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.

Nutrition delivery across hospitalisation in critically ill patients with COVID-19: An observational study of the Australian experience.

BACKGROUND: Data on nutrition delivery over the whole hospital admission in critically ill patients with COVID-19 are scarce, particularly in the Australian setting. OBJECTIVES: The objective of this study was to describe nutrition delivery in critically ill patients admitted to Australian intensive care units (ICUs) with coronavirus disease 2019 (COVID-19), with a focus on post-ICU nutrition practices. METHODS: A multicentre observational study conducted at nine sites included adult patients with a positive COVID-19 diagnosis admitted to the ICU for >24 h and discharged to an acute ward over a 12-month recruitment period from 1 March 2020. Data were extracted on baseline characteristics and clinical outcomes. Nutrition practice data from the ICU and weekly in the post-ICU ward (up to week four) included route of feeding, presence of nutrition-impacting symptoms, and nutrition support received. RESULTS: A total of 103 patients were included (71% male, age: 58 ± 14 years, body mass index: 30±7 kg/m2), of whom 41.7% (n = 43) received mechanical ventilation within 14 days of ICU admission. While oral nutrition was received by more patients at any time point in the ICU (n = 93, 91.2% of patients) than enteral nutrition (EN) (n = 43, 42.2%) or parenteral nutrition (PN) (n = 2, 2.0%), EN was delivered for a greater duration of time (69.6% feeding days) than oral and PN (29.7% and 0.7%, respectively). More patients received oral intake than the other modes in the post-ICU ward (n = 95, 95.0%), and 40.0% (n = 38/95) of patients were receiving oral nutrition supplements. In the week after ICU discharge, 51.0% of patients (n = 51) had at least one nutrition-impacting symptom, most commonly a reduced appetite (n = 25; 24.5%) or dysphagia (n = 16; 15.7%). CONCLUSION: Critically ill patients during the COVID-19 pandemic in Australia were more likely to receive oral nutrition than artificial nutrition support at any time point both in the ICU and in the post-ICU ward, whereas EN was provided for a greater duration when it was prescribed. Nutrition-impacting symptoms were common.

Study protocol for TARGET protein: The effect of augmented administration of enteral protein to critically ill adults on clinical outcomes: A cluster randomised, cross-sectional, double cross-over, clinical trial.

Background: It is unknown whether increasing dietary protein to 1.2-2.0 g/kg/day as recommended in international guidelines compared to current practice improves outcomes in intensive care unit (ICU) patients. The TARGET Protein trial will evaluate this. Objective: To describe the study protocol for the TARGET Protein trial. Design setting and participants: TARGET Protein is a cluster randomised, cross-sectional, double cross-over, pragmatic clinical trial undertaken in eight ICUs in Australia and New Zealand. Each ICU will be randomised to use one of two trial enteral formulae for three months before crossing over to the other formula, which is then repeated, with enrolment continuing at each ICU for 12 months. All patients aged ≥16 years in their index ICU admission commencing enteral nutrition will be eligible for inclusion. Eligible patients will receive the trial enteral formula to which their ICU is allocated. The two trial enteral formulae are isocaloric with a difference in protein dose: intervention 100g/1000 ml and comparator 63g/1000 ml. Staggered recruitment commenced in May 2022. Main outcomes measures: The primary outcome is days free of the index hospital and alive at day 90. Secondary outcomes include days free of the index hospital at day 90 in survivors, alive at day 90, duration of invasive ventilation, ICU and hospital length of stay, incidence of tracheostomy insertion, renal replacement therapy, and discharge destination. Conclusion: TARGET Protein aims to determine whether augmented enteral protein delivery reduces days free of the index hospital and alive at day 90. Trial registration: Australian New Zealand Clinical Trials Registry (ACTRN12621001484831).

Muscle size, strength, and physical function in response to augmented calorie delivery: A TARGET sub-study.

