Development and validation of a nomogram for predicting pulmonary embolism in patients with pulmonary tuberculosis

Background: The coexistence of pulmonary tuberculosis (PTB) and pulmonary embolism (PE) is an uncommon clinical condition, and its rarity is associated with a high mortality rate, underscoring the critical importance of early diagnosis. The purpose of this study is to develop and validate a nomogram model for predicting risk of PE in patients with PTB. Methods: We included 694 patients with PTB in the development cohort and 236 patients in the validation cohort from another center. A prediction model was established based on independent risk factors. The nomogram's performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC), calibration curve analysis, and decision curve analysis (DCA). Results: D-dimer, age, tumor, chest pain, dyspnea, and surgery were independent risk factors for PTB with PE, and a nomogram model was established to predict PTB with PE. The AUC of the development and validation cohort model was 0.903 and 0.821. The calibration curves for both cohorts showed that the probabilities predicted by the model were very close to the actual probabilities. The DCA also demonstrated that the nomogram model showed significant clinical application value. Conclusions: The risk factor-related nomogram model identified in this study has a high predictive accuracy and provides a clinical application for assessing the risk of PE in patients with tuberculosis.