Elevated glycohemoglobin is linked to critical illness in CoVID-19: a retrospective analysis.

COVID-19 diabetes hemoglobin A1c intensive care unit mechanical ventilation

Journal

Therapeutic advances in infectious disease
ISSN: 2049-9361
Titre abrégé: Ther Adv Infect Dis
Pays: England
ID NLM: 101606715

Informations de publication

Date de publication:
Historique:
received: 27 02 2021
accepted: 04 06 2021
entrez: 12 7 2021
pubmed: 13 7 2021
medline: 13 7 2021
Statut: epublish

Résumé

Several studies have explored hospitalization risk factors with the novel coronavirus disease 2019 (COVID-19) infection. Our goal was to identify clinical characteristics outside of laboratory or radiologic data associated with intubation or death within 7 days of admission. The first 436 patients admitted to the University of Colorado Hospital (Denver metropolitan area) with confirmed COVID-19 were included. Demographics, comorbidities, and select medications were collected by chart abstraction. Missing height for calculating body mass index (BMI) was imputed using the median height for patients' sex and race/ethnicity. Adjusted odds ratios (aOR) were estimated using multivariable logistic regression and a minimax concave penalty (MCP) regularized logistic regression explored prediction. Participants had a mean [standard deviation (SD)] age 55 (17), BMI 30.9 (8.2), 55% were male and 80% were ethnic/racial minorities. Increasing age [aOR: 1.24 (1.07, 1.45) per 10 years], higher BMI (aOR 1.03 (1.00, 1.06), and poorly controlled diabetes [hemoglobin A1C (HbA1c) ⩾ 8] (aOR 2.26 (1.24, 4.12) were significantly ( In a hospitalized patient cohort with COVID-19, worsening control of diabetes as evidenced by higher HbA1c was associated with increased risk of intubation or death within 7 days of admission. These results complement and help clarify previous associations found between diabetes and acute disease in COVID-19. Importantly, our analysis is missing some known predictors of severity in COVID-19. Our predictive model had limited success, suggesting unmeasured factors contribute to disease severity differences.

Sections du résumé

BACKGROUND BACKGROUND
Several studies have explored hospitalization risk factors with the novel coronavirus disease 2019 (COVID-19) infection. Our goal was to identify clinical characteristics outside of laboratory or radiologic data associated with intubation or death within 7 days of admission.
METHODS METHODS
The first 436 patients admitted to the University of Colorado Hospital (Denver metropolitan area) with confirmed COVID-19 were included. Demographics, comorbidities, and select medications were collected by chart abstraction. Missing height for calculating body mass index (BMI) was imputed using the median height for patients' sex and race/ethnicity. Adjusted odds ratios (aOR) were estimated using multivariable logistic regression and a minimax concave penalty (MCP) regularized logistic regression explored prediction.
RESULTS RESULTS
Participants had a mean [standard deviation (SD)] age 55 (17), BMI 30.9 (8.2), 55% were male and 80% were ethnic/racial minorities. Increasing age [aOR: 1.24 (1.07, 1.45) per 10 years], higher BMI (aOR 1.03 (1.00, 1.06), and poorly controlled diabetes [hemoglobin A1C (HbA1c) ⩾ 8] (aOR 2.26 (1.24, 4.12) were significantly (
CONCLUSION CONCLUSIONS
In a hospitalized patient cohort with COVID-19, worsening control of diabetes as evidenced by higher HbA1c was associated with increased risk of intubation or death within 7 days of admission. These results complement and help clarify previous associations found between diabetes and acute disease in COVID-19. Importantly, our analysis is missing some known predictors of severity in COVID-19. Our predictive model had limited success, suggesting unmeasured factors contribute to disease severity differences.

Identifiants

pubmed: 34249357
doi: 10.1177/20499361211027390
pii: 10.1177_20499361211027390
pmc: PMC8239973
doi:

Types de publication

Journal Article

Langues

eng

Pagination

20499361211027390

Subventions

Organisme : NIA NIH HHS
ID : R01 AG054366
Pays : United States

Informations de copyright

© The Author(s), 2021.

Déclaration de conflit d'intérêts

Conflict of interest statement: The authors declare that there is no conflict of interest.

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Auteurs

Samuel Windham (S)

Division of Infectious Disease, Department of Medicine, School of Medicine, University of Colorado, Aurora, CO, USA.

Melissa P Wilson (MP)

Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO, USA.

Connor Fling (C)

University of Colorado School of Medicine, Aurora, CO, USA.

David Sheneman (D)

University of Colorado School of Medicine, Aurora, CO, USA.

Taylor Wand (T)

University of Colorado School of Medicine, Aurora, CO, USA.

Lyndsey Babcock (L)

University of Colorado School of Medicine, Aurora, CO, USA.

Samantha MaWhinney (S)

Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO, USA.

Kristine M Erlandson (KM)

Division of Infectious Disease, Department of Medicine, School of Medicine, University of Colorado, 12700 E. 19th Avenue, Mail Stop B168, Aurora, CO 80045, USA.

Classifications MeSH