PURPOSE: Augmented calories may attenuate muscle loss experienced in critical illness. This exploratory sub-study assessed the effect of augmented calorie delivery on muscle mass, strength, and function. MATERIALS AND METHODS: Patients in The Augmented versus Routine approach to Giving Energy Trial (TARGET) randomised to 1.5 kcal/ml or 1.0 kcal/ml enteral formulae at a single-centre were included. Ultrasound-derived muscle layer thickness (MLT) at quadriceps, forearm and mid-upper arm, and handgrip strength, were measured weekly from baseline to hospital discharge, and 3- and 6-months. Physical function was assessed at 3- and 6-months using the 'get up and go' and 6-min walk tests. Data are mean ± SD. RESULTS: Eighty patients were recruited (1.5 kcal: n = 38, 58 ± 14y, 60%M, APACHE II 20 ± 7; 1.0 kcal: n = 42, 54 ± 18y, 66%M, APACHE II 22 ± 10). The 1.5 kcal/ml group received more calories with no difference in quadriceps MLT at any timepoint including ICU discharge (primary outcome) (2.90 ± 1.27 vs 2.39 ± 1.06 cm; P = 0.141). Relationships were similar for all MLT measures, handgrip strength, and 6-min walk test. Patients in the 1.5 kcal/ml group had improved 'get up and go' test at 3-months (6.66 ± 1.33 vs. 9.11 ± 2.94 s; P = 0.014). CONCLUSION: Augmented calorie delivery may not attenuate muscle loss or recovery of strength or function 6-months post-ICU, but this requires exploration in a larger trial.

Muscle Protein Synthesis after Protein Administration in Critical Illness.

Rationale: Dietary protein may attenuate the muscle atrophy experienced by patients in the ICU, yet protein handling is poorly understood. Objectives: To quantify protein digestion and amino acid absorption and fasting and postprandial myofibrillar protein synthesis during critical illness. Methods: Fifteen mechanically ventilated adults (12 male; aged 50 ± 17 yr; body mass index, 27 ± 5 kg⋅m-2) and 10 healthy control subjects (6 male; 54 ± 23 yr; body mass index, 27 ± 4 kg⋅m-2) received a primed intravenous L-[ring-2H5]-phenylalanine, L-[3,5-2H2]-tyrosine, and L-[1-13C]-leucine infusion over 9.5 hours and a duodenal bolus of intrinsically labeled (L-[1-13C]-phenylalanine and L-[1-13C]-leucine) intact milk protein (20 g protein) over 60 minutes. Arterial blood and muscle samples were taken at baseline (fasting) and for 6 hours following duodenal protein administration. Data are mean ± SD, analyzed with two-way repeated measures ANOVA and independent samples t test. Measurements and Main Results: Fasting myofibrillar protein synthesis rates did not differ between ICU patients and healthy control subjects (0.023 ± 0.013% h-1 vs. 0.034 ± 0.016% h-1; P = 0.077). After protein administration, plasma amino acid availability did not differ between groups (ICU patients, 54.2 ± 9.1%, vs. healthy control subjects, 61.8 ± 13.1%; P = 0.12), and myofibrillar protein synthesis rates increased in both groups (0.028 ± 0.010% h-1 vs. 0.043 ± 0.018% h-1; main time effect P = 0.046; P-interaction = 0.584) with lower rates in ICU patients than in healthy control subjects (main group effect P = 0.001). Incorporation of protein-derived phenylalanine into myofibrillar protein was ∼60% lower in ICU patients (0.007 ± 0.007 mol percent excess vs. 0.017 ± 0.009 mol percent excess; P = 0.007). Conclusions: The capacity for critically ill patients to use ingested protein for muscle protein synthesis is markedly blunted despite relatively normal protein digestion and amino acid absorption.

The use of smartphone-derived location data to evaluate participation following critical illness: A pilot observational cohort study.

