Assessment of resting energy expenditure in mechanically ventilated patients

ESPEN practical guideline on clinical nutrition in hospitalized patients with acute or chronic kidney disease

BACKGROUND AND AIMS

Hospitalized patients often have acute kidney disease (AKD) or chronic kidney disease (CKD), with important metabolic and nutritional consequences. Moreover, in case kidney replacement therapy (KRT) is started, the possible impact on nutritional requirements cannot be neglected. On this regard, the present guideline aims to provide evidence-based recommendations for clinical nutrition in hospitalized patients with KD.

METHODS

The standard operating procedure for ESPEN guidelines was used. Clinical questions were defined in both the PICO format, and organized in subtopics when needed, and in non-PICO questions for the more general topics. The literature search was from January 1st, 1999 until January 1st, 2020. Each question led to one or more recommendation/statement and related commentaries. Existing evidence was graded, as well as recommendations and statements were developed and agreed upon in a multistage consensus process.

RESULTS

The present guideline provides 32 evidence-based recommendations and 8 statements, defining how to assess nutritional status, how to define patients at risk, how to choose the route of feeding, and how to integrate nutrition with KRT. In the final online voting, a strong consensus was reached in 84% at least of recommendations and 100% of statements.

CONCLUSION

The presence of KD in hospitalized patients identifies a highly heterogeneous group of subjects with widely varying nutrient needs and intakes. Considering the high nutritional risk related with this clinical condition, an individualized approach consisting of nutritional status evaluation and monitoring, frequent evaluation of nutritional requirements, and careful integration with KRT should be planned to avoid both underfeeding and overfeeding. Practical recommendations and statements were developed, aiming at defining suggestions for everyday clinical practice in the individualization of nutritional support in this patient setting. Literature areas with scarce or without evidence were also identified, thus requiring further basic or clinical research.

Metabolic and nutritional aspects in continuous renal replacement therapy

Nutrition is one of the foundations for supporting and treating critically ill patients. Nutritional support provides calories, protein, electrolytes, vitamins, and trace elements via the enteral or parenteral route. Acute kidney injury (AKI) is a common and devastating problem in critically ill patients and has significant metabolic and nutritional consequences. Moreover, renal replacement therapy (RRT), whatever the modality used, also profoundly impacts metabolism. RRT and of the extracorporeal circuit impede 'effect the evaluation of a patient's energy requirements by clinicians. Substrates added and removed within the extracorporeal treatment are not always taken into consideration, making treatment even more challenging. Furthermore, evidence on nutritional support during continuous renal replacement therapy (CRRT) is scarce, and there are no clinical guidelines for nutrition adaptations during CRRT in critically ill patients. Most recommendations are based on expert opinions. This review discusses the complex interaction between nutritional support and CRRT and presents some milestones for nutritional support in critically ill patients on CRRT.

Comparison of resting energy expenditure measured with metabolic cart and calculated with predictive formulas in critically ill patients on mechanical ventilation

INTRODUCTION

The purpose was to compare the resting energy expenditure (REE) measured with the Q-NRG™+ metabolic-cart (MREE) with REE predicted by equations (the Harris-Benedict formula and an equation developed in ward, REE-HB and REE-W, respectively). We also aimed to assess the agreement of the measurements of oxygen consumption (V̇O₂) and carbon dioxide production (V̇CO₂) at different inspired fractions of oxygen (FiO₂).

METHODS

27 mechanically ventilated ICU patients were enrolled. V̇O₂ and V̇CO₂ were measured by Q-NRG™+ during breathing 40% and 60% FiO₂. MREE was compared with REE-W and REE-HB normalized for body weight.

RESULTS

V̇O₂ was 233.0 (95.2) ml/min and 217.5 (89.8) ml/min at FiO₂ 40% and 60%, respectively (NS). V̇CO₂ was 199.0 (91.7) ml/min at FiO₂ 40%, and 197.5 (85.5) ml/min at FiO₂ 60% (NS). The REE estimated from the equations was significantly different from the MREE. The best agreement was found for the Harris-Benedict equation without correction for stress-factors. Harris-Benedict equation corrected overestimates REE.

CONCLUSIONS

This new metabolic cart Q-NRG™+ provides a concordance of values for V̇O₂ and V̇CO₂ when measured at different FiO₂, and is a reliable tool for estimating energy expenditure and assessing the nutritional needs of the patient. This study demonstrates that the estimation of REE using predictive formulas does not allow accurate calculation of metabolic demands in ventilated intensive care patient. However, predictive equations allow for a rapid assessment of REE and calculation of the amount of energy derived from different substrates.

Accuracy of predictive equations for resting energy expenditure estimation in mechanically ventilated Thai patients

Background

Indirect calorimetry (IC) is the most precise approach for estimating calorie demand in critically ill patients. Despite this, owing to unaffordable devices, it is rarely used in practice. Predictive equations are the alternatives.

Objectives

To assess the accuracy of 14 predictive resting energy expenditure(REE) equations in ventilated Thai patients.

Methods

We compared the accuracy and agreement of 14 equations. The equations included the American College of Chest Physicians(ACCP) equation, Harris-Benedict equation(HBE), 1.2×HBE, 1.5×HBE, Mifflin-St. Jeor(MSJ), Ireton-Jones 1992 and 2002, Penn State 2003(HBE and MSJ) and 2010, Swinamer 1990, Faisy, Brandi 1999, and 25 kcal/kg equation. An equation was ascertained as accurate if the calculated values fell within ±10% of the measured REEs. Spearman correlation coefficient, Bland-Altman method, and intraclass correlation coefficient were used to analysis.

Results

We obtained data from 24 ventilated patients undergoing REE measurement by IC. Fifty percent of them were male with a median age of 64.5 years, a median height of 160 cm, and a median body mass index of 22.95 kg/m2. The predictive precision of all equations was poor, with largely different accuracies from 6.7% to 48.1%. The most reliable equation was Penn State 2010. The ACCP, HBE, MSJ, and Penn State 2003(HBE) tended to underestimate calorie need. Contrastingly, the other equations tended to overestimate REEs. Despite a moderate degree of correlations, the Bland-Altman plots demonstrated clinically unacceptable discrepancies between measured REE and REE calculated by each equation.

Conclusions

In ventilated Thai patients, there were no precise equations for determining REE.

