Development of a Nomogram Model to Predict in-Hospital Survival in Patients with Multiple Trauma.
Journal
Computational and mathematical methods in medicine
ISSN: 1748-6718
Titre abrégé: Comput Math Methods Med
Pays: United States
ID NLM: 101277751
Informations de publication
Date de publication:
2022
2022
Historique:
received:
07
06
2022
revised:
19
07
2022
accepted:
22
07
2022
entrez:
18
8
2022
pubmed:
19
8
2022
medline:
20
8
2022
Statut:
epublish
Résumé
Herein, we purposed to establish a nomogram model capable of assessing the probability of in-hospital survival in patients with multiple trauma. 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. 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. The nomogram model established here has good predictive efficacy for in-hospital survival of patients with multiple injuries.
Sections du résumé
Background
UNASSIGNED
Herein, we purposed to establish a nomogram model capable of assessing the probability of in-hospital survival in patients with multiple trauma.
Methods
UNASSIGNED
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
UNASSIGNED
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
UNASSIGNED
The nomogram model established here has good predictive efficacy for in-hospital survival of patients with multiple injuries.
Identifiants
pubmed: 35979040
doi: 10.1155/2022/7107063
pmc: PMC9377950
doi:
Types de publication
Journal Article
Retracted Publication
Langues
eng
Sous-ensembles de citation
IM
Pagination
7107063Commentaires et corrections
Type : RetractionIn
Informations de copyright
Copyright © 2022 Lin Ling et al.
Déclaration de conflit d'intérêts
The authors declare that they have no conflicts of interest.
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