BACKGROUND: Disability is common following critical illness, impacting the quality of life of survivors, and is difficult to measure. 'Participation' can be quantified as involvement in life outside of their home requiring movement from their home to other locations. Participation restriction is a key element of disability, and following critical illness, participation may be diminished. It may be possible to quantify this change using pre-existing smartphone data. OBJECTIVES: The feasibility of extracting location data from smartphones of survivors of intensive care unit (ICU) admission and assessing participation, using location-based outcomes, during recovery from critical illness was evaluated. METHODS: Fifty consecutively admitted, consenting adult survivors of non-elective admission to ICU of greater than 48-h duration were recruited to a prospective observational cohort study where they were followed up at 3 and 6 months following discharge. The feasibility of extracting location data from survivors' smartphones and creating location-derived outcomes assessing participation was investigated over three 28-d study periods: pre-ICU admission and at 3 and 6 months following discharge. The following were calculated: time spent at home; the number of destinations visited; linear distance travelled; and two 'activity spaces', a minimum convex polygon and standard deviation ellipse. RESULTS: Results are median [interquartile range] or n (%). The number of successful extractions was 9/50 (18%), 12/39 (31%), and 13/33 (39%); the percentage of time spent at home was 61 [56-68]%, 77 [66-87]%, and 67 [58-77]% (P = 0.16); the number of destinations visited was 34 [18-64], 38 [22-63], and 65 [46-88] (P = 0.02); linear distance travelled was 367 [56-788], 251 [114-323], and 747 [326-933] km over 28 d (P = 0.02), pre-ICU admission and at 3 and 6 months following ICU discharge, respectively. Activity spaces were successfully created. CONCLUSION: Limited smartphone ownership, missing data, and time-consuming data extraction limit current implementation of mass extraction of location data from patients' smartphones to aid prognostication or measure outcomes. The number of journeys taken and the linear distance travelled increased between 3 and 6 months, suggesting participation may improve over time.

Systematic review of clinicians' knowledge, attitudes, and beliefs about nutrition in intensive care.

Nutrition is a key component of care for critically ill patients; yet nutrition delivery is below international recommendations. In order to improve nutrition delivery to critically ill patients, an understanding of the barriers that prevent guideline adherence is required. It is known that clinicians' knowledge, attitudes, and beliefs of the role of nutrition may act as a potential barrier to nutrition delivery, but whether this remains true in critical care is unknown. The aim of this systematic scoping review was to summarize the literature exploring the knowledge, attitudes, and beliefs of clinicians around nutrition support in critically ill patients. A search of four online databases (MEDLINE via Ovid, Emcare via Ovid, PsycINFO, and CINAHL via EBSCOhost) was conducted on August 14, 2020, to identify literature that reported on clinicians' knowledge, attitudes, and beliefs of nutrition in adult intensive care patients. Data were extracted on study and participant characteristics, methodology, and key study outcomes related to nutrition. Eighteen articles met eligibility criteria and were included in the review. Key findings included the following: nutrition was seen as a priority that ranked below life-saving interventions; differences in perceived clinician responsibilities exist; common barriers to nutrition delivery included inadequate resourcing, lack of nutrition protocols, and gastrointestinal intolerance; and identified facilitators included nutrition education and the presence of a supportive multidisciplinary team. The implementation of nutrition protocols, enhanced clinical nutrition education, and further clarification of roles and responsibilities pertaining to nutrition may assist in improving nutrition delivery in critical care.

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.

Nocturnal Hypoglycemia in Patients With Diabetes Discharged From ICUs: A Prospective Two-Center Cohort Study.

