ID
45483
Description
Principal Investigator: Harold I. Feldman, MD, MSCE, University of Pennsylvania, Philadelphia, PA, USA MeSH: Chronic Renal Insufficiency https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000524 The Chronic Renal Insufficiency Cohort (CRIC study) was established in 2001 by the National Institute of Diabetes, Digestive, and Kidney Diseases (NIDDK) to improve the understanding of the relationship between chronic kidney disease and cardiovascular disease. The goals of the CRIC Study are to examine risk factors for progression of chronic kidney disease and cardiovascular disease among patients with chronic kidney disease and to develop predictive models to identify high-risk subgroups, informing future treatment trials and increasing application of available preventive therapies.
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Mots-clés
Versions (2)
- 31/10/2022 31/10/2022 - Simon Heim
- 13/12/2022 13/12/2022 - Kristina Keller
Détendeur de droits
Harold I. Feldman, MD, MSCE, University of Pennsylvania, Philadelphia, PA, USA
Téléchargé le
13 décembre 2022
DOI
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Licence
Creative Commons BY 4.0
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dbGaP phs000524 Chronic Renal Insufficiency Cohort Study (CRIC)
The data table contains mapping of study subject IDs to sample IDs for subjects with chronic renal insufficiency. Samples are the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs. Also included is the sample use.
- StudyEvent: SEV1
- Eligibility Criteria
- This data table contains subject IDs and consent group information for subjects with chronic renal insufficiency.
- The data table contains mapping of study subject IDs to sample IDs for subjects with chronic renal insufficiency. Samples are the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs. Also included is the sample use.
- The subject phenotype data table includes self-reported medical history (n=9 variables; asthma, arthritis, COPD, MI/prior revascularization, PVD, CHF, stroke, any CVD, and atrial fibrillation/heart arrythmia), family history (n=2 variables; CAD and renal disease), anthropometric measurements (n=5 variables; height, weight, BMI, BSA, and waist), blood pressure and pulse measures (systolic/diastolic, MAP, pulse, ankle brachial indices), CO2 measurement, lipid data (n=5 variables), diabetes screening (n=2 variables), eGFR, serum lab measurements (n=16 variables), CBC measurements (n=2 variables), urine lab measurements (n=3 variables), Becks and MMSE scores, smoking status (n=2 variables), alcohol use, medications (n=3 variables), and medication indicators (n=47 variables).
- The sample attributes data table includes sample analyte type (DNA or RNA), body site where samples were collected, is tumor status, and histological type.
Similar models
The data table contains mapping of study subject IDs to sample IDs for subjects with chronic renal insufficiency. Samples are the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs. Also included is the sample use.
- StudyEvent: SEV1
- Eligibility Criteria
- This data table contains subject IDs and consent group information for subjects with chronic renal insufficiency.
- The data table contains mapping of study subject IDs to sample IDs for subjects with chronic renal insufficiency. Samples are the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs. Also included is the sample use.
- The subject phenotype data table includes self-reported medical history (n=9 variables; asthma, arthritis, COPD, MI/prior revascularization, PVD, CHF, stroke, any CVD, and atrial fibrillation/heart arrythmia), family history (n=2 variables; CAD and renal disease), anthropometric measurements (n=5 variables; height, weight, BMI, BSA, and waist), blood pressure and pulse measures (systolic/diastolic, MAP, pulse, ankle brachial indices), CO2 measurement, lipid data (n=5 variables), diabetes screening (n=2 variables), eGFR, serum lab measurements (n=16 variables), CBC measurements (n=2 variables), urine lab measurements (n=3 variables), Becks and MMSE scores, smoking status (n=2 variables), alcohol use, medications (n=3 variables), and medication indicators (n=47 variables).
- The sample attributes data table includes sample analyte type (DNA or RNA), body site where samples were collected, is tumor status, and histological type.