Applying the Global Leadership Initiative on Malnutrition criteria in patients admitted with SARS-CoV-2 infection using computed tomography imaging.

Abstract

Patients with low muscle mass and acute SARS-CoV-2 infection meet the Global Leadership Initiative on Malnutrition (GLIM) etiologic and phenotypic criteria to diagnose malnutrition, respectively. However, available cut-points to classify individuals with low muscle mass are not straightforward. Using computed tomography (CT) to determine low muscularity, we assessed the prevalence of malnutrition using the GLIM framework and associations with clinical outcomes. A retrospective cohort was conducted gathering patient data from various clinical resources. Patients admitted to the COVID-19 unit (March 2020 to June 2020) with appropriate/evaluable CT studies (chest or abdomen/pelvis) within the first 5 days of admission were considered eligible. Sex- and vertebral-specific skeletal muscle indices (SMI; cm2 /m2 ) from healthy controls were used to determine low muscle mass. Injury-adjusted SMI were derived, extrapolated from cancer cut-points and explored. Descriptive statistics and mediation analyses were completed. Patients (n = 141) were 58.2 years of age and racially diverse. Obesity (46%), diabetes (40%), and cardiovascular disease (68%) were prevalent. Using healthy controls and injury-adjusted SMI, malnutrition prevalence was 26% (n = 36/141) and 50% (n = 71/141), respectively. Mediation analyses demonstrated a significant reduction in the effect of malnutrition on outcomes in the presence of Acute Physiology and Chronic Health Evaluation II, supporting the mediating effects of severity of illness intensive care unit (ICU) admission, ICU length of stay, mechanical ventilation, complex respiratory support, discharge status (all P values = 0.03), and 28-day mortality (P = 0.04). Future studies involving the GLIM criteria should consider these collective findings in their design, analyses, and implementation.