Development and Internal Validation of a Nomogram for Predicting Severe Complications After Snakebite: A Retrospective Cohort Study.
8 affiliations
- 1Department of Clinical Laboratory, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, People's Republic of China.
- 2Department of Burns and Plastic Surgery, Fourth Medical Centre of Chinese PLA General Hospital, Beijing, People's Republic of China.
- 3Medical College, Yan' an University, Yan'an, Shaanxi, People's Republic of China.
- 4Translational Medicine Centre of Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, People's Republic of China.
- 5Second Department of General Surgery, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, People's Republic of China.
- 6Department of Critical Care Medicine, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, People's Republic of China.
- 7Medical Administration Department of Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, People's Republic of China.
- 8Department of Information, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, People's Republic of China.
Abstract
Background
Snakebite envenomation is a global public health concern with high mortality and morbidity. Given the highly heterogeneous clinical progression and the potential for rapid deterioration in severe cases, early risk stratification is crucial for improving outcomes. This study aimed to develop a nomogram based on simple laboratory indicators to assist primary care clinicians in rapidly identifying high-risk patients, thereby optimizing interventions and reducing mortality and healthcare burden.Methods
We conducted a retrospective analysis of 10,505 snakebite envenomation cases admitted to the Medical Laboratory Center of Shaanxi Provincial People's Hospital between March 2014 and October 2025. After applying strict eligibility criteria, 2762 patients were randomly assigned to a training cohort (n=2072) and a validation cohort (n=690) at a 3:1 ratio. LASSO regression and multivariate logistic regression were used to identify independent risk factors for severe complications, which were then incorporated into a nomogram. Model performance was assessed by the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis (DCA).Results
Of the 2762 patients, 64 (2.32%) developed severe complications, most commonly acute myocardial injury, acute liver injury, coagulopathy, and multiple organ dysfunction; the majority presented with two or more. Time from bite to presentation (OR=1.017, 95% CI 1.005-1.027), white blood cell count (OR=1.116, 95% CI 1.043-1.190), and prothrombin time (OR=1.103, 95% CI 1.011-1.203) were identified as independent predictors. The nomogram demonstrated strong discrimination, with AUCs of 0.812 (95% CI 0.741-0.882) and 0.839 (95% CI 0.734-0.945) in the training and validation cohorts, respectively. Calibration was excellent (Hosmer-Lemeshow P>0.05), and decision curve analysis confirmed net clinical benefit.Conclusion
This readily accessible nomogram, based on time to presentation, WBC, and PT, demonstrates strong predictive performance, high operability, and clinical accessibility, facilitating early identification of high-risk patients and optimization of treatment decisions.
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BibTeX
@article{guan2026development,
title = {{Development and Internal Validation of a Nomogram for Predicting Severe Complications After Snakebite: A Retrospective Cohort Study.}},
author = {Jiahao Guan and Zhenkai Zhao and Fei Wang and Wenli Zhang and Xianglong Duan and Lixia Zhang and Zhenguo Liu and Liang Shan and Duo Dai and Zifan Lu},
journal = {International journal of general medicine},
year = {2026},
month = oct,
doi = {10.2147/ijgm.s640320},
url = {https://europepmc.org/article/MED/42928901},
note = {CC BY-NC},
}
RIS
TY - JOUR
TI - Development and Internal Validation of a Nomogram for Predicting Severe Complications After Snakebite: A Retrospective Cohort Study.
AU - Jiahao Guan
AU - Zhenkai Zhao
AU - Fei Wang
AU - Wenli Zhang
AU - Xianglong Duan
AU - Lixia Zhang
AU - Zhenguo Liu
AU - Liang Shan
AU - Duo Dai
AU - Zifan Lu
PY - 2026
DA - 2026/10/21
JO - International journal of general medicine
DO - 10.2147/ijgm.s640320
UR - https://europepmc.org/article/MED/42928901
AB - Background Snakebite envenomation is a global public health concern with high mortality and morbidity. Given the highly heterogeneous clinical progression and the potential for rapid deterioration in severe cases, early risk stratification is crucial for improving outcomes. This study aimed to develop a nomogram based on simple laboratory indicators to assist primary care clinicians in rapidly identifying high-risk patients, thereby optimizing interventions and reducing mortality and healthcare burden.Methods We conducted a retrospective analysis of 10,505 snakebite envenomation cases admitted to the Medical Laboratory Center of Shaanxi Provincial People's Hospital between March 2014 and October 2025. After applying strict eligibility criteria, 2762 patients were randomly assigned to a training cohort (n=2072) and a validation cohort (n=690) at a 3:1 ratio. LASSO regression and multivariate logistic regression were used to identify independent risk factors for severe complications, which were then incorporated into a nomogram. Model performance was assessed by the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis (DCA).Results Of the 2762 patients, 64 (2.32%) developed severe complications, most commonly acute myocardial injury, acute liver injury, coagulopathy, and multiple organ dysfunction; the majority presented with two or more. Time from bite to presentation (OR=1.017, 95% CI 1.005-1.027), white blood cell count (OR=1.116, 95% CI 1.043-1.190), and prothrombin time (OR=1.103, 95% CI 1.011-1.203) were identified as independent predictors. The nomogram demonstrated strong discrimination, with AUCs of 0.812 (95% CI 0.741-0.882) and 0.839 (95% CI 0.734-0.945) in the training and validation cohorts, respectively. Calibration was excellent (Hosmer-Lemeshow P>0.05), and decision curve analysis confirmed net clinical benefit.Conclusion This readily accessible nomogram, based on time to presentation, WBC, and PT, demonstrates strong predictive performance, high operability, and clinical accessibility, facilitating early identification of high-risk patients and optimization of treatment decisions.
SN - 1178-7074
ER -