Suchergebnisse

Objectives: To compare patient-reported social determinants of health (SDOH) to the Brokamp Area Deprivation Index (ADI), and evaluate the association of patient-reported SDOH and ADI with mortality in patients with cardiovascular disease (CVD).Design: Prospective cohort.Setting: Academic medical center.Participants: Adults with acute coronary syndrome (ACS) and/or acute exacerbation of heart failure (HF) hospitalized between 2011 and 2015.Methods: Patient-reported SDOH included: income range, education, health insurance, and household size. ADI was calculated using census tract level variables of poverty, median income, high school completion, lack of health insurance, assisted income, and vacant housing.Primary outcome: All-cause mortality, up to 5 years follow-up.Results: The sample was 60% male, 84% White, and 93% insured; mean patient-reported household income was $48,000 (SD $34,000). ADI components were significantly associated with corresponding patient-report­ed variables. In age, sex, and race adjusted Cox regression models, ADI was associated with mortality for ACS (HR 1.23, 95% CI 1.06, 1.42), but not HF (HR 1.09, 95% CI .99, 1.21). Mortality models for ACS improved with consideration of social determinants data (C-statistics: base demographic model=.612; ADI added=.644; patient-reported SDOH added=.675; both ADI and patient-reported SDOH added=.689). HF mortality models improved only slightly (C-statistics: .600, .602, .617, .620, respectively).Conclusions: The Brokamp ADI is associated with mortality in hospitalized patients with CVD. In the absence of available patient-reported data, hospitals could implement the Brokamp ADI as an approximation for patient-reported data to enhance risk stratification of patients with CVD. Ethn Dis. 2021;31(1):9-22; doi:10.18865/ed.31.1.9

Only Vanderbilt University affiliated authors are listed on VUIR. For a full list of authors, access the version of record at https://www.nature.com/articles/s41467-019-11704-w ; Chronic kidney disease (CKD), defined by low estimated glomerular filtration rate (eGFR), contributes to global morbidity and mortality. Here we conduct a transethnic Genome-Wide Association Study of eGFR in 280,722 participants of the Million Veteran Program (MVP), with replication in 765,289 participants from the Chronic Kidney Disease Genetics (CKDGen) Consortium. We identify 82 previously unreported variants, confirm 54 loci, and report interesting findings including association of the sickle cell allele of betaglobin among non-Hispanic blacks. Our transcriptome-wide association study of kidney function in healthy kidney tissue identifies 36 previously unreported and nine known genes, and maps gene expression to renal cell types. In a Phenome-Wide Association Study in 192,868 MVP participants using a weighted genetic score we detect associations with CKD stages and complications and kidney stones. This investigation reinterprets the genetic architecture of kidney function to identify the gene, tissue, and anatomical context of renal homeostasis and the clinical consequences of dysregulation. ; This work was supported by VA grant I01BX003360 (to A.M.H.), for the contributions of A. G., A.M.H. and D.R.V.E. This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration. Acknowledgment of VA Million Veteran Program leadership and staff contributions can be found in Supplementary Note 2. This work was supported using resources and facilities of the VA Informatics and Computing Infrastructure (VINCI), VA HSR RES 13-457. We would also like to acknowledge the grants Genetics of Cardiometabolic Diseases in the VA Population (BX-003362-01); Veterans Affairs Office of Research and Development; PIs: PS Tsao and K-M Chang and U.S. Department of Veterans Affairs IK2-CX001870 (Damrauer PI); U.S. Department of Veterans Affairs I01-BX002641(PI Tsao and Chang). This project was supported in part the by VA Clinical Science research and Development investigator-initiated grant CX000570-06(Roumie). AMH was further supported by 1I01CX000982. This publication does not represent the views of the Department of Veterans Affairs or the United States Government. The authors are grateful to members of the Chronic Kidney Disease Genetics (CKDGen) Consortium for providing summary data for replication. A full list of CKDGen consortium membership can be found in Supplementary Note 3. D.R.V.E. and T.L.E. received support from NIH/NHLBI (HL121429). J.N.H. was supported by the Vanderbilt Molecular and Genetic Epidemiology of Cancer (MAGEC) training program, funded by T32CA160056 (PI: X.O. Shu). The work of J.N.H. and A.G. is supported by K12HD043483 (PI: K.E. Hartmann). J.M.K. is supported by the Vanderbilt Genomic Medicine Training Program. The Vanderbilt Genomic Medicine Training Program is supported by an institutional training grant (T32HG008341) from the National Human Genome Research Institute of the National Institute of Health. K.S. was funded by R01DK076077, R01DK105821, and DP3DK108220. The work of A.K. was supported by KO 3598/3-1 and CRCs 1140 and 992 of the German Research Foundation. The work of M.G. was supported by DFG BO3815/4-1. The work of M.W. was supported by DFG CRC 1140 and the Else Kroener Fresenius Forschungskolleg NAKSYS, and Y. L. was supported by DFG KO 3598/4-1. C.P.C. was supported by K23AR064768 (NIAMS) and the Rheumatology Research Foundation. C.R.-C. was supported by NIH/NIDDK K01DK109019. A dataset used for the analyses described were obtained from Vanderbilt University Medical Center's BioVU which is supported by institutional funding, the 1S10RR025141-01 instrumentation award, and by the CTSA grant UL1TR000445 from NCATS/NIH. Additional funding provided by the NIH through grants P50GM115305 and U19HL065962. The authors wish to acknowledge the technical support of the VANTAGE and VANGARD core facilities, supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA068485) and Vanderbilt Vision Center (P30 EY08126).