Machine learning based study of longitudinal HbA1c trends and their association with all-cause mortality: analyses from a national diabetes registry
Abstract
OBJECTIVE: The association of long-term HbA1c variability with mortality has been previously suggested. However, the significance of HbA1c variability and trends in different age and HbA1c categories is unclear. RESEARCH DESIGN AND METHODS: Data on patients with diabetes listed in the Israeli National Diabetes Registry during years 2012-2016 (observation period) were collected. Patients with >4 HbA1c measurements, type 1 diabetes, eGFR < 30mg/ml/min, persistent HbA1c < 6% or malignancy were excluded. Utilizing machine learning methods, patients were classified into clusters according to their HbA1c trend (increasing, stable, decreasing). Mortality risk during 2017-2019 was calculated in subgroups defined by age (35-54, 55-69, 70-89 years) and last HbA1c (≤7% and >7%) at end of observation period. Models were adjusted for demographic, clinical and laboratory measurements including HbA1c, standard deviation (SD) of HbA1c and HbA1c trend. RESULTS: This historical cohort study included 293,314 patients. Increased HbA1c variability (high SD) during the observation period was an independent predictor of mortality in patients aged more than 55 years (p < 0.01). The HbA1c trend was another independent predictor of mortality. Patients with a decreasing versus stable HbA1c trend had a greater mortality risk; this association persisted in all age groups in patients with HbA1c > 7% at the end of the observation period (p = 0.02 in age 35-54; p < 0.01 in aged >55). Patients with an increasing versus stable HbA1c trend had a greater mortality risk only in the elderly group (>70), yet in both HbA1c categories (p < 0.01). CONCLUSIONS: HbA1c variability and trend are important determinants of mortality risk and should be considered when adjusting glycaemic targets.
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Glucose variability is associated with an increased risk for hypoglycemia.
“Glucose variability is also associated with an increased risk for hypoglycemia (92).”
From 6. Glycemic Targets: <i>Standards of Care in Diabetes—2023</i> (2023) · cites this paper as [92]
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6. Glycemic Targets: <i>Standards of Medical Care in Diabetes—2022</i>
American Diabetes Association Professional Practice Committee (2022) · Diabetes Care · doi:10.2337/dc22-s006 · Cited by 1,403 · see citing works
6. Glycemic Targets: <i>Standards of Care in Diabetes—2023</i>
ElSayed, N. A., Aleppo, G., Aroda, V. R., Bannuru, R. R., Brown, F. M., Bruemmer, D., Collins, B. S., Hilliard, M. E., Isaacs, D., Johnson, E. L., et al. (2023) · Diabetes Care · doi:10.2337/dc23-s006 · Cited by 684 · see citing works
- Authors
- Cahn, A., Zuker, I., Eilenberg, R., Uziel, M., Tsadok, M. A., Raz, I., & Lutski, M.
- Affiliations
- Hebrew University of Jerusalem (IL)
- Israel Center for Disease Control Ministry of Health Ramat Gan Israel
- Israel Ministry of Health (IL)
- Tel Aviv University (IL)
- Venue
- Diabetes/Metabolism Research and Reviews
- Publisher
- Wiley
- Published
- 2021-07-13
- Volume
- 38
- Issue
- 1
- Pages
- e3485-e3485
- ISSN
- 1520-7552 (ISSN-L)
- 1520-7560
- OpenAlex
- W3182093666
- Cited by
- 9
- References
- 26
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 2 · 2022: 4 · 2021: 1
- FWCI
- 1.49
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Diabetes/Metabolism Research and Reviews (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Keywords
- HbA1c variability, HbA1c trends, all-cause mortality, diabetes mellitus, glycemic control, glycemic targets, type 1 diabetes, age differences in mortality risk
- MeSH terms
- Machine Learning, Adult, Aged, Diabetes Mellitus, Type 2, Glycated Hemoglobin, Humans, Middle Aged, Registries, Risk Factors, Cohort Studies
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