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PURPOSE: This study aimed to analyze the independent risk factors contributing to preoperative DVT in TKA and constructed a predictive nomogram to accurately evaluate its occurrence based on these factors. METHODS: The study encompassed 496 patients who underwent total knee arthroplasty at our hospital between June 2022 and June 2023. The dataset was randomly divided into a training set (n = 348) and a validation set (n = 148) in a 7:3 ratio. The least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression analysis were used to screen the predictors of preoperative DVT occurrence in TKA and construct a nomogram. The performance of the predictive models was evaluated using the concordance index (C-index), calibration curves, and the receiver operating characteristic (ROC) curves. Decision curve analysis was used to analyze the clinical applicability of nomogram. RESULTS: A total of 496 patients who underwent TKA were included in this study, of which 28 patients were examined for lower extremity DVT preoperatively. Platelet crit, Platelet distribution width, Procalcitonin, prothrombin time, and D-dimer were predictors of preoperative occurrence of lower extremity DVT in the nomograms of the TKA patients. In addition, the areas under the curve of the ROC of the training and validation sets were 0.935 (95%CI: 0.880-0.990) and 0.854 (95%CI: 0.697-1.000), and the C-indices of the two sets were 0.919 (95%CI: 0.860-0.978) and 0.900 (95%CI: 0.791-1.009). The nomogram demonstrated precise risk prediction of preoperative DVT occurrence in TKA as confirmed by the calibration curve and decision curve analysis. CONCLUSIONS: This Nomogram demonstrates great differentiation, calibration and clinical validity. By assessing individual risk, clinicians can promptly detect the onset of DVT, facilitating additional life monitoring and necessary medical interventions to prevent the progression of DVT effectively.
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Objective@#To examine mental health problems among adolescents in Taiyuan City and its relationship to chronotype, so as to give a scientific basis for supporting mental health of middle school students.@*Methods@#From October to November 2021, a total of 2 621 pupils were enrolled from three junior high schools and two senior high schools in Taiyuan by using a multi stage stratified cluster random sampling method to investigate demographic characteristics, mental health status, and chronotype. Chi squared test, Spearman correlation analysis and Logistic regression were used to analyze the relationship between sleep patterns and mental health problems in middle school students.@*Results@#The proportion of morning, intermediate and evening types of middle school students sleep were 17.9%, 65.6%, and 16.4%, respectively. The overall detection rate of mental health problems was 13.8 %, which was statistically significant among middle school students in different grades, self perceived family economic status, the number of friends and sleep patterns ( χ 2=42.69, 29.15, 46.02, 93.99, P <0.05). After adjusting for grade, self perceived family economic status and the number of friends, Logistic regression analysis revealed that mental health problems were positively associated with evening type ( OR =2.84) and negatively associated with morning type ( OR =0.61)( P ＜0.05).@*Conclusion@#Chronotype is associated with mental health problems among middle school students, with a higher risk for evening type and a lower risk for morning type. Mental health of middle school students can be enhanced by changing their chronotype.
