An independently validated nomogram for individualised estimation of short-term mortality risk among patients with severe traumatic brain injury: a modelling analysis of the CENTER-TBI China Registry StudyResearch in context
Summary: Background: Severe traumatic brain injury (sTBI) is extremely disabling and associated with high mortality. Early detection of patients at risk of short-term (≤14 days after injury) death and provision of timely treatment is critical. This study aimed to establish and independently validat...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-05-01
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| Series: | EClinicalMedicine |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589537023001529 |
| _version_ | 1827957242158120960 |
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| author | Lijian Lang Tianwei Wang Li Xie Chun Yang Loren Skudder-Hill Jiyao Jiang Guoyi Gao Junfeng Feng |
| author_facet | Lijian Lang Tianwei Wang Li Xie Chun Yang Loren Skudder-Hill Jiyao Jiang Guoyi Gao Junfeng Feng |
| author_sort | Lijian Lang |
| collection | DOAJ |
| description | Summary: Background: Severe traumatic brain injury (sTBI) is extremely disabling and associated with high mortality. Early detection of patients at risk of short-term (≤14 days after injury) death and provision of timely treatment is critical. This study aimed to establish and independently validate a nomogram to estimate individualised short-term mortality for sTBI based on large-scale data from China. Methods: The data were from the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) China registry (between Dec 22, 2014, and Aug 1, 2017; registered at ClinicalTrials.gov, NCT02210221). This analysis included information of eligible patients with diagnosed sTBI from 52 centres (2631 cases). 1808 cases from 36 centres were enrolled in the training group (used to construct the nomogram) and 823 cases from 16 centres were enrolled in the validation group. Multivariate logistic regression was used to identify independent predictors of short-term mortality and establish the nomogram. The discrimination of the nomogram was evaluated using area under the receiver operating characteristic curves (AUC) and concordance indexes (C-index), the calibration was evaluated using calibration curves and Hosmer–Lemeshow tests (H-L tests). Decision curve analysis (DCA) was used to evaluate the net benefit of the model for patients. Findings: In the training group, multivariate logistic regression demonstrated that age (odds ratio [OR] 1.013, 95% confidence interval [CI] 1.003−1.022), Glasgow Coma Scale score (OR 33.997, 95% CI 14.657−78.856), Injury Severity Score (OR 1.020, 95% CI 1.009−1.032), abnormal pupil status (OR 1.738, 95% CI 1.178−2.565), midline shift (OR 2.266, 95% CI 1.378−3.727), and pre-hospital intubation (OR 2.059, 95% CI 1.472−2.879) were independent predictors for short-term death in patients with sTBI. A nomogram was built using the logistic regression prediction model. The AUC and C-index were 0.859 (95% CI 0.837–0.880). The calibration curve of the nomogram was close to the ideal reference line, and the H-L test p value was 0.504. DCA curve demonstrated significantly better net benefit with the model. Application of the nomogram in external validation group still showed good discrimination (AUC and C-index were 0.856, 95% CI 0.827–0.886), calibration, and clinical usefulness. Interpretation: A nomogram was developed for predicting the occurrence of short-term (≤14 days after injury) death in patients with sTBI. This can provide clinicians with an effective and accurate tool for the early prediction and timely management of sTBI, as well as support clinical decision-making around the withdrawal of life-sustaining therapy. This nomogram is based on Chinese large-scale data and is especially relevant to low- and middle-income countries. Funding: Shanghai Academic Research Leader (21XD1422400), Shanghai Medical and Health Development Foundation (20224Z0012). |
| first_indexed | 2024-04-09T15:17:14Z |
| format | Article |
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| institution | Directory Open Access Journal |
| issn | 2589-5370 |
| language | English |
| last_indexed | 2024-04-09T15:17:14Z |
| publishDate | 2023-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | EClinicalMedicine |
| spelling | doaj.art-7dcac577b37a447896996fbc76899af62023-04-29T14:57:46ZengElsevierEClinicalMedicine2589-53702023-05-0159101975An independently validated nomogram for individualised estimation of short-term mortality risk among patients with severe traumatic brain injury: a modelling analysis of the CENTER-TBI China Registry StudyResearch in contextLijian Lang0Tianwei Wang1Li Xie2Chun Yang3Loren Skudder-Hill4Jiyao Jiang5Guoyi Gao6Junfeng Feng7Brain Injury Centre, Renji Hospital, Shanghai Jiao Tong University School of Medicine, 160 Pujian Road, Shanghai, 200127, China; Shanghai Institute of Head Trauma, 160 Pujian Road, Shanghai, 200127, ChinaDepartment of Neurosurgery, Zhujiang Hospital, Southern Medical University, 253 Gongye Dadao, Haizhu District, Guangzhou, 510282, ChinaClinical Research Institute, Shanghai Jiao Tong University School of Medicine, 227 Chongqing Road, Shanghai, ChinaShanghai Institute of Head Trauma, 160 Pujian Road, Shanghai, 200127, ChinaDepartment of Neurosurgery, Yuquan Hospital Affiliated to Tsinghua University School of Clinical Medicine, 5 Shijingshan Road, Shijingshan, Beijing, 100049, ChinaBrain Injury Centre, Renji Hospital, Shanghai Jiao Tong University School of Medicine, 160 Pujian Road, Shanghai, 200127, China; Shanghai Institute of Head Trauma, 160 Pujian Road, Shanghai, 200127, ChinaShanghai Institute of Head Trauma, 160 