Comparison of energy intake in critical illness survivors, general medical patients, and healthy volunteers: A descriptive cohort study.

BACKGROUND: Intensive care unit (ICU) survivors have reduced oral intake; it is unknown whether intake and associated barriers are unique to this group. OBJECTIVE: To quantify energy intake and potential barriers in ICU survivors compared with general medical (GM) patients and healthy volunteers. DESIGN: A descriptive cohort study in ICU survivors, GM patients, and healthy volunteers. Following an overnight fast, participants consumed a 200 ml test-meal (213 kcal) and 180 min later an ad libitum meal to measure energy intake (primary outcome). Secondary outcomes; taste recognition, nutrition-impacting symptoms, malnutrition, and quality of life (QoL). Data are mean ± SD, median (interquartile range [IQR]) or number [percentage]). RESULTS: Twelve ICU survivors (57 ± 17 years, BMI: 30 ± 6), eight GM patients (69 ± 19 years, BMI: 30 ± 6), and 25 healthy volunteers (58 ± 27 years, BMI: 25 ± 4) were included. Recruitment ceased early because of slow recruitment and SARS-CoV-2. Energy intake was lower in both patient groups than in health (ICU: 289 [288, 809], GM: 426 [336, 592], health: 815 [654, 1165] kcal). Loss of appetite was most common (ICU: 78%, GM: 67%). For ICU survivors, GM patients and healthy volunteers, respectively, severe malnutrition prevalence; 40%, 14%, and 0%; taste identification; 8.5 [7.0, 11.0], 8.5 [7.0, 9.5], and 8.0 [6.0, 11.0]; and QoL; 60 [40-65], 50 [31-55], and 90 [81-95] out of 100. CONCLUSIONS: Energy intake at a buffet meal is lower in hospital patients than in healthy volunteers but similar between ICU survivors and GM patients. Appetite loss potentially contributes to reduced energy intake.

Observed differences in nutrition management at two time points spanning a decade in critically ill trauma patients with and without head injury.

BACKGROUND: Nutritional needs of trauma patients admitted to the intensive care unit may differ from general critically ill patients, but most current evidence is based on large clinical trials recruiting mixed populations. OBJECTIVE: The aim of the study was to investigate nutrition practices at two time points that span a decade in trauma patients with and without head injury. METHODS: This observational study recruited adult trauma patients receiving mechanical ventilation and artificial nutrition from a single-centre intensive care unit between February 2005 to December 2006 (cohort 1), and December 2018 to September 2020 (cohort 2). Patients were categorised into head injury and non-head injury subgroups. Data regarding energy and protein prescription and delivery were collected. Data are presented as median [interquartile range]. Wilcoxon rank-sum test assessed the differences between cohorts and subgroups, with a P value ≤ 0.05. The protocol was registered with the Australian and New Zealand Clinical Trials Registry (Trial ID: ACTRN12618001816246). RESULTS: Cohort 1 included 109 patients, and 112 patients were included in cohort 2 (age: 46 ± 19 vs 50 ± 19 y; 80 vs 79% M). Overall, nutrition practice did not differ between head-injured and non-head-injured subgroups (all P > 0.05). Energy prescription and delivery decreased from time point one to time point two, regardless of subgroup (Prescription: 9824 [8820-10 581] vs 8318 [7694-9071] kJ; Delivery: 6138 [5130-7188] vs 4715 [3059-5996] kJ; all P < 0.05). Protein prescription did not change from time point one to time point two. Although protein delivery remained constant from time point one to time point two in the head injury group, protein delivery reduced in the non-head injury subgroup (70 [56-82] vs 45 [26-64] g/d, P < 0.05). CONCLUSION: In this single-centre study, energy prescription and delivery in critically ill trauma patients reduced from time point one to time point two. Protein prescription did not change, but protein delivery reduced from time point one to time point two in non-head injury patients. Reasons for these differing trajectories require exploration. STUDY REGISTRATION: Trial registered at www.anzctr.org.au. TRIAL ID: ACTRN12618001816246.

Assessment of physiological barriers to nutrition following critical illness.