Resting Energy Expenditure in the Critically Ill and Healthy Elderly-A Retrospective Matched Cohort Study

The use of indirect calorimetry to measure resting energy expenditure (mREE) is widely recommended as opposed to calculating REE (cREE) by predictive equations (PE). The aim of this study was to compare mREE with cREE in critically ill, mechanically ventilated patients aged ≥ 75 years and a healthy control group matched by age, gender and body mass index. The primary outcome was the PE accuracy rate of mREE/cREE, derived using Bland Altman plots. Secondary analyses included linear regression analyses for determinants of intraindividual mREE/cREE differences in the critically ill and interindividual mREE differences in the matched healthy cohort. In this retrospective study, 90 critically ill patients (median age 80 years) and 58 matched healthy persons were included. Median mREE was significantly higher in the critically ill (1457 kcal/d) versus the healthy cohort (1351 kcal/d), with low PE accuracy rates (21% to 49%). Independent predictors of mREE/cREE differences in the critically ill were body temperature, heart rate, FiO₂, hematocrit, serum sodium and urea. Body temperature, respiratory rate, and FiO₂ were independent predictors of interindividual mREE differences (critically ill versus healthy control). In conclusion, the commonly used PE in the elderly critically ill are inaccurate. Respiratory, metabolic and energy homeostasis variables may explain intraindividual mREE/cREE as well as interindividual mREE differences.

Local problems need global solutions: The metabolic needs of regenerating organisms

The vast majority of species that belong to the plant or animal kingdom evolved with two main strategies to counter tissue damage-scar formation and regeneration. Whereas scar formation provides a fast and cost-effective repair to exit life-threatening conditions, complete tissue regeneration is time-consuming and requires vast resources to reinstall functionality of affected organs or structures. Local environments in wound healing are widely studied and findings have provided important biomedical applications. Less well understood are organismic physiological parameters and signalling circuits essential to maintain effective tissue repair. Here, we review accumulated evidence that positions the interplay of local and systemic changes in metabolism as essential variables modulating the injury response. We particularly emphasise the role of lipids and lipid-like molecules as significant components long overlooked.

Effect of Combined Protein-Enriched Enteral Nutrition and Early Cycle Ergometry in Mechanically Ventilated Critically Ill Patients—A Pilot Study

Background: Cycle ergometry (CE) is a method of exercise used in clinical practice. Limited data demonstrate its effectiveness in critically ill patients. We aimed to evaluate the combination of CE and a high-protein diet in critically ill patients. Methods: This was an open label pilot trial comparing conventional physiotherapy with enteral nutrition (EN) (control, Group 1), CE with EN (Group 2), and CE with protein-enriched EN (Group 3). The primary outcome was length of ventilation (LOV). Secondary outcomes were intensive care unit (ICU) mortality, length of ICU stay (ICU LOS), length of hospital stay (Hospital LOS), and rate of re-intubation. Results: Per protocol, 41 ICU patients were enrolled. Thirteen patients were randomized to Group 1 (control), fourteen patients to Group 2, and fourteen patients to Group 3 (study groups). We found no statistically significant difference in LOV between the study arms (14.2 ± 9.6 days, 15.8 ± 7.1 days, and 14.9 ± 9.4 days, respectively, p = 0.89). Secondary outcomes did not demonstrate any significant differences between arms. Conclusions: In this pilot trial, CE combined with either standard EN or protein-enriched EN was not associated with better clinical outcomes, as compared to conventional physiotherapy with standard EN. Larger trials are needed in order to further evaluate this combination.

Correlations between First 72 h Hypophosphatemia, Energy Deficit, Length of Ventilation, and Mortality-A Retrospective Cohort Study

INTRODUCTION

Hypophosphatemia may prolong ventilation and induce weaning failure. Some studies have associated hypophosphatemia with increased mortality. Starting or restarting nutrition in a critically ill patient may be associated with refeeding syndrome and hypophosphatemia. The correlation between nutrition, mechanical ventilation, and hypophosphatemia has not yet been fully elucidated.

METHODS

A retrospective cohort study of 825 admissions during two consecutive years was conducted. Using the electronic medical chart, demographic and clinical data were obtained. Hypophosphatemia was defined as a phosphate level below 2.5 mg/dL (0.81 mmol/L) in the first 72 h of ICU admission. Comparisons between baseline characteristics and outcomes and multivariate analysis were performed.

RESULTS

A total of 324 (39.27%) patients had hypophosphatemia during the first 72 h of ICU admission. Patients with hypophosphatemia tended to be younger, with lower APACHE-II, SOFA24, and ΔSOFA scores. They had a longer length of stay and length of ventilation, more prevalent prolonged ventilation, and decreased mortality. Their energy deficit was lower. There was no effect of hypophosphatemia severity on these results. In multivariate analysis, hypophosphatemia was not found to be statistically significant either with respect to mortality or survivor's length of ventilation, but lower average daily energy deficit and SOFA24 were found to be statistically significant with respect to survivor's length of ventilation.

CONCLUSION

Hypophosphatemia had no effect on mortality or length of ventilation. Lower average daily energy deficit is associated with a longer survivor's length of ventilation.

Nutrition Management in Patients With Traumatic Brain Injury: A Narrative Review

Traumatic brain injury (TBI) is a major cause of long-term physical and psychological disability and death. In patients with TBI, undernutrition is associated with an increased mortality rate, more infectious complications, and worse neurologic outcomes. Therefore, timely and effective nutritional therapy is particularly crucial in the management of TBI to improve patients' prognoses. This narrative review summarizes the issues encountered in clinical practice for patients with neurotrauma who receive acute and post-acute in-patient rehabilitation services, and it comprehensively incorporates a wide range of studies, including recent clinical practice guidelines (CPGs), with the aim of better understanding the current evidence for optimal nutritional therapy focused on TBI patients. Recent CPGs were reviewed for 6 topics: 1) hypermetabolism and variation in energy expenditure in patients with TBI, 2) delayed gastric emptying and intolerance to enteral nutrition, 3) decision-making on the route and timing of access in patients with TBI who are unable to maintain volitional intake (enteral nutrition versus parenteral nutrition), 4) decision-making on the enteral formula (standard or immune-modulating formulas), 5) glycemic control, and 6) protein support. We also identified areas that need further research in the future.

