Substrate utilization and energy expenditure pattern in sepsis by indirect calorimetry
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RESEARCH LETTER
Open Access
Substrate utilization and energy expenditure pattern in sepsis by indirect calorimetry Andrew Li1,2*
and Amartya Mukhopadhyay1,2,3
Keywords: Indirect calorimetry, Respiratory quotient, Sepsis, Metabolism, Energy expenditure Temporal metabolic profiles in sepsis are altered by the hormonal changes related to reduced food intake before admission and fasting after mechanical ventilation (MV), followed by refeeding [1]. Animal models suggest that preterminal rats were hypometabolic, compared to surviving animals [2]. This was further corroborated among septic patients, where higher metabolic rates and lower respiratory quotients (RQ) were observed [3]. However, longitudinal data using indirect calorimetry (IC) remain sparse. We aimed to determine the temporal trends of energy expenditure (EE) and RQ among septic patients receiving MV. All MV septic adults in the intensive care unit of a tertiary hospital were screened between September 2018 and December 2019 with ethics approval (DSRB 2017/01001). Patients were excluded if they received MV < 3 days, dialysis, fraction of inspired oxygen > 0.6, and chest drain. Patients demographics, anthropometric indices, outcomes, energy (target 25 kcal/kg/day) and protein (target 1.5 g/kg/day) delivery, propofol dose, and glucose infusions were collected. We initiated enteral feeding within 24 h of MV commencement. IC data collected (RQ, oxygen consumption, carbon dioxide production, and total EE) using Carescape B650 (GE Healthcare, USA), standardized for temperature, barometric pressure, and * Correspondence: [email protected] 1 Yong Loo Lin School of Medicine, National University of Singapore, Singapore 2 Division of Respiratory and Critical Care Medicine, Department of Medicine, National University Hospital, Singapore Full list of author information is available at the end of the article
humidity, were obtained post-intubation (baseline), within 2 h of feeding initiation and thereafter, daily up to 5 days or till extubation, whichever was earlier. A steady state of 30 min was mandated to ensure IC data validity. Categorical and continuous variables were reported as proportion and mean (SD) or median (IQR), respectively. Comparisons of medians were performed using Mann–Whitney U test. All statistical tests were twotailed. P < 0.05 was considered significant. To determine metabolism status, we followed the methods by Giovannini and Fried [2, 3]. Hyper- and hypometabolism were determined by positive and negative EE when compared to the resting state by Harris-Benedict equation. To understand substrate utilization, we followed the RQ trends. A balanced diet’s RQ is approximately 0.8. We divided the cohort into RQ ≤ 0.8 (lipid as predominant substrate) and > 0.8 (carbohydrate as predominant substrate). STATA 14 (Stata Corp, College Station, TX, USA) was used. Table 1 displays the baseline characteristics between survivors (n = 20) and non-survivors (n = 14). Median age and BMI were 63.5 (24–73) years and 22.5 (20.4–22.7) kg/m2, respectively
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