Pujian Road, Shanghai, 200127, China; Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China; Corresponding author. Shanghai Institute of Head Trauma, 160 Pujian Road, Shanghai, 200127, China.Brain Injury Centre, Renji Hospital, Shanghai Jiao Tong University School of Medicine, 160 Pujian Road, Shanghai, 200127, China; Shanghai Institute of Head Trauma, 160 Pujian Road, Shanghai, 200127, China; Corresponding author. Brain Injury Centre, Renji Hospital, Shanghai Jiao Tong University School of Medicine, 160 Pujian Road, Shanghai, China.Summary: Background: Severe traumatic brain injury (sTBI) is extremely disabling and associated with high mortality. Early detection of patients at risk of short-term (≤14 days after injury) death and provision of timely treatment is critical. This study aimed to establish and independently validate a nomogram to estimate individualised short-term mortality for sTBI based on large-scale data from China. Methods: The data were from the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) China registry (between Dec 22, 2014, and Aug 1, 2017; registered at ClinicalTrials.gov, NCT02210221). This analysis included information of eligible patients with diagnosed sTBI from 52 centres (2631 cases). 1808 cases from 36 centres were enrolled in the training group (used to construct the nomogram) and 823 cases from 16 centres were enrolled in the validation group. Multivariate logistic regression was used to identify independent predictors of short-term mortality and establish the nomogram. The discrimination of the nomogram was evaluated using area under the receiver operating characteristic curves (AUC) and concordance indexes (C-index), the calibration was evaluated using calibration curves and Hosmer–Lemeshow tests (H-L tests). Decision curve analysis (DCA) was used to evaluate the net benefit of the model for patients. Findings: In the training group, multivariate logistic regression demonstrated that age (odds ratio [OR] 1.013, 95% confidence interval [CI] 1.003−1.022), Glasgow Coma Scale score (OR 33.997, 95% CI 14.657−78.856), Injury Severity Score (OR 1.020, 95% CI 1.009−1.032), abnormal pupil status (OR 1.738, 95% CI 1.178−2.565), midline shift (OR 2.266, 95% CI 1.378−3.727), and pre-hospital intubation (OR 2.059, 95% CI 1.472−2.879) were independent predictors for short-term death in patients with sTBI. A nomogram was built using the logistic regression prediction model. The AUC and C-index were 0.859 (95% CI 0.837–0.880). The calibration curve of the nomogram was close to the ideal reference line, and the H-L test p value was 0.504. DCA curve demonstrated significantly better net benefit with the model. Application of the nomogram in external validation group still showed good discrimination (AUC and C-index were 0.856, 95% CI 0.827–0.886), calibration, and clinical usefulness. Interpretation: A nomogram was developed for predicting the occurrence of short-term (≤14 days after injury) death in patients with sTBI. This can provide clinicians with an effective and accurate tool for the early prediction and timely management of sTBI, as well as support clinical decision-making around the withdrawal of life-sustaining therapy. This nomogram is based on Chinese large-scale data and is especially relevant to low- and middle-income countries. Funding: Shanghai Academic Research Leader (21XD1422400), Shanghai Medical and Health Development Foundation (20224Z0012).http://www.sciencedirect.com/science/article/pii/S2589537023001529Prediction modelTraumatic brain injuryPrognosisCENTER-TBILow- and middle-income countries |
| spellingShingle | Lijian Lang Tianwei Wang Li Xie Chun Yang Loren Skudder-Hill Jiyao Jiang Guoyi Gao Junfeng Feng An independently validated nomogram for individualised estimation of short-term mortality risk among patients with severe traumatic brain injury: a modelling analysis of the CENTER-TBI China Registry StudyResearch in context EClinicalMedicine Prediction model Traumatic brain injury Prognosis CENTER-TBI Low- and middle-income countries |
| title | An independently validated nomogram for individualised estimation of short-term mortality risk among patients with severe traumatic brain injury: a modelling analysis of the CENTER-TBI China Registry StudyResearch in context |
| title_full | An independently validated nomogram for individualised estimation of short-term mortality risk among patients with severe traumatic brain injury: a modelling analysis of the CENTER-TBI China Registry StudyResearch in context |
| title_fullStr | An independently validated nomogram for individualised estimation of short-term mortality risk among patients with severe traumatic brain injury: a modelling analysis of the CENTER-TBI China Registry StudyResearch in context |
| title_full_unstemmed | An independently validated nomogram for individualised estimation of short-term mortality risk among patients with severe traumatic brain injury: a modelling analysis of the CENTER-TBI China Registry StudyResearch in context |
| title_short | An independently validated nomogram for individualised estimation of short-term mortality risk among patients with severe traumatic brain injury: a modelling analysis of the CENTER-TBI China Registry StudyResearch in context |
| title_sort | independently validated nomogram for individualised estimation of short term mortality risk among patients with severe traumatic brain injury a modelling analysis of the center tbi china registry studyresearch in context |
| topic | Prediction model Traumatic brain injury Prognosis CENTER-TBI Low- and middle-income countries |
| url | http://www.sciencedirect.com/science/article/pii/S2589537023001529 |
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