Indirect Calorimetry Critical in Identifying Early Hypometabolism and Late-Stage Hypermetabolism in Post-surgical Patients

Background: Indirect calorimetry (IC) is the gold-standard procedure for measuring resting energy expenditure (REE) in hospitalized patients. Predictive energy equations commonly use static variables and rarely account for changes in REE throughout hospitalization. We hypothesize that predictive equations are typically inaccurate in surgical intensive care unit (ICU) patients. More specifically, we hypothesize that predictive equations often overpredict measured resting energy expenditure (mREE) in early-stage critical illness and underpredict needs later in surgical ICU stay, leading to over-/under-feeding and associated complications. Method(s): This prospective observational trial enrolled surgical ICU patients who underwent emergent or urgent operations for abdominal trauma, perforated viscus, or ischemic bowel within 72 hours of their surgical procedure. Metabolic assessments were performed using the COSMED Q-NRG + Metabolic Monitor ventilator, mask, and canopy at regular intervals during and post ICU admission until hospital discharge. Measurements were categorized by post-surgical intervention ICU admission days 0-3, 4-7, 8-14, 15-21, and 22-28. Patients with multiple measurements taken during the same time interval were averaged. mREE reported in calories (kcal) per kilogram (kg) of admission body weight per day were compared in obese (BMI > 30 kg/m2) and non-obese (BMI < 30 kg/m2) subgroups. Compared to IC, the Mifflin St Jeor (MSJ) equation determined predicted REE using ICU admission anthropometrics. Data are reported as mean+/-standard error of the mean (SEM) and median (interquartile range), and a two-sided p-value of <0.05 was determined significant. Result(s): In total, 18 surgical ICU patients who contributed 47 IC measurements were included in the analysis (Table 1). Most measures were obtained within the first 7 days of post-surgical ICU admission (72%). mREE peaked between days 8-14 in obese and non-obese subgroups (20.6 vs 28.5 kcal/kg;p = 0.02) and was lowest during 0-3 days of post-surgical ICU admission in both groups. Across all 5-time intervals, average kcal/ kg ranged from 14.7-20.6 among obese patients and from 20.1-28.5 in non-obese counterparts (Table 2). Non-obese patients had higher mREE per kg of body weight than obese patients at all time points (Figure 1). MSJ over-predicted mREE during the first 7 days post ICU admission in non-obese patients and within the first 3 days in obese patients and underpredicted mREE in both groups thereafter. Conclusion(s): Equations such as MSJ over- and under-predict mREE in post-operative surgical ICU patients depending on the days elapsed since post-surgical ICU admission. ASPEN's current guideline recommendation of 12-25 kcal/kg may also underfeed post-surgical populations while 25 kcal/kg may not support hypermetabolism among non-obese patients seen in week 2 following post-surgical ICU admission. Alternatively, MSJ multiplied by a 1.2 activity factor may account for hypermetabolism during this time. Notably, non-obese patients experienced greater hypermetabolism than obese patients during week 2 which is consistent with our previously published data in mechanically ventilated COVID- 19 patients. Additionally, the striking dichotomy between the mREE of obese and non-obese patients at all post-surgical time points should be considered in the clinical care of patients. Ultimately, IC remains the gold-standard means of measuring REE and is a critical tool to capture the dynamic nature of energy requirements in post-surgical populations as weight-based and predictive equations continually fall short. (Table Presented).

How do guideline recommended energy targets compare with measured energy expenditure in critically ill adults with obesity: A systematic literature review.

BACKGROUND: Critically ill patients with obesity have unique and complex nutritional needs, with clinical practice guidelines conflicting regarding recommended energy targets. The aim of this systematic review was to 1) describe measured resting energy expenditure (mREE) reported in the literature and; 2) compare mREE to predicted energy targets using the European (ESPEN) and American (ASPEN) guideline recommendations when indirect calorimetry is not available in critically ill patients with obesity. METHODS: The protocol was registered apriori and literature was searched until 17th March, 2022. Original studies were included if they reported mREE using indirect calorimetry in critically ill patients with obesity (BMI≥30 kg/m2). Group-level mREE data was reported as per the primary publication using mean ± standard deviation or median [interquartile range]. Where individual patient data was available, Bland-Altman analysis was used to assess mean bias (95% limits of agreement) between guideline recommendations and mREE targets (i.e. ASPEN for BMI 30-50, 11-14 kcal/kg actual weight compared to 70% mREE and ESPEN 20-25 kcal/kg adjusted weight compared to 100% mREE). Accuracy was assessed by the percentage (%) of estimates within ±10% of mREE targets. RESULTS: After searching 8019 articles, 24 studies were included. mREE ranged from 1607 ± 385 to 2919 [2318-3362]kcal and 12-32kcal/actual body weight. For the ASPEN recommendations of 11-14 kcal/kg, a mean bias of -18% (-50% to +13%) and 4% (-36% to +44%) was observed, respectively (n = 104). For the ESPEN recommendations 20-25 kcal/kg, a bias of -22% (-51% to +7%) and -4% (-43% to +34%), was observed, respectively (n = 114). The guideline recommendations were able to accurately predict mREE targets on 30%-39% occasions (11-14 kcal/kg actual) and 15%-45% occasions (20-25 kcal/kg adjusted), for ASPEN and ESPEN recommendations, respectively. CONCLUSIONS: Measured energy expenditure in critically ill patients with obesity is variable. Energy targets generated using predictive equations recommended in both the ASPEN and ESPEN clinical guidelines have poor agreement with mREE and are frequently not able to accurately predict within ±10% of mREE, most commonly underestimating energy needs.

