Development of a Nomogram Model to Predict in-Hospital Survival in Patients with Multiple Trauma.
COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022;
2022:7107063. [PMID:
35979040 PMCID:
PMC9377950 DOI:
10.1155/2022/7107063]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 07/19/2022] [Accepted: 07/22/2022] [Indexed: 11/17/2022]
Abstract
Background
Herein, we purposed to establish a nomogram model capable of assessing the probability of in-hospital survival in patients with multiple trauma.
Methods
Our retrospective study is associated with 286 multiple trauma patients with 21 variables from 2017 to 2021 in The Second Affiliated Hospital, Hengyang Medical School, University of South China. We performed the univariate and multivariate logistic regression analyses for investigating the risk factors of multiple trauma. Further, we constructed a novel nomogram model, and this nomogram was evaluated by a calibration plot. Based on the multivariate analysis or the nomogram prediction model, we calculated the risk score of each patient for multiple trauma. Moreover, we compared the survival probability between the high-risk score and low-risk score groups. Finally, we assessed the discrimination of the risk score by using the C-index and the time-dependent receiver operating characteristics (ROC) curve.
Results
Multivariate regression analysis revealed that the age and ISS scores were the independent risk factors, while the GCS score had protective effects on in-hospital survival. The high C-index and area under the curve (AUC) of the ROC curve confirmed reasonable discrimination for the multivariate analysis and the nomogram prediction model. Further, the calibration plot indicated reasonable accuracy of the nomogram predicting 30-day and 60-day survival probabilities.
Conclusion
The nomogram model established here has good predictive efficacy for in-hospital survival of patients with multiple injuries.
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