Fasting Blood Glucose and COVID-19 Severity: Nonlinearity Matters

Abstract

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 AND METHODS 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. A wealth of immunological evidence points out that hyperglycemic status (regardless of diabetes) makes individuals more susceptible to infection as well as higher in-hospital complications (1-5). However, quantitative reviews of published epidemiological studies of morbidity and mortality usually follow a standard approach of modeling blood glucose either linearly (per unit increase), dichotomously (using a preidentified cutoff, e.g., 7 mmol/L), or categorically (creating more than two groups based on preidentified cutoffs) (6). These conventional modeling approaches may not fully describe the nature of the exposure-response relationship. For example, these models assume a completely different response between having a fasting blood glucose (FBG) level of 6.9 and 7 mmol/L or assume that an increase from 5 to 10 mmol/L has the same risk as an increase from 30 to 35 mmol/L. We aimed to investigate possible nonlinearities in the relationship between FBG and the risk of being admitted to the intensive care unit (ICU) among coronavirus disease 2019 (COVID-19) patients using data from Kuwait.

High admission blood glucose independently predicts poor prognosis in COVID-19 patients: A systematic review and dose-response meta-analysis

“…However, in contrast with Zhu et al [34], we did not observe a J-shaped association between admission FBG and COVID-19 severity, which may be explained by the fact that all but one study [34] reported only three categories. Despite this, our findings were in accordance with a study by Alahmad et al [44] which stated that the association between admission FBG and ICU admission was logarithmic, thus further corroborating our premises.…”

Impact of Diabetes in Patients Diagnosed With COVID-19

“…Maddaloni et al have shown that patients with cardiometabolic multimorbidity, and not diabetes or CVD alone, experience worse COVID-19 outcomes (61). Nevertheless, plasma glucose levels and diabetes are independent predictors of mortality and morbidity in patients with SARS (24,62). Mechanisms that likely increase the vulnerability for COVID-19 in DM patients comprise increased binding affinity and efficient virus entry, reduced viral clearance, weakened T-cell role, increased susceptibility to cytokine storm disorder, and the existence of CVD.…”

Clinical characteristics of coronavirus disease 2019 (COVID-19) patients in Kuwait

“…In contrast, patients with severe cases develop ARDS and severe cardiac and renal complications, which can potentially lead to death [6,7]. Additionally, a poorer prognosis has been associated with older age, being male, and having pre-existing chronic conditions, such as hypertension, cardiovascular disease, and diabetes [8,9]. At the same time, pediatric cases have shown a milder clinical course [10].…”