Validation of Oura ring energy expenditure and steps in laboratory and free-living.

BACKGROUND: Commercial activity trackers are increasingly used in research and compared with research-based accelerometers are often less intrusive, cheaper, with improved storage and battery capacity, although typically less validated. The present study aimed to determine the validity of Oura Ring step-count and energy expenditure (EE) in both laboratory and free-living. METHODS: Oura Ring EE was compared against indirect calorimetry in the laboratory, followed by a 14-day free-living study with 32 participants wearing an Oura Ring and reference monitors (three accelerometers positioned at hip, thigh, and wrist, and pedometer) to evaluate Oura EE variables and step count. RESULTS: Strong correlations were shown for Oura versus indirect calorimetry in the laboratory (r = 0.93), and versus reference monitors for all variables in free-living (r ≥ 0.76). Significant (p < 0.05) mean differences for Oura versus reference methods were found for laboratory measured sitting (- 0.12 ± 0.28 MET), standing (- 0.27 ± 0.33 MET), fast walk (- 0.82 ± 1.92 MET) and very fast run (- 3.49 ± 3.94 MET), and for free-living step-count (2124 ± 4256 steps) and EE variables (MET: - 0.34-0.26; TEE: 362-494 kcal; AEE: - 487-259 kcal). In the laboratory, Oura tended to underestimate EE with increasing discrepancy as intensity increased. The combined activities and slow running in the laboratory, and all MET placements, TEE hip and wrist, and step count in free-living had acceptable measurement errors (< 10% MAPE), whereas the remaining free-living variables showed close to (≤13.2%) acceptable limits. CONCLUSION: This is the first study investigating the validity of Oura Ring EE against gold standard methods. Oura successfully identified major changes between activities and/or intensities but was less responsive to detailed deviations within activities. In free-living, Oura step-count and EE variables tightly correlated with reference monitors, though with systemic over- or underestimations indicating somewhat low intra-individual validity of the ring versus the reference monitors. However, the correlations between the devices were high, suggesting that the Oura can detect differences at group-level for active and total energy expenditure, as well as step count.

Nutritional and metabolic management of COVID-19 intensive care patients.

Nutritional and metabolic disturbances are observed in patients critically ill with Coronavirus disease 19 (COVID-19) patients. The aim of this review is to describe these disturbances during the progression of the disease, from the pre-intubation phase through the ventilated condition to the post extubation phase. The analysis of new data describing the prevalence of malnutrition, the modifications in energy expenditure and body composition are guiding medical nutritional therapy to prevent patients from experiencing severe energy deficit and muscle loss. Rehabilitation may be extremely prolonged and therefore, nutrition is mandatory to decrease this recondition period. This review also comments on the European Society of Parenteral and Enteral Nutrition (ESPEN) nutritional statements.

Nutritional adequacy and accuracy in long-stay critically ill patients as measured by indirect calorimetry

