The need to set explicit goals for human germline gene editing public dialogues.

Given the potentially large ethical and societal implications of human germline gene editing (HGGE) the urgent need for public and stakeholder engagement (PSE) has been repeatedly expressed. However, the explicit goals of such PSE efforts often remain poorly defined. In this program report, we outline the goals of our Dutch project called De DNA dialogen (The DNA dialogues). We believe that setting explicit goals in advance is essential to enable meaningful PSE efforts. Moreover, it enables the evaluation of our engagement efforts. The following four goals, which result from intensive consultations among the transdisciplinary projects' consortium members and based on the literature, form the foundation for how we will engage the public and stakeholders in deliberation about HGGE: 1) Enable publics and stakeholders to deliberate on "what if" questions, before considering "whether" and "how" questions regarding HGGE, 2) Investigate agreement and disagreement in values and beliefs regarding HGGE in order to agree and disagree more precisely, 3) Involve diverse publics with various perspectives, with a focus on those that are typically underrepresented in PSE, 4) Enable societally aligned policy making by providing policymakers, health care professionals and legal experts insight into how values are weighed and ascribed meaning in the context of HGGE by various publics, and how these values relate to the principles of democratic rule of law and fundamental rights. The effort to describe our goals in detail may serve as an example and can inform future initiatives striving for open science and open governance in the context of PSE.

Prognostic models for COVID-19 needed updating to warrant transportability over time and space.

BACKGROUND: Supporting decisions for patients who present to the emergency department (ED) with COVID-19 requires accurate prognostication. We aimed to evaluate prognostic models for predicting outcomes in hospitalized patients with COVID-19, in different locations and across time. METHODS: We included patients who presented to the ED with suspected COVID-19 and were admitted to 12 hospitals in the New York City (NYC) area and 4 large Dutch hospitals. We used second-wave patients who presented between September and December 2020 (2137 and 3252 in NYC and the Netherlands, respectively) to evaluate models that were developed on first-wave patients who presented between March and August 2020 (12,163 and 5831). We evaluated two prognostic models for in-hospital death: The Northwell COVID-19 Survival (NOCOS) model was developed on NYC data and the COVID Outcome Prediction in the Emergency Department (COPE) model was developed on Dutch data. These models were validated on subsequent second-wave data at the same site (temporal validation) and at the other site (geographic validation). We assessed model performance by the Area Under the receiver operating characteristic Curve (AUC), by the E-statistic, and by net benefit. RESULTS: Twenty-eight-day mortality was considerably higher in the NYC first-wave data (21.0%), compared to the second-wave (10.1%) and the Dutch data (first wave 10.8%; second wave 10.0%). COPE discriminated well at temporal validation (AUC 0.82), with excellent calibration (E-statistic 0.8%). At geographic validation, discrimination was satisfactory (AUC 0.78), but with moderate over-prediction of mortality risk, particularly in higher-risk patients (E-statistic 2.9%). While discrimination was adequate when NOCOS was tested on second-wave NYC data (AUC 0.77), NOCOS systematically overestimated the mortality risk (E-statistic 5.1%). Discrimination in the Dutch data was good (AUC 0.81), but with over-prediction of risk, particularly in lower-risk patients (E-statistic 4.0%). Recalibration of COPE and NOCOS led to limited net benefit improvement in Dutch data, but to substantial net benefit improvement in NYC data. CONCLUSIONS: NOCOS performed moderately worse than COPE, probably reflecting unique aspects of the early pandemic in NYC. Frequent updating of prognostic models is likely to be required for transportability over time and space during a dynamic pandemic.

Health care utilization and outcomes in older adults after Traumatic Brain Injury: A CENTER-TBI study.

INTRODUCTION: The incidence of Traumatic Brain Injury (TBI) is increasingly common in older adults aged ≥65 years, forming a growing public health problem. However, older adults are underrepresented in TBI research. Therefore, we aimed to provide an overview of health-care utilization, and of six-month outcomes after TBI and their determinants in older adults who sustained a TBI. METHODS: We used data from the prospective multi-center Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. In-hospital and post-hospital health care utilization and outcomes were described for patients aged ≥65 years. Ordinal and linear regression analyses were performed to identify determinants of the Glasgow Outcome Scale Extended (GOSE), health-related quality of life (HRQoL), and mental health symptoms six-months post-injury. RESULTS: Of 1254 older patients, 45% were admitted to an ICU with a mean length of stay of 9 days. Nearly 30% of the patients received inpatient rehabilitation. In total, 554/1254 older patients completed the six-month follow-up questionnaires. The mortality rate was 9% after mild and 60% after moderate/severe TBI, and full recovery based on GOSE was reported for 44% of patients after mild and 6% after moderate/severe TBI. Higher age and increased injury severity were primarily associated with functional impairment, while pre-injury systemic disease, psychiatric conditions and lower educational level were associated with functional impairment, lower generic and disease-specific HRQoL and mental health symptoms. CONCLUSION: The rate of impairment and disability following TBI in older adults is substantial, and poorer outcomes across domains are associated with worse preinjury health. Nonetheless, a considerable number of patients fully or partially returns to their preinjury functioning. There should not be pessimism about outcomes in older adults who survive.

