A nomogram model for poor surgical wound healing after the removal of thoracic and abdominal cavity drainage tube.

Abstract

Exploring the risk factors for poor surgical wound healing after the removal of thoracic and abdominal cavity drainage tube and constructing a nomogram model. We recruited 420 patients who underwent after the removal of thoracic and abdominal cavity drainage tube at Joint Logistic Support Force 921th Hospital from March 2021 to May 2024. A random number table method was utilized to allocate these patients into 2 cohorts for training (n = 294) and validation (n = 126), following a 7:3 ratio. Least absolute shrinkage and selection operator regression was applied to optimize the screening variables. Predictive models were developed using multifactorial logistic regression analysis with column line plots. Receiver operating characteristic curves, calibration curves, and Hosmer-Lemeshow goodness-of-fit tests were used to verify and evaluate the discrimination and calibration of the prediction models. Decision curve analysis was used to assess the clinical validity of the prediction models. Seven risk factors for predicting poor wound healing have been identified. This includes abnormal serum albumin, catheterization time, the volume of exudation during catheterization, duration of exudation, unplanned extubation, the volume of exudation after extubation, and incision infection. The Nomogram model demonstrated sufficient predictive accuracy, with area under the curve values of 0.930 (95% confidence interval: 0.890-0.970) and 0.948 (95% confidence interval: 0.888-1.000) in the training cohort and validation cohort, respectively. The calibration curve shows good consistency between the predicted risk of the model and the actual risk. The nomogram model established in this study for predicting poor surgical wound healing after the removal of thoracic and abdominal cavity drainage tube has good predictive value.