Introduction: Nutritional optimisation is recognised as having significant impact on clinical and functional outcomes of critically ill patients.1 Clinical recommendations suggest use of indirect calorimetry guided nutrition in the intensive care unit (ICU),2 and a recent systematic review demonstrated improved outcomes from its use.3 The COVID-19 pandemic has seen a greater proportion of patients with prolonged critical illness, a cohort for whom nutritional optimisation is a key unmet need.4 Objectives: To assess rates of over and underfeeding in a tertiary centre ICU and how these relate to markers of catabolism and persistent critical illness. Methods: Serial measurements of REE (resting energy expenditure) and RQ (respiratory quotient) by indirect calorimetry were performed using Q-NRG+ device (COSMED, Rome, Italy). Nutritional intake and estimations of requirements were recorded concurrently together with routine clinical observations, and markers of critical illness, catabolism and over or underfeeding. Results: Across 30 patients, REE was lower than estimated energy requirements, 24.2 (IQR 20.0-28.1) kcal/ day/kg IBW vs. 29.1(IQR 25.4-33.1) kcal/day/kg IBW, p<0.001. 41.8% of measurements showed overfeeding (actual calorie intake >110% of REE), and 23.3% showed underfeeding (actual calorie intake <85% of REE). Obese patients (n=15) were underfed (-98kcal/day deficit) compared to non-obese patients (n=15), who were on average overfed (+256kcal/day surplus), p=0.021. Overfeeding was also associated with greater length of ICU admission (R2 0.159, p<0.005). Median day of ICU admission in overfed patients was 39 days (IQR 24-56), and in underfed patients 21.5 (IQR 7.5-45.25). However, there was no significant association between calorie surplus or deficit, and other markers of overfeeding PaCO2, insulin use, ureacreatinine-ratio. Conclusion: This service evaluation recorded measurements of REE and RQ in critically ill patients with high lengths of ICU stay (up to 66 days). We observed increased rates of overfeeding with increased duration of ICU admission, and increased overfeeding in non-obese patients.

Comparison of Nutritional Pattern and Use Between Covid and Non-Covid ICU Patients

Introduction: Nutrition plays an important role in ICU patients, more so in hypercatabolic COVID-19 illness. Among other lifethreatening problems, nutrition seemed to have taken a backseat in many hospitals due to logistics, reduction of manpower, isolation practices, etc. Objectives: To study the pattern and use of nutrition in our tertiary care COVID ICU in comparison to the non-COVID ICU. Materials and methods: An observational study was performed of 941 consecutive patients from March 2020 to June 2021 by collecting data from the iNUTRIMON software.1 In view of the various challenges faced in the delivery of appropriate nutrition and the hypermetabolic nature of the disease a COVID-specific nutrition protocol was formulated at the start of the pandemic.2 It involved the use of enteral scientific feeding formula for all COVID patients tolerating an oral diet. The protocol can be accessed at https://www.opensciencepublications.com/fulltextarticles/IJN- 2395-2326-7-216.html. The energy was prescribed using simple predictive equations (i.e., 25 kcal/kg). In case of mechanically ventilated patients, indirect calorimetry-derived measures were used. All patients were prescribed 1.8 g/kg proteins. The protocol for nutrition patients remained the same with the exception that in non-COVID patients oral supplements were added only if 50% of the kitchen diet was not taken within 3 days. The use of TPN for both groups remained as per the protocol. The software iNutrimon calculated the scientific feeding formulae (product) based on the prescription of energy, proteins, and volumes, taking into account the viscosity and precise water requirement per scoop of formula feed. Results: The mean length of ICU stay of COVID patients was 9.31 days as compared to 6.8 days in non-COVID patients. 8.8% of the patients required TPN as compared to 1.4% of the non-COVID population. Only 0.6% of the total enteral feeding in the COVID ICU was with kitchen diet alone compared to 7.8% in the non-COVID ICU. The incidence of use of supplemental nutrition was 97% per patient as compared to 57.6% per non-COVID patient. Among the scientific feeding formulae, the use of peptamen (85%) was highest in COVID patients as compared to 25% in non-COVID patients. The per-day cost of nutrition for COVID patients admitted to the ICU was found to be comparable to non-COVID patients when a cost analysis was done. Conclusion: There was a 168% increase in the use of scientific feeding formula and a 60% increase in the use of TPN in COVID patients as compared to non-COVID patients. This is also reflected as an increase in the cost of feeding. The use of TPN seems to suggest the increased intolerance to enteral nutrition. The increased use of scientific feeding formulae may indicate the adherence to protocol and also seems to suggest that COVID patients needed to be supplemented as kitchen feeds were unable to meet the requirements.

Are We Feeding Our Critically Ill Covid Patients, Right?