OBJECTIVES: There is very limited information about glycemic control after discharge from the ICU. The aims of this study were to evaluate the prevalence of hypoglycemia in ICU survivors with type-2 diabetes and determine whether hypoglycemia is associated with cardiac arrhythmias. DESIGN: Prospective, observational, two-center study. Participants underwent up to 5 days of simultaneous blinded continuous interstitial glucose monitoring and ambulatory 12-lead electrocardiogram monitoring immediately after ICU discharge during ward-based care. Frequency of arrhythmias, heart rate variability, and cardiac repolarization markers were compared between hypoglycemia (interstitial glucose ≤ 3.5 mmol/L) and euglycemia (5-10 mmol/L) matched for time of day. SETTING: Mixed medical-surgical ICUs in two geographically distinct university-affiliated hospitals. PATIENTS: Patients with type-2 diabetes who were discharged from ICU after greater than or equal to 24 hours with greater than or equal to one organ failure and were prescribed subcutaneous insulin were eligible. MEASUREMENTS AND MAIN RESULTS: Thirty-one participants (mean ± sd, age 65 ± 13 yr, glycated hemoglobin 64 ± 22 mmol/mol) were monitored for 101 ± 32 hours post-ICU (total 3,117 hr). Hypoglycemia occurred in 12 participants (39%; 95% CI, 22-56%) and was predominantly nocturnal (40/51 hr) and asymptomatic (25/29 episodes). Participants experiencing hypoglycemia had 2.4 ± 0.7 discrete episodes lasting 45 minutes (interquartile range, 25-140 min). Glucose nadir was less than or equal to 2.2 mmol/L in 34% of episodes. The longest episode of nocturnal hypoglycemia was 585 minutes with glucose nadir less than 2.2 mmol/L. Simultaneous electrocardiogram and continuous interstitial glucose monitoring recordings were obtained during 44 hours of hypoglycemia and 991 hours of euglycemia. Hypoglycemia was associated with greater risk of bradycardia but did not affect atrial or ventricular ectopics, heart rate variability, or cardiac repolarization. CONCLUSIONS: In ICU survivors with insulin-treated type-2 diabetes, hypoglycemia occurs frequently and is predominantly nocturnal, asymptomatic, and prolonged.

Effects of Standard vs Energy-Dense Formulae on Gastric Retention, Energy Delivery, and Glycemia in Critically Ill Patients.

BACKGROUND: Energy-dense formulae are often provided to critically ill patients with enteral feed intolerance with the aim of increasing energy delivery, yet the effect on gastric emptying is unknown. The rate of gastric emptying of a standard compared with an energy-dense formula was quantified in critically ill patients. METHODS: Mechanically ventilated adults were randomized to receive radiolabeled intragastric infusions of 200 mL standard (1 kcal/mL) or 100 mL energy-dense (2 kcal/mL) enteral formulae on consecutive days in this noninferiority, blinded, crossover trial. The primary outcome was scintigraphic measurement of gastric retention (percentage at 120 minutes). Other measures included area under the curve (AUC) for gastric retention and intestinal energy delivery (calculated from gastric retention of formulae over time), blood glucose (peak and AUC), and intestinal glucose absorption (using 3-O-methyl-D-gluco-pyranose [3-OMG] concentrations). Comparisons were undertaken using paired mixed-effects models. Data presented are mean ± SE. RESULTS: Eighteen patients were studied (male/female, 14:4; age, 55.2 ± 5.3 years). Gastric retention at 120 minutes was greater with the energy-dense formula (standard, 17.0 ± 5.9 vs energy-dense, 32.5 ± 7.1; difference, 12.7% [90% confidence interval, 0.8%-30.1%]). Energy delivery (AUC120 , 13,038 ± 1119 vs 9763 ± 1346 kcal/120 minutes; P = 0.057), glucose control (peak glucose, 10.1 ± 0.3 vs 9.7 ± 0.3 mmol/L, P = 0.362; and glucose AUC120 8.7 ± 0.3 vs 8.5 ± 0.3 mmol/L.120 minutes, P = 0.661), and absorption (3-OMG AUC120 , 38.5 ± 4.0 vs 35.7 ± 4.0 mmol/L.120 minutes; P = .508) were not improved with the energy-dense formula. CONCLUSION: In critical illness, administration of an energy-dense formula does not reduce gastric retention, increase energy delivery to the small intestine, or improve glucose absorption or glucose control; instead, there is a signal for delayed gastric emptying.

