ArticleFrontiers in neurology2022
Development and validation of a prediction nomogram for a 6-month unfavorable prognosis in traumatic brain-injured patients undergoing primary decompressive craniectomy: An observational study.
Article in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Decompressive Craniectomy for Intracranial Pathologies in the Intensive Care Unit : Effects on Mortality and Clinical Course.Journal of Korean Neurosurgical Society · 2026Article
- Machine learning prediction models for in-hospital postoperative functional outcome after moderate-to-severe traumatic brain injury.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2024Article
- Long-term survival after primary decompressive craniectomy for severe traumatic brain injury: an observational study from 1 to 17 years.Neurosurgical review · 2024Observational
- Decompressive craniectomy at the National Hospital of Niamey: Prospective study of the epidemioclinical profile, indications, surgical techniques, and results in a context of limited resources.Surgical neurology international · 2024Article
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Authors and funding
8 authors.
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Abstract
Objective: This study was designed to develop and validate a risk-prediction nomogram to predict a 6-month unfavorable prognosis in patients with traumatic brain-injured (TBI) undergoing primary decompressive craniectomy (DC). Methods: The clinical data of 391 TBI patients with primary DC who were admitted from 2012 to 2020 were reviewed, from which 274 patients were enrolled in the training group, while 117 were enrolled in the internal validation group, randomly. The external data sets containing 80 patients were obtained from another hospital. Independent predictors of the 6-month unfavorable prognosis were analyzed using multivariate logistic regression. Furthermore, a nomogram prediction model was constructed using R software. After evaluation of the model, internal and external validations were performed to verify the efficiency of the model using the area under the receiver operating characteristic curves and the calibration plots. Results: In multivariate analysis, age( Conclusion: This prediction model for a 6-month unfavorable prognosis in patients with TBI undergoing primary DC can evaluate the prognosis accurately and enhance the early identification of high-risk patients.
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