Establishment and external validation of a nomogram for predicting 28-day mortality in patients with skull fracture
BackgroundSkull fracture can lead to significant morbidity and mortality, yet the development of effective predictive tools has remained a challenge. This study aimed to establish and validate a nomogram to evaluate the 28-day mortality risk among patients with skull fracture.Materials and methodsDa...
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Frontiers Media S.A.
2024-01-01
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| Series: | Frontiers in Neurology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fneur.2023.1338545/full |
| _version_ | 1827383183804465152 |
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| author | Jia Tang Zhenguang Zhong Muyesai Nijiati Changdong Wu |
| author_facet | Jia Tang Zhenguang Zhong Muyesai Nijiati Changdong Wu |
| author_sort | Jia Tang |
| collection | DOAJ |
| description | BackgroundSkull fracture can lead to significant morbidity and mortality, yet the development of effective predictive tools has remained a challenge. This study aimed to establish and validate a nomogram to evaluate the 28-day mortality risk among patients with skull fracture.Materials and methodsData extracted from the Medical Information Mart for Intensive Care (MIMIC) database were utilized as the training set, while data from the eICU Collaborative Research Database were employed as the external validation set. This nomogram was developed using univariate Cox regression, best subset regression (BSR), and the least absolute shrinkage and selection operator (LASSO) methods. Subsequently, backward stepwise multivariable Cox regression was employed to refine predictor selection. Variance inflation factor (VIF), akaike information criterion (AIC), area under the receiver operating characteristic curve (AUC), concordance index (C-index), calibration curve, and decision curve analysis (DCA) were used to assess the model's performance.ResultsA total of 1,527 adult patients with skull fracture were enrolled for this analysis. The predictive factors in the final nomogram included age, temperature, serum sodium, mechanical ventilation, vasoactive agent, mannitol, extradural hematoma, loss of consciousness and Glasgow Coma Scale score. The AUC of our nomogram was 0.857, and C-index value was 0.832. After external validation, the model maintained an AUC of 0.853 and a C-index of 0.829. Furthermore, it showed good calibration with a low Brier score of 0.091 in the training set and 0.093 in the external validation set. DCA in both sets revealed that our model was clinically useful.ConclusionA nomogram incorporating nine features was constructed, with a good ability in predicting 28-day mortality in patients with skull fracture. |
| first_indexed | 2024-03-08T14:36:29Z |
| format | Article |
| id | doaj.art-b04562bcecdc4d889122970d4ec66b78 |
| institution | Directory Open Access Journal |
| issn | 1664-2295 |
| language | English |
| last_indexed | 2024-03-08T14:36:29Z |
| publishDate | 2024-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neurology |
| spelling | doaj.art-b04562bcecdc4d889122970d4ec66b782024-01-12T04:43:16ZengFrontiers Media S.A.Frontiers in Neurology1664-22952024-01-011410.3389/fneur.2023.13385451338545Establishment and external validation of a nomogram for predicting 28-day mortality in patients with skull fractureJia Tang0Zhenguang Zhong1Muyesai Nijiati2Changdong Wu3Graduate School of Xinjiang Medical University, Ürümqi, ChinaDepartment of Bioengineering, Imperial College London, London, United KingdomXinjiang Emergency Center, People's Hospital of Xinjiang Uygur Autonomous Region, Ürümqi, ChinaXinjiang Emergency Center, People's Hospital of Xinjiang Uygur Autonomous Region, Ürümqi, ChinaBackgroundSkull fracture can lead to significant morbidity and mortality, yet the development of effective predictive tools has remained a challenge. This study aimed to establish and validate a nomogram to evaluate the 28-day mortality risk among patients with skull fracture.Materials and methodsData extracted from the Medical Information Mart for Intensive Care (MIMIC) database were utilized as the training set, while data from the eICU Collaborative Research Database were employed as the external validation set. This nomogram was developed using univariate Cox regression, best subset regression (BSR), and the least absolute shrinkage and selection operator (LASSO) methods. Subsequently, backward stepwise multivariable Cox regression was employed to refine predictor selection. Variance inflation factor (VIF), akaike information criterion (AIC), area under the receiver operating characteristic curve (AUC), concordance index (C-index), calibration curve, and decision curve analysis (DCA) were used to assess the model's performance.ResultsA total of 1,527 adult patients with skull fracture were enrolled for this analysis. The predictive factors in the final nomogram included age, temperature, serum sodium, mechanical ventilation, vasoactive agent, mannitol, extradural hematoma, loss of consciousness and Glasgow Coma Scale score. The AUC of our nomogram was 0.857, and C-index value was 0.832. After external validation, the model maintained an AUC of 0.853 and a C-index of 0.829. Furthermore, it showed good calibration with a low Brier score of 0.091 in the training set and 0.093 in the external validation set. DCA in both sets revealed that our model was clinically useful.ConclusionA nomogram incorporating nine features was constructed, with a good ability in predicting 28-day mortality in patients with skull fracture.https://www.frontiersin.org/articles/10.3389/fneur.2023.1338545/fullskull fracturehead traumaprognosisnomogramprediction model |
| spellingShingle | Jia Tang Zhenguang Zhong Muyesai Nijiati Changdong Wu Establishment and external validation of a nomogram for predicting 28-day mortality in patients with skull fracture Frontiers in Neurology skull fracture head trauma prognosis nomogram prediction model |
| title | Establishment and external validation of a nomogram for predicting 28-day mortality in patients with skull fracture |
| title_full | Establishment and external validation of a nomogram for predicting 28-day mortality in patients with skull fracture |
| title_fullStr | Establishment and external validation of a nomogram for predicting 28-day mortality in patients with skull fracture |
| title_full_unstemmed | Establishment and external validation of a nomogram for predicting 28-day mortality in patients with skull fracture |
| title_short | Establishment and external validation of a nomogram for predicting 28-day mortality in patients with skull fracture |
| title_sort | establishment and external validation of a nomogram for predicting 28 day mortality in patients with skull fracture |
| topic | skull fracture head trauma prognosis nomogram prediction model |
| url | https://www.frontiersin.org/articles/10.3389/fneur.2023.1338545/full |
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