Feasibility of critical care ergometry: Exercise data of patients on mechanical ventilation analyzed as nine-panel plots

Nine-panel plots are standard displays of cardiopulmonary exercise data, used in cardiac and pulmonary medicine to investigate the nature of exercise limitation. We explored whether this approach could be used to analyze the data of critically ill patients on mechanical ventilation, capable of exercising actively. Patients followed an incremental exercise protocol using a bedside cycle ergometer. Respiratory gases were analyzed using indirect calorimetry, and blood gases were sampled from arterial catheters. Data of seven patients were combined into nine-panel plots. Systematic analysis clarified the nature of exercise limitation in six cases. Resting metabolic rate was increased in all patients, with a median oxygen uptake ( V˙O2 ) of 5.52 (IQR 4.29-6.31) ml/kg/min. Unloaded cycling increased the V˙O2 by 19.8% to 6.61 (IQR 5.99-7.08) ml/kg/min. Adding load to the ergometer increased the V˙O2 by another 20.0% to reach V˙O2peak at a median of 7.14 (IQR 6.67-10.75) ml/kg/min, corresponding to a median extrinsic workload of 7 W. This was accompanied by increased CO₂ production, respiratory minute volume, heart rate, and oxygen pulse. Three patients increased their V˙O2 to >40% of predicted V˙O2max , two patients passed the anaerobic threshold. Dead space ventilation was 44%, decreasing to 42% and accompanied by lower ventilatory equivalents during exercise. Exercise produced no net change in alveolo-arterial PO₂ difference. We concluded that diagnostic ergometry in mechanically ventilated patients was feasible. Analysis of the data as nine-panel plots provided insight into individual limitations to exercise.

Specific nutritional and metabolic characteristics of COVID‐19 persistent critically ill patients

Background

Little is known about metabolic and nutrition characteristics of patients with coronavirus disease 2019 (COVID‐19) and persistent critical illness. We aimed to compare those characteristics in patients with PCI and COVID‐19 and patients without COVID‐19 infection (non‐CO)—primarily, their energy balance.

Methods

This is a prospective observational study including two consecutive cohorts, defined as needing intubation for >10 days. We collected demographic data, severity scores, nutrition variables, length of stay, and mortality.

Results

Altogether, 104 patients (52 per group) were included (59 ± 14 years old [mean ± SD], 75% men) between July 2019 and May 2020. SAPSII, Nutrition Risk Screening (NRS) score, proportion of obese patients, duration of intubation (18.2 ± 11.7 days), and mortality rates were similar. Patients with COVID‐19 (vs non‐CO) had lower SOFA scores (P = 0.013) and more frequently needed prone position (P < 0.0001) and neuromuscular blockade (P < 0.0001): lengths of ICU (P = 0.03) and hospital stays were shorter (P < 0.0001). Prescribed energy targets were below those of the ICU protocol. The energy balance of patients with COVID‐19 was significantly more negative after day 10. Enteral nutrition (EN) started earlier (P < 0.0001). During the first 10 days, COVID‐19 patients received more lipid (propofol sedation) and less protein. Higher admission C‐reactive protein (P = 0.002) decreased faster (P < 0.001). Whereas intestinal function was characterized by constipation in both groups during the first 10 days, diarrhea was less common in patients with COVID‐19 thereafter.

Conclusion

Compared with non‐CO patients, COVID‐19 patients were not more obese, had lower SOFA scores, and were fed more rapidly with EN, because of a more normal gastrointestinal function possibly due to fewer non–respiratory organ failures: their energy balances were more negative after the first 10 days. Propofol sedation reduced protein delivery.

Do we need different predictive equations for the acute and late phases of critical illness? A prospective observational study with repeated indirect calorimetry measurements

BACKGROUND

Predictive equations (PEs) for estimating resting energy expenditure (REE) that have been developed from acute phase data may not be applicable in the late phase and vice versa. This study aimed to assess whether separate PEs are needed for acute and late phases of critical illness and to develop and validate PE(s) based on the results of this assessment.

METHODS

Using indirect calorimetry, REE was measured at acute (≤5 days; n = 294) and late (≥6 days; n = 180) phases of intensive care unit admission. PEs were developed by multiple linear regression. A multi-fold cross-validation approach was used to validate the PEs. The best PEs were selected based on the highest coefficient of determination (R²), the lowest root mean square error (RMSE) and the lowest standard error of estimate (SEE). Two PEs developed from paired 168-patient data were compared with measured REE using mean absolute percentage difference.

RESULTS

Mean absolute percentage difference between predicted and measured REE was <20%, which is not clinically significant. Thus, a single PE was developed and validated from data of the larger sample size measured in the acute phase. The best PE for REE (kcal/day) was 891.6(Height) + 9.0(Weight) + 39.7(Minute Ventilation)-5.6(Age) - 354, with R² = 0.442, RMSE = 348.3, SEE = 325.6 and mean absolute percentage difference with measured REE was: 15.1 ± 14.2% [acute], 15.0 ± 13.1% [late].

CONCLUSIONS

Separate PEs for acute and late phases may not be necessary. Thus, we have developed and validated a PE from acute phase data and demonstrated that it can provide optimal estimates of REE for patients in both acute and late phases.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03319329.

Estimated versus measured energy expenditure in ventilated surgical-trauma critically Ill patients

BACKGROUND

The American and European guidelines recommend measuring resting energy expenditure (REE) using indirect calorimetry (IC). Predictive equations (PEs) are used to estimate REE, but there is limited evidence for their use in critically ill patients. The aim of this study is to evaluate the degree of agreement and accuracy between IC-REE and ten different PEs in mechanically ventilated surgical-trauma critically ill patients who met their estimated caloric requirement.

METHODS

IC-REE was retrospectively compared to PE-REE by 10 PEs. Degree of agreement between REE-PE and REE-IC was analyzed by the Bland-Altman test (BAt) and the Concordance Correlation Coefficient (CCC). The accuracy was calculated by the percentage of patients whose REE-PE values differ by up to ±10% in relation to REE-IC. All analyses were stratified by gender and BMI (< 25 vs ≥ 25).

RESULTS

104 patients were analyzed and the closest estimate to IC-REE was the modified Harris-Benedict equation (mHB) by the BAt with a mean difference of 49.2 overall, 61.6 for males, 28.5 for females, 67.5 for BMI < 25 and 42.5 for BMI ≥ 25. The overall CCC between the IC-REE and mHB was 0.652; 0.560 for males; 0.496 for females; 0.570 for BMI < 25; and 0.598 for BMI ≥ 25. Modified HB equation was the most accurate with overall accuracy of 44.2%.

CONCLUSIONS

Effectiveness of PEs for estimating REE of mechanically ventilated surgical-trauma critically ill patients is limited. Nonetheless, of all the 10 equations examined, the closest to IC measured REE was the modified HB equation. This article is protected by copyright. All rights reserved.

