Development of prognostic models for Health-Related Quality of Life following traumatic brain injury

Background Traumatic brain injury (TBI) is a leading cause of impairments affecting Health-Related Quality of Life (HRQoL). We aimed to identify predictors of and develop prognostic models for HRQoL following TBI. Methods We used data from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Core study, including patients with a clinical diagnosis of TBI and an indication for computed tomography presenting within 24 h of injury. The primary outcome measures were the SF-36v2 physical (PCS) and mental (MCS) health component summary scores and the Quality of Life after Traumatic Brain Injury (QOLIBRI) total score 6 months post injury. We considered 16 patient and injury characteristics in linear regression analyses. Model performance was expressed as proportion of variance explained (R2) and corrected for optimism with bootstrap procedures. Results 2666 Adult patients completed the HRQoL questionnaires. Most were mild TBI patients (74%). The strongest predictors for PCS were Glasgow Coma Scale, major extracranial injury, and pre-injury health status, while MCS and QOLIBRI were mainly related to pre-injury mental health problems, level of education, and type of employment. R2 of the full models was 19% for PCS, 9% for MCS, and 13% for the QOLIBRI. In a subset of patients following predominantly mild TBI (N = 436), including 2 week HRQoL assessment improved model performance substantially (R2 PCS 15% to 37%, MCS 12% to 36%, and QOLIBRI 10% to 48%). Conclusion Medical and injury-related characteristics are of greatest importance for the prediction of PCS, whereas patient-related characteristics are more important for the prediction of MCS and the QOLIBRI following TBI.Output Status: Forthcoming/Available Onlin

Clustering identifies endotypes of traumatic brain injury in an intensive care cohort: a CENTER-TBI study

Background While the Glasgow coma scale (GCS) is one of the strongest outcome predictors, the current classification of traumatic brain injury (TBI) as ‘mild’, ‘moderate’ or ‘severe’ based on this fails to capture enormous heterogeneity in pathophysiology and treatment response. We hypothesized that data-driven characterization of TBI could identify distinct endotypes and give mechanistic insights. Methods We developed an unsupervised statistical clustering model based on a mixture of probabilistic graphs for presentation (< 24 h) demographic, clinical, physiological, laboratory and imaging data to identify subgroups of TBI patients admitted to the intensive care unit in the CENTER-TBI dataset (N = 1,728). A cluster similarity index was used for robust determination of optimal cluster number. Mutual information was used to quantify feature importance and for cluster interpretation. Results Six stable endotypes were identified with distinct GCS and composite systemic metabolic stress profiles, distinguished by GCS, blood lactate, oxygen saturation, serum creatinine, glucose, base excess, pH, arterial partial pressure of carbon dioxide, and body temperature. Notably, a cluster with ‘moderate’ TBI (by traditional classification) and deranged metabolic profile, had a worse outcome than a cluster with ‘severe’ GCS and a normal metabolic profile. Addition of cluster labels significantly improved the prognostic precision of the IMPACT (International Mission for Prognosis and Analysis of Clinical trials in TBI) extended model, for prediction of both unfavourable outcome and mortality (both p < 0.001). Conclusions Six stable and clinically distinct TBI endotypes were identified by probabilistic unsupervised clustering. In addition to presenting neurology, a profile of biochemical derangement was found to be an important distinguishing feature that was both biologically plausible and associated with outcome. Our work motivates refining current TBI classifications with factors describing metabolic stress. Such data-driven clusters suggest TBI endotypes that merit investigation to identify bespoke treatment strategies to improve care

Rehabilitation and outcomes after complicated vs uncomplicated mild TBI: results from the CENTER-TBI study

Background: Despite existing guidelines for managing mild traumatic brain injury (mTBI), evidence-based treatments are still scarce and large-scale studies on the provision and impact of specific rehabilitation services are needed. This study aimed to describe the provision of rehabilitation to patients after complicated and uncomplicated mTBI and investigate factors associated with functional outcome, symptom burden, and TBI-specific health-related quality of life (HRQOL) up to six months after injury. Methods: Patients (n = 1379) with mTBI from the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) study who reported whether they received rehabilitation services during the first six months post-injury and who participated in outcome assessments were included. Functional outcome was measured with the Glasgow Outcome Scale – Extended (GOSE), symptom burden with the Rivermead Post Concussion Symptoms Questionnaire (RPQ), and HRQOL with the Quality of Life after Brain Injury – Overall Scale (QOLIBRI-OS). We examined whether transition of care (TOC) pathways, receiving rehabilitation services, sociodemographic (incl. geographic), premorbid, and injury-related factors were associated with outcomes using regression models. For easy comparison, we estimated ordinal regression models for all outcomes where the scores were classified based on quantiles. Results: Overall, 43% of patients with complicated and 20% with uncomplicated mTBI reported receiving rehabilitation services, primarily in physical and cognitive domains. Patients with complicated mTBI had lower functional level, higher symptom burden, and lower HRQOL compared to uncomplicated mTBI. Rehabilitation services at three or six months and a higher number of TOC were associated with unfavorable outcomes in all models, in addition to pre-morbid psychiatric problems. Being male and having more than 13 years of education was associated with more favorable outcomes. Sustaining major trauma was associated with unfavorable GOSE outcome, whereas living in Southern and Eastern European regions was associated with lower HRQOL. Conclusions: Patients with complicated mTBI reported more unfavorable outcomes and received rehabilitation services more frequently. Receiving rehabilitation services and higher number of care transitions were indicators of injury severity and associated with unfavorable outcomes. The findings should be interpreted carefully and validated in future studies as we applied a novel analytic approach. Trial registration: ClinicalTrials.gov NCT02210221

