Predicted Unfavorable Neurologic Outcome Is Overestimated by the Marshall Computed Tomography Score, Corticosteroid Randomization After Significant Head Injury (CRASH), and International Mission for Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury (IMPACT) Models in Patients with Severe Traumatic Brain Injury Managed with Early Decompressive Craniectomy

Charry, José D.; Tejada, Jorman H.; Pinzón, Miguel A.; Tejada, Wilson A.; Ochoa, Juan D.; Falla, Manuel; Tovar, Jesús H.; Cuellar-Bahamón, Ana M.; Solano, Juan P.

doi:10.1016/j.wneu.2017.02.051

Cited by 23 publications

(7 citation statements)

References 19 publications

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“…Marshall's and Rotterdam's scores are based on data of patients managed in the '80s and early '90s, they overestimate mortality in patients managed with more recent protocols, especially in patients that underwent decompression procedures. Considering the particularities of epidemiological characteristics of TBI in LMICs 23 , 26 and that neurosurgeons dealing with neurotrauma in hospitals with limited neuromonitoring resources in the ICU use damage control almost daily, 44 , 45 the present study stands out for evaluating the prediction of mortality from these scores in a recent database.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of Computed Tomography Scoring Systems in the Prediction of Short-Term Mortality in Traumatic Brain Injury Patients from a Low- to Middle-Income Country

Souza

Côrtes

Silva

et al. 2022

Neurotrauma Reports

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The present study aims to evaluate the accuracy of the prognostic discrimination and prediction of the short-term mortality of the Marshall computed tomography (CT) classification and Rotterdam and Helsinki CT scores in a cohort of TBI patients from a low- to middle-income country. This is a post hoc analysis of a previously conducted prospective cohort study conducted in a university-associated, tertiary-level hospital that serves a population of >12 million in Brazil. Marshall CT class, Rotterdam and Helsinki scores, and their components were evaluated in the prediction of 14-day and in-hospital mortality using Nagelkerk's pseudo- R 2 and area under the receiver operating characteristic curve. Multi-variate regression was performed using known outcome predictors (age, Glasgow Coma Scale, pupil response, hypoxia, hypotension, and hemoglobin values) to evaluate the increase in variance explained when adding each of the CT classification systems. Four hundred forty-seven patients were included. Mean age of the patient cohort was 40 (standard deviation, 17.83) years, and 85.5% were male. Marshall CT class was the least accurate model, showing pseudo- R 2 values equal to 0.122 for 14-day mortality and 0.057 for in-hospital mortality, whereas Rotterdam CT scores were 0.245 and 0.194 and Helsinki CT scores were 0.264 and 0.229. The AUC confirms the best prediction of the Rotterdam and Helsinki CT scores regarding the Marshall CT class, which presented greater discriminative ability. When associated with known outcome predictors, Marshall CT class and Rotterdam and Helsinki CT scores showed an increase in the explained variance of 2%, 13.4%, and 21.6%, respectively. In this study, Rotterdam and Helsinki scores were more accurate models in predicting short-term mortality. The study denotes a contribution to the process of external validation of the scores and may collaborate with the best risk stratification for patients with this important pathology.

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Section: Discussionmentioning

confidence: 99%

Evaluation of Computed Tomography Scoring Systems in the Prediction of Short-Term Mortality in Traumatic Brain Injury Patients from a Low- to Middle-Income Country

Souza

Côrtes

Silva

et al. 2022

Neurotrauma Reports

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“…The IMPACT and CRASH models had been extensively validated in five observational studies conducted recently including (1) the prospective cohort study of severe TBI dataset of 587 cases in the USA,26 (2) the prospective cohort study using the national Neuroscience Institute data of 300 cases in Singapore,27 (3) dataset of 137 elderly patients with severe TBI from the retrospective cohort study in China,28 (4) the retrospective data of 229 moderate and severe TBI conducted in Java29 and (5) the retrospective cohort study of 127 patients with severe TBI who underwent decompressive craniectomy in a Colombian university hospital 30…”

Section: Discussionmentioning

confidence: 99%

IMPACT and CRASH prognostic models for traumatic brain injury: external validation in a South-American cohort

et al. 2020

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ObjectiveTo develop a robust prognostic model, the more diverse the settings in which the system is tested and found to be accurate, the more likely it will be generalisable to untested settings. This study aimed to externally validate the International Mission for Prognosis and Clinical Trials in Traumatic Brain Injury (IMPACT) and Corticosteroid Randomization after Significant Head Injury (CRASH) models for low-income and middle-income countries using a dataset of patients with severe traumatic brain injury (TBI) from the Benchmark Evidence from South American Trials: Treatment of Intracranial Pressure study and a simultaneously conducted observational study.MethodA total of 550 patients with severe TBI were enrolled in the study, and 466 of those were included in the analysis. Patient admission characteristics were extracted to predict unfavourable outcome (Glasgow Outcome Scale: GOS<3) and mortality (GOS 1) at 14 days or 6 months.ResultsThere were 48% of the participants who had unfavourable outcome at 6 months and these included 38% who had died. The area under the receiver operating characteristic curve (AUC) values were 0.683–0.775 and 0.640–0.731 for the IMPACT and CRASH models respectively. The IMPACT CT model had the highest AUC for predicting unfavourable outcomes, and the IMPACT Lab model had the best discrimination for predicting 6-month mortality. The discrimination for both the IMPACT and CRASH models improved with increasing complexity of the models. Calibration revealed that there were disagreement between observed and predicted outcomes in the IMPACT and CRASH models.ConclusionThe overall performance of all IMPACT and CRASH models was adequate when used to predict outcomes in the dataset. However, some disagreement in calibration suggests the necessity for updating prognostic models to maintain currency and generalisability.

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“…In addition, the Marshall scale shows that there is a direct relationship between these four diagnostic categories and the mortality rate . The patients that presented with Marshall scores of IV would be predicted to have poor outcomes, but it is suggested that this scale could overestimate the number of poor outcomes from traumatic brain injury patients . It is also known that patients with Rotterdam scores of 5 or 6 had an 80% chance of experiencing expansions of their hemorrhagic contusions following a decompressive craniectomy .…”

Section: Discussionmentioning

confidence: 99%

Primary bilateral fronto‐temporoparietal decompressive craniectomy—An alternative treatment for severe traumatic brain injury: Case report and technical note

Pérez-Alfayate

Sallabanda-Diaz

2019

Clinical Case Reports

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Cited by 23 publications

References 19 publications

Evaluation of Computed Tomography Scoring Systems in the Prediction of Short-Term Mortality in Traumatic Brain Injury Patients from a Low- to Middle-Income Country

Evaluation of Computed Tomography Scoring Systems in the Prediction of Short-Term Mortality in Traumatic Brain Injury Patients from a Low- to Middle-Income Country

IMPACT and CRASH prognostic models for traumatic brain injury: external validation in a South-American cohort

Primary bilateral fronto‐temporoparietal decompressive craniectomy—An alternative treatment for severe traumatic brain injury: Case report and technical note

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