Associations of measured resting energy expenditure with predictive equations, NUTRIC score, and patient outcomes

Background

Indirect calorimetry is the reference method for measuring resting energy expenditure (REE), but the necessary equipment and technical expertise are not always available. Meanwhile, the NUTrition Risk in the Critically ill (NUTRIC) scale is designed to identify patients who would benefit from nutrition therapy, but no data are available regarding the association of NUTRIC scores with REE. Several predictive formulas are available as alternatives to indirect calorimetry for calculation of energy requirements, but they have not been compared in a homogeneous group of critically ill patients. The purpose of the study is to examine the correlations between energy expenditure and NUTRIC scores or patient outcomes, and to compare measured REE with estimations of energy expenditure.

Methods

In this observational, prospective study, indirect calorimetry was performed on 50 mechanically ventilated patients. Energy expenditure was also estimated with the bodyweight-based, Faisy–Fagon, and Penn-State PSU_m equations.

Results

REE was higher in patients who survived treatment than in those who died, and was positively correlated with length of stay and duration of ventilation. NUTRIC scores did not correlate with REE. The Faisy–Fagon equation overestimated expenditure, whereas PSU_m was unbiased and accurate. Calculations based on 25 kcal/kg bodyweight/day overestimated expenditure, whereas 23 kcal/kg/day produced unbiased estimates with greater accuracy than PSU_m.

Conclusion

REE was positively associated with patient outcomes. Energy expenditure was accurately predicted by calculations of 23 kcal/kg bodyweight/day.

Indirect Calorimetry as an Instrument of Research to Identify the Effect of Hypermetabolism in Critical Patients' Prognosis

Background: Energy expenditure (EE) evaluation in Intensive Care Unit (ICU) patients can be very challenging. Critical illness is characterized by great variability in EE, which is influenced by the disease itself and the effects of treatment. Indirect calorimetry (IC) is currently the gold standard to measure EE in Intensive Care Unit (ICU) patients. However, calorimeters are not widely available, and predictive formulas (PF) are still commonly used, leading to under or overfeeding and deleterious consequences.Important metabolic changes occur and catabolism becomes prominent in critically ill patients.Both hyper and hypometabolism can be observed, but hypermetabolic patients appear to have higher mortality rates compared to metabolically normal patients. This study aimed to assess hypermetabolism incidence and compare clinical outcomes between hypermetabolic and normometabolic patients in ICU.

Methods: A single-center, retrospective, and observational study was conducted in the ICU of the Hospital do Divino Espírito Santo in Ponta Delgada, between August 2018 and February 2021. Only invasively mechanically ventilated patients were included. Resting energy expenditure (REE) was predicted by 25 kcal/kg/day formula to obtain predicted resting energy expenditure (PREE), and REE was measured by IC to obtain measured resting energy expenditure (MREE). According to their metabolic state (PREE/MREE), patients were divided into hypermetabolic (≥1.3) and normometabolic (<1.3). To determine the limits of agreement between PREE and MREE, we performed a Bland-Altman (BA) analysis. Baseline characteristics, severity criteria, nutritional status, and main diagnosis on admission were compared. The primary outcome considered was 30-day mortality. Other outcomes such as the ICU length of stay (LOS), in-hospital LOS, and length of invasive ventilation were also evaluated.

Results: Among the 80 ICU patients included in the final analysis, 67 patients were normometabolic (83.4%). Patients admitted due to pneumonia were more hypermetabolic, 8 (61.5%) vs. 10 (14.9%); p<0.001. Hypermetabolism was found also in patients admitted due to sepsis/septic shock, 7 (53.8%) vs. 16 (23.9%); p=0.029. Hypermetabolic patients had lower body mass index (22.5 [interquartile range (IQR): 21.5-24.9] vs. 27.7 [IQR: 25.0-32.4] kg/m²; p=0.001) and higher MREE (2715.0 [2399.0-3090.0] vs. 1690.0 [1410.0-2190.0] kcal/day; p<0.001). Bland-Altman analysis showed a mean difference of -5.6 ± 744.7 Kcal/day between the PREE and MREE by IC. No statistically significant difference was found between the two groups, neither in 30-day mortality nor in the other outcomes considered.

Conclusions: Hypermetabolism was not seen to present a greater risk of death in mechanically ventilated patients in ICU. Lower BMI, sepsis/septic shock, and pneumonia appear to be associated with a hypermetabolic state.

How Have Nutrition Practices in the ICU Changed in the Last Decade (2011-2020): A Scoping Review

Malnutrition is more prevalent in the critically ill than ambulatory patients due to a variety of factors. Strategies employed in the optimization of nutrition practices rely largely on the review of published literature and guidelines. While the last decade was marked by some landmark large randomized controlled trials taking place and some high-quality systematic reviews, it still has left us with many unanswered questions. The evidence generated by these trials can, to a good extent, extrapolate to the developed countries. However, its implementation in developing and third-world countries needs further elaboration and logistical considerations. With this scoping review, we attempt to provide insights into the landmark developments in the decade 2011-2020. Solutions to employ and implement the results of these developments and ways for their corroboration into a larger population are also discussed.

A Single-Center Prospective Observational Study Comparing Resting Energy Expenditure in Different Phases of Critical Illness: Indirect Calorimetry Versus Predictive Equations

OBJECTIVES

Several predictive equations have been developed for estimation of resting energy expenditure, but no study has been done to compare predictive equations against indirect calorimetry among critically ill patients at different phases of critical illness. This study aimed to determine the degree of agreement and accuracy of predictive equations among ICU patients during acute phase (≤ 5 d), late phase (6-10 d), and chronic phase (≥ 11 d).

DESIGN

This was a single-center prospective observational study that compared resting energy expenditure estimated by 15 commonly used predictive equations against resting energy expenditure measured by indirect calorimetry at different phases. Degree of agreement between resting energy expenditure calculated by predictive equations and resting energy expenditure measured by indirect calorimetry was analyzed using intraclass correlation coefficient and Bland-Altman analyses. Resting energy expenditure values calculated from predictive equations differing by ± 10% from resting energy expenditure measured by indirect calorimetry was used to assess accuracy. A score ranking method was developed to determine the best predictive equations.

SETTING

General Intensive Care Unit, University of Malaya Medical Centre.

