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Predictors of New Onset Dysglycemia Post COVID-19

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Background: Hyperglycemia postcoronavirus disease 2019 (COVID-19) infection is multifactorial and warrants serial monitoring of blood glucose. Aims: The aim of the study was to assess the incidence of glucose intolerance and new-onset diabetes in patients who have recovered from COVID-19 and to correlate the risk factors for dysglycemia. Materials and Methods: Participants who were admitted for COVID-19 infection at St John’s Hospital, Bangalore, India, at least 6 months previously were enrolled in the study using telephonic interviews. Details regarding age, gender, weight, and history were obtained. Laboratory parameters such as fasting blood sugar, postprandial blood sugar, and glycated hemoglobin (HbA1c) were obtained. The comparison between the dysglycemia and normoglycemia groups was conducted using either independent samples t -test or Mann–Whitney U test and using the Chi-squared test or Fisher’s exact test, as appropriate. Multivariate logistic regression was employed to determine the adjusted effect of multiple variables on dysglycemia. Results: The overall mean age of the study group was 40 ± 13 years with 68 (52%) male patients. Of the 131 patients, 93 had mild, 32 had moderate, and 6 had severe COVID-19. Thirty-nine percent of patients who were previously infected with COVID-19 were found to have elevated fasting, postprandial, or HbA1c levels. Of these, 3.1% were diagnosed as having type 2 diabetes mellitus and 9.9% had prediabetes. On excluding those with an isolated HbA1c elevation and comparing prediabetes and diabetes with normoglycemia, age, overweight and obese range body mass index (BMI), and the presence of comorbidities showed significant association ( P < 0.05). Age (odds ratio [OR] 1.06, 95% confidence interval [CI] 1.02–1.11), the presence of comorbidities (OR 4.84, 95% CI 1.49–15.5), and overweight and obese range BMI (OR 3.48, 95% CI 1.13–13.1) were associated with dysglycemia on multivariate logistic regression analysis. Conclusion: A high incidence of dysglycemia over 6 months post-COVID-19 infection, especially in those with higher BMI, comorbidities, and in those in the middle age group warrants serial long-term monitoring of glucose levels in view of the high background risk of diabetes in the Asian population.
Title: Predictors of New Onset Dysglycemia Post COVID-19
Description:
Background: Hyperglycemia postcoronavirus disease 2019 (COVID-19) infection is multifactorial and warrants serial monitoring of blood glucose.
Aims: The aim of the study was to assess the incidence of glucose intolerance and new-onset diabetes in patients who have recovered from COVID-19 and to correlate the risk factors for dysglycemia.
Materials and Methods: Participants who were admitted for COVID-19 infection at St John’s Hospital, Bangalore, India, at least 6 months previously were enrolled in the study using telephonic interviews.
Details regarding age, gender, weight, and history were obtained.
Laboratory parameters such as fasting blood sugar, postprandial blood sugar, and glycated hemoglobin (HbA1c) were obtained.
The comparison between the dysglycemia and normoglycemia groups was conducted using either independent samples t -test or Mann–Whitney U test and using the Chi-squared test or Fisher’s exact test, as appropriate.
Multivariate logistic regression was employed to determine the adjusted effect of multiple variables on dysglycemia.
Results: The overall mean age of the study group was 40 ± 13 years with 68 (52%) male patients.
Of the 131 patients, 93 had mild, 32 had moderate, and 6 had severe COVID-19.
Thirty-nine percent of patients who were previously infected with COVID-19 were found to have elevated fasting, postprandial, or HbA1c levels.
Of these, 3.
1% were diagnosed as having type 2 diabetes mellitus and 9.
9% had prediabetes.
On excluding those with an isolated HbA1c elevation and comparing prediabetes and diabetes with normoglycemia, age, overweight and obese range body mass index (BMI), and the presence of comorbidities showed significant association ( P < 0.
05).
Age (odds ratio [OR] 1.
06, 95% confidence interval [CI] 1.
02–1.
11), the presence of comorbidities (OR 4.
84, 95% CI 1.
49–15.
5), and overweight and obese range BMI (OR 3.
48, 95% CI 1.
13–13.
1) were associated with dysglycemia on multivariate logistic regression analysis.
Conclusion: A high incidence of dysglycemia over 6 months post-COVID-19 infection, especially in those with higher BMI, comorbidities, and in those in the middle age group warrants serial long-term monitoring of glucose levels in view of the high background risk of diabetes in the Asian population.

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