Objective: Primary objective: To study the energy expenditure in a significant number of mechanically ventilated COVID-19 patients in ARDS. Secondary objective: 1. To compare the deviations seen with predictive equations based on actual and ideal body weight. 2. To compare the EE derived versus the VCO2 based estimation. Materials and methods: The Resting Energy expenditure (REE) of 60 patients was measured with the help of the ESCOVYX-module for indirect calorimetry using the GE CARESCAPE R860 ventilator. The steady-state was validated by ensuring a respiratory quotient of 0.7-0.8 and variation of 5% for VCO2 and VO2 for at least 30 minutes. It was ensured that for 60 minutes the patient was not disturbed by endotracheal tube suction, no ventilatory changes were performed, and no vasopressors alteration was done. The absence of a leak was ascertained on the ventilator. The calculation was done from day 2 onwards after mechanical ventilation and subsequently every 2nd day till the patient was on ventilator. The resting energy expenditure was also calculated by the simple predictive equations as per ESPEN COVID-19 guidelines, i.e., 25-30 kcal/kg of which the mean of 27 kcal/kg was chosen. Bodyweight was estimated by height equation 50 kg for 5 ft plus 2.3 kg for each inch >5 feet. The quantitative measures were studied by Bland and Altman plot to describe an agreement between the two by constructing a line of agreement. The limits were calculated by using the mean and standard deviation of the difference between the two measurements. Statistics: The EE derived from the two methods is compared by Bland and Altman plots. Reliability and adequacy between the methods are tested using ROC curves with kappa coefficient (reliability coefficient). For the coefficient of variation, ANOVA is used when applicable. IBM SPSS Statistics for Windows, version 24.0 (IBM Corporation, Chicago, USA) was used to perform analyses. MedCalc version 19 (MedCalc bv, Ostend, Belgium) was used to create BlandeAltman plots. Results: No 1: The estimated mean energy expenditure derived from weight-based calculations was 2576 ± 469 kcal/24 hours, which was significantly higher when compared with an estimation of EE from indirect calorimetry of 1507 ± 499 kcal/24 hours (15-20 kcal/kg/day). This correlation is significant but not useful for prediction (R = 0.345). No 2: The estimated mean EEVCO2 was 1388 ± 467 kcal/24 hours compared with an estimation of EE from indirect calorimetry of 1507 ± 499 kcal/24 hours. The Bias and precision, as visualized by the limits of agreement, are shown in the Bland-Altman plot where there was a significant bias of only 118 kcal/day (95% CI (-187 to 422 kcal);p < 0.001. The regression analysis reveals that for every one unit change in EEVCO2 value, there is one unit change in EE by IC. This correlation is significant (R = 0.951). Similarly, the Bland-Altman plot was tested between the estimated mean EEVCO2 and EE derived from weight-based calculations. The difference was wide with significant bias of 1187 kcal/day (95% CI (-2256 to (-118) kcal);p < 0.001). Conclusion: The ESPEN guidelines (30 kcal/kg through the disease state) for energy estimation may not be right in COVID-19 patients and the study calls for more personalisation of energy estimation by the correct use of indirect calorimetry.

Energy expenditure in COVID-19 mechanically ventilated patients: A comparison of three methods of energy estimation.

BACKGROUND: Indirect calorimetry (IC) is the gold standard for measuring resting energy expenditure. Energy expenditure (EE) estimated by ventilator-derived carbon dioxide consumption (EEVCO2 ) has also been proposed. In the absence of IC, predictive weight-based equations have been recommended to estimate daily energy requirements. This study aims to compare simple predictive weight-based equations with those estimated by EEVCO2 and IC in mechanically ventilated patients of COVID-19. METHODS: Retrospective study of a cohort of critically ill adult patients with COVID-19 requiring mechanical ventilation and artificial nutrition to compare energy estimations by three methods through the calculation of bias and precision agreement, reliability, and accuracy rates. RESULTS: In 58 mechanically ventilated patients, a total of 117 paired measurements were obtained. The mean estimated energy derived from weight-based calculations was 2576 ± 469 kcal/24 h, as compared with 1507 ± 499 kcal/24 h when EE was estimated by IC, resulting in a significant bias of 1069 kcal/day (95% CI [-2158 to 18.7 kcal]; P < 0.001). Similarly, estimated mean EEVCO2 was 1388 ± 467 kcal/24 h when compared with estimation of EE from IC. A significant bias of only 118 kcal/day (95% CI [-187 to 422 kcal]; P < 0.001), compared by the Bland-Altman plot, was noted. CONCLUSION: The energy estimated with EEVCO2 correlated better with IC values than energy derived from weight-based calculations. Our data suggest that the use of simple predictive equations may potentially lead to overfeeding in mechanically ventilated patients with COVID-19.

