腔腹腔引流管引流，分析、比较两组引流的疗效。结果：采用双套管负压冲洗引流的病人发生引流管堵塞3例，隔下感染及积液4例，采用传统的单腔腹腔引流管引流的病人发生引流管堵塞12例，隔下感染及积液15例，差异有统计学意义（Ｐ＜0.05）。结论：肝脏手术后应用双套管持续负压冲洗引流在防止引流管堵塞、隔下感染疗效优于传统的单腔腹腔引流管引流。
Objective To investigate the methodological characteristics of observational studies on the correlation between drug exposure during pregnancy and birth defects. Methods The PubMed database was searched from January 1, 2020 to December 31, 2020 to identify observational studies investigating the correlation between drug use during pregnancy and birth defects. Literature screening and data extraction were conducted by two researchers and statistical analysis was performed using R 3.6.1 software. Results A total of 40 relevant articles were identified, of which 8 (20.0%) were published in the four major medical journals and their sub-journals, 21 (42.5%) were conducted in Europe and the United States, and 4 were conducted (10.0%) in China. Cohort studies (30, 75.0%) and case-control studies (10, 25%) were the most commonly used study designs. Sixteen studies (40.0%) did not specify how the databases were linked. Sixteen studies (40.0%) did not report a clear definition of exposure, while 17 studies (42.5%) defined exposure as prescribing a drug that could not be guaranteed to have been taken by the pregnant women, possibly resulting in misclassification bias. Six studies (15.0%) did not report the diagnostic criteria for birth defects and 18 studies (45.0%) did not report the types of birth defects. In addition, 33 studies (82.5%) did not control for confounding factors in the study design, while only 19 studies (47.5%) considered live birth bias. Conclusion Improvements are imperative in reporting and conducting observational studies on the correlation between drug use during pregnancy and birth defects. This includes the methods for linking data sources, definition of exposure and outcomes, and control of confounding factors. Methodological criteria are needed to improve the quality of these studies to provide higher quality evidence for policymakers and researchers.
ObjectiveTo explore the utilization of longitudinal data in constructing non-time-varying outcome prediction models and to compare the impact of different modeling approaches on prediction performance. MethodsClinical predictors were selected using univariate analysis and Lasso regression. Non-time-varying outcome prediction models were developed based on latent class trajectory analysis, the two-stage model, and logistic regression. Internal validation was performed using Bootstrapping resampling, and model performance was evaluated using ROC curves, PR curves, sensitivity, specificity and other relevant metrics. ResultsA total of 49 629 pregnant women were included in the study, with mean age of 31.42±4.13 years and pre-pregnancy BMI of 20.91±2.62kg/m². Fourteen predictors were incorporated into the final model. Prediction models utilizing longitudinal data demonstrated high accuracy, with AUROC values exceeding 0.90 and PR-AUC values greater than 0.47. The two-stage model based on late-pregnancy hemoglobin data showed the best performance, achieving AUROC of 0.93 (95%CI 0.92 to 0.94) and PR-AUC of 0.60 (95%CI 0.56 to 0.64). Internal validation confirmed robust model performance, and calibration curves indicated a good agreement between predicted and observed outcomes. ConclusionFor the longitudinal data, the two-stage model can well capture the dynamic change trajectory of the longitudinal data. For different clinical outcomes, the predictive value of repeated measurement data is different.
The use of repeated measurement data from patients to improve the classification ability of prediction models is a key methodological issue in the current development of clinical prediction models. This study aims to investigate the statistical modeling approach of the two-stage model in developing prediction models for non-time-varying outcomes using repeated measurement data. Using the prediction of the risk of severe postpartum hemorrhage as a case study, this study presents the implementation process of the two-stage model from various perspectives, including data structure, basic principles, software utilization, and model evaluation, to provide methodological support for clinical investigators.
ObjectiveBased on the requirements of the era of big medical data and discipline development, this study aimed to enhance the clinical research capabilities of medical postgraduates by exploring and evaluating some teaching innovations. MethodsA research-oriented clinical research design course was developed for postgraduate students, focusing on enhancing their clinical research abilities. Innovative teaching content and methods were implemented, and a questionnaire survey was conducted to assess the effectiveness of the teaching innovations among clinical medical master's students. ResultsA total of 699 clinical medical master's students completed the survey questionnaire. 94% of students expressed satisfaction with the course, 96% believed that the relevant knowledge covered in the course met the requirements of clinical research, 94% felt that their research capabilities had improved after completing the course, and 99% believed that the course helped them publish academic papers and complete their master's theses. ConclusionStudents recognized the teaching innovations in the course, which stimulated their initiative and enthusiasm for learning, improved the teaching quality of the course, and enhanced the research capabilities of the students.
Evidence synthesis is the process of systematically gathering, analyzing, and integrating available research evidence. The quality of evidence synthesis depends on the quality of the original studies included. Validity assessment, also known as risk of bias assessment, is an essential method for assessing the quality of these original studies. Currently, there are numerous validity assessment tools available, but some of them lack a rigorous development process and evaluation. The application of inappropriate validity assessment tools to assessing the quality of the original studies during the evidence synthesis process may compromise the accuracy of study conclusions and mislead the clinical practice. To address this dilemma, the LATITUDES Network, a one-stop resource website for validity assessment tools, was established in September 2023, led by academics at the University of Bristol, U.K. This Network is dedicated to collecting, sorting and promoting validity assessment tools to improve the accuracy of original study validity assessments and increase the robustness and reliability of the results of evidence synthesis. This study introduces the background of the establishment of the LATITUDES Network, the included validity assessment tools, and the training resources for the use of validity assessment tools, in order to provide a reference for domestic scholars to learn more about the LATITUDES Network, to better use the appropriate validity assessment tools to conduct study quality assessments, and to provide references for the development of validity assessment tools.