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Haemoglobin A1c is a predictor of COVID-19 severity in patients with diabetes. | LitMetric

Haemoglobin A1c is a predictor of COVID-19 severity in patients with diabetes.

Diabetes Metab Res Rev

Diabetes Unit, Institute of Endocrinology, Metabolism and Hypertension, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel.

Published: July 2021


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Article Abstract

Aim: Poor outcomes of coronavirus disease 2019 (COVID-19) have been linked to diabetes, but its relation to pre-infection glycaemic control is still unclear.

Materials And Methods: To address this question, we report here the association between pre-infection Haemoglobin A1c (HbA1c) levels and COVID-19 severity as assessed by need for hospitalization in a cohort of 2068 patients with diabetes tested for COVID-19 in Leumit Health Services (LHSs), Israel, between 1 February and 30 April 2020. Using the LHS-integrated electronic medical records system, we were able to collect a large amount of clinical information including age, sex, socio-economic status, weight, height, body mass index, HbA1c, prior diagnosis of ischaemic heart disease, depression/anxiety, schizophrenia, dementia, hypertension, cerebrovascular accident, congestive heart failure, smoking, and chronic lung disease.

Results: Of the patients included in the cohort, 183 (8.85%) were diagnosed with COVID-19 and 46 were admitted to hospital. More hospitalized patients were female, came from higher socio-economic background and had a higher baseline HbA1c. A prior diagnosis of cerebrovascular accident and chronic lung disease conferred an increased risk of hospitalization but not obesity or smoking status. In a multivariate analysis, controlling for multiple prior clinical conditions, the only parameter associated with a significantly increased risk for hospitalization was HbA1c ≥ 9%.

Conclusion: Using pre-infection glycaemic control data, we identify HbA1c as a clear predictor of COVID-19 severity. Pre-infection risk stratification is crucial to successfully manage this disease, efficiently allocate resources, and minimize the economic and social burden associated with an undiscriminating approach.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7460936PMC
http://dx.doi.org/10.1002/dmrr.3398DOI Listing

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