Comparing retrospective PSU measurements with the LEEP-COVID 2020 study to ascertain similarities in calories per kilogram of body weight for ventilator-dependent COVID-19 patients

Background: Critically ill COVID-19 patients are suspected to have high caloric needs.1 Indirect calorimetry (IC) is the gold standard used to measure resting energy expenditure (mREE), but it is expensive and not widely available. Predictive equations are often used to assess metabolic requirements and the Pennsylvania State University (PSU) equation has demonstrated comparable results to IC in identifying caloric requirements for critically ill patients. This article describes a simple, comparative retrospective presentation of PSU calculations to that of the study published in 2020 by Whittle et al. on Longitudinal Energy Expenditure in Critically Ill Patients with COVID-19 (LEEP-COVID).1 PSU measurements were compared to the IC data by the LEEP-COVID study to ascertain similarities in calories per kilogram (kcal/kg) of body weight for ventilator-dependent COVID-19 patients over a duration of 30 days. Methods: A retrospective chart review was performed on critically ill COVID-19 patients between March and June of 2020 to collect their PSU calculations. Patients on extracorporeal membrane oxygenation (ECMO) and volumetric diffusive respirator (VDR), were excluded as these devices could skew the minute ventilation and yield an inaccurate PSU calculation. Patients for whom the PSU data was not clearly labeled were also removed, leaving 38 adult ventilator-dependent COVID-19 patients for review. PSU data was then compared to the LEEP-COVID 2020 study by Whittle et al. Results: Out of the 38 ventilator-dependent COVID-19 patients, the median age was 65 years old, 65.8% were male and 48% had a BMI >30. As illustrated in figure 1, kcal/kg of actual body weight (ABW) for the non-obese group (BMI < 30) from days 0 - 3: 21.9 kcal/kg, days 4 - 6: 23.5 kcal/kg, days 7 - 9: 23.4 kcal/kg, days 10 - 12: 24 kcal/kg, days 13 - 15: 23.1 kcal/kg, days 16 - 18: 22.4 kcal/kg, days 19 - 21: 21.3 kcal/kg, days 22 - 24: 24.6 kcal/kg, days 25 - 27: 19.5 kcal/kg and days 28 - 30: 22.9 kcal/kg. Figure 1 also shows the kcal/kg of ABW for the obese group (BMI 30 - 40) from days 0 - 3: 19 kcal/kg, days 4 - 6: 18.1 kcal/kg, days 7 - 9: 18.2 kcal/kg, days 10 - 12: 19.6 kcal/kg, days 13 - 15: 18.6 kcal/kg, days 16 - 18: 20.4 kcal/kg, days 19 - 21: 19.2 kcal/kg, days 22 - 24: 21.0 kcal/ kg, days 25 - 27: 17.8 kcal/kg and days 28 - 30: 19.4 kcal/kg. Compared to the LEEP-COVID 2020 study, non-obese ventilated COVID-19 patients from days 0 - 14 had a mREE using IC of 19.2 - 26 kcal/kg ABW and obese patients: 17.5 - 21 kcal/kg ABW. Our retrospective study using the PSU equation from days 0 - 15 revealed caloric needs of 21.9 - 24 kcal/kg ABW for non-obese patients and 18 - 19.8 kcal/kg ABW for obese patients. Conclusion: In performing a simple comparative review of the LEEP-COVID study to our retrospective data, we identified that the PSU equation may be useful in estimating the caloric needs for ventilated COVID-19 patients from days 0 - 15.

Effect of extracorporeal carbon dioxide removal on respiratory quotient measured by indirect calorimetry: Unravelling the mystery.

NEW FINDINGS: What is the main observation in this case? Several studies have reported progressive hypoxaemia once extracorporeal carbon dioxide removal is started in patients with hypercapnic respiratory failure, possibly attributable to an altered respiratory quotient. What insights does it reveal? In this quality control report, we show that the respiratory quotient exhibits only minimal alteration when extracorporeal carbon dioxide removal is started and assume that the progressive hypoxaemia is attributable to an increase in intrapulmonary shunt. ABSTRACT: The use of extracorporeal carbon dioxide removal (ECCO2 R) has been proposed in patients with acute respiratory distress syndrome to achieve lung-protective ventilation and in patients with selective hypercapnic respiratory failure. However, several studies have reported progressive hypoxaemia, as expressed by a need to increase the inspired oxygen fraction (Fi O2 ) to maintain adequate oxygenation or by a decrease in the ratio of arterial oxygen tension (Pa O2 ) to Fi O2 once ECCO2 R is started. We present the case of a patient who was admitted to the intensive care unit for a coronavirus disease 2019 pneumonia and who was intubated because of hypercapnic respiratory insufficiency. Extracorporeal carbon dioxide removal was started, and the patient subsequently developed progressive hypoxaemia. To test whether the hypoxaemia was attributable to the ECCO2 R, blood samples were taken in different settings: (1) 'no ECCO2 R', blood flow 150 ml/min with a ECCO2 R gas flow of 0 L/min; and (2) 'with ECCO2 R', blood flow 400 ml/min with gas flow 12 L/min. We measured Pa O2 , alveolar oxygen tension, Pa O2 /Fi O2 , alveolar-arterial oxygen tension difference, arterial carbon dioxide tension and the respiratory quotient (RQ) by indirect calorimetry in each setting. The RQ was 0.60 without ECCO2 R and 0.57 with ECCO2 R. The alveolar oxygen tension was 220.4 mmHg without ECCO2 R and increased to 240.3 mmHg with ECCO2 R, whereas Pa O2 /Fi O2 decreased from 177 to 171. Our study showed only a minimal change in RQ when ECCO2 R was started. We were the first to measure the RQ directly, before and after the initiation of ECCO2 R, in a patient with hypercapnic respiratory failure.