Serum metabolome associated with severity of acute traumatic brain injury.

Complex metabolic disruption is a crucial aspect of the pathophysiology of traumatic brain injury (TBI). Associations between this and systemic metabolism and their potential prognostic value are poorly understood. Here, we aimed to describe the serum metabolome (including lipidome) associated with acute TBI within 24 h post-injury, and its relationship to severity of injury and patient outcome. We performed a comprehensive metabolomics study in a cohort of 716 patients with TBI and non-TBI reference patients (orthopedic, internal medicine, and other neurological patients) from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) cohort. We identified panels of metabolites specifically associated with TBI severity and patient outcomes. Choline phospholipids (lysophosphatidylcholines, ether phosphatidylcholines and sphingomyelins) were inversely associated with TBI severity and were among the strongest predictors of TBI patient outcomes, which was further confirmed in a separate validation dataset of 558 patients. The observed metabolic patterns may reflect different pathophysiological mechanisms, including protective changes of systemic lipid metabolism aiming to maintain lipid homeostasis in the brain.

Prognostic Research in Traumatic Brain Injury: Markers, Modeling, and Methodological Principles.

Prognostic assessment in traumatic brain injury (TBI) is embedded deeply in clinical care. Considering the limitations of current prognostic indicators, there is increasing interest in understanding the role of new biomarkers, and in finding other prognostic indicators of long-term outcomes following TBI. New prognostic indicators may result in the development of more accurate prediction models that could be useful for both risk stratification and clinical decision making. We aimed to review methodological issues and provide tentative guidelines for prognostic research in TBI. Prognostic factor research focuses on the role of a specific patient or disease-related characteristic in relation to outcome. Typically, univariable relations of the prognostic factor are studied, followed by analyses adjusting for other variables related to the outcome. Following existing guidelines, we emphasize the importance of transparent reporting of patient and specimen characteristics, study design, clinical end-points, and statistical analysis. Prognostic model research considers combinations of predictors, with challenges for model specification, estimation, evaluation, validation, and presentation. We highlight modern approaches and opportunities related to missing values, exploration of non-linear effects, and assessing between-study heterogeneity. Prognostic research in TBI can be improved if key methodological principles are adhered to and when research is performed in collaboration among multiple centers to ensure generalizability.

Prediction of Global Functional Outcome and Post-Concussive Symptoms after Mild Traumatic Brain Injury: External Validation of Prognostic Models in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Study.

The majority of traumatic brain injuries (TBIs) are categorized as mild, according to a baseline Glasgow Coma Scale (GCS) score of 13-15. Prognostic models that were developed to predict functional outcome and persistent post-concussive symptoms (PPCS) after mild TBI have rarely been externally validated. We aimed to externally validate models predicting 3-12-month Glasgow Outcome Scale Extended (GOSE) or PPCS in adults with mild TBI. We analyzed data from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) project, which included 2862 adults with mild TBI, with 6-month GOSE available for 2374 and Rivermead Post-Concussion Symptoms Questionnaire (RPQ) results available for 1605 participants. Model performance was evaluated based on calibration (graphically and characterized by slope and intercept) and discrimination (C-index). We validated five published models for 6-month GOSE and three for 6-month PPCS scores. The models used different cutoffs for outcome and some included symptoms measured 2 weeks post-injury. Discriminative ability varied substantially (C-index between 0.58 and 0.79). The models developed in the Corticosteroid Randomisation After Significant Head Injury (CRASH) trial for prediction of GOSE <5 discriminated best (C-index 0.78 and 0.79), but were poorly calibrated. The best performing models for PPCS included 2-week symptoms (C-index 0.75 and 0.76). In conclusion, none of the prognostic models for early prediction of GOSE and PPCS has both good calibration and discrimination in persons with mild TBI. In future studies, prognostic models should be tailored to the population with mild TBI, predicting relevant end-points based on readily available predictors.

Treatment for posttraumatic stress disorder in patients with a history of traumatic brain injury: A systematic review.

Posttraumatic stress disorder (PTSD) frequently co-occurs with traumatic brain injury (TBI). We conducted a systematic review to evaluate the appropriateness and effectiveness of treatments for PTSD in adult patients with a history of TBI. We searched for longitudinal studies aimed at treatments for PTSD patients who sustained a TBI, published in English between 1980 and February 2019. Twenty-three studies were found eligible, and 26 case studies were included for a separate overview. The quality of eligible studies was assessed using the Research Triangle Institute item bank. The majority of studies included types of cognitive-behavioral therapy (CBT) in male service members and veterans with a history of mild TBI in the United States. Studies using prolonged exposure (PE), cognitive-processing therapy (CPT) or other types of CBT, usually in combination with additional treatments, showed favorable outcomes. A smaller number of studies described complementary and novel therapies, which showed promising results. Overall, the quality of studies was considered low. We concluded that CBT seem appropriate for the patient population with history of TBI. The evidence is less strong for other therapies. We recommend controlled studies of PTSD treatments including more female patients and those with a history of moderate to severe TBIs in civilian and military populations.