Protein delivery in mechanically ventilated adults in Australia and New Zealand: current practice.

Objective: To quantify current protein prescription and delivery in critically ill adults in Australia and New Zealand and compare it with international guidelines. Design: Prospective, multicentre, observational study. Setting: Five intensive care units (ICUs) across Australia and New Zealand. Participants: Mechanically ventilated adults who were anticipated to receive enteral nutrition for ≥ 24 hours. Main outcome measures: Baseline demographic and nutrition data in ICU, including assessment of requirements, prescription and delivery of enteral nutrition, parenteral nutrition and protein supplementation, were collected. The primary outcome was enteral nutrition protein delivery (g/kg ideal body weight [IBW] per day). Data are reported as mean ± standard deviation or n (%). Results: 120 patients were studied (sex, 60% male; mean age, 59 ± 16 years; mean admission APACHE II score, 20 ± 8). Enteral nutrition was delivered on 88%, parenteral nutrition on 6.8%, and protein supplements on 0.3% of 1156 study days. For the 73% (88/120) of patients who had a nutritional assessment, the mean estimated protein requirements were 99 ± 22 g/day (1.46 ± 0.55 g/kg IBW per day). The mean daily protein delivery was 54 ± 23 g (0.85 ± 0.35 g/kg IBW per day) from enteral nutrition and 56 ± 23 g (0.88 ± 0.35 g/kg IBW per day) from all sources (enteral nutrition, parenteral nutrition, protein supplements). Protein delivery was ≥ 1.2 g/kg IBW per day on 29% of the total study days per patient. Conclusions: Protein delivery as a part of current usual care to critically ill adults in Australia and New Zealand remains below that recommended in international guidelines.

Use of a High-Protein Enteral Nutrition Formula to Increase Protein Delivery to Critically Ill Patients: A Randomized, Blinded, Parallel-Group, Feasibility Trial.

BACKGROUND: International guidelines recommend critically ill adults receive more protein than most receive. We aimed to establish the feasibility of a trial to evaluate whether feeding protein to international recommendations would improve outcomes, in which 1 group received protein doses representative of international guideline recommendations (high protein) and the other received doses similar to usual practice. METHODS: We conducted a prospective, randomized, blinded, parallel-group, feasibility trial across 6 intensive care units. Critically ill, mechanically ventilated adults expected to receive enteral nutrition (EN) for ≥2 days were randomized to receive EN containing 63 or 100 g/L protein for ≤28 days. Data are mean (SD) or median (interquartile range). RESULTS: The recruitment rate was 0.35 (0.13) patients per day, with 120 patients randomized and data available for 116 (n = 58 per group). Protein delivery was greater in the high-protein group (1.52 [0.52] vs 0.99 [0.27] grams of protein per kilogram of ideal body weight per day; difference, 0.53 [95% CI, 0.38-0.69] g/kg/d protein), with no difference in energy delivery (difference, -26 [95% CI, -190 to 137] kcal/kg/d). There were no between-group differences in the duration of feeding (8.7 [7.3] vs 8.1 [6.3] days), and blinding of the intervention was confirmed. There were no differences in clinical outcomes, including 90-day mortality (14/55 [26%] vs 15/56 [27%]; risk difference, -1.3% [95% CI, -17.7% to 15.0%]). CONCLUSION: Conducting a multicenter blinded trial is feasible to compare protein delivery at international guideline-recommended levels with doses similar to usual care during critical illness.

Outcome Measures in Critical Care Nutrition Interventional Trials: A Systematic Review.