Nutritional status of COVID-19 patients one year post-ICU stay

Introduction: Our aim was to describe nutritional status (NS) of critically ill COVID-19 patients 1 year post-ICU stay. Malnutrition and weight loss were observed during hospitalization. Post-ICU discharge patients often continue to suffer from physical complaints and poor nutritional intake, which can negatively affect NS. Methods: Observational study including adult COVID-19 patients 1 year post-ICU stay. NS assessment (nutrient balance, body composition and physical status) was performed. Nutritional intake (energy and protein), nutrition related complaints and losses were examined. Indirect calorimetry (Q-NRG +) was performed to determine nutritional requirements. Body composition (e.g. fat mass, fat free mass) was measured with bio-electrical impedance analysis (InbodyS10). Fat-free mass index (FFMI) and fat mass index (FMI) were calculated. Physical status was determined with handgrip strength (HGS). Overall values ≤ 10th percentile were considered too low and ≥ 90th too high. Descriptive statistics were used for analysis. Results: 48 patients were included (72% male;median age 60 years [IQR 52;65]). Median ICU stay was 19 days [IQR 10;30]. Median weight loss during ICU stay was 13% [IQR - 10;- 16] and 12% of this loss [IQR 7;16] was regained after 1 year. BMI was 26 kg/m2 [IQR 23;30] 1 year post-ICU, of which 24% was obese (BMI > 30 kg/m2). Normometabolism was predominantly observed (62%), followed by hypermetabolism (30%). Mean nutritional intake was 78% of calculated requirements. Nutrition related complaints occurred in < 5% of the patients. Most patients had a high FMI (55%) and minority had low FFMI (35%). Combination of a high FFMI and FMI was present in 17%. Three patients (6%) had low HGS. Conclusions: Weight loss was almost fully regained 1 year post-ICU, often in combination with a high fat mass. A minority had low physical function. Whereas reported calculated requirements were not met, lifestyle coaching remains indicated to optimize NS.

Energy requirements for critically ill patients with COVID-19.

Early reports suggested that predictive equations significantly underestimate the energy requirements of critically ill patients with coronavirus disease 2019 (COVID-19) based on the results of indirect calorimetry (IC) measurements. IC is the gold standard for measuring energy expenditure in critically ill patients. However, IC is not available in many institutions. If predictive equations significantly underestimate energy requirements in severe COVID-19, this increases the risk of underfeeding and malnutrition, which is associated with poorer clinical outcomes. As such, the purpose of this narrative review is to summarize and synthesize evidence comparing measured resting energy expenditure via IC with predicted resting energy expenditure determined via commonly used predictive equations in adult critically ill patients with COVID-19. Five articles met the inclusion criteria for this review. Their results suggest that many critically ill patients with COVID-19 are in a hypermetabolic state, which is underestimated by commonly used predictive equations in the intensive care unit (ICU) setting. In nonobese patients, energy expenditure appears to progressively increase over the course of ICU admission, peaking at week 3. The metabolic response pattern in patients with obesity is unclear because of conflicting findings. Based on limited evidence published thus far, the most accurate predictive equations appear to be the Penn State equations; however, they still had poor individual accuracy overall, which increases the risk of underfeeding or overfeeding and, as such, renders the equations an unsuitable alternative to IC.

Prolonged progressive hypermetabolism during COVID-19 hospitalization undetected by common predictive energy equations.

