A prediction nomogram for mortality in patients following wasp stings: a retrospective study

Abstract

Numerous studies have shown that wasp stings can lead to serious, sometimes fatal, health outcomes. Predicting deaths associated with wasp stings remains challenging yet is of critical importance. This study was conducted to identify predictors and develop a visual model for predicting mortality following wasp stings. Clinical data from 486 patients were analyzed, dividing them into two groups: survival group (N = 435) and death group (N = 51). Various statistical methods were used to create a prognostic model, including one-way analysis, the least absolute shrinkage and selection operator (LASSO) regression, and binary logistic regression. The model’s accuracy was evaluated through ROC curves, calibration plots, and decision curve analysis (DCA). The study identified four key predictors of mortality: receiving more than 50 stings, having serum lactate dehydrogenase (LDH) levels of ≥ 2200 U/L, activated partial thromboplastin time (APTT) of ≥ 90 s, and the requirement for invasive mechanical ventilation within 24 h. These factors contributed to a model with an area under the ROC curve of 0.980 (95% CI: [0.968–0.992]), indicating high calibration and applicability. The decision curve analysis confirmed the model’s substantial net clinical benefit. Thus, the number of stings, serum LDH, APTT, and the need for early invasive mechanical ventilation are reliable, independent predictors of death among patients experiencing wasp stings. The developed predictive model exhibits high levels of accuracy, sensitivity, consistency, and practical use.