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Improved individual and population-level HbA1c estimation using CGM data and patient characteristics.
Grossman, Joshua; Ward, Andrew; Crandell, Jamie L; Prahalad, Priya; Maahs, David M; Scheinker, David.
  • Grossman J; Department of Management Science and Engineering, Stanford School of Engineering, Stanford, CA, USA.
  • Ward A; Department of Management Science and Engineering, Stanford School of Engineering, Stanford, CA, USA.
  • Crandell JL; School of Nursing, Department of Biostatistics, UNC Chapel Hill, Chapel Hill, NC, USA.
  • Prahalad P; Division of Pediatric Endocrinology, Stanford School of Medicine, Stanford, CA, USA; Lucile Packard Children's Hospital, Stanford, CA, USA.
  • Maahs DM; Division of Pediatric Endocrinology, Stanford School of Medicine, Stanford, CA, USA; Lucile Packard Children's Hospital, Stanford, CA, USA; Stanford Diabetes Research Center, Stanford School of Medicine, Stanford, CA, USA; Department of Health Research and Policy, Stanford School of Medicine, Stanfo
  • Scheinker D; Department of Management Science and Engineering, Stanford School of Engineering, Stanford, CA, USA; Division of Pediatric Endocrinology, Stanford School of Medicine, Stanford, CA, USA; Lucile Packard Children's Hospital, Stanford, CA, USA; Stanford Diabetes Research Center, Stanford School of Medic
J Diabetes Complications ; 35(8): 107950, 2021 08.
Article in English | MEDLINE | ID: covidwho-1230603
ABSTRACT
Machine learning and linear regression models using CGM and participant data reduced HbA1c estimation error by up to 26% compared to the GMI formula, and exhibit superior performance in estimating the median of HbA1c at the cohort level, potentially of value for remote clinical trials interrupted by COVID-19.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Glycated Hemoglobin / Blood Specimen Collection / Diabetes Mellitus, Type 1 / COVID-19 Type of study: Cohort study / Observational study / Prognostic study Limits: Adolescent / Adult / Child / Female / Humans / Male / Young adult Language: English Journal: J Diabetes Complications Journal subject: Endocrinology Year: 2021 Document Type: Article Affiliation country: J.jdiacomp.2021.107950

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Glycated Hemoglobin / Blood Specimen Collection / Diabetes Mellitus, Type 1 / COVID-19 Type of study: Cohort study / Observational study / Prognostic study Limits: Adolescent / Adult / Child / Female / Humans / Male / Young adult Language: English Journal: J Diabetes Complications Journal subject: Endocrinology Year: 2021 Document Type: Article Affiliation country: J.jdiacomp.2021.107950