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Funder: Integra LifeSciences, Funder: One Mind, Funder: ZNS - Hannelore Kohl Stiftung, When a patient is admitted to the intensive care unit (ICU) after a traumatic brain injury (TBI), an early prognosis is essential for baseline risk adjustment and shared decision making. TBI outcomes are commonly categorised by the Glasgow Outcome Scale-Extended (GOSE) into eight, ordered levels of functional recovery at 6 months after injury. Existing ICU prognostic models predict binary outcomes at a certain threshold of GOSE (e.g., prediction of survival [GOSE > 1]). We aimed to develop ordinal prediction models that concurrently predict probabilities of each GOSE score. From a prospective cohort (n = 1,550, 65 centres) in the ICU stratum of the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) patient dataset, we extracted all clinical information within 24 hours of ICU admission (1,151 predictors) and 6-month GOSE scores. We analysed the effect of two design elements on ordinal model performance: (1) the baseline predictor set, ranging from a concise set of ten validated predictors to a token-embedded representation of all possible predictors, and (2) the modelling strategy, from ordinal logistic regression to multinomial deep learning. With repeated k-fold cross-validation, we found that expanding the baseline predictor set significantly improved ordinal prediction performance while increasing analytical complexity did not. Half of these gains could be achieved with the addition of eight high-impact predictors to the concise set. At best, ordinal models achieved 0.76 (95% CI: 0.74-0.77) ordinal discrimination ability (ordinal c-index) and 57% (95% CI: 54%- 60%) explanation of ordinal variation in 6-month GOSE (Somers' Dxy). Model performance and the effect of expanding the predictor set decreased at higher GOSE thresholds, indicating the difficulty of predicting better functional outcomes shortly after ICU admission. Our results motivate the search for informative predictors that improve confidence in prognosis of higher GOSE and the development of ordinal dynamic prediction models.

BACKGROUND/OBJECTIVE: Dysnatremia is common in severe traumatic brain injury (TBI) patients and may contribute to mortality. However, serum sodium variability has not been studied in TBI patients. We hypothesized that such variability would be independently associated with mortality. METHODS: We collected 6-hourly serum sodium levels for the first 7 days of ICU admission from 240 severe TBI patients in 14 neurotrauma ICUs in Europe and Australia. We evaluated the association between daily serum sodium standard deviation (dNaSD), an index of variability, and 28-day mortality. RESULTS: Patients were 46 ± 19 years of age with a median initial GCS of 6 [4-8]. Overall hospital mortality was 28%. Hypernatremia and hyponatremia occurred in 64% and 24% of patients, respectively. Over the first 7 days in ICU, serum sodium standard deviation was 2.8 [2.0-3.9] mmol/L. Maximum daily serum sodium standard deviation (dNaSD) occurred at a median of 2 [1-4] days after admission. There was a significant progressive decrease in dNaSD over the first 7 days (coefficient - 0.15 95% CI [- 0.18 to - 0.12], p < 0.001). After adjusting for baseline TBI severity, diabetes insipidus, the use of osmotherapy, the occurrence of hypernatremia, and hyponatremia and center, dNaSD was significantly independently associated with 28-day mortality (HR 1.27 95% CI (1.01-1.61), p = 0.048). CONCLUSIONS: Our study demonstrates that daily serum sodium variability is an independent predictor of 28-day mortality in severe TBI patients. Further prospective investigations are necessary to confirm the significance of sodium variability in larger cohorts of TBI patients and test whether attenuating such variability confers outcome benefits to such patients.

