Nomogram model for prediction of pulmonary tuberculosis patients with intestinal tuberculosis

Background In clinical settings, pulmonary tuberculosis (PTB) patients were often found to have intestinal tuberculosis (ITB). The aim of this study was to construct a predictive model to evaluate the probability of intestinal tuberculosis in patients with pulmonary tuberculosis. Methods The present case-control study retrospectively collected information from 348 patients affected by PTB who received treatment from January 1, 2019 - August 1, 2023 at Changsha Central Hospital. The 348 patients were divided into ITB group and non-ITB group according to the presence or absence of intestinal tuberculosis. logistic regression analysis was performed and a nomogram was established using the selected predictors. Bootstrapping was performed for internal validation. Results Five variables [age, abdominal pain, diarrhoea, hemoglobin (HGB), albumin (ALB)] were validated and used to develop a predictive model which showed good discrimination capability [area under the curve (AUC) = 0.856]. The calibration curve demonstrated the best consistency between nomogram predictions and actual observations. In addition, Decision Curve Analysis (DCA) showed that the nomogram model is effective in clinical practice. Conclusions We developed a preliminary predictive model that can help assess the probability of intestinal tuberculosis in pulmonary tuberculosis patients. Its clinical utility requires further validation in multi-center, prospective studies. Clinical trial Not applicable.