BACKGROUND & AIMS: Nutrition may be important for recovery from critical illness. Gastrointestinal dysfunction is a key barrier to nutrition delivery in the Intensive Care Unit (ICU) and metabolic rate is elevated exacerbating nutritional deficits. Whether these factors persist following ICU discharge is unknown. We assessed whether delayed gastric emptying (GE) and impaired glucose absorption persist post-ICU discharge. METHODS: A prospective observational study was conducted in mechanically ventilated adults at 3 time-points: in ICU (V1); on the post-ICU ward (V2); and 3-months after ICU discharge (V3); and compared to age-matched healthy volunteers. On each visit, all participants received a test-meal containing 100 ml of 1 kcal/ml liquid nutrient, labelled with 0.1 g 13C-octanoic acid and 3 g 3-O-Methyl-glucose (3-OMG), and breath and blood samples were collected over 240min to quantify GE (gastric emptying coefficient (GEC)), and glucose absorption (3-OMG concentration; area under the curve (AUC)). Data are mean ± standard error of the mean (SEM) and differences shown with 95% confidence intervals (95%CI). RESULTS: Twenty-six critically ill patients completed V1 (M:F 20:6; 62.0 ± 2.9 y; BMI 29.8 ± 1.2 kg/m2; APACHE II 19.7 ± 1.9), 15 completed V2 and eight completed V3; and were compared to 10 healthy volunteers (M:F 6:4; 60.5 ± 7.5 y; BMI 26.0 ± 1.0 kg/m2). GE was significantly slower on V1 compared to health (GEC difference: -0.96 (95%CI -1.61, -0.31); and compared to V2 (-0.73 (-1.16, -0.31) and V3 (-1.03 (-1.47, -0.59). GE at V2 and V3 were not different to that in health (V2: -0.23 (-0.61, 0.14); V3: 0.10 (-0.27, 0.46)). GEC: V1: 2.64 ± 0.19; V2: 3.37 ± 0.12; V3: 3.67 ± 0.10; health: 3.60 ± 0.13. Glucose absorption (3-OMG AUC0-240) was impaired on V1 compared to V2 (-37.9 (-64.2, -11.6)), and faster on V3 than in health (21.8 (0.14, 43.4) but absorption at V2 and V3 did not differ from health. Intestinal glucose absorption: V1: 63.8 ± 10.4; V2: 101.7 ± 7.0; V3: 111.9 ± 9.7; health: 90.7 ± 3.8. CONCLUSION: This study suggests that delayed GE and impaired intestinal glucose absorption recovers rapidly post-ICU. This requires further confirmation in a larger population. The REINSTATE trial was prospectively registered at www.anzctr.org.au. TRIAL ID: ACTRN12618000370202.

Nutrition-related outcomes and dietary intake in non-mechanically ventilated critically ill adult patients: A pilot observational descriptive study.

BACKGROUND: Critically ill patients who do not receive invasive mechanical ventilation (IMV) are a growing population, experiencing complex interventions that may impair dietary intake and nutrition-related outcomes. OBJECTIVES: The objectives of this study were to quantify intake and nutrition-related outcomes of non-IMV critically ill patients and to establish feasibility of methods to measure nutrition-related outcomes in this population. METHODS: Non-IMV adult patients expected to remain in the intensive care unit (ICU) for ≥24 h were eligible. Nutrition-related outcomes were assessed at baseline by subjective global assessment (SGA); on alternate study days by mid-upper arm circumference (MUAC), calf circumference (CC), and ultrasound of quadriceps muscle layer thickness (QMLT); and daily by body weight and bioelectrical impedance analysis (BIA). Data were censored at day 5 or ICU discharge. Dietary intake from all sources, including oral intake via investigator-led weighed food records, was quantified on days 1-3. Feasibility was defined as data completion rate ≥70%. Data are expressed as mean (standard deviation) or median [interquartile range (IQR)]. RESULTS: Twenty-three patients consented (50% male; 53 [42-64] y; ICU stay: 2.8 [1.9-4.0] d). Nutrition-related outcomes at baseline and ICU discharge were as follows: MUAC: 33.2 (8.6) cm (n = 18) and 29.3 (5.4) cm (n = 6); CC: 39.5 (7.4) cm (n = 16) and 37.5 (6.2) cm (n = 6); body weight: 95.3 (34.8) kg (n = 19) and 95.6 (41.0) kg (n = 10); and QMLT: 2.6 (0.8) cm (n = 15) and 2.5 (0.3) cm (n = 5), respectively. Oral intake provided 3155 [1942-5580] kJ and 32 [20-53] g protein, with poor appetite identified as a major barrier. MUAC, CC, QMLT, and SGA were feasible, while BIA and body weight were not. CONCLUSIONS: Oral intake in critically ill patients not requiring IMV is below estimated requirements, largely because of poor appetite. The small sample and short study duration were not sufficient to quantify changes in nutrition-related outcomes. MUAC, CC, QMLT, and SGA are feasible methods to assess nutrition-related outcomes at a single time point in this population.