Keywords
Insuffisance coronarienne ×
Mostra di più Keywords
Sommario
  1. 1. Test clinico
  2. 2. Documentazione di routine
  3. 3. Registro / studio di coorte
  4. 4. Garanzia di qualità
  5. 5. Dati Standard
  6. 6. Risultato segnalato dal paziente
  7. 7. Specialità mediche
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- 27/11/24 - 6 moduli, 2 itemgroups, 11 elementi, 1 linguaggio
Itemgroups: IG.elig, IG.elig
Principal Investigator: Scott T. Weiss, MD, MS, Partners HealthCare System, Boston, MA, USA MeSH: Hypercholesterolemia,Asthma,Arthritis, Rheumatoid,Attention Deficit Disorder with Hyperactivity,Bipolar Disorder,Coronary Disease,Depression,Heart Failure,Inflammatory Bowel Diseases,Multiple Sclerosis,Schizophrenia,Stroke https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000944 The Partners HealthCare Biobank is a large research data and sample repository working within the framework of Partners Personalized Medicine. It provides researchers access to high quality, consented samples to help foster research, advance understanding of the causes of common diseases, and advance the practice of medicine. The Partners Biobank provides banked samples (plasma, serum and DNA) collected from consented patients. These samples are available for distribution to Partners HealthCare investigators with appropriate approval from the Partners Institutional Review board (IRB). They are linked to clinical data that originates in the Electronic Medical Record (EMR), as well as additional health information collected in a self-reported survey. The Partners Biobank will be genotyping 25,000 subjects with the Illumina Multiethnic Beadchip 1.6 million SNPs with exome and custom content ( 60,000 LoFs). Of the participants genotyped so far, 4929 of 4962 (99.3%) individuals have genotype data that passed the default quality thresholds for the Infinium array (call rate = 0.99). We are submitting the genotype data to dbGaP for 4929 subjects with 12 phenotypes (based on icd9 codes). We will do annual releases until we reach the full 25,000 genotyped subjects.

pht004847.v1.p1

1 ItemGroup 5 elementi

pht005288.v1.p1

1 ItemGroup 6 elementi

pht004844.v1.p1

1 ItemGroup 2 elementi

pht004845.v1.p1

1 ItemGroup 3 elementi

pht004846.v1.p1

1 ItemGroup 18 elementi
- 28/04/24 - 5 moduli, 1 ItemGroup, 1 elemento, 1 linguaggio
ItemGroup: IG.elig
Principal Investigator: Ruth Loos, PhD, The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA MeSH: Cardiovascular Diseases,Obesity,Diabetes Mellitus, Type 2,Glucose,Kidney Failure, Chronic,Cholesterol, HDL,Cholesterol, LDL,Triglycerides,Coronary Disease,Myocardial Infarction,Inflammation,Stroke,Body Height https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000925 The Institute for Personalized Medicine (IPM) Bio*Me* Biobank is a consented, EMR-linked medical care setting biorepository of the Mount Sinai Medical Center (MSMC) drawing from a population of over 70,000 inpatients and 800,000 outpatient visits annually. MSMC serves diverse local communities of upper Manhattan, including Central Harlem (86% African American), East Harlem (88% Hispanic Latino), and Upper East Side (88% Caucasian/white) with broad health disparities. IPM Bio*Me* Biobank populations include 28% African American, 38% Hispanic Latino predominantly of Caribbean origin, 23% Caucasian/White. IPM BioMe Biobank disease burden is reflective of health disparities with broad public health impact. Biobank operations are fully integrated in clinical care processes, including direct recruitment from clinical sites waiting areas and phlebotomy stations by dedicated Biobank recruiters independent of clinical care providers, prior to or following a clinician standard of care visit. Recruitment currently occurs at a broad spectrum of over 30 clinical care sites. This study is part of the Population Architecture using Genomics and Epidemiology (PAGE) study (phs000356).

pht005176.v1.p1

1 ItemGroup 4 elementi

pht005178.v1.p1

1 ItemGroup 6 elementi

pht006203.v1.p1

1 ItemGroup 6 elementi

pht005177.v1.p1

1 ItemGroup 5 elementi
- 10/01/23 - 6 moduli, 1 ItemGroup, 2 elementi, 1 linguaggio
ItemGroup: pht003668

pht003670.v1.p1

1 ItemGroup 16 elementi

pht003672.v1.p1

1 ItemGroup 15 elementi

pht003673.v1.p1

1 ItemGroup 4 elementi

pht003669.v1.p1

1 ItemGroup 5 elementi

pht003671.v1.p1

1 ItemGroup 4 elementi
- 28/12/22 - 6 moduli, 1 ItemGroup, 1 elemento, 1 linguaggio
ItemGroup: IG.elig
Principal Investigator: Ranjan Deka, PhD, University of Cincinnati, Cincinnati, OH, USA MeSH: Metabolic Syndrome X,Diabetes mellitus type 2,Hypertension, Essential,Dyslipidemia,Coronary Heart Disease,Gout https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000737 The major objective of this study was to conduct a systematic genetic study of metabolic traits involved in metabolic syndrome through collection and analysis of epidemiological, demographic, environmental, and relevant biological and clinical data from a relatively isolated island population of the eastern Adriatic coast of Croatia. The population was chosen for the following reasons: 1) in spite of practicing a largely traditional life style and dietary habits, high rates of obesity, arterial hypertension, dyslipidemia and related metabolic abnormalities were found in previous studies; 2) the population was established by a relatively small number of founders, predominantly of Slavic descent from the mainland during 15th to 18th century AD, a genetically homogeneous population living in a homogeneous environment; 3) sharing a common European ancestry, a relevant population for study in the context of the general US population; 4) Croatian collaborators have been conducting anthropological and genetic studies in these communities for over three decades. There were two major aims of the study: 1) to recruit ~1200 adult participants and collect blood samples together with demographic, anthropometric, environmental and clinical data from the island of Hvar; to perform biochemical tests to measure glucose, insulin, uric acid and lipid levels; 2) conduct a genome-wide association analysis of metabolic traits and phenotypes using genome-wide SNP arrays (Affymetrix Genome-Wide Human SNP Array 5.0).

pht004443.v1.p1

1 ItemGroup 4 elementi

pht004444.v1.p1

1 ItemGroup 5 elementi

pht004445.v1.p1

1 ItemGroup 7 elementi

pht004446.v1.p1

1 ItemGroup 52 elementi

pht004447.v1.p1

1 ItemGroup 6 elementi
- 17/09/21 - 1 modulo, 12 itemgroups, 272 elementi, 1 linguaggio
Itemgroups: Demographic Information, Smoking, Diet/Body weight, Physical activity, Blood pressure,Cholesterol and Diabetes, Risk factor awareness and targets, Lifestyle changes, Risk perception, Medication, Family history of cardiovascular disease, Physical measurements, Blood sample

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