The Inflammation-Coagulation-Muscle Injury cascade: a clinically actionable nomogram for early mechanical ventilation prediction in tetanus

Objective This study aimed to develop and internally validate a nomogram model for predicting the risk of mechanical ventilation (MV) requirement in adult patients with tetanus, based on routine clinical and laboratory indicators, to facilitate early identification of high-risk patients and optimize allocation of critical care resources. Methods A retrospective cohort of 227 adult tetanus patients admitted to two largest tertiary hospitals in Southern Jiangxi between January 2012 and December 2024 was included. Patients were stratified into a MV group and a non-mechanical ventilation (NMV) group based on MV implementation. Independent predictors of MV requirement were identified through LASSO regression and multivariate logistic regression analyses. A nomogram prediction model was subsequently constructed. Internal validation was performed using the Bootstrap method with 1,000 resamples and 10-fold cross-validation. Model performance was comprehensively evaluated through ROC curves, calibration plots, and Decision Curve Analysis (DCA) to assess discrimination, calibration, and clinical utility. Results Five independent predictors of MV requirement were identified: age (OR = 1.032, 95% CI :1.011–1.054), chronic kidney disease (CKD,OR = 4.939, 95% CI :1.621–18.681), neutrophil count (NEUT,OR = 1.187, 95% CI :1.078–1.321), D-dimer (DD,OR = 1.089, 95% CI :1.019–1.182), and creatine kinase-MB (CK-MB,OR = 1.034, 95% CI :1.015–1.057). The nomogram demonstrated robust predictive performance, with AUC of 0.813 (95% CI :0.757–0.868), excellent calibration (mean absolute error = 0.029), and clinical net benefit across threshold probabilities of 0.1–0.8 confirmed by DCA. Conclusion We successfully developed a nomogram incorporating five readily available clinical parameters to predict MV risk in adult tetanus patients. The model exhibited favorable discrimination, calibration, and clinical utility, offering a practical tool for early risk stratification and targeted management of critical care resources. Future multicenter external validation is warranted to promote its clinical application.