Fasting Blood Glucose and COVID-19 Severity: Nonlinearity Matters.
Diabetes Care
; 43(12): 3113-3116, 2020 12.
Article
in English
| MEDLINE | ID: covidwho-868844
ABSTRACT
OBJECTIVE:
Fasting blood glucose (FBG) could be an independent predictor for coronavirus disease 2019 (COVID-19) morbidity and mortality. However, when included as a predictor in a model, it is conventionally modeled linearly, dichotomously, or categorically. We comprehensively examined different ways of modeling FBG to assess the risk of being admitted to the intensive care unit (ICU). RESEARCH DESIGN ANDMETHODS:
Utilizing COVID-19 data from Kuwait, we fitted conventional approaches to modeling FBG as well as a nonlinear estimation using penalized splines.RESULTS:
For 417 patients, the conventional linear, dichotomous, and categorical approaches to modeling FBG missed key trends in the exposure-response relationship. A nonlinear estimation showed a steep slope until about 10 mmol/L before flattening.CONCLUSIONS:
Our results argue for strict glucose management on admission. Even a small incremental increase within the normal range of FBG was associated with a substantial increase in risk of ICU admission for COVID-19 patients.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Severity of Illness Index
/
Blood Glucose
/
Diabetes Mellitus, Type 2
/
SARS-CoV-2
/
COVID-19
Type of study:
Prognostic study
Topics:
Long Covid
Limits:
Female
/
Humans
/
Male
/
Middle aged
Country/Region as subject:
Asia
Language:
English
Journal:
Diabetes Care
Year:
2020
Document Type:
Article
Affiliation country:
Dc20-1941
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