Search

Patients with ischemic stroke (IS) are at increased risk of mortality and recurrent cerebro- or cardiovascular events. Determining prognosis after IS remains challenging but blood-based biomarkers might provide additional prognostic information. As platelets are crucially involved in the pathophysiology of vascular diseases, platelet surface proteins (PSP) are promising candidates as prognostic markers in the hyperacute stage. In this pilot study, feasibility of PSP analysis by flow cytometry (HMGB1, CD84, CXCR4, CXCR7, CD62p with and without ADP-stimulation, CD41, CD61, CD40, GPVI) was investigated in 99 (median 66 years, 67.5% male) acute IS patients admitted to Stroke Unit within a substudy of the Stroke-Induced Cardiac FAILure in mice and men (SICFAIL) cohort study. Association between PSP expression and unfavorable one-year outcome (cerebro- or cardiovascular event, all-cause mortality and care dependency defined as Barthel Index Trial registration: German Clinical Trials Register (DRKS00011615).

Background and Purpose: Outcome prognostication in ischemic stroke patients remains challenging due to limited predictive properties of existing models. Blood-based biomarkers might provide additional information to established prognostic factors. We intended to identify the most promising prognostic biomarkers in ischemic stroke, their incremental prognostic value, and whether their predictive value differs among etiologies. Methods: We searched MEDLINE (Ovid) and Institute for Scientific Information Web of Knowledge for articles reporting the predictive performance of blood-based biomarkers measured up to 7 days after ischemic stroke and reporting functional outcome or death at least 7 days after stroke. This work updates a previous systematic review (up to January 2007), follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement and was registered (International Prospective Register of Systematic Reviews PROSPERO 2018; https://www.crd.york.ac.uk/PROSPERO /; Unique identifier: CRD42018094671). Results: Two hundred ninety-one articles published between January 2007 and August 2018 comprising 257 different biomarkers met inclusion criteria. Median sample size was 232 (interquartile range, 110–455); 260 (89%) articles reported regression analyses with 78% adjusting for stroke severity, 82% for age, 67% for both, and 9% for none of them; 37% investigated discrimination, 5% calibration, and 11% reclassification. Including publications from a previous systematic review (1960–January 2007), natriuretic peptides, copeptin, procalcitonin, mannose-binding lectin, adipocyte fatty acid–binding protein, and cortisol were the biomarkers most consistently associated with poor outcome in higher-quality studies showing an incremental value over established prognostic factors. Other biomarkers were less consistently associated with poor outcome or were reported in lower quality studies. High heterogeneity among studies precluded the performance of a meta-analysis. Conclusions: The number of reports on prognostic blood-based biomarkers in ischemic stroke increased 3.5-fold in the period January 2007 to August 2018. Although sample size increased, methodological flaws are still common. Natriuretic peptides and markers of inflammation, atherogenesis, and stress response are the most promising prognostic biomarkers among identified studies.

The German government initiated the Network University Medicine (NUM) in early 2020 to improve national research activities on the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. To this end, 36 German Academic Medical Centers started to collaborate on 13 projects, with the largest being the National Pandemic Cohort Network (NAPKON). The NAPKON’s goal is creating the most comprehensive Coronavirus Disease 2019 (COVID-19) cohort in Germany. Within NAPKON, adult and pediatric patients are observed in three complementary cohort platforms (Cross-Sectoral, High-Resolution and Population-Based) from the initial infection until up to three years of follow-up. Study procedures comprise comprehensive clinical and imaging diagnostics, quality-of-life assessment, patient-reported outcomes and biosampling. The three cohort platforms build on four infrastructure core units (Interaction, Biosampling, Epidemiology, and Integration) and collaborations with NUM projects. Key components of the data capture, regulatory, and data privacy are based on the German Centre for Cardiovascular Research. By December 01, 2021, 34 university and 34 non-university hospitals have enrolled 4,241 patients with local data quality reviews performed on 2,812 (66%). 47% were female, the median age was 53 (IQR: 38-63)) and 3 pediatric cases were included. 30% of patients were hospitalized, 11% admitted to an intensive care unit, and 4% of patients deceased while enrolled. 7,143 visits with biosampling in 3,595 patients were conducted by November 29, 2021. In this overview article, we summarize NAPKON’s design, relevant milestones including first study population characteristics, and outline the potential of NAPKON for German and international research activities.Trial registration:· https://clinicaltrials.gov/ct2/show/NCT04768998· https://clinicaltrials.gov/ct2/show/NCT04747366· https://clinicaltrials.gov/ct2/show/NCT04679584

