Objective To analyze the research hotspots and trends of Chinese literature on medical quality evaluation indicators in China in recent years. Methods We searched for relevant Chinese literature on medical quality evaluation indicators on China National Knowledge Infrastructure from January 2000 to December 2024, and analyzed the annual publication volume, authors and institutions, research hotspots and frontiers. Results Finally, 177 articles were included in the literature. From 2000 to 2024, the number of Chinese literature on medical quality evaluation indicators in China showed a fluctuating upward trend, reaching 15 articles per year in both 2015 and 2024. The issuing units mainly included the National Institute of Hospital Administration, the School of Public Health of Peking University, Huazhong University of Science and Technology, etc. The publishing team mainly included author teams such as MA Xiemin, LIANG Minghui, XIA Ping, etc. The high frequency keywords and top 10 keywords for centrality ranking included medical quality, evaluation indicators, indicator system, Delphi method, evaluation, evaluation system, quality evaluation, indicators, clinical pathways, and hospital management. “Case classification” was the earliest emerging term in the study of medical quality evaluation indicators. In terms of burst intensity, the top 5 keywords for burst intensity included Delphi method, case classification, problem, data quality, and evidence-based evaluation. Conclusion The publishing institutions and research teams of Chinese literature on medical quality evaluation indicators in China are relatively loose, and there are still problems such as insufficient practical application of medical quality evaluation indicators and single research tools and methods.
Objective To develop and validate a nomogram prediction model of early knee function improvement after total knee arthroplasty (TKA). Methods One hundred and sixty-eight patients who underwent TKA at Sichuan Province Orthopedic Hospital between January 2018 and February 2021 were prospectively selected to collect factors that might influence the improvement of knee function in the early postoperative period after TKA, and the improvement of knee function was assessed using the Knee Score Scale of the Hospital for Special Surgery (HSS) at 6 months postoperatively. The patients were divided into two groups according to the postoperative knee function improvement. The preoperative, intraoperative and postoperative factors were compared between the two groups; multiple logistic regression was performed after the potential factors screened by LASSO regression; then, a nomogram predictive model was established by R 4.1.3 language and was validated internally. Results All patients were followed up at 6 months postoperatively, and the mean HSS score of the patients increased from 55.19±8.92 preoperatively to 89.27±6.18 at 6 months postoperatively (t=−40.706, P<0.001). LASSO regression screened eight influencing factors as potential factors, with which the results of multiple logistic regression analysis showed that preoperative body mass index, etiology, preoperative joint mobility, preoperative HSS scores, postoperative lower limb force line, and postoperative analgesia were independent influencing factors for the improvement of knee function in the early postoperative period after TKA (P<0.05). A nomogram model was established based on the multiple logistic regression results, and the calibration curve showed that the prediction curve basically fitted the standard curve; the receiver operating characteristic curve showed that the area under the curve of the nomogram model for the prediction of suboptimal knee function in the early postoperative period after TKA was 0.894 [95% confidence interval (0.825, 0.963)]. Conclusions There is a significant improvement in knee function in patients after TKA, and the improvement of knee function in the early postoperative period after TKA is influenced by preoperative body mass index, etiology, and preoperative joint mobility, etc. The nomogram model established accordingly can be used to predict the improvement of knee function in the early postoperative period after TKA with a high degree of differentiation and accuracy.