Funder: University of Helsinki including Helsinki University Central Hospital, BACKGROUND: The prognosis of penetrating traumatic brain injury (pTBI) is poor yet highly variable. Current computerized tomography (CT) severity scores are commonly not used for pTBI prognostication but may provide important clinical information in these cohorts. METHODS: All consecutive pTBI patients from two large neurotrauma databases (Helsinki 1999-2015, Stockholm 2005-2014) were included. Outcome measures were 6-month mortality and unfavorable outcome (Glasgow Outcome Scale 1-3). Admission head CT scans were assessed according to the following: Marshall CT classification, Rotterdam CT score, Stockholm CT score, and Helsinki CT score. The discrimination (area under the receiver operating curve, AUC) and explanatory variance (pseudo-R2) of the CT scores were assessed individually and in addition to a base model including age, motor response, and pupil responsiveness. RESULTS: Altogether, 75 patients were included. Overall 6-month mortality and unfavorable outcome were 45% and 61% for all patients, and 31% and 51% for actively treated patients. The CT scores' AUCs and pseudo-R2s varied between 0.77-0.90 and 0.35-0.60 for mortality prediction and between 0.85-0.89 and 0.50-0.57 for unfavorable outcome prediction. The base model showed excellent performance for mortality (AUC 0.94, pseudo-R2 0.71) and unfavorable outcome (AUC 0.89, pseudo-R2 0.53) prediction. None of the CT scores increased the base model's AUC (p > 0.05) yet increased its pseudo-R2 (0.09-0.15) for unfavorable outcome prediction. CONCLUSION: Existing head CT scores demonstrate good-to-excellent performance in 6-month outcome prediction in pTBI patients. However, they do not add independent information to known outcome predictors, indicating that a unique score capturing the intracranial severity in pTBI may be warranted.

BACKGROUND: Traumatic brain injury (TBI) is a major contributor to morbidity and mortality. Computerized tomography (CT) scanning of the brain is essential for diagnostic screening of intracranial injuries in need of neurosurgical intervention, but may also provide information concerning patient prognosis and enable baseline risk stratification in clinical trials. Novel CT scoring systems have been developed to improve current prognostic models, including the Stockholm and Helsinki CT scores, but so far have not been extensively validated. The primary aim of this study was to evaluate the Stockholm and Helsinki CT scores for predicting functional outcome, in comparison with the Rotterdam CT score and Marshall CT classification. The secondary aims were to assess which individual components of the CT scores best predict outcome and what additional prognostic value the CT scoring systems contribute to a clinical prognostic model. METHODS AND FINDINGS: TBI patients requiring neuro-intensive care and not included in the initial creation of the Stockholm and Helsinki CT scoring systems were retrospectively included from prospectively collected data at the Karolinska University Hospital (n = 720 from 1 January 2005 to 31 December 2014) and Helsinki University Hospital (n = 395 from 1 January 2013 to 31 December 2014), totaling 1,115 patients. The Marshall CT classification and the Rotterdam, Stockholm, and Helsinki CT scores were assessed using the admission CT scans. Known outcome predictors at admission were acquired (age, pupil responsiveness, admission Glasgow Coma Scale, glucose level, and hemoglobin level) and used in univariate, and multivariable, regression models to predict long-term functional outcome (dichotomizations of the Glasgow Outcome Scale [GOS]). In total, 478 patients (43%) had an unfavorable outcome (GOS 1-3). In the combined cohort, overall prognostic performance was more accurate for the Stockholm CT score (Nagelkerke's pseudo-R2 range 0.24-0.28) and the Helsinki CT score (0.18-0.22) than for the Rotterdam CT score (0.13-0.15) and Marshall CT classification (0.03-0.05). Moreover, the Stockholm and Helsinki CT scores added the most independent prognostic value in the presence of other known clinical outcome predictors in TBI (6% and 4%, respectively). The aggregate traumatic subarachnoid hemorrhage (tSAH) component of the Stockholm CT score was the strongest predictor of unfavorable outcome. The main limitations were the retrospective nature of the study, missing patient information, and the varying follow-up time between the centers. CONCLUSIONS: The Stockholm and Helsinki CT scores provide more information on the damage sustained, and give a more accurate outcome prediction, than earlier classification systems. The strong independent predictive value of tSAH may reflect an underrated component of TBI pathophysiology. A change to these newer CT scoring systems may be warranted.