BACKGROUND & AIMS: Indirect calorimetry (IC) is the gold-standard for determining measured resting energy expenditure (mREE) in critical illness. When IC is not available, predicted resting energy expenditure (pREE) equations are commonly utilized, which often inaccurately predict metabolic demands leading to over- or under-feeding. This study aims to longitudinally assess mREE via IC in critically ill patients with SARS-CoV-2 (COVID-19) infection throughout the entirety of, often prolonged, intensive care unit (ICU) stays and compare mREE to commonly utilized pREE equations. METHODS: This single-center prospective cohort study of 38 mechanically ventilated COVID-19 patients from April 1, 2020 to February 1, 2021. The Q-NRG® Metabolic Monitor was used to obtain IC data. The Harris-Benedict (HB), Mifflin St-Jeor (MSJ), Penn State University (PSU), and weight-based equations from the American Society of Parenteral and Enteral Nutrition - Society of Critical Care Medicine (ASPEN-SCCM) Clinical Guidelines were utilized to assess the accuracy of common pREE equations and their ability to predict hypo/hypermetabolism in COVID-19 ICU patients. RESULTS: The IC measures collected revealed a relatively normometabolic or minimally hypermetabolic mREE at 21.3 kcal/kg/d or 110% of predicted by the HB equation over the first week of mechanical ventilation (MV). This progressed to significant and uniquely prolonged hypermetabolism over successive weeks to 28.1 kcal/kg/d or 143% of HB predicted by MV week 3, with hypermetabolism persisting to MV week 7. Obese individuals displayed a more truncated response with significantly lower mREE versus non-obese patients in MV week 1 (19.5 ± 1.0 kcal/kg/d vs 25.1 ± 1.8 kcal/kg/d, respectively; p < 0.01), with little change in weeks 2-3 (19.5 ± 1.5 kcal/kg/d vs 28.0 ± 2.0 kcal/kg/d; p < 0.01). Both ASPEN-SCCM upper range and PSU pREE equations provided close approximations of mREE yet, like all pREE equations, occasionally over- and under-predicted energy needs and typically did not predict late hypermetabolism. CONCLUSIONS: Study results show a truly unique metabolic response in COVID-19 ICU patients, characterized by significant and prolonged, progressive hypermetabolism peaking at 3 weeks' post-intubation, persisting for up to 7 weeks in ICU. This pattern was more clearly demonstrated in non-obese versus obese patients. This response is unique and distinct from any previously described model of ICU stress response in its prolonged hypermetabolic nature. This data reaffirms the need for routine, longitudinal IC measures to provide accurate energy targets in COVID-19 ICU patients. The PSU and ASPEN-SCCM equations appear to yield the most reasonable estimation to IC-derived mREE in COVID-19 ICU patients, yet still often over-/under-predict energy needs. These findings provide a practical guide for caloric prescription in COVID-19 ICU patients in the absence of IC.

Energy requirements of long-term ventilated COVID-19 patients with resolved SARS-CoV-2 infection.

BACKGROUND & AIMS: Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can rapidly progress into acute respiratory distress syndrome accompanied by multi-organ failure requiring invasive mechanical ventilation and critical care treatment. Nutritional therapy is a fundamental pillar in the management of hospitalized patients. It is broadly acknowledged that overfeeding and underfeeding of intensive care unit (ICU) patients are associated with increased morbidity and mortality. This study aimed to assess the energy demands of long-term ventilated COVID-19 patients using indirect calorimetry and to evaluate the applicability of established predictive equations to estimate their energy expenditure. METHODS: We performed a retrospective, single-center study in 26 mechanically ventilated COVID-19 patients with resolved SARS-CoV-2 infection in three independent intensive care units. Resting energy expenditure (REE) was evaluated by repetitive indirect calorimetry (IC) measurements. Simultaneously the performance of 12 predictive equations was examined. Patient's clinical data were retrieved from electronic medical charts. Bland-Altman plots were used to assess agreement between measured and calculated REE. RESULTS: Mean mREE was 1687 kcal/day and 20.0 kcal relative to actual body weight (ABW) per day (kcal/kg/day). Longitudinal mean mREE did not change significantly over time, although mREE values had a high dispersion (SD of mREE ±487). Obese individuals were found to have significantly increased mREE, but lower energy expenditure relative to their body mass. Calculated REE showed poor agreement with mREE ranging from 33 to 54%. CONCLUSION: Resolution of SARS-CoV-2 infection confirmed by negative PCR leads to stabilization of energy demands at an average 20 kcal/kg in ventilated critically ill patients. Due to high variations in mREE and low agreement with calculated energy expenditure IC remains the gold standard for the guidance of nutritional therapy.

Point-Counterpoint: Indirect Calorimetry Is not Necessary for Optimal Nutrition Therapy in Critical Illness.

