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Abstract To purpose was to assess and compare the health-related quality of life (HRQoL) and risk of depression two years after trauma, between patients with and without traumatic brain injury (TBI) in a mixed Swedish trauma cohort. In this prospective cohort study, TBI and non-TBI trauma patients included in the Swedish Trauma registry 2019 at a level II trauma center in Stockholm, Sweden, were contacted two years after admission. HRQoL was assessed with RAND-36 and EQ-5D-3L, and depression with Montgomery Åsberg depression Rating Scale self-report (MADRS-S). Abbreviated Injury Score (AIS) head was used to grade TBI severity, and American Society of Anesthesiologists (ASA) score was used to assess comorbidities. Data were compared using Chi-squared test, Mann Whitney U test and ordered logistic regression, and Bonferroni correction was applied. A total of 170 of 737 eligible patients were included. TBI was associated with higher scores in 5/8 domains of RAND-36 and 3/5 domains of EQ-5D (p

Abstract Intensive care for patients with traumatic brain injury (TBI) aims to optimize intracranial pressure (ICP) and cerebral perfusion pressure (CPP). The transformation of ICP and CPP time-series data into a dynamic prediction model could aid clinicians to make more data-driven treatment decisions. We retrained and externally validated a machine learning model to dynamically predict the risk of mortality in patients with TBI. Retraining was done in 686 patients with 62,000 h of data and validation was done in two international cohorts including 638 patients with 60,000 h of data. The area under the receiver operating characteristic curve increased with time to 0.79 and 0.73 and the precision recall curve increased with time to 0.57 and 0.64 in the Swedish and American validation cohorts, respectively. The rate of false positives decreased to ≤2.5%. The algorithm provides dynamic mortality predictions during intensive care that improved with increasing data and may have a role as a clinical decision support tool.

Abstract Matrix metalloproteinases (MMPs) are extracellular enzymes involved in the degradation of extracellular matrix (ECM) proteins. Increased expression of MMPs have been described in traumatic brain injury (TBI) and may contribute to additional tissue injury and blood–brain barrier damage. The objectives of this study were to determine longitudinal changes in cerebrospinal fluid (CSF) concentrations of MMPs after acute TBI and in relation to clinical outcomes, with patients with idiopathic normal pressure hydrocephalus (iNPH) serving as a contrast group. The study included 33 TBI patients with ventricular CSF serially sampled, and 38 iNPH patients in the contrast group. Magnetic bead-based immunoassays were utilized to measure the concentrations of eight MMPs in ventricular human CSF. CSF concentrations of MMP-1, MMP-3 and MMP-10 were increased in TBI patients (at baseline) compared with the iNPH group (p

Abstract Extracorporeal membrane oxygenation (ECMO) is a life-supportive treatment in neonatal patients with refractory lung and/or heart failure. Intracranial hemorrhage (ICH) is a severe complication and reliable predictors are warranted. The aims of this study were to explore the incidence and possible predictors of ICH in ECMO-treated neonatal patients. We performed a single-center retrospective observational cohort study. Patients aged ≤ 28 days treated with ECMO between 2010 and 2018 were included. Exclusion criteria were ICH, ischemic stroke, cerebrovascular malformation before ECMO initiation or detected within 12 h of admission, ECMO treatment 12 h. The primary outcome was a CT-verified ICH. Logistic regression models were employed to identify possible predictors of the primary outcome. Of the 223 patients included, 29 (13%) developed an ICH during ECMO treatment. Thirty-day mortality was 59% in the ICH group and 16% in the non-ICH group (p

Abstract To determine the incidence and identify predictors of brain infarctions (BI) in neonatal patients treated with extracorporeal membrane oxygenation (ECMO). We performed a retrospective cohort study at ECMO Centre Karolinska, Stockholm, Sweden. Logistic regression models were used to identify BI predictors. Neonates (age 0–28 days) treated with veno-arterial (VA) or veno-venous (VV) ECMO between 2010 and 2018. The primary outcome was a computed tomography (CT) verified BI diagnosed during ECMO treatment. In total, 223 patients were included, 102 patients (46%) underwent at least one brain CT and 27 patients (12%) were diagnosed with a BI. BI diagnosis was associated with increased 30-day mortality (48% vs. 18%). High pre-ECMO Pediatric Index of Mortality score, sepsis as the indication for ECMO treatment, VA ECMO, conversion between ECMO modes, use of continuous renal replacement therapy, and extracranial thrombosis were identified as independent predictors of BI development. The incidence of BI in neonatal ECMO patients may be higher than previously understood. Risk factor identification may help initiate steps to lower the risk or facilitate earlier diagnosis of BI in neonates undergoing ECMO treatment.

Abstract Non-hemorrhagic brain infarction (BI) is a recognized complication in adults treated with extracorporeal membrane oxygenation (ECMO) and associated with increased mortality. However, predictors of BI in these patients are poorly understood. The aim of this study was to identify predictors of BI in ECMO-treated adult patients. We conducted an observational cohort study of all adult patients treated with venovenous or venoarterial (VA) ECMO at our center between 2010 and 2018. The primary endpoint was a computed tomography (CT) verified BI. Logistic regression models were employed to identify BI predictors. In total, 275 patients were included, of whom 41 (15%) developed a BI. Pre-ECMO Simplified Acute Physiology Score III, pre-ECMO cardiac arrest, VA ECMO and conversion between ECMO modes were identified as predictors of BI. In the multivariable analysis, VA ECMO demonstrated independent risk association. VA ECMO also remained the independent BI predictor in a sub-group analysis excluding patients who did not undergo a head CT scan during ECMO treatment. The incidence of BI in adult ECMO patients may be higher than previously believed and is independently associated with VA ECMO mode. Larger prospective trials are warranted to validate these findings and ascertain their clinical significance.