Phase angle and rectus femoris cross-sectional area as predictors of severe malnutrition and their relationship with complications in outpatients with post-critical SARS-CoV2 disease

The diagnosis of malnutrition in post-critical COVID-19 patients is challenging as a result of the high prevalence of obesity, as well as the variability and previously reported inconsistencies across currently available assessment methods. Bioelectrical impedance vector analysis (BIVA) with phase angle (PhA) and nutritional ultrasound (NU®) are emerging techniques that have been proven successful in assessing body composition with high precision in previous studies. Our study aims to determine the performance and usefulness of PhA and rectus femoris cross-sectional area (RF-CSA) measurements in assessing body composition as part of the full routine morphofunctional assessment used in the clinical setting, as well as their capacity to predict severe malnutrition and to assess complications and aggressive therapy requirements during recent intensive care unit (ICU) admission, in a cohort of post-critically ill COVID-19 outpatients.This prospective observational study included 75 post-critical outpatients who recovered from severe COVID-19 pneumonia after requiring ICU admission. Correlations between all the morphofunctional parameters, complications, and aggressive therapy requirements during admission were analyzed. Multivariate logistic regression analysis and ROC curves were provided to determine the performance of NU® and PhA to predict severe malnutrition. Differences in complications and aggressive therapy requirements using the cutoff points obtained were analyzed.In total, 54.7% of patients were classified by Subjective Global Assessment (SGA) as SGA-B and 45.3% as SGA-C, while 78.7% met the Global Leadership Initiative of Malnutrition (GLIM) criteria. PhA correlates positively with body cell mass/height (BCM/h) (r = 0.74), skeletal muscle index (SMI) (r = 0.29), RF-CSA (r = 0.22), RF-Y axis (r = 0.42), and handgrip strength (HGS) assessed using dynamometry (r = 0.42) and the Barthel scale (r = 0.29) and negatively with ICU stay (r = -0.48), total hospital stay (r = -0.57), need for invasive mechanical ventilation (IMV) (r = -0.39), days of IMV (r = -0.41), need for tracheostomy (r = -0.51), and number of prone maneuvers (r = -0.20). RF-CSA correlates positively with BCM/h (r = 0.41), SMI (r = 0.58), RF-Y axis (r = 0.69), and HGS assessed using dynamometry (r = 0.50) and the Barthel scale (r = 0.15) and negatively with total hospital stay (r = -0.22) and need for IMV (r = -0.28). Cutoff points of PhA < 5.4° and standardized phase angle (SPhA) < -0.79 showed good capacity to predict severe malnutrition according to SGA and revealed differences in ICU stay, total hospital stay, number of prone maneuvers, need for IMV, and need for rehabilitation, with statistical significance (p < 0.05). An RF-CSA/h < 2.52 cm2/m (for men) and <2.21 cm2/m (for women) also showed good performance in predicting severe malnutrition and revealed differences with statistical significance (p < 0.05) in ICU stay and total hospital stay.More than 75% of the post-critical COVID-19 survivors had malnutrition, and approximately half were obese. PhA, SPhA, RF-CSA, and RF-CSA/h, when applied to the assessment of body composition in post-critical COVID-19 patients, showed moderate-to-high correlation with other morphofunctional parameters and good performance to predict severe malnutrition and to assess complications and aggressive therapy requirements during ICU admission. Besides being readily available methods, BIVA and NU® can help improve the morphofunctional assessment of malnutrition in post-critical COVID-19 survivors; however, more studies are needed to assess the performance of these methods in other populations.