Historically, randomized controlled trials (RCTs) in critical care have used mortality as the primary outcome, yet most show no effect on this outcome. Therefore, there has been a shift in the literature to focus on alternative outcomes. This review aimed to describe primary outcomes selected in RCTs of nutrition interventions in critical illness. Systematic search of the literature identified RCTs of nutrition interventions in critically ill adults published between January 2007 and December 2018. Primary outcomes were documented and categorized as mortality, morbidity, health service/cost-effectiveness, or nutrition outcome. The direction of effect of the intervention on the primary outcome (positive, neutral, or negative) was extracted. Of 1163 citations identified and assessed for eligibility, 125 articles were included. However, 52 articles (42%) did not provide a sample-size calculation, leaving 73 articles (58%) for data extraction. The primary outcomes reported were morbidity (n = 24, 32.9%); health service/cost-effectiveness (n = 21, 28.8%); nutrition outcomes (n = 16, 21.9%); mortality (n = 11, 15.1%); and other (n = 1, 1.4%). No RCTs with mortality as the primary outcome reported a difference between intervention and control. Trials that included other primary outcomes frequently reported a difference (n = 27 of 62; 43.5%). Morbidity was the most frequently reported outcome category in RCTs that evaluated a nutrition intervention in critically ill adults, with mortality least frequent. Power calculations were only reported in 58% of included studies. Trials were more likely to show a significant result when an outcome other than mortality was the primary outcome.

Observed appetite and nutrient intake three months after ICU discharge.

BACKGROUND & AIMS: Oral intake is diminished immediately after ICU discharge, yet factors affecting nutritional intake after hospital discharge have not been evaluated. The aim of this study was to evaluate dietary intake and factors which may influence intake - appetite and gastric emptying - 3-months after ICU discharge. METHODS: Inception cohort study with ICU survivors compared to healthy subjects. Following an overnight fast, all participants consumed a standardized carbohydrate drink, containing 13C-octanoic acid, to measure gastric emptying. Dietary intake was assessed by recall of the preceding day and a standard weighed buffet meal 4-h post-drink. Appetite was assessed pre-drink (fasting) and pre- and post-buffet using visual analogue scales. RESULTS: Fifty-one ICU survivors (82% male; 70 ± 9 y; BMI 28 ± 6 kg/m2) and 25 healthy subjects (60% male; 67 ± 12 y; BMI 27 ± 4 kg/m2) were evaluated. From the 24-h recall ICU survivors consumed less calories (ICU 1876 (708) vs. healthy subjects 2291 (834) kcal; p = 0.025) with no difference in macronutrient intake, however reported a lower preference for fat (p < 0.001). Calorie and macronutrient intake from the weighed buffet was similar between groups: calories (ICU: 658 (301) vs. healthy subjects: 736 (325) kcal; p = 0.149); protein (ICU: 37 (19) vs. healthy subjects: 40 (17) g; p = 0.275); fat (ICU: 23 (12) vs healthy subjects: 26 (13) g; p = 0.261); and carbohydrates (ICU: 69 (35) vs. healthy subjects: 79 (42) g; p = 0.141). ICU survivors reported feeling less full regardless of time-point (p = 0.041). There was no difference in the rate of gastric emptying between the two groups (p = 0.216). CONCLUSIONS: ICU survivors reported less preference for fat and less calorie consumption than healthy subjects. However, intake of calories and macronutrients at a weighed meal was similar in the two groups, as was the rate of gastric emptying. ICU survivors reported being less full after the test meal, suggesting factors other than appetite may influence intake.

Incident Diabetes in Survivors of Critical Illness and Mechanisms Underlying Persistent Glucose Intolerance: A Prospective Cohort Study.

