Risk factor analysis and nomogram model establishment for in-hospital death of elderly patients with surgically treated traumatic acute subdural hematoma.

The purpose of this study was to investigate the risk factors for in-hospital death in elderly patients with surgically treated traumatic acute subdural hematoma (ASDH) and to construct a nomogram model for in-hospital death risk prediction. We analyzed 104 elderly patients who underwent decompressive craniotomy (DC) for isolated traumatic ASDH between May 2013 and May 2021 in our department. Independent factors for in-hospital death were identified via univariate and multivariate logistic regression analyses, and a nomogram model was constructed and validated. The overall in-hospital mortality rate was 58.7% (61/104). Sex (odds ratio [OR] = 11.94), dilated pupils (bilateral vs absent; OR = 194.16) and subarachnoid hemorrhage (SAH) (OR = 16.01) were independent risk factors for in-hospital death. A nomogram model for in-hospital death risk prediction was constructed based on these variables. Statistical analysis revealed that this model had good predictive performance, and receiver operating characteristic (ROC) curve analysis revealed that the area under the curve (AUC) of the nomogram model was 0.916 (95% confidence interval [CI] = 0.861-0.970). The calibration plot, which compared the predicted effective rate and observed effective rate, revealed the accurate predictive ability of the model. The model was internally validated via 200 bootstrap samples to calculate the discrimination accuracy, and the concordance index was 0.891. Decision curve analysis (DCA) demonstrated that the nomogram was clinically beneficial. The most important risk factors for in-hospital death in elderly patients with surgically treated traumatic ASDH were sex, dilated pupils, and SAH. The nomogram constructed from these data could be a promising and convenient tool to predict in-hospital death risk, but further external validation is needed.