Literature DB >> 34137288

Can Innovative Technologies Overcome HbA1c Disparity for African-American Youth with Type 1 Diabetes?

Stuart Chalew1, Alan M Delamater2, Sonja Washington3, Jayalakshmi Bhat1, Diane Franz4, Ricardo Gomez1, Dania Felipe1, Peter Tieh1, Laurie Finger3.   

Abstract

Achieving normal or near-normal glycemic control as reflected by HbA1c levels in patients with type 1 diabetes (T1D) is important for preventing the development and progression of chronic complications. Despite delineation and dissemination of HbA1c management targets and advances in insulin pharmacology, insulin delivery systems, and glucose monitoring, the majority of children with T1D do not achieve HbA1c goals. In particular, African Americans are more likely not to reach HbA1c goals and have persistently higher HbA1c than Non-Hispanic Whites. Availability of pumps and other technology has not eliminated the disparity in HbA1c. Multiple factors play a role in the persisting racial disparity in HbA1c outcome. The carefully designed application and deployment of new technology to help the patient/family and facilitate the supportive role of the diabetes management team may be able to overcome racial disparity in glycemic outcome and improve patient quality of life.

Entities:  

Keywords:  African American; HbA1c; non-Hispanic Black; racial disparity; type 1 diabetes; youth

Mesh:

Substances:

Year:  2021        PMID: 34137288      PMCID: PMC8442203          DOI: 10.1177/19322968211021386

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


  85 in total

1.  Current state of type 1 diabetes treatment in the U.S.: updated data from the T1D Exchange clinic registry.

Authors:  Kellee M Miller; Nicole C Foster; Roy W Beck; Richard M Bergenstal; Stephanie N DuBose; Linda A DiMeglio; David M Maahs; William V Tamborlane
Journal:  Diabetes Care       Date:  2015-06       Impact factor: 19.112

2.  Differences in Red Blood Cell Indices Do Not Explain Racial Disparity in Hemoglobin A1c in Children with Type 1 Diabetes.

Authors:  Mahmoud Adeeb Ahmad Hamdan; James M Hempe; Cruz Velasco-Gonzalez; Ricardo Gomez; Alfonso Vargas; Stuart Chalew
Journal:  J Pediatr       Date:  2016-05-04       Impact factor: 4.406

3.  Pediatric Diabetes Consortium Type 1 Diabetes New Onset (NeOn) Study: factors associated with HbA1c levels one year after diagnosis.

Authors:  Maria J Redondo; Crystal G Connor; Katrina J Ruedy; Roy W Beck; Craig Kollman; Jamie R Wood; Bruce Buckingham; Georgeanna J Klingensmith; Janet Silverstein; William V Tamborlane
Journal:  Pediatr Diabetes       Date:  2013-07-24       Impact factor: 4.866

4.  Clinical outcomes in youth beyond the first year of type 1 diabetes: Results of the Pediatric Diabetes Consortium (PDC) type 1 diabetes new onset (NeOn) study.

Authors:  Eda Cengiz; Peiyao Cheng; Katrina J Ruedy; Craig Kollman; William V Tamborlane; Georgeanna J Klingensmith; Robin L Gal; Janet Silverstein; Joyce Lee; Maria J Redondo; Roy W Beck
Journal:  Pediatr Diabetes       Date:  2016-10-19       Impact factor: 4.866

5.  The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus.

Authors:  D M Nathan; S Genuth; J Lachin; P Cleary; O Crofford; M Davis; L Rand; C Siebert
Journal:  N Engl J Med       Date:  1993-09-30       Impact factor: 91.245

6.  Biological variation in HbA1c predicts risk of retinopathy and nephropathy in type 1 diabetes.

Authors:  Robert J McCarter; James M Hempe; Ricardo Gomez; Stuart A Chalew
Journal:  Diabetes Care       Date:  2004-06       Impact factor: 19.112

7.  "I Didn't Really Have a Choice": Qualitative Analysis of Racial-Ethnic Disparities in Diabetes Technology Use Among Young Adults with Type 1 Diabetes.

Authors:  Shivani Agarwal; Gladys Crespo-Ramos; Judith A Long; Victoria A Miller
Journal:  Diabetes Technol Ther       Date:  2021-09       Impact factor: 7.337

8.  Racial-Ethnic Inequity in Young Adults With Type 1 Diabetes.

Authors:  Shivani Agarwal; Lauren G Kanapka; Jennifer K Raymond; Ashby Walker; Andrea Gerard-Gonzalez; Davida Kruger; Maria J Redondo; Michael R Rickels; Viral N Shah; Ashley Butler; Jeffrey Gonzalez; Alandra S Verdejo; Robin L Gal; Steven Willi; Judith A Long
Journal:  J Clin Endocrinol Metab       Date:  2020-08-01       Impact factor: 5.958

Review 9.  Data-Driven Blood Glucose Pattern Classification and Anomalies Detection: Machine-Learning Applications in Type 1 Diabetes.

Authors:  Ashenafi Zebene Woldaregay; Eirik Årsand; Taxiarchis Botsis; David Albers; Lena Mamykina; Gunnar Hartvigsen
Journal:  J Med Internet Res       Date:  2019-05-01       Impact factor: 5.428

10.  Changes to care delivery at nine international pediatric diabetes clinics in response to the COVID-19 global pandemic.

Authors:  Angelica Cristello Sarteau; Katherine Janine Souris; Jessica Wang; Amira A Ramadan; Ananta Addala; Deborah Bowlby; Sarah Corathers; Gun Forsander; Bruce King; Jennifer R Law; Wei Liu; Faisal Malik; Catherine Pihoker; Michael Seid; Carmel Smart; Frida Sundberg; Nikhil Tandon; Michael Yao; Terry Headley; Elizabeth Mayer-Davis
Journal:  Pediatr Diabetes       Date:  2021-02-16       Impact factor: 3.409

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