OBJECTIVES: Stress hyperglycemia occurs in critically ill patients and may be a risk factor for subsequent diabetes. The aims of this study were to determine incident diabetes and prevalent prediabetes in survivors of critical illness experiencing stress hyperglycemia and to explore underlying mechanisms. DESIGN: This was a prospective, single center, cohort study. At admission to ICU, hemoglobin A1c was measured in eligible patients. Participants returned at 3 and 12 months after ICU admission and underwent hemoglobin A1c testing and an oral glucose tolerance test. Blood was also collected for hormone concentrations, whereas gastric emptying was measured via an isotope breath test. ß-cell function was modeled using standard techniques. SETTING: Tertiary-referral, mixed medical-surgical ICU. PATIENTS: Consecutively admitted patients who developed stress hyperglycemia and survived to hospital discharge were eligible. MEASUREMENTS AND MAIN RESULTS: Consent was obtained from 40 patients (mean age, 58 yr [SD, 10], hemoglobin A1c 36.8 mmol/mol [4.9 mmol/mol]) with 35 attending the 3-month and 26 the 12-month visits. At 3 months, 13 (37%) had diabetes and 15 (43%) had prediabetes. At 12 months, seven (27%) participants had diabetes, whereas 11 (42%) had prediabetes. Mean hemoglobin A1c increased from baseline during the study: +0.7 mmol/mol (-1.2 to 2.5 mmol/mol) at 3 months and +3.3 mmol/mol (0.98-5.59 mmol/mol) at 12 months (p = 0.02). Gastric emptying was not significantly different across groups at either 3 or 12 months. CONCLUSIONS: Diabetes and prediabetes occur frequently in survivors of ICU experiencing stress hyperglycemia. Based on the occurrence rate observed in this cohort, structured screening and intervention programs appear warranted.

Are point-of-care measurements of glycated haemoglobin accurate in the critically ill?

INTRODUCTION: Critically ill patients with type 2 diabetes mellitus (T2DM) and chronic hyperglycaemia may benefit from a more liberal approach to glucose control than patients with previously normal glucose tolerance. It may therefore be useful to rapidly determine HbA1c concentrations. Point-of-care (POC) analysers offer rapid results but may be less accurate than laboratory analysis. AIM(S): The aim of this study was to determine agreement between POC and laboratory HbA1c testing in critically ill patients with T2DM. METHODS: Critically ill patients with T2DM had concurrent laboratory, capillary-, and arterial-POC HbA1c measurements performed. Data are presented as mean (standard deviation) or median [interquartile range]. Measurement agreement was assessed by Lin's concordance correlation coefficient, Bland-Altman 95% limits of agreement, and classification by Cohen's kappa statistic. RESULTS: HbA1c analysis was performed for 26 patients. The time to obtain a result from POC analysis took a median of 9 [7, 10] minutes. Laboratory analysis took a median of 328 [257, 522] minutes from the time of test request to the time of report. Lin's correlation coefficient showed almost perfect agreement (0.99%) for arterial- vs capillary-POC and both POC methods vs arterial laboratory analysis. Bland-Altman plots showed a mean difference of 2.0 (3.7) with 95% limits of agreement of -5.4 to 9.3 for capillary vs laboratory, 1.6 (3.4) and -5.1 to 8.4 for arterial vs laboratory, and -0.137 (2.6) and -5.2 to 4.9 for capillary vs arterial. Patient classification as having inadequately controlled diabetes (>53 mmol/mol) showed 100% agreement across all tests. CONCLUSIONS: HbA1c values can be accurately and rapidly obtained using POC testing in the critically ill.

Postprandial hypotension in older survivors of critical illness.

PURPOSE: In older people postprandial hypotension occurs frequently; and is an independent risk factor for falls, cardiovascular events, stroke and death. The primary aim of this pilot study was to estimate the frequency of postprandial hypotension and evaluate the mechanisms underlying this condition in older survivors of an Intensive Care Unit (ICU). MATERIALS AND METHODS: Thirty-five older (>65 years) survivors were studied 3 months after discharge. After an overnight fast, participants consumed a 300 mL drink containing 75 g glucose, labelled with 20 MBq 99mTc-calcium phytate. Patients had concurrent measurements of blood pressure, heart rate, blood glucose and gastric emptying following drink ingestion. Proportion of participants is presented as percent (95% CI) and continuous variables as mean (SD). RESULTS: Postprandial hypotension was evident in 10 (29%; 95% CI 14-44), orthostatic hypotension in 2 (6%; 95% CI 0-13) and cardiovascular autonomic dysfunction in 2 (6%; 95% CI 0-13) participants. The maximal postprandial nadir for systolic blood pressure and diastolic blood pressures were -29 (14) mmHg and -18 (7) mmHg. CONCLUSIONS: In this cohort of older survivors of ICU postprandial hypotension occurred frequently . This suggests that postprandial hypotension is an unrecognised issue in older ICU survivors.

