ObjectiveTo systematically evaluate the risk prediction model of knee osteoarthritis (KOA). MethodsThe CNKI, WanFang Data, VIP, PubMed, Embase, Web of Science and Cochrane Library databases were electronically searched to collect relevant studies on KOA’s risk prediction model from inception to April, 2024. After study screening and data extraction by two independent researchers, the PROBAST bias risk assessment tool was used to evaluate the bias risk and applicability of the risk prediction model. ResultsA total of 12 studies involving 21 risk prediction models for KOA were included. The number of predictors ranged from 3 to 12, and the most common predictors were age, sex, and BMI. The range of modeling AUC included in the model was 0.554-0.948, and the range of testing AUC was 0.6-0.94. The overall predictive performance of the models was mediocre and the risk of overall bias was high, and more than half of the models were not externally verified. ConclusionAt present, the overall quality and applicability of the KOA morbidity risk prediction model still have great room for improvement. Future modeling should follow the CHARMS and PROBAST to reduce the risk of bias, explore the combination of multiple modeling methods, and strengthen the external verification of the model.
ObjectiveTo investigate the value of plasma microRNA-216 (miR-216) in patients with acute pancreatitis as a clinical biomarker to early identify severe acute pancreatitis (SAP).MethodsPatients with acute pancreatitis who admitted to the hospital within 48 hours after the onset of disease between September and November 2014 were enrolled in this study. Plasam and clinical data of all the patients were collected. MiR-216 in the plasma was detected using quantitative real time-polymerase chain reaction.ResultsA total of 25 patients were enrolled. The Ct value of plasma miR-216 in SAP patients (32.40±1.43) was significantly upregulated than mild acute pancreatitis (MAP) (35.85±1.91, P<0.05) and moderately severe acute pancreatitis (MSAP) patients (35.90±2.44,P<0.05), respectively. The area under receiver operating characteristic curve for plasmamiR-216 in predicting SAP was 0.792 (P<0.05), which did not differ much from other conventional parameters such as C-reactive protein, urinary nitrogen, and cytokines (P>0.05).ConclusionPlasma miR-216 is significantly upregulated in SAP patients compared with MAP and MSAP, but it shows no inferior efficiency than the investigated conventional predictors in predicting SAP.