The German government initiated the Network University Medicine (NUM) in early 2020 to improve national research activities on the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. To this end, 36 German Academic Medical Centers started to collaborate on 13 projects, with the largest being the National Pandemic Cohort Network (NAPKON). The NAPKON’s goal is creating the most comprehensive Coronavirus Disease 2019 (COVID-19) cohort in Germany. Within NAPKON, adult and pediatric patients are observed in three complementary cohort platforms (Cross-Sectoral, High-Resolution and Population-Based) from the initial infection until up to three years of follow-up. Study procedures comprise comprehensive clinical and imaging diagnostics, quality-of-life assessment, patient-reported outcomes and biosampling. The three cohort platforms build on four infrastructure core units (Interaction, Biosampling, Epidemiology, and Integration) and collaborations with NUM projects. Key components of the data capture, regulatory, and data privacy are based on the German Centre for Cardiovascular Research. By April 01, 2022, 34 university and 40 non-university hospitals have enrolled 5298 patients with local data quality reviews performed on 4727 (89%). 47% were female, the median age was 52 (IQR 36–62-) and 50 pediatric cases were included. 44% of patients were hospitalized, 15% admitted to an intensive care unit, and 12% of patients deceased while enrolled. 8845 visits with biosampling in 4349 patients were conducted by April 03, 2022. In this overview article, we summarize NAPKON’s design, relevant milestones including first study population characteristics, and outline the potential of NAPKON for German and international research activities.Trial registrationhttps://clinicaltrials.gov/ct2/show/NCT04768998.https://clinicaltrials.gov/ct2/show/NCT04747366.https://clinicaltrials.gov/ct2/show/NCT04679584

Orphanet journal of rare diseases : OJRD 17(1), 47 (2022). doi:10.1186/s13023-022-02176-1, Published by BioMed Central, London

Purpose Over the course of COVID-19 pandemic, evidence has accumulated that SARS-CoV-2 infections may affect multiple organs and have serious clinical sequelae, but on-site clinical examinations with non-hospitalized samples are rare. We, therefore, aimed to systematically assess the long-term health status of samples of hospitalized and non-hospitalized SARS-CoV-2 infected individuals from three regions in Germany. Methods The present paper describes the COVIDOM-study within the population-based cohort platform (POP) which has been established under the auspices of the NAPKON infrastructure (German National Pandemic Cohort Network) of the national Network University Medicine (NUM). Comprehensive health assessments among SARS-CoV-2 infected individuals are conducted at least 6 months after the acute infection at the study sites Kiel, Würzburg and Berlin. Potential participants were identified and contacted via the local public health authorities, irrespective of the severity of the initial infection. A harmonized examination protocol has been implemented, consisting of detailed assessments of medical history, physical examinations, and the collection of multiple biosamples (e.g., serum, plasma, saliva, urine) for future analyses. In addition, patient-reported perception of the impact of local pandemic-related measures and infection on quality-of-life are obtained. Results As of July 2021, in total 6813 individuals infected in 2020 have been invited into the COVIDOM-study. Of these, about 36% wished to participate and 1295 have already been examined at least once. Conclusion NAPKON-POP COVIDOM-study complements other Long COVID studies assessing the long-term consequences of an infection with SARS-CoV-2 by providing detailed health data of population-based samples, including individuals with various degrees of disease severity. Trial registration Registered at the German registry for clinical studies (DRKS00023742).

Aims: Ischaemic stroke (IS) might induce alterations of cardiac function. Prospective data on frequency of cardiac dysfunction and heart failure (HF) after IS are lacking. We assessed prevalence and determinants of diastolic dysfunction (DD), systolic dysfunction (SD), and HF in patients with acute IS. Methods and results: The Stroke-Induced Cardiac FAILure in mice and men (SICFAIL) study is a prospective, hospital-based cohort study. Patients with IS underwent a comprehensive assessment of cardiac function in the acute phase (median 4 days after IS) including clinical examination, standardized transthoracic echocardiography by expert sonographers, and determination of blood-based biomarkers. Information on demographics, lifestyle, risk factors, symptoms suggestive of HF, and medical history was collected by a standardized personal interview. Applying current guidelines, cardiac dysfunction was classified based on echocardiographic criteria into SD (left ventricular ejection fraction