Antecedent Hypoglycemia Does Not Attenuate the Acceleration of Gastric Emptying by Hypoglycemia.

Context: Acute hypoglycemia accelerates gastric emptying and increases cardiac contractility. However, antecedent hypoglycemia attenuates counterregulatory hormonal responses to subsequent hypoglycemia. Objective: To determine the effect of antecedent hypoglycemia on gastric and cardiac responses to subsequent hypoglycemia in health. Design: A prospective, single-blind, randomized, crossover study (performed at the Royal Adelaide Hospital, Adelaide, South Australia, Australia). Patients: Ten healthy young men 18 to 35 years of age were studied for 36 hours on two occasions. Interventions: Participants were randomly assigned to either antecedent hypoglycemia [three 45-minute periods of strict hypoglycemia (2.8 mmol/L] or control [three 45-minute periods of strict euglycemia (6 mmol/L)] during the initial 12-hour period. Participants were monitored overnight, and the following morning blood glucose was clamped at 2.8 mmol/L for 60 minutes and then at 6 mmol/L for 120 minutes. At least 6 weeks later participants returned for the alternative intervention. Gastric emptying and cardiac fractional shortening were measured with scintigraphy and two-dimensional echocardiography, respectively, on the morning of all 4 study days. Results: A single, acute episode of hypoglycemia accelerated gastric emptying (P = 0.01) and augmented fractional shortening (P < 0.01). Gastric emptying was unaffected by antecedent hypoglycemia (P = 0.74) whereas fractional shortening showed a trend to attenuation (P = 0.06). The adrenaline response was diminished (P < 0.05) by antecedent hypoglycemia. Conclusions: In health, the acceleration of gastric emptying during hypoglycemia is unaffected by antecedent hypoglycemia, whereas the increase in cardiac contractility may be attenuated.

Wide Disagreement Between Alternative Assessments of Premorbid Physical Activity: Subjective Patient and Surrogate Reports and Objective Smartphone Data.

OBJECTIVES: Surrogate-decision maker and patient self-reported estimates of the distances walked prior to acute illness are subjective and may be imprecise. It may be possible to extract objective data from a patient's smartphone, specifically, step and global position system data, to quantify physical activity. The objectives were to 1) assess the agreement between surrogate-decision maker and patient self-reported estimates of distance and time walked prior to resting and daily step-count and 2) determine the feasibility of extracting premorbid physical activity (step and global position system) data from critically ill patients. DESIGN: Prospective cohort study. SETTING: Quaternary ICU. PATIENTS: Fifty consecutively admitted adult patients who owned a smartphone, who were ambulatory at baseline, and who remained in ICU for more than 48 hours participated. MEASURMENTS AND MAIN RESULTS: There was no agreement between patients and surrogates for all premorbid walking metrics (mean bias 108% [99% lower to 8,700% higher], 83% [97% to 2,100%], and 71% [96% to 1,080%], for distance, time, and steps, respectively). Step and/or global position system data were successfully extracted from 24 of 50 phones (48%; 95% CI, 35-62%). Surrogate-decision makers, but not patient self-reported, estimates of steps taken per day correlated with smartphone data (surrogates: n = 13, ρ = 0.56, p < 0.05; patients: n = 13, ρ = 0.30, p = 0.317). CONCLUSION: There was a lack of agreement between surrogate-decision maker and patient self-reported subjective estimates of distance walked. Obtaining premorbid physical activity data from the current-generation smartphones was feasible in approximately 50% of patients.