The burden of traumatic brain injury (TBI) poses a large public health and societal problem, but the characteristics of patients and their care pathways in Europe are poorly understood. We aimed to characterise patient case-mix, care pathways, and outcomes of TBI. CENTER-TBI is a Europe-based, observational cohort study, consisting of a core study and a registry. Inclusion criteria for the core study were a clinical diagnosis of TBI, presentation fewer than 24 h after injury, and an indication for CT. Patients were differentiated by care pathway and assigned to the emergency room (ER) stratum (patients who were discharged from an emergency room), admission stratum (patients who were admitted to a hospital ward), or intensive care unit (ICU) stratum (patients who were admitted to the ICU). Neuroimages and biospecimens were stored in repositories and outcome was assessed at 6 months after injury. We used the IMPACT core model for estimating the expected mortality and proportion with unfavourable Glasgow Outcome Scale Extended (GOSE) outcomes in patients with moderate or severe TBI (Glasgow Coma Scale [GCS] score ≤12). The core study was registered with ClinicalTrials.gov, number NCT02210221, and with Resource Identification Portal (RRID: SCR_015582). Data from 4509 patients from 18 countries, collected between Dec 9, 2014, and Dec 17, 2017, were analysed in the core study and from 22 782 patients in the registry. In the core study, 848 (19%) patients were in the ER stratum, 1523 (34%) in the admission stratum, and 2138 (47%) in the ICU stratum. In the ICU stratum, 720 (36%) patients had mild TBI (GCS score 13-15). Compared with the core cohort, the registry had a higher proportion of patients in the ER (9839 [43%]) and admission (8571 [38%]) strata, with more than 95% of patients classified as having mild TBI. Patients in the core study were older than those in previous studies (median age 50 years [IQR 30-66], 1254 [28%] aged >65 years), 462 (11%) had serious comorbidities, 772 (18%) were taking anticoagulant or antiplatelet medication, and alcohol was contributory in 1054 (25%) TBIs. MRI and blood biomarker measurement enhanced characterisation of injury severity and type. Substantial inter-country differences existed in care pathways and practice. Incomplete recovery at 6 months (GOSE <8) was found in 207 (30%) patients in the ER stratum, 665 (53%) in the admission stratum, and 1547 (84%) in the ICU stratum. Among patients with moderate-to-severe TBI in the ICU stratum, 623 (55%) patients had unfavourable outcome at 6 months (GOSE <5), similar to the proportion predicted by the IMPACT prognostic model (observed to expected ratio 1·06 [95% CI 0·97-1·14]), but mortality was lower than expected (0·70 [0·62-0·76]). Patients with TBI who presented to European centres in the core study were older than were those in previous observational studies and often had comorbidities. Overall, most patients presented with mild TBI. The incomplete recovery of many patients should motivate precision medicine research and the identification of best practices to improve these outcomes. European Union 7th Framework Programme, the Hannelore Kohl Stiftung, OneMind, and Integra LifeSciences Corporation.

Background:. Early computerized tomography (CT) abnormalities are important predictors of outcome after traumatic brain injury (TBI).Objective:. To deve

Optimal oxygen and carbon dioxide levels during postcardiac arrest care are currently undefined and observational studies have suggested harm from hyperoxia exposure. We aimed to assess whether mean and time-weighted oxygen and carbon dioxide levels during the first 24 hours of postcardiac arrest care correlate with 12-month neurologic outcome. Prospective observational cohort study. Twenty-one ICUs in Finland. Out-of-hospital cardiac arrest patients treated in ICUs in Finland between March 2010 and February 2011. None. Arterial blood PaO2 and PaCO2 during the first 24 hours from admission were divided into predefined categories from the lowest to the highest. Proportions of time spent in different categories and the mean PaO2 and PaCO2 values during the first 24 hours were included in separate multivariable regression models along with resuscitation factors. The cerebral performance category at 12 months was used as primary endpoint. A total of 409 patients with arterial blood gases analyzed at least once and with a complete set of resuscitation data were included. The average amount of PaO2 and PaCO2 measurements was eight per patient. The mean 24 hours PaCO2 level was an independent predictor of good outcome (odds ratio, 1.054; 95% CI, 1.006-1.104; p = 0.027) but the mean PaO2 value was not (odds ratio, 1.006; 95% CI, 0.998-1.014; p = 0.149). With multivariate regression analysis, time spent in the PaCO2 band higher than 45 mm Hg was associated with good outcome (odds ratio, 1.015; 95% CI, 1.002-1.029; p = 0.024, for each percentage point increase in time) but time spent in different oxygen categories were not. In this multicenter study, hypercapnia was associated with good 12-month outcome in patients resuscitated from out-of-hospital cardiac arrest. We were unable to verify any harm from hyperoxia exposure. Further trials should focus on whether moderate hypercapnia during postcardiac arrest care improves outcome.

Our aim was to create simple and largely scalable machine learning-based algorithms that could predict mortality in a real-time fashion during intensive care after traumatic brain injury. We performed an observational multicenter study including adult TBI patients that were monitored for intracranial pressure (ICP) for at least 24 h in three ICUs. We used machine learning-based logistic regression modeling to create two algorithms (based on ICP, mean arterial pressure [MAP], cerebral perfusion pressure [CPP] and Glasgow Coma Scale [GCS]) to predict 30-day mortality. We used a stratified cross-validation technique for internal validation. Of 472 included patients, 92 patients (19%) died within 30 days. Following cross-validation, the ICP-MAP-CPP algorithm’s area under the receiver operating characteristic curve (AUC) increased from 0.67 (95% confidence interval [CI] 0.60–0.74) on day 1 to 0.81 (95% CI 0.75–0.87) on day 5. The ICP-MAP-CPP-GCS algorithm’s AUC increased from 0.72 (95% CI 0.64–0.78) on day 1 to 0.84 (95% CI 0.78–0.90) on day 5. Algorithm misclassification was seen among patients undergoing decompressive craniectomy. In conclusion, we present a new concept of dynamic prognostication for patients with TBI treated in the ICU. Our simple algorithms, based on only three and four main variables, discriminated between survivors and non-survivors with accuracies up to 81% and 84%. These open-sourced simple algorithms can likely be further developed, also in low and middle-income countries.

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.