ObjectiveTo systematically review the risk prediction model of intensive care unit (ICU) readmissions. MethodsCNKI, WanFang Data, VIP, CBM, PubMed, EMbase, Web of Science and The Cochrane Library databases were electronically searched to collect the related studies on risk prediction models of ICU readmissions from inception to June 12th, 2022. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies; then, the qualitative systematic review was performed. ResultsA total of 15 studies involving 23 risk prediction models were included. The area under the ROC curve of the models was 0.609-0.924. The most common five predictors of the included model were age, length of ICU hospitalization, heart rate, respiration, and admission diagnosis. ConclusionThe overall prediction performance of the risk prediction model of ICU readmissions is good; however, there are differences in research types and outcomes, and the clinical value of the model needs to be further studied.
ObjectiveExplore the impact of a digital-intelligence-based quality control platform for thyroid cancer on the effectiveness of clinical diagnosis and treatment quality management. MethodsThe digital-intelligence-based quality control platform for thyroid cancer at Zhejiang Provincial People’s Hospital was launched at the end of July 2022. In its initial phase, six quality control indicators related to the standardized diagnosis and treatment of thyroid cancer were deployed. This study analyzed the changes in these six quality control indicators between January 2022 and November 2023, comparing data before and after the platform’s implementation. ResultsCompared with the period from January to July 2022 (prior to the platform’s launch), the rates of preoperative cytopathological examination (t=–8.490, P<0.001) and postoperative pTNM staging for thyroid cancer patients (t=–3.027, P=0.013) increased from July to November 2023 (one year post-launch). However, the proportion of minimally invasive surgeries among thyroid cancer patients (t=4.085, P=0.002) decreased. The linear regression model results indicated that, following the platform’s launch, there was a gradual increase over time in both the preoperative cytopathological examination rate for thyroid cancer (standard β=0.765, P=0.001) and the postoperative pTNM staging rate (standard β=0.499, P=0.049). ConclusionPreliminary results of this study suggest that the thyroid cancer digital-intelligence-based quality control platform developed by our team can effectively enhance the standardized quality control of clinical diagnosis and treatment for thyroid cancer.