Predicting outcome in severe traumatic brain injury using a simple prognostic model (original) (raw)
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International Surgery Journal, 2021
Traumatic brain injury (TBI) is a major burden with approximately 10 million annual victims reported on the health care system throughout the world. TBI is defined as ‘an alteration in brain function, or other evidence of brain pathology, caused by an external force’. A severe TBI is defined by a Glasgow coma score (GCS) score of 8 or less during the first post traumatic day. It is a neurosurgical emergency and timely intervention is critical for favorable outcome. In addition to the impact of TBI on the individual, it can negatively impact families, communities, and the economy. Its outcome prediction is paramount in clinical decision making, counselling relatives and targeted use of limited healthcare resources in developing countries like India. Although several prognostic models have been developed, the accurate assessment of short term and long-term prognosis of severe TBI needs further evaluation. A number of factors are believed to influence the outcome of TBI patients includ...
Predicting Outcome after traumatic brain injury
Objective To develop and validate practical prognostic models for death at 14 days and for death or severe disability six months after traumatic brain injury. Design Multivariable logistic regression to select variables that were independently associated with two patient outcomes. Two models designed: “basic” model (demographic and clinical variables only) and “CT” model (basic model plus results of computed tomography). The models were subsequently developed for high and lowmiddle income countries separately. Setting Medical Research Council (MRC) CRASH Trial. Subjects 10 008 patients with traumatic brain injury. Models externally validated in a cohort of 8509. Results The basic model included four predictors: age, Glasgow coma scale, pupil reactivity, and the presence of major extracranial injury. The CT model also included the presence of petechial haemorrhages, obliteration of the third ventricle or basal cisterns, subarachnoid bleeding, midline shift, and non-evacuated haematoma. In the derivation sample the models showed excellent discrimination (C statistic above 0.80). The models showed good calibration graphically. The Hosmer- Lemeshow test also indicated good calibration, except for the CT model in low-middle income countries. External validation for unfavourable outcome at six months in high income countries showed that basic and CT models had good discrimination (C statistic 0.77 for both models) but poorer calibration. Conclusion Simple prognostic models can be used to obtain valid predictions of relevant outcomes in patients with traumatic brain injury.
Critical Care, 2014
and SOFA (Sequential Organ Failure Assessment) scores compared to simpler models based on age and Glasgow Coma Scale (GCS) in predicting long-term outcome of patients with moderate-to-severe traumatic brain injury (TBI) treated in the intensive care unit (ICU). Methods: A national ICU database was screened for eligible TBI patients (age over 15 years, GCS 3-13) admitted in 2003-2012. Logistic regression was used for customization of APACHE II, SAPS II and SOFA score-based models for six-month mortality prediction. These models were compared to an adjusted SOFA-based model (including age) and a reference model (age and GCS). Internal validation was performed by a randomized split-sample technique. Prognostic performance was determined by assessing discrimination, calibration and precision. Results: In total, 1,625 patients were included. The overall six-month mortality was 33%. The APACHE II and SAPS II-based models showed good discrimination (area under the curve (AUC) 0.79, 95% confidence interval (CI) 0.75 to 0.82; and 0.80, 95% CI 0.77 to 0.83, respectively), calibration (P > 0.05) and precision (Brier score 0.166 to 0.167). The SOFA-based model showed poor discrimination (AUC 0.68, 95% CI 0.64 to 0.72) and precision (Brier score 0.201) but good calibration (P > 0.05). The AUC of the SOFA-based model was significantly improved after the insertion of age and GCS (ΔAUC +0.11, P < 0.001). The performance of the reference model was comparable to the APACHE II and SAPS II in terms of discrimination (AUC 0.77; compared to APACHE II, ΔAUC −0.02, P = 0.425; compared to SAPS II, ΔAUC −0.03, P = 0.218), calibration (P > 0.05) and precision (Brier score 0.181). Conclusions: A simple prognostic model, based only on age and GCS, displayed a fairly good prognostic performance in predicting six-month mortality of ICU-treated patients with TBI. The use of the more complex scoring systems APACHE II, SAPS II and SOFA added little to the prognostic performance.
Prediction of outcome after moderate and severe traumatic brain injury
Critical Care Medicine, 2012
and Corticoid Randomisation After Significant Head injury (CRASH) prognostic models predict outcome after traumatic brain injury (TBI) but have not been compared in large datasets. The objective of this is study is to validate externally and compare the IMPACT and CRASH prognostic models for prediction of outcome after moderate or severe TBI.