Clinicians have widely recognized that indirect calorimetry (IC) is the "gold standard" for measuring energy expenditure (EE) and thus would intuitively anticipate that its use would be needed to provide optimal nutrition support in critical illness. Recent studies in the literature as well as dramatic changes in clinical practice over the past decade, though, would suggest that such a precise measure by IC to set energy goals is not required to maximize clinical benefit from early feeding in the intensive care unit (ICU). Results from randomized controlled trials evaluating permissive underfeeding, use of supplemental parenteral nutrition to achieve tight calorie control, and caloric density of formulas to increase energy delivery have provided an important perspective on 3 pertinent issues. First, a simple weight-based predictive equation (25 kcal/kg/day) provides a clinically useful approximation of EE. Second, a precise measure of EE by IC does not appear to improve outcomes compared with use of this less accurate estimation of energy requirements. And third, providing some percentage of requirements (50%-80%), achieves similar clinical benefit to full feeding (100%) in the early phases of critical illness. The value from IC use lies in the determination of caloric requirements in conditions for which weight-based equations are rendered inaccurate (anasarca, amputation, severe obesity) or the clinical state is markedly altered (such as the prolonged hyperinflammatory state of coronavirus disease 2019 [COVID-19]). In most other circumstances, routine use of IC would not be expected to change clinical outcomes from early nutrition therapy in the ICU.

Point-Counterpoint: Indirect Calorimetry Is Essential for Optimal Nutrition Therapy in the Intensive Care Unit.

Iatrogenic malnutrition and underfeeding are ubiquitous in intensive care units (ICUs) worldwide for prolonged periods after ICU admission. A major driver leading to the lack of emphasis on timely ICU nutrition delivery is lack of objective data to guide nutrition care. If we are to ultimately overcome current fundamental challenges to effective ICU nutrition delivery, we must all adopt routine objective, longitudinal measurement of energy targets via indirect calorimetry (IC). Key evidence supporting the routine use of IC in the ICU includes (1) universal societal ICU nutrition guidelines recommending IC to determine energy requirements; (2) data showing predictive equations or body weight calculations that are consistently inaccurate and correlate poorly with measured energy expenditure, ultimately leading to routine overfeeding and underfeeding, which are both associated with poor ICU outcomes; (3) recent development and worldwide availability of a new validated, accurate, easy-to-use IC device; and (4) recent data in ICU patients with coronavirus disease 2019 (COVID-19) showing progressive hypermetabolism throughout ICU stay, emphasizing the inaccuracy of predictive equations and marked day-to-day variability in nutrition needs. Thus, given the availability of a new validated IC device, these findings emphasize that routine longitudinal IC measures should be considered the new standard of care for ICU and post-ICU nutrition delivery. As we would not deliver vasopressors without accurate blood pressure measurements, the ICU community is only likely to embrace an increased focus on the importance of early nutrition delivery when we can consistently provide objective IC measures to ensure personalized nutrition care delivers the right nutrition dose, in the right patient, at the right time to optimize clinical outcomes.

Effects of wearing a FFP2 mask on indirect calorimetry measurements: A pilot study.

BACKGROUND & AIMS: During the coronavirus disease 2019 (COVID-19) pandemic the use of Indirect calorimetry (IC) during nutritional rehabilitation program requires special precautions due to possible contagions for patients and health professionals. We evaluated in a sample of healthy subjects the agreement between oxygen consumption (VO2 mL/min), carbon dioxide production (VCO2 mL/min), respiratory quotient (RQ) and resting energy expenditure (REE kcal/24 h/day) measured by IC with and without a filtering facepiece mask. MATERIALS: 10 subjects with a mean (SD) age of 43 (10) years and a body mass index of 25.2 (5.8) kg/m2 underwent indirect calorimetry both with and without a class 2 filtering facepiece mask (FFP2), in random order. The limits of agreement (LOA) and the concordance correlation coefficient (CCC) were used to evaluate the interchangeability of the measurement conditions. RESULTS: The LOA between REE measured with and without FFP2 (-111 to 189 kcal/day) were comparable to those for repeated IC tests without wearing masks and CCC (0.95) showed substantial agreement. CONCLUSIONS: We observed high agreement between REE measured by IC with and without FFP2 mask. These procedures are interchangeable in clinical practice.

Practical guidance for the use of indirect calorimetry during COVID 19 pandemic.

The daily practice requires the use of indirect calorimetry to define the energy requirements of intensive care patients. In the time of COVID-19 pandemic, this practice is challenging. The purpose of this methodology paper is to provide practical guidance to health professionals to perform this measurement safely, using various metabolic monitors.