Observational studyNeurocritical care2024
Derivation of Coagulation Phenotypes and the Association with Prognosis in Traumatic Brain Injury: A Cluster Analysis of Nationwide Multicenter Study.
Observational study in Neurocritical care, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- Unsupervised Clustering in Neurocritical Care: A Systematic Review.Neurocritical care · 2025Pooled it
- Skull fractures may be associated with hyperfibrinolysis in patients with isolated traumatic brain injury.Clinical and experimental emergency medicine · 2026Article
- Effects of coagulation dysfunction and platelet changes on rebleeding and prognosis in acute subdural hematoma.American journal of translational research · 2026Article
- Inflammatory-neurological deficit versus metabolic dysregulation: unsupervised clustering and SHAP analysis.Frontiers in immunology · 2026Article
- Therapeutic target of high fresh frozen plasma to red blood cell ratio in severe blunt trauma.Critical care (London, England) · 2025Article
- Development of Machine-learning Model to Predict Anticoagulant Use and Type in Geriatric Traumatic Brain Injury Using Coagulation Parameters.Neurologia medico-chirurgica · 2025Article
- Phenotypes of Patients with Intracerebral Hemorrhage, Complications, and Outcomes.Neurocritical care · 2025Article
- Development and validation of a nomogram-based risk prediction model for unfavorable outcomes in pediatric traumatic brain injury: a retrospective study.Frontiers in pediatrics · 2025Article
- Discovery of generalizable TBI phenotypes using multivariate time-series clustering.Computers in biology and medicine · 2024Article
- Article
- Explainable artificial intelligence in emergency medicine: an overview.Clinical and experimental emergency medicine · 2023Article
- AI and machine learning in resuscitation: Ongoing research, new concepts, and key challenges.Resuscitation plus · 2023Review
Corrections and comments
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Authors and funding
6 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe pathogenesis and pathophysiology of traumatic coagulopathy during traumatic brain injury is not well understood, and the appropriate treatment strategy for this condition has not been established. This study aimed to evaluate the coagulation phenotypes and their effect on prognosis in patients with isolated traumatic brain injury.
methodsIn this multicenter cohort study, we retrospectively analyzed data from the Japan Neurotrauma Data Bank. Adults with isolated traumatic brain injury (head abbreviated injury scale > 2; abbreviated injury scale of any other trauma < 3) who were registered in the Japan Neurotrauma Data Bank were included in this study. The primary outcome was the association of coagulation phenotypes with in-hospital mortality. Coagulation phenotypes were derived using k-means clustering with coagulation markers, including prothrombin time international normalized ratio (PT-INR), activated partial thromboplastin time (APTT), fibrinogen (FBG), and D-dimer (DD) on arrival at the hospital. Multivariable logistic regression analyses were conducted to calculate the adjusted odds ratios of coagulation phenotypes with their 95% confidence intervals (CIs) for in-hospital mortality.
resultsIn total, 556 patients were enrolled and five coagulation phenotypes were identified. The median (interquartile range) score for the Glasgow Coma Scale was 6 (4-9). Cluster A (n = 129) had the closest to normal coagulation values; cluster B (n = 323) had a mild high DD phenotype; cluster C (n = 30) had a prolonged PT-INR phenotype with a higher frequency of antithrombotic medication in elderly patients than in younger patients; cluster D (n = 45) had a low amount of FBG, high DD, and prolonged APTT phenotype with a high incidence of skull fracture; and cluster E (n = 29) had a low amount of FBG and extremely high DD phenotype with high energy trauma and a high incidence of skull fracture. In the multivariable logistic regression analysis, the association of clusters B, C, D, and E with in-hospital mortality yielded the corresponding adjusted odds ratios of 2.17 (95% CI 1.22-3.86), 2.61 (95% CI 1.01-6.72), 10.0 (95% CI 4.00-25.2), and 24.1 (95% CI 7.12-81.3), respectively, relative to cluster A.
conclusionsThis multicenter, observational study identified five different coagulation phenotypes of traumatic brain injury and showed associations of these phenotypes with in-hospital mortality.
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