Arquivos De Neuro-psiquiatria, 2023
Background Pupil reactivity and the Glasgow Coma Scale (GCS) score are the most clinically relevant information to predict the survival of traumatic brain injury (TBI) patients. Objective We evaluated the accuracy of the GCS-Pupil score (GCS-P) as a prognostic index to predict hospital mortality in Brazilian patients with severe TBI and compare it with a model combining GCS and pupil response with additional clinical and radiological prognostic factors. Methods Data from 1,066 patients with severe TBI from 5 prospective studies were analyzed. We determined the association between hospital mortality and the combination of GCS, pupil reactivity, age, glucose levels, cranial computed tomography (CT), or the GCS-P score by multivariate binary logistic regression. Results Eighty-five percent (n ¼ 908) of patients were men. The mean age was 35 years old, and the overall hospital mortality was 32.8%. The area under the receiver operating characteristic curve (AUROC) was 0.73 (0.70-0.77) for the model using the
Prognostic Indicators and Outcome Prediction Model for Severe Traumatic Brain Injury
Journal of Trauma: Injury, Infection & Critical Care, 2009
Background: Although some predictive models for patient outcomes after severe traumatic brain injury have been proposed, a mathematical model with high predictive value has not been established. The purpose of the present study was to analyze the most important indicators of prognosis and to develop the best outcome prediction model. Methods: One hundred eleven consecutive patients with a Glasgow Coma Scale score of <9 were examined and 14 factors were evaluated. Intracranial pressure and cerebral perfusion pressure were recorded at admission to the intensive care unit. The absence of the basal cisterns , presence of extensive subarachnoid hemorrhage, and degree of midline shift were evaluated by means of computed tomography within 24 hours after injury. Multivariate logistic regression analysis was used to identify independent risk factors for a poor prognosis and to develop the best prediction model. Results: The best model included the following variables: age (p < 0.01), light reflex (p ؍ 0.01), extensive subarachnoid hemorrhage (p ؍ 0.01), intracranial pressure (p ؍ 0.04), and midline shift (p ؍ 0.12). Positive predictive value of the model was 97.3%, negative predictive value was 87.1%, and overall predictive value was 94.2%. The area under the receiver operating characteristic curve was 0.977, and the p value for the Hosmer-Lemeshow goodness-of-fit was 0.866. Conclusions: Our predictive model based on age, absence of light reflex, presence of extensive subarachnoid hemorrhage, intracranial pressure, and midline shift was shown to have high predictive value and will be useful for decision making, review of treatment, and family counseling in case of traumatic brain injury.
Neurocritical Care
Background/Objective Current severe traumatic brain injury (TBI) outcome prediction models calculate the chance of unfavourable outcome after 6 months based on parameters measured at admission. We aimed to improve current models with the addition of continuously measured neuromonitoring data within the first 24 h after intensive care unit neuromonitoring. Methods Forty-five severe TBI patients with intracranial pressure/cerebral perfusion pressure monitoring from two teaching hospitals covering the period May 2012 to January 2019 were analysed. Fourteen high-frequency physiological parameters were selected over multiple time periods after the start of neuromonitoring (0–6 h, 0–12 h, 0–18 h, 0–24 h). Besides systemic physiological parameters and extended Corticosteroid Randomisation after Significant Head Injury (CRASH) score, we added estimates of (dynamic) cerebral volume, cerebral compliance and cerebrovascular pressure reactivity indices to the model. A logistic regression model ...
BMJ open, 2017
Severe traumatic brain injury is a significant cause of morbidity and mortality in young adults. Assessing long-term neurological outcome after such injury is difficult and often characterised by uncertainty. The objective of this feasibility study was to establish the feasibility of conducting a large, multicentre prospective study to develop a prognostic model of long-term neurological outcome in critically ill patients with severe traumatic brain injury. A prospective cohort study. 9 Canadian intensive care units enrolled patients suffering from acute severe traumatic brain injury. Clinical, biological, radiological and electrophysiological data were systematically collected during the first week in the intensive care unit. Mortality and functional outcome (Glasgow Outcome Scale extended) were assessed on hospital discharge, and then 3, 6 and 12 months following injury. The compliance to protocolised test procedures was the primary outcome. Secondary outcomes were enrolment rate ...
Journal of Neurosciences in Rural Practice, 2017
Objectives: Prognosis of outcome after traumatic brain injury (TBI) is important in the assessment of quality of care and can help improve treatment and outcome. The aim of this study was to compare the prognostic value of relatively simple injury severity scores between each other and against a gold standard model – the IMPACT-extended (IMP-E) multivariable prognostic model. Materials and Methods: For this study, 866 patients with moderate/severe TBI from Austria were analyzed. The prognostic performances of the Glasgow coma scale (GCS), GCS motor (GCSM) score, abbreviated injury scale for the head region, Marshall computed tomographic (CT) classification, and Rotterdam CT score were compared side-by-side and against the IMP-E score. The area under the receiver operating characteristics curve (AUC) and Nagelkerke's R 2 were used to assess the prognostic performance. Outcomes at the Intensive Care Unit, at hospital discharge, and at 6 months (mortality and unfavorable outcome) w...