Background Traumatic brain injury (TBI) is a major contributor to morbidity and mortality. Computerized tomography (CT) scanning of the brain is essential for diagnostic screening of intracranial injuries in need of neurosurgical intervention, but may also provide information concerning patient prognosis and enable baseline risk stratification in clinical trials. Novel CT scoring systems have been developed to improve current prognostic models, including the Stockholm and Helsinki CT scores, but so far have not been extensively validated. The primary aim of this study was to evaluate the Stockholm and Helsinki CT scores for predicting functional outcome, in comparison with the Rotterdam CT score and Marshall CT classification. The secondary aims were to assess which individual components of the CT scores best predict outcome and what additional prognostic value the CT scoring systems contribute to a clinical prognostic model. Methods and findings TBI patients requiring neuro-intensive care and not included in the initial creation of the Stockholm and Helsinki CT scoring systems were retrospectively included from prospectively collected data at the Karolinska University Hospital (n = 720 from 1 January 2005 to 31 December 2014) and Helsinki University Hospital (n = 395 from 1 January 2013 to 31 December 2014), totaling 1,115 patients. The Marshall CT classification and the Rotterdam, Stockholm, and Helsinki CT scores were assessed using the admission CT scans. Known outcome predictors at admission were acquired (age, pupil responsiveness, admission Glasgow Coma Scale, glucose level, and hemoglobin level) and used in univariate, and multivariable, regression models to predict long-term functional outcome (dichotomizations of the Glasgow Outcome Scale [GOS]). In total, 478 patients (43%) had an unfavorable outcome (GOS 1–3). In the combined cohort, overall prognostic performance was more accurate for the Stockholm CT score (Nagelkerke’s pseudo-R2 range 0.24–0.28) and the Helsinki CT score (0.18–0.22) than for the Rotterdam CT score (0.13–0.15) and Marshall CT classification (0.03–0.05). Moreover, the Stockholm and Helsinki CT scores added the most independent prognostic value in the presence of other known clinical outcome predictors in TBI (6% and 4%, respectively). The aggregate traumatic subarachnoid hemorrhage (tSAH) component of the Stockholm CT score was the strongest predictor of unfavorable outcome. The main limitations were the retrospective nature of the study, missing patient information, and the varying follow-up time between the centers. Conclusions The Stockholm and Helsinki CT scores provide more information on the damage sustained, and give a more accurate outcome prediction, than earlier classification systems. The strong independent predictive value of tSAH may reflect an underrated component of TBI pathophysiology. A change to these newer CT scoring systems may be warranted., Using data from two cohorts, Eric Thelin and colleagues compare the prognostic performance of computerized tomography scoring systems in patients with severe traumatic brain injury., Author summary Why was this study done? Most patients who suffer from a significant traumatic brain injury (TBI) undergo head computerized tomography (CT) scanning to visualize injuries. The generated image contains information, incorporated into specific “scoring systems,” that can be used to predict patient outcomes and for better stratification of patients in clinical trials. Preliminary data have shown that novel CT scoring systems may outperform previous CT scoring systems, but these novel CT scoring systems have not previously been extensively evaluated. What did the researchers do and find? We evaluated 2 novel CT scoring systems (the Stockholm CT score and the Helsinki CT score) in a combined cohort of 1,115 TBI patients from 2 of the larger trauma centers in Europe. We found that the 2 novel CT scoring systems systematically outperformed the previous CT scoring systems (the Marshall CT classification and the Rotterdam CT score). In addition to other factors known to predict outcome in TBI patients, such as high age and low level of consciousness, the Stockholm and Helsinki CT scoring systems added significant discriminatory performance to outcome prediction systems. A more detailed analysis revealed that traumatic subarachnoid hemorrhage was the most important individual component of the CT scores for outcome prediction, presumably due to the lack of effective treatment strategies. What do these findings mean? Our findings suggest that a change to the Stockholm and Helsinki CT scoring systems may be warranted, as they seem to better incorporate clinically relevant injuries. Implementation of the novel CT scoring systems could help improve stratification of TBI patients for future clinical trials and also help healthcare providers prioritize resource use. We do however acknowledge the need for further validation of these observational findings, preferably through prospective multicenter trials.