Research Note: Prognostic model research: overfitting, validation and application

Analysis and support of clinical decision makin

Resonance Raman Analysis of Charge-Transfer Reorganization Energies in Covalent Dicyanoethylene-azaadamantane

Resonance Raman cross sections have been measured for a covalent electron donor-acceptor substituted aza-adamantane. Excitation near the maximum of the strong charge-transfer absorption results in resonance enhancement of a number of Raman fundamentals, overtones, and combination bands. The reorganization energy in each molecular mode and the solvent contribution to the electronic linewidth are determined through quantitative modeling of the absorption, Raman, and fluorescence spectra, which are sensitive to solvent dynamics on different time scales. The results suggest that the solvent-induced broadening in methanol has components that fluctuate on a wide range of timescales.link_to_subscribed_fulltex

Outcome Prediction after Moderate and Severe Traumatic Brain Injury: External Validation of Two Established Prognostic Models in 1742 European Patients

The International Mission on Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury (IMPACT) and Corticoid Randomisation After Significant Head injury (CRASH) prognostic models predict functional outcome after moderate and severe traumatic brain injury (TBI). We aimed to assess their performance in a contemporary cohort of patients across Europe. The Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) core study is a prospective, observational cohort study in patients presenting with TBI and an indication for brain computed tomography. The CENTER-TBI core cohort consists of 4509 TBI patients available for analyses from 59 centers in 18 countries across Europe and Israel. The IMPACT validation cohort included 1173 patients with GCS ≤12, age ≥14, and 6-month Glasgow Outcome Scale-Extended (GOSE) available. The CRASH validation cohort contained 1742 patients with GCS ≤14, age ≥16, and 14-day mortality or 6-month GOSE available. Performance of the three IMPACT and two CRASH model variants was assessed with discrimination (area under the receiver operating characteristic curve; AUC) and calibration (comparison of observed vs. predicted outcome rates). For IMPACT, model discrimination was good, with AUCs ranging between 0.77 and 0.85 in 1173 patients and between 0.80 and 0.88 in the broader CRASH selection (n = 1742). For CRASH, AUCs ranged between 0.82 and 0.88 in 1742 patients and between 0.66 and 0.80 in the stricter IMPACT selection (n = 1173). Calibration of the IMPACT and CRASH models was generally moderate, with calibration-in-the-large and calibration slopes ranging between-2.02 and 0.61 and between 0.48 and 1.39, respectively. The IMPACT and CRASH models adequately identify patients at high risk for mortality or unfavorable outcome, which supports their use in research settings and for benchmarking in the context of quality-of-care assessment

Development of prognostic models for Health-Related Quality of Life following traumatic brain injury

Background: Traumatic brain injury (TBI) is a leading cause of impairments affecting Health-Related Quality of Life (HRQoL). We aimed to identify predictors of and develop prognostic models for HRQoL following TBI. Methods: We used data from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Core study, including patients with a clinical diagnosis of TBI and an indication for computed tomography presenting within 24 h of injury. The primary outcome measures were the SF-36v2 physical (PCS) and mental (MCS) health component summary scores and the Quality of Life after Traumatic Brain Injury (QOLIBRI) total score 6 months post injury. We considered 16 patient and injury characteristics in linear regression analyses. Model performance was expressed as proportion of variance explained (R2) and corrected for optimism with bootstrap procedures. Results: 2666 Adult patients completed the HRQoL questionnaires. Most were mild TBI patients (74%). The strongest predictors for PCS were Glasgow Coma Scale, major extracranial injury, and pre-injury health status, while MCS and QOLIBRI were mainly related to pre-injury mental health problems, level of education, and type of employment. R2 of the full models was 19% for PCS, 9% for MCS, and 13% for the QOLIBRI. In a subset of patients following predominantly mild TBI (N = 436), including 2 week HRQoL assessment improved model performance substantially (R2 PCS 15% to 37%, MCS 12% to 36%, and QOLIBRI 10% to 48%). Conclusion: Medical and injury-related characteristics are of greatest importance for the prediction of PCS, whereas patient-related characteristics are more important for the prediction of MCS and the QOLIBRI following TBI