OBJECTIVE: The purpose of the study was to investigate the effect of comorbid depression on glycemic control and on response to a telemedicine case management intervention for elderly, ethnically diverse diabetic patients. RESEARCH DESIGN AND METHODS: Medicare beneficiaries in underserved areas were participants (n = 1,665) in the Informatics for Diabetes Education and Telemedicine (IDEATel) project and randomized to atelemedicine case management intervention or usual care. The data analyzed include baseline demographics (age, sex, race/ethnicity, marital status, insulin use, years of education, years of diabetes, and pack-years smoked) and measures of glycemic control (HbA(1c) [A1C]), comorbidity, diabetes symptom severity, functional disability and depression, and 1-year (n = 1,578) A1C. The association between depression and glycemic control was analyzed cross-sectionally and prospectively. RESULTS: At baseline, there was a significant correlation between depression and A1C and a trend for depression to predict A1C when other factors were controlled. However, in prospective analyses, depression did not predict change in A1C, either in the control or intervention group. CONCLUSIONS: In this large sample of elderly diabetic patients, a weak relationship between depression and A1C was found, but depression did not prospectively predict change in glycemic control. Thus, there is no evidence that depression should be used to exclude patients from interventions. Also, we should evaluate the impact of depression on outcomes other than glycemic control.
RCT Entities:
OBJECTIVE: The purpose of the study was to investigate the effect of comorbid depression on glycemic control and on response to a telemedicine case management intervention for elderly, ethnically diverse diabeticpatients. RESEARCH DESIGN AND METHODS: Medicare beneficiaries in underserved areas were participants (n = 1,665) in the Informatics for Diabetes Education and Telemedicine (IDEATel) project and randomized to a telemedicine case management intervention or usual care. The data analyzed include baseline demographics (age, sex, race/ethnicity, marital status, insulin use, years of education, years of diabetes, and pack-years smoked) and measures of glycemic control (HbA(1c) [A1C]), comorbidity, diabetes symptom severity, functional disability and depression, and 1-year (n = 1,578) A1C. The association between depression and glycemic control was analyzed cross-sectionally and prospectively. RESULTS: At baseline, there was a significant correlation between depression and A1C and a trend for depression to predict A1C when other factors were controlled. However, in prospective analyses, depression did not predict change in A1C, either in the control or intervention group. CONCLUSIONS: In this large sample of elderly diabeticpatients, a weak relationship between depression and A1C was found, but depression did not prospectively predict change in glycemic control. Thus, there is no evidence that depression should be used to exclude patients from interventions. Also, we should evaluate the impact of depression on outcomes other than glycemic control.
Authors: Priya Palta; Sherita Hill Golden; Jeanne A Teresi; Walter Palmas; Paula Trief; Ruth S Weinstock; Steven Shea; Jennifer J Manly; Jose A Luchsinger Journal: J Diabetes Complications Date: 2014-07-01 Impact factor: 2.852
Authors: Dana March; José A Luchsinger; Jeanne A Teresi; Joseph P Eimicke; Sally E Findley; Olveen Carrasquillo; Walter Palmas Journal: J Health Care Poor Underserved Date: 2014-02
Authors: Kavita Venkataraman; Anjur Tupil Kannan; Om Prakash Kalra; Jasvinder Kaur Gambhir; Arun Kumar Sharma; K R Sundaram; V Mohan Journal: J Community Health Date: 2012-06
Authors: Ching-Ju Chiu; Linda A Wray; Elizabeth A Beverly; Oralia G Dominic Journal: Soc Psychiatry Psychiatr Epidemiol Date: 2009-04-03 Impact factor: 4.328
Authors: Lawrence Fisher; Joseph T Mullan; Patricia Arean; Russell E Glasgow; Danielle Hessler; Umesh Masharani Journal: Diabetes Care Date: 2009-10-16 Impact factor: 19.112