PATIENTS

Mechanically ventilated critically ill patients.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Indirect calorimetry was measured thrice during acute, late, and chronic phases among 305, 180, and 91 ICU patients, respectively. There were significant differences (F= 3.447; p = 0.034) in mean resting energy expenditure measured by indirect calorimetry among the three phases. Pairwise comparison showed mean resting energy expenditure measured by indirect calorimetry in late phase (1,878 ± 517 kcal) was significantly higher than during acute phase (1,765 ± 456 kcal) (p = 0.037). The predictive equations with the best agreement and accuracy for acute phase was Swinamer (1990), for late phase was Brandi (1999) and Swinamer (1990), and for chronic phase was Swinamer (1990). None of the resting energy expenditure calculated from predictive equations showed very good agreement or accuracy.

CONCLUSIONS

Predictive equations tend to either over- or underestimate resting energy expenditure at different phases. Predictive equations with "dynamic" variables and respiratory data had better agreement with resting energy expenditure measured by indirect calorimetry compared with predictive equations developed for healthy adults or predictive equations based on "static" variables. Although none of the resting energy expenditure calculated from predictive equations had very good agreement, Swinamer (1990) appears to provide relatively good agreement across three phases and could be used to predict resting energy expenditure when indirect calorimetry is not available.

The centenary of the Harris-Benedict equations: How to assess energy requirements best? Recommendations from the ESPEN expert group

BACKGROUND & AIMS

The year 2019 marked the centenary of the publication of the Harris and Benedict equations for estimation of energy expenditure. In October 2019 a Scientific Symposium was organized by the European Society for Clinical Nutrition and Metabolism (ESPEN) in Vienna, Austria, to celebrate this historical landmark, looking at what is currently known about the estimation and measurement of energy expenditure.

METHODS

Current evidence was discussed during the symposium, including the scientific basis and clinical knowledge, and is summarized here to assist with the estimation and measurement of energy requirements that later translate into energy prescription.

RESULTS

In most clinical settings, the majority of predictive equations have low to moderate performance, with the best generally reaching an accuracy of no more than 70%, and often lead to large errors in estimating the true needs of patients. Generally speaking, the addition of body composition measurements did not add to the accuracy of predictive equations. Indirect calorimetry is the most reliable method to measure energy expenditure and guide energy prescription, but carries inherent limitations, greatly restricting its use in real life clinical practice.

CONCLUSIONS

While the limitations of predictive equations are clear, their use is still the mainstay in clinical practice. It is imperative to recognize specific patient populations for whom a specific equation should be preferred. When available, the use of indirect calorimetry is advised in a variety of clinical settings, aiming to avoid under-as well as overfeeding.

ESPEN guideline on clinical nutrition in hospitalized patients with acute or chronic kidney disease

Acute kidney disease (AKD) - which includes acute kidney injury (AKI) - and chronic kidney disease (CKD) are highly prevalent among hospitalized patients, including those in nephrology and medicine wards, surgical wards, and intensive care units (ICU), and they have important metabolic and nutritional consequences. Moreover, in case kidney replacement therapy (KRT) is started, whatever is the modality used, the possible impact on nutritional profiles, substrate balance, and nutritional treatment processes cannot be neglected. The present guideline is aimed at providing evidence-based recommendations for clinical nutrition in hospitalized patients with AKD and CKD. Due to the significant heterogeneity of this patient population as well as the paucity of high-quality evidence data, the present guideline is to be intended as a basic framework of both evidence and - in most cases - expert opinions, aggregated in a structured consensus process, in order to update the two previous ESPEN Guidelines on Enteral (2006) and Parenteral (2009) Nutrition in Adult Renal Failure. Nutritional care for patients with stable CKD (i.e., controlled protein content diets/low protein diets with or without amino acid/ketoanalogue integration in outpatients up to CKD stages four and five), nutrition in kidney transplantation, and pediatric kidney disease will not be addressed in the present guideline.

Malnutrition Essentials for Neurologists and Neurosurgeons: A Review of the Literature

Malnutrition still causes deaths in the world today and protein energy malnutrition (PEM) is characterized by increased oxidative stress, immune deficiency, and development of various infections. Even today, however, it is an underrecognized and undertreated entity in neurology and neurosurgery. In this article, we therefore seek to review the available literature regarding various factors affecting surgical outcome of children with malnutrition undergoing some neurosurgical interventions including shunt surgery and traumatic brain injury in intensive care unit, in addition to its effects upon oxidative stress status and immunity. Furthermore, we attempt to provide essential knowledge of malnutrition affecting surgical outcome of patients with PEM. Based on available evidence in the published literature, it is concluded that it is a serious public health problem characterized by increased oxidative stress, immune deficiency, and development of various infections.

Proposal of a new equation for estimating resting energy expenditure of acute kidney injury patients on dialysis: a machine learning approach

Background

The objective of this study was to develop a new predictive equation of resting energy expenditure (REE) for acute kidney injury patients (AKI) on dialysis.

Materials and methods

A cross-sectional descriptive study was carried out of 114 AKI patients, consecutively selected, on dialysis and mechanical ventilation, aged between 19 and 95 years. For construction of the predictive model, 80% of cases were randomly separated to training and 20% of unused cases to validation. Several machine learning models were tested in the training data: linear regression with stepwise, rpart, support vector machine with radial kernel, generalised boosting machine and random forest. The models were selected by ten-fold cross-validation and the performances evaluated by the root mean square error.

Results

There were 364 indirect calorimetry measurements in 114 patients, mean age of 60.65 ± 16.9 years and 68.4% were males. The average REE was 2081 ± 645 kcal. REE was positively correlated with C-reactive protein, minute volume (MV), expiratory positive airway pressure, serum urea, body mass index and inversely with age. The principal variables included in the selected model were age, body mass index, use of vasopressors, expiratory positive airway pressure, MV, C-reactive protein, temperature and serum urea. The final r-value in the validation set was 0.69.

Conclusion

We propose a new predictive equation for estimating the REE of AKI patients on dialysis that uses a non-linear approach with better performance than actual models.

Predictive energy equations for spinal muscular atrophy type I children

BACKGROUND

Knowledge on resting energy expenditure (REE) in spinal muscular atrophy type I (SMAI) is still limited. The lack of a population-specific REE equation has led to poor nutritional support and impairment of nutritional status.

OBJECTIVE

To identify the best predictors of measured REE (mREE) among simple bedside parameters, to include these predictors in population-specific equations, and to compare such models with the common predictive equations.

METHODS

Demographic, clinical, anthropometric, and treatment variables were examined as potential predictors of mREE by indirect calorimetry (IC) in 122 SMAI children consecutively enrolled in an ongoing longitudinal observational study. Parameters predicting REE were identified, and prespecified linear regression models adjusted for nusinersen treatment (discrete: 0 = no; 1 = yes) were used to develop predictive equations, separately in spontaneously breathing and mechanically ventilated patients.

RESULTS

In naïve patients, the median (25th, 75th percentile) mREE was 480 (412, 575) compared with 394 (281, 554) kcal/d in spontaneously breathing and mechanically ventilated patients, respectively (P = 0.009).In nusinersen-treated patients, the median (25th, 75th percentile) mREE was 609 (592, 702) compared with 639 (479, 723) kcal/d in spontaneously breathing and mechanically ventilated patients, respectively (P = 0.949).Both in spontaneously breathing and mechanically ventilated patients, the best prediction of REE was obtained from 3 models, all using as predictors: 1 body size related measurement and nusinersen treatment status. Nusinersen treatment was correlated with higher REE both in spontaneously breathing and mechanically ventilated patients. The population-specific equations showed a lower interindividual variability of the bias than the other equation tested, however, they showed a high root mean squared error.

CONCLUSIONS

We demonstrated that ventilatory status, nusinersen treatment, demographic, and anthropometric characteristics determine energy requirements in SMAI. Our SMAI-specific equations include variables available in clinical practice and were generally more accurate than previously published equations. At the individual level, however, IC is strongly recommended for assessing energy requirements. Further research is needed to externally validate these predictive equations.

A novel prediction equation of resting energy expenditure for Japanese septic patients

Estimating nutrient consumption and administering appropriate nutritional therapy is essential for improving clinical outcomes in critically ill patients. Various equations, such as the Harris-Benedict equation, have been developed to estimate the required calories. Previous equations, however, targeted Westerners, whose physical characteristics are likely different from those of Asians. Hence, it is unclear whether these equations can be used for Asian patients. This study focused specifically on sepsis patients admitted to a single Japanese ICU, and aimed to develop novel equations to estimate their total energy expenditure. A total of 95 sepsis patients were included in this study. We measured resting energy expenditure (REE) by using indirect calorimetry, and created equations to calculate basal metabolic rate (BMR) using height, weight and age as variables. REE was predicted by multiplying BMR by the novel equation with the stress factor of 1.4. The prediction error of our novel equations were smaller than those of other conventional equations. We further confirmed the accuracy of our equations and that they were unaffected by patient age and disease severity by using data obtained from another patient group. The current study suggested that these equations might allow accurate estimation of the total energy expenditure and proper management of nutritional therapy in Asian sepsis patients.

Improved ICU mortality prediction based on SOFA scores and gastrointestinal parameters

BACKGROUND

The Sequential Organ Failure Assessment (SOFA) score is commonly used in ICUs around the world, designed to assess the severity of the patient's clinical state based on function/dysfunction of six major organ systems. The goal of this work is to build a computational model to predict mortality based on a series of SOFA scores. In addition, we examined the possibility of improving the prediction by incorporating a new component designed to measure the performance of the gastrointestinal system, added to the other six components.

METHODS

In this retrospective study, we used patients' three latest SOFA scores recorded during an individual ICU stay as input to different machine learning models and ensemble learning models. We added three validated parameters representing gastrointestinal failure. Among others, we used classification models such as Support Vector Machines (SVMs), Neural Networks, Logistic Regression and a penalty function used to increase model robustness in regard to certain extreme cases, which may be found in ICU population. We used the Area under Curve (AUC) performance metric to examine performance.

RESULTS

We found an ensemble model of linear and logistic regression achieves a higher AUC compared related works in past years. After incorporating the gastrointestinal failure score along with the penalty function, our best performing ensemble model resulted in an additional improvement in terms of AUC metrics. We implemented and compared 36 different models that were built using both the information from the SOFA score as well as that of the gastrointestinal system. All compared models have approximately similar and relatively large AUC (between 0.8645 and 0.9146) with the best results are achieved by incorporating the gastrointestinal parameters into the prediction models.

CONCLUSIONS

Our findings indicate that gastrointestinal parameters carry significant information as a mortality predictor in addition to the conventional SOFA score. This information improves the predictive power of machine learning models by extending the SOFA to include information related to gastrointestinal organ system. The described method improves mortality prediction by considering the dynamics of the extended SOFA score. Although tested on a limited data set, the results' stability across different models suggests robustness in real-time use.

Systematic review of factors associated with energy expenditure in the critically ill

BACKGROUND AND AIMS

Indirect calorimetry is the reference standard for energy expenditure measurement. Predictive formulae that replace it are inaccurate. Our aim was to review the patient and clinical factors associated with energy expenditure in critically ill patients.

METHODS

We conducted a systematic review of the literature. Eligible studies were those reporting an evaluation of factors and energy expenditure. Energy expenditure and factor associations with p-values were extracted from each study, and each factor was classified as either significantly, indeterminantly, or not associated with energy expenditure. Regression coefficients were summarized as measures of central tendency and spread. Metanalysis was performed on correlations.

RESULTS

The search strategy yielded 8521 unique articles, 307 underwent full text review, and 103 articles were included. Most studies were in adults. There were 95 factors with 352 evaluations. Minute volume, weight, age, % body surface area burn, sedation, post burn day, and caloric intake were significantly associated with energy expenditure. Heart rate, fraction of inspired oxygen, respiratory rate, respiratory disease diagnosis, positive end expiratory pressure, intensive care unit days, C- reactive protein, and size were not associated with energy expenditure. Multiple factors (n = 37) were identified with an unclear relationship with energy expenditure and require further evaluation.

CONCLUSIONS

An important interval step in the development of accurate formulae for energy expenditure estimation is a better understanding of relationships between patient and clinical factors and energy expenditure. The review highlights the limitations of currently available data, and identifies important factors that are not included in current prediction formulae of the critically ill.

An Exploratory Retrospective Study of Factors Affecting Energy Expenditure in Critically Ill Children

BACKGROUND

Accurate measurement of energy expenditure is not widely available. Patient and clinical factors associated with energy expenditure have been poorly explored, leading to errors in estimation formulae. The objective of this study was to determine clinical factors associated with measured energy expenditure (MEE), expressed in kcal/kg/d, in critically ill children.

METHODS

This was a retrospective study at 2 Canadian pediatric intensive care units (ICUs). Patients were mechanically ventilated children who had 1 or more MEE using indirect calorimetry. Associations between MEE and 28 clinical factors were evaluated in univariate regression and 16 factors in a multivariate regression model accounting for repeated measurements.

RESULTS

Data from 239 patients (279 measurements) were analyzed. Median (Q1, Q3) MEE was 34.8 (26.8, 46.2) kcal/kg/d. MEE was significantly associated with weight, heart rate, diastolic blood pressure, ICU day of indirect calorimetry (P = 0.004), minute ventilation, vasoactive inotropic score (P = 0.004), opioids, chloral hydrate, dexmedetomidine, inhaled salbutamol (P = 0.02), and propofol dose (all P < 0.0001 unless otherwise specified) in the final multivariate regression model.

CONCLUSIONS

This study demonstrated association between MEE (kcal/kg/d) and factors not previously explored in pediatric critical illness. Further evaluation of these factors to confirm associations and more precisely quantify the magnitude of effect is required to support refinement of formulae to estimate energy expenditure.

Standardized nutritional supply versus individual nutritional assessment: Impact on weight changes, complications and functional outcome from neurological early rehabilitation

BACKGROUND & AIMS

Approximately 55% of neurological and neurosurgical early rehabilitation (NNER) patients are in need of enteral nutrition, but long-term nutritional assessment of these critically ill patients is suboptimal. Therefore, this study analyzed the effect of an individual nutritional assessment on weight changes during rehabilitation and impact on complications and functional outcome.

METHODS

170 NNER patients on enteral nutrition were enrolled in the study. According to the initial ward, patients were assigned to receive standardized enteral nutrition (n = 107, control group) or an individual nutritional assessment (n = 63, intervention group). Weight changes, complications, assessment of the functional outcome (Early Rehabilitation Index, Barthel Index, Early Rehabilitation Barthel Index) and the length of stay were recorded and compared between groups using non-parametric tests for non-paired samples (Mann-Whitney U test for metric data or the χ² test for categorical data) or paired samples (Wilcoxon test). In addition, daily energy requirement was calculated and compared with daily intake. Correlation analysis by Spearman was performed to investigate linear relationship between weight changes and the difference of administered and calculated calories in both study groups.

RESULTS

A weight loss was observed in the control group, whereas the weight of the intervention group remained stable over time. The difference between calculated and administered calories correlated with weight changes in the control group. Regarding complications during rehabilitation, control patients showed more frequently impaired diuresis. In addition, control patients were suffering longer from diarrhea than patients of the intervention group. Both groups improved in functional status to a comparable degree. Relationships between these improvements and weight changes or administered calories could not be found.

CONCLUSIONS

Individual nutritional assessment had not an additional affect for the improvement of functional outcome or the prevention of complications. However, weight turned out to be more stable and signs of nutritional incompatibilities are less frequent among patients being treated with an individualized nutritional assessment.

Case of a Hypertensive Crisis in Diffuse Axonal Injury

This case considers underdosing of analgesics as a prime contributor to hypertension in diffuse axonal injury (DAI) patients who are being mechanically ventilated. In the air medical environment, obtunded patients' hemodynamic parameters are the primary tools available in diagnosing complex disorders such as an acute rise in intracranial pressure (ICP) when invasive ICP monitoring is not available. Therefore, differential diagnoses must follow a continuum, from most severe to least, in order to deal with sudden-onset hypertension rapidly. Not until all critical differentials have been eliminated is analgesia considered. Mimicking the signs of ICP, a compensatory rise in the mean arterial pressure (MAP) is displayed in an acute pain response for mechanically ventilated patients. Therefore, poor analgesic coverage should be considered early in DAI patients who are being ventilated, especially when an increased metabolic drive may be occurring, forcing the therapeutic dosing intervals to be increased. This patient was transferred from Europe back to North America via a fixed wing aircraft, a 16-hour transport time.

Indirect calorimetry as point of care testing

Determining energy requirement is a fundamental of nutrition support. Indirect calorimetry (IC) has been long recognized as the gold standard for assessing basal or resting energy expenditure (REE). The measurement of REE is recommended particularly in the situation where adjustment of energy provision is critical. The result of the IC measurement can lead to changes in treatment and since the change can be carried out immediately at the bedside, this may be considered as point-of-care testing. Beyond the nutritional aspects, studies of energy expenditure with IC have brought out more understanding of the metabolic changes during the natural course of diseases or conditions as well as those related to the intervention. The literature in various disease states has shown that changes in energy expenditure may reveal hidden metabolic information that might be translated into clinical information and have the potential of being both prognostic indicators and/or treatment targets.

Indirect calorimetry in critically ill mechanically ventilated patients: Comparison of E-sCOVX with the deltatrac

BACKGROUND & AIMS

Indirect calorimetry is recommended to measure energy expenditure (EE) in critically ill, mechanically ventilated patients. The most validated system, the Deltatrac® (Datex-Ohmeda, Helsinki, Finland) is no longer in production. We tested the agreement of a new breath-by-breath metabolic monitor E-sCOVX® (GE healthcare, Helsinki, Finland), with the Deltatrac. We also compared the performance of the E-sCOVX to commonly used predictive equations.

METHODS

We included mechanically ventilated patients eligible to undergo indirect calorimetry. After a stabilization period, EE was measured simultaneously with the Deltatrac and the E-sCOVX for 2 h. Agreement and precision of the E-sCOVX was tested by determining bias, limits of agreement and agreement rates compared to the Deltatrac. Performance of the E-sCOVX was also compared to four predictive equations: the 25 kcal/kg, Penn State University 2003b, Faisy, and Harris-Benedict equation.

RESULTS

We performed 29 measurements in 16 patients. Mean EE-Deltatrac was 1942 ± 274 kcal/day, and mean EE-E-sCOVX was 2177 ± 319 kcal/day (p < 0.001). E-sCOVX overestimated EE with a bias of 235 ± 149 kcal/day, being 12.1% of EE-Deltatrac. Limits of agreement were -63 to +532 kcal/day. The 10% and 15% agreement rates of EE-E-sCOVX compared to the Deltatrac were 34% and 72% respectively. The bias of E-sCOVX was lower than the bias of the 25 kcal/kg-equation, but higher than bias of the other equations. Agreement rates for E-sCOVX were similar to the equations. The Faisy-equation had the highest 15% agreement rate.

CONCLUSION

The E-sCOVX metabolic monitor is not accurate in estimating EE in critically ill mechanically ventilated patients when compared to the Deltatrac, the present reference method. The E-sCOVX overestimates EE with a bias and precision that are clinically unacceptable.

