Racial Differences in the Effectiveness of a Multifactorial Telehealth Intervention to Slow Diabetic Kidney Disease.
| dc.contributor.author | Kobe, Elizabeth A | |
| dc.contributor.author | Diamantidis, Clarissa J | |
| dc.contributor.author | Bosworth, Hayden B | |
| dc.contributor.author | Davenport, Clemontina A | |
| dc.contributor.author | Oakes, Megan | |
| dc.contributor.author | Alexopoulos, Anastasia-Stefania | |
| dc.contributor.author | Pendergast, Jane | |
| dc.contributor.author | Patel, Uptal D | |
| dc.contributor.author | Crowley, Matthew J | |
| dc.date.accessioned | 2024-01-02T20:47:35Z | |
| dc.date.available | 2024-01-02T20:47:35Z | |
| dc.date.issued | 2020-11 | |
| dc.description.abstract | BackgroundAfrican Americans are significantly more likely than non-African Americans to have diabetes, chronic kidney disease, and uncontrolled hypertension, increasing their risk for kidney function decline.ObjectiveThe objective of this study was to compare how African Americans and non-African Americans with diabetes responded to a multifactorial telehealth intervention designed to slow kidney function decline.Research designSecondary analysis of a randomized trial. Primary care patients (N=281, 56% African American) were allocated to either: (1) a multifactorial, pharmacist-delivered phone-based telehealth intervention focused on behavioral and medication management of diabetic kidney disease; or (2) an education control.MeasuresThe primary study outcome was change in estimated glomerular filtration rate (eGFR). Linear mixed models were used to explore the moderating effect of race on the relationship between study arm and eGFR decline over time; the mean annual rate of eGFR decline was estimated by race and study arm.ResultsFindings demonstrated a differential intervention effect on kidney function over time by race (Pinteraction=0.005). Among African Americans, the intervention arm had significantly greater preservation of eGFR over time than the control arm (difference in the annual rate of eGFR decline=1.5 mL/min/1.73 m; 95% confidence interval: 0.04, 3.02). For non-African Americans, the intervention arm had a faster decline in eGFR over time than the control arm (difference in the annual rate of eGFR decline=-1.7 mL/min/1.73 m; 95% confidence interval: -3.3, -0.02).ConclusionA multifactorial, pharmacist-delivered telehealth intervention for diabetic kidney disease may be more effective for slowing eGFR decline among African Americans than non-African Americans. | |
| dc.identifier | 00005650-202011000-00006 | |
| dc.identifier.issn | 0025-7079 | |
| dc.identifier.issn | 1537-1948 | |
| dc.identifier.uri | ||
| dc.language | eng | |
| dc.publisher | Ovid Technologies (Wolters Kluwer Health) | |
| dc.relation.ispartof | Medical care | |
| dc.relation.isversionof | 10.1097/mlr.0000000000001387 | |
| dc.rights.uri | ||
| dc.subject | Humans | |
| dc.subject | Diabetic Nephropathies | |
| dc.subject | Diabetes Mellitus, Type 2 | |
| dc.subject | Glomerular Filtration Rate | |
| dc.subject | Health Behavior | |
| dc.subject | Telemedicine | |
| dc.subject | Socioeconomic Factors | |
| dc.subject | Telephone | |
| dc.subject | Adolescent | |
| dc.subject | Adult | |
| dc.subject | Aged | |
| dc.subject | Middle Aged | |
| dc.subject | Pharmacists | |
| dc.subject | Disease Management | |
| dc.subject | Female | |
| dc.subject | Male | |
| dc.subject | Patient Education as Topic | |
| dc.subject | Medication Adherence | |
| dc.subject | Young Adult | |
| dc.subject | Racial Groups | |
| dc.subject | White People | |
| dc.subject | Black or African American | |
| dc.title | Racial Differences in the Effectiveness of a Multifactorial Telehealth Intervention to Slow Diabetic Kidney Disease. | |
| dc.type | Journal article | |
| duke.contributor.orcid | Diamantidis, Clarissa J|0000-0001-8212-6288 | |
| duke.contributor.orcid | Bosworth, Hayden B|0000-0001-6188-9825 | |
| duke.contributor.orcid | Crowley, Matthew J|0000-0002-6205-4536 | |
| pubs.begin-page | 968 | |
| pubs.end-page | 973 | |
| pubs.issue | 11 | |
| pubs.organisational-group | Duke | |
| pubs.organisational-group | School of Medicine | |
| pubs.organisational-group | Staff | |
| pubs.organisational-group | Basic Science Departments | |
| pubs.organisational-group | Clinical Science Departments | |
| pubs.organisational-group | Institutes and Centers | |
| pubs.organisational-group | Biostatistics & Bioinformatics | |
| pubs.organisational-group | Medicine | |
| pubs.organisational-group | Psychiatry & Behavioral Sciences | |
| pubs.organisational-group | Medicine, Endocrinology, Metabolism, and Nutrition | |
| pubs.organisational-group | Medicine, General Internal Medicine | |
| pubs.organisational-group | Medicine, Nephrology | |
| pubs.organisational-group | Duke Cancer Institute | |
| pubs.organisational-group | Duke Clinical Research Institute | |
| pubs.organisational-group | Institutes and Provost's Academic Units | |
| pubs.organisational-group | University Institutes and Centers | |
| pubs.organisational-group | Duke Global Health Institute | |
| pubs.organisational-group | Center for the Study of Aging and Human Development | |
| pubs.organisational-group | Initiatives | |
| pubs.organisational-group | Duke Science & Society | |
| pubs.organisational-group | Population Health Sciences | |
| pubs.organisational-group | Duke Innovation & Entrepreneurship | |
| pubs.organisational-group | Psychiatry & Behavioral Sciences, Behavioral Medicine & Neurosciences | |
| pubs.organisational-group | Duke - Margolis Center For Health Policy | |
| pubs.organisational-group | Biostatistics & Bioinformatics, Division of Biostatistics | |
| pubs.publication-status | Published | |
| pubs.volume | 58 |
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