Introduction The Berlin Long-term Observation of Vascular Events is a prospective cohort study that aims to improve prediction and disease-overarching mechanistic understanding of cardiovascular ... Show moreIntroduction The Berlin Long-term Observation of Vascular Events is a prospective cohort study that aims to improve prediction and disease-overarching mechanistic understanding of cardiovascular (CV) disease progression by comprehensively investigating a high-risk patient population with different organ manifestations.Methods and analysis A total of 8000 adult patients will be recruited who have either suffered an acute CV event (CVE) requiring hospitalisation or who have not experienced a recent acute CVE but are at high CV risk. An initial study examination is performed during the acute treatment phase of the index CVE or after inclusion into the chronic high risk arm. Deep phenotyping is then performed after similar to 90 days and includes assessments of the patient's medical history, health status and behaviour, cardiovascular, nutritional, metabolic, and anthropometric parameters, and patient-related outcome measures. Biospecimens are collected for analyses including 'OMICs' technologies (e.g., genomics, metabolomics, proteomics). Subcohorts undergo MRI of the brain, heart, lung and kidney, as well as more comprehensive metabolic, neurological and CV examinations. All participants are followed up for up to 10 years to assess clinical outcomes, primarily major adverse CVEs and patient-reported (value-based) outcomes. State-of-the-art clinical research methods, as well as emerging techniques from systems medicine and artificial intelligence, will be used to identify associations between patient characteristics, longitudinal changes and outcomes.Ethics and dissemination The study was approved by the Charite-Universitatsmedizin Berlin ethics committee (EA1/066/17). The results of the study will be disseminated through international peer-reviewed publications and congress presentations.Clinical Registry Platform: http://apps.who.int/trialsearch/Trial2.aspx? TrialID=DRKS00016852. Recruitment started on July 18, 2017.Second study phase: Approved WHO primary register: German Clinical Trials Register DRKS00023323, date of registration: November 4, 2020, URL: http://www.drks.de/DRKS00023323. Recruitment started on January 1, 2021. Show less
Traumatic brain injury (TBI) remains one of the leading causes of death and disability worldwide. To better understand its impact on various outcome domains, this study pursues the following: (1)... Show moreTraumatic brain injury (TBI) remains one of the leading causes of death and disability worldwide. To better understand its impact on various outcome domains, this study pursues the following: (1) longitudinal outcome assessments at three, six, and twelve months post-injury; (2) an evaluation of sociodemographic, premorbid, and injury-related factors, and functional recovery contributing to worsening or improving outcomes after TBI. Using patient-reported outcome measures, recuperation trends after TBI were identified by applying Multivariate Latent Class Mixed Models (MLCMM). Instruments were grouped into TBI-specific and generic health-related quality of life (HRQoL; QOLIBRI-OS, SF-12v2), and psychological and post-concussion symptoms (GAD-7, PHQ-9, PCL-5, RPQ). Multinomial logistic regressions were carried out to identify contributing factors. For both outcome sets, the four-class solution provided the best match between goodness of fit indices and meaningful clinical interpretability. Both models revealed similar trajectory classes: stable good health status (HRQoL: n = 1944; symptoms: n = 1963), persistent health impairments (HRQoL: n = 442; symptoms: n = 179), improving health status (HRQoL: n = 83; symptoms: n = 243), and deteriorating health status (HRQoL: n = 86; symptoms: n = 170). Compared to individuals with stable good health status, the other groups were more likely to have a lower functional recovery status at three months after TBI (i.e., the GOSE), psychological problems, and a lower educational attainment. Outcome trajectories after TBI show clearly distinguishable patterns which are reproducible across different measures. Individuals characterized by persistent health impairments and deterioration require special attention and long-term clinical monitoring and therapy. Show less
Wijk, R.P.J. van; Dijck, J.T.J.M. van; Timmers, M.; Veen, E. van; Citerio, G.; Lingsma, H.F.; ... ; CENTER-TB1 Investigators 2020
Purpose: Enrolling traumatic brain injury (731) patients with an inability to provide informed consent in research is challenging. Alternatives to patient consent are not sufficiently embedded in... Show morePurpose: Enrolling traumatic brain injury (731) patients with an inability to provide informed consent in research is challenging. Alternatives to patient consent are not sufficiently embedded in European and national legislation, which allows procedural variation and bias. We aimed to quantify variations in informed consent policy and practice.Methods: Variation was explored in the CENTER-TBI study. Policies were reported by using a questionnaire and national legislation. Data on used informed consent procedures were available for 4498 patients from 57 centres across 17 European countries.Results: Variation in the use of informed consent procedures was found between and within EU member states. Proxy informed consent (N = 1377;64%) was the most frequently used type of consent in the ICU, followed by patient informed consent (N 426;20%) and deferred consent (N 334;16%). Deferred consent was only actively used in 15 centres (26%), although it was considered valid in 47 centres (82%).Conclusions: Alternatives to patient consent are essential for TBI research. While there seems to be concordance amongst national legislations, there is regional variability in institutional practices with respect to the use of different informed consent procedures. Variation could be caused by several reasons, including inconsistencies in clear legislation or knowledge of such legislation amongst researchers. (C) 2020 Published by Elsevier Inc. Show less
UNICEF Nederland; Liefaard, T.; Helbing, S.; Schmidt, S.; Leeuw, S. de; Bikker, M.; ... ; Kokx, S. 2020
Studying individuals with extreme phenotypes could facilitate the understanding of disease modification by genetic or environmental factors. Our aim was to identify Huntington's disease (HD)... Show moreStudying individuals with extreme phenotypes could facilitate the understanding of disease modification by genetic or environmental factors. Our aim was to identify Huntington's disease (HD) patients with extreme symbol digit modality test (SDMT) scores. We first examined in HD the contribution of cognitive measures of the Unified Huntington's Disease Rating Scale (UHDRS) in predicting clinical endpoints. The language-independent SDMT was used to identify patients performing very well or very poorly relative to their CAG and age cohort. We used data from REGISTRY and COHORT observational study participants (5,603 HD participants with CAG repeats above 39 with 13,868 visits) and of 1,006 healthy volunteers (with 2,241 visits), included to identify natural aging and education effects on cognitive measures. Separate Cox proportional hazards models with CAG, age at study entry, education, sex, UHDRS total motor score and cognitive (SDMT, verbal fluency, Stroop tests) scores as covariates were used to predict clinical endpoints. Quantile regression for longitudinal language-independent SDMT data was used for boundary (2.5% and 97.5% quantiles) estimation and extreme score analyses stratified by age, education, and CAG repeat length. Ten percent of HD participants had an extreme SDMT phenotype for at least one visit. In contrast, only about 3% of participants were consistent SDMT extremes at two or more visits. The thresholds for the one-visit and two-visit extremes can be used to classify existing and new individuals. The identification of these phenotype extremes can be useful in the search for disease modifiers. Show less
Essen, T.A. van; Boogert, H.F. den; Cnossen, M.C.; Ruiter, G.C.W. de; Haitsma, I.; Polinder, S.; ... ; Jagt, M. van der 2019
Clopidogrel (Plavix®), is a widely used antiplatelet agent, which shows high inter-individual variability in treat- ment response in patients following the standard dosing regimen. In this study, a... Show moreClopidogrel (Plavix®), is a widely used antiplatelet agent, which shows high inter-individual variability in treat- ment response in patients following the standard dosing regimen. In this study, a physiology-directed population pharmacokinetic/pharmacodynamic (PK/PD) model was developed based on clopidogrel and clopidogrel active metabolite (clop-AM) data from the PAPI and the PGXB2B studies using a step-wise approach in NONMEM (ver- sion 7.2). The developed model characterized the in vivo disposition of clopidogrel, its bioactivation into clop-AM in the liver and subsequent platelet aggregation inhibition in the systemic circulation reasonably well. It further allowed the identification of covariates that significantly impact clopidogrel's dose–concentration–response re- lationship. In particular, CYP2C19 intermediate and poor metabolizers converted 26.2% and 39.5% less clopidogrel to clop-AM, respectively, compared to extensive metabolizers. In addition, CES1 G143E mutation carriers have a reduced CES1 activity (82.9%) compared to wild-type subjects, which results in a significant increase in clop-AM formation. An increase in BMI was found to significantly decrease clopidogrel's bioactivation, whereas increased age was associated with increased platelet reactivity. Our PK/PD model analysis suggests that, in order to optimize clopidogrel dosing on a patient-by-patient basis, all of these factors have to be considered simultaneously, e.g. by using quantitative clinical pharmacology tools. Show less
Masters, D.; Capak, P.; Stern, D.; Ilbert, O.; Salvato, M.; Schmidt, S.; ... ; Cavuoti, S. 2015
Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common... Show moreAlthough it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (< 0.1 Hz)fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's "functional connectome." Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon_1000/. Show less