Predictive equations versus measured energy expenditure by indirect calorimetry: A retrospective validation

BACKGROUND & AIMS

Measuring resting energy expenditure (REE) via indirect calorimetry (IC) in intensive care unit (ICU) patient is the gold standard recommended by guidelines. However technical difficulties hinder its use and predictive equations are largely used instead. We sought to validate commonly used equations using a large cohort of patients.

METHODS

Patients hospitalized from 2003 to 2015 in a 16-bed ICU at a university-affiliated, tertiary care hospital who had IC measurement to assess caloric targets were included. Data was drawn from a computerized system and included REE and other variables required by equations. Measurements were restricted to 5 REE per patient to avoid bias. Equation performance was assessed by comparing means, standard deviations, correlation, concordance and agreement, which was defined as a measurement within 85-115% of measured REE. A total of 8 equations were examined.

RESULTS

A total of 3573 REE measurements in 1440 patients were included. Mean patient age was 58 years and 65% were male. A total of 562 (39%) patients had >2 REE measurements. Standard deviation of REE ranged from 430 to 570 kcal. The Faisy equation had the least mean difference (90 Kcal); Harris-Benedict had the highest correlation (52%) and agreement (50%) and Jolliet the highest concordance (62%). Agreement within 10% of caloric needs was met only in a third of patients.

CONCLUSIONS

Predictive equations have low performance when compared to REE in ICU patients. We therefore suggest that predictive equations cannot wholly replace indirect calorimetry for the accurate estimation of REE in this population.

Development and Validation of a New Cardio-Specific Resting Energy Expenditure Equation for Adults

BACKGROUND

This study tested the accuracy of resting energy expenditure (REE) equations among patients who underwent cardiopulmonary bypass and developed/validated a more accurate cardio-specific equation (CSE).

MATERIALS AND METHODS

Prospective observational cohort of 240 adults (derivation data set, 170 patients; validation data set, 70 patients). REEs were calculated with 6 equations-Penn State 2003a, Penn State 2003b, Ireton-Jones, Swinamer, Faisy, and American College of Chest Physicians-and results were compared with indirect calorimetry (IC). Multivariable linear regression analysis was used to develop the CSE. Agreement between measured and calculated REEs was assessed with Lin's concordance correlation coefficient (LCCC), Bland-Altman plot, and regression analysis.

RESULTS

LCCCs present poor agreement between measured and calculated REEs: 0.24 (95% CI, 0.19-0.29), for the Faisy equation; 0.15 (95% CI, 0.1-0.19), Ireton-Jones; 0.31 (95% CI, 0.25-0.37), Swinamer; 0.17 (95% CI, 0.13-0.21), Penn State 2003a; 0.19 (95% CI, 0.14-0.23), Penn State 2003b; and 0.11 (95% CI, 0.07-0.15), American College of Chest Physicians. Based on the derivation data set, REEs are explained by the following equation: CSE = 616 - 8 × age in years + 13 × weight in kilograms + 450 if on ventilator + 159 × MV in liters + 145 if on inotropes. Based on the validation study results, the LCCC between IC and the CSE was 0.82 (95% CI, 0.73-0.88).

CONCLUSION

The CSE has adequate precision and could be used for REE estimation for patients undergoing cardiopulmonary bypass if IC is unavailable.

Energy and Protein in Critically Ill Patients with AKI: A Prospective, Multicenter Observational Study Using Indirect Calorimetry and Protein Catabolic Rate

The optimal nutritional support in Acute Kidney Injury (AKI) still remains an open issue. The present study was aimed at evaluating the validity of conventional predictive formulas for the calculation of both energy expenditure and protein needs in critically ill patients with AKI. A prospective, multicenter, observational study was conducted on adult patients hospitalized with AKI in three different intensive care units (ICU). Nutrient needs were estimated by different methods: the Guidelines of the European Society of Parenteral and Enteral Nutrition (ESPEN) for both calories and proteins, the Harris-Benedict equation, the Penn-State and Faisy-Fagon equations for energy. Actual energy and protein needs were repeatedly measured by indirect calorimetry (IC) and protein catabolic rate (PCR) until oral nutrition start, hospital discharge or renal function recovery. Forty-two patients with AKI were enrolled, with 130 IC and 123 PCR measurements obtained over 654 days of artificial nutrition. No predictive formula was precise enough, and Bland-Altman plots wide limits of agreement for all equations highlight the potential to under- or overfeed individual patients. Conventional predictive formulas may frequently lead to incorrect energy and protein need estimation. In critically ill patients with AKI an increased risk for under- or overfeeding is likely when nutrient needs are estimated instead of measured.

Resting energy expenditure in critically ill patients: Evaluation methods and clinical applications

Patients on intensive care present systemic, metabolic, and hormonal alterations that may adversely affect their nutritional condition and lead to fast and important depletion of lean mass and malnutrition. Several factors and medical conditions can influence the energy expenditure (EE) of critically ill patients, such as age, gender, surgery, serious infections, medications, ventilation modality, and organ dysfunction. Clinical conditions that can present with EE change include acute kidney injury, a complex disorder commonly seen in critically ill patients with manifestations that can range from minimum elevations in serum creatinine to renal failure requiring dialysis. The nutritional needs of this population are therefore complex, and determining the resting energy expenditure is essential to adjust the nutritional supply and to plan a proper diet, ensuring that energy requirements are met and avoiding complications associated with overfeeding and underfeeding. Several evaluation methods of EE in this population have been described, but all of them have limitations. Such methods include direct calorimetry, doubly labeled water, indirect calorimetry (IC), various predictive equations, and, more recently, the rule of thumb (kcal/kg of body weight). Currently, IC is considered the gold standard.

Optimizing Protein Intake and Nitrogen Balance (OPINiB) in Adult Critically Ill Patients: A Study Protocol for a Randomized Controlled Trial

BACKGROUND

Adequate nutrition of critically ill patients plays a key role in the modulation of metabolic response to stress.

OBJECTIVE

This paper presents the development of a protocol for a randomized controlled trial (RCT) aimed at comparing clinical outcomes of patients in the intensive care unit (ICU) administered with standard and protein-fortified diet. Together with the RCT study protocol, the results of the observational analysis conducted to assess the feasibility of the RCT are presented.

METHODS

An RCT on adult patients admitted to ICU and undergoing mechanical ventilation in the absence of renal or hepatic failure will be conