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Development and Internal Validation of a Predictive Nomogram for Assessing Rhabdomyolysis Risk After Wasp Stings: A
Xiaoyan Xian1, Guoqiang Chen2, Jianping Hu3
1Department of Emergency Medicine, Laboratory of Emergency Medicine, West China Hospital, and Disaster Medical Center, Sichuan University, Chengdu 610041, Sichuan, China, scu.edu.cn.
Emergency Medicine International
|July 30, 2026
Summary
A new nomogram predicts rhabdomyolysis risk after wasp stings. This tool uses clinical variables to identify patients needing early intervention for better outcomes.
Area of Science:
- Toxicology
- Clinical Prediction Modeling
- Epidemiology
Background:
- Wasp venom-induced rhabdomyolysis (RM) presents a significant clinical challenge with poor prognoses.
- Existing predictive models for RM following wasp stings are insufficient.
Purpose of the Study:
- To develop and internally validate a clinical prediction model for RM in wasp sting patients.
- To identify key predictors for early RM risk assessment.
Main Methods:
- A multicenter retrospective cohort study of 607 patients with wasp stings.
- Least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression identified predictors.
- A nomogram was constructed and validated using discrimination and decision curve analysis (DCA).
Main Results:
- 178 out of 607 patients (29.3%) developed RM.
- Nine predictors were identified: age, sting species, number of stings, tea-colored urine, WBC, LDH, TBIL, APTT, and month of injury.
- The nomogram demonstrated excellent predictive performance (AUC: 0.949, C-index: 0.948) with good clinical utility.
Conclusions:
- A validated nomogram using readily available clinical variables enables early prediction of RM risk post-wasp sting.
- This model aids in identifying high-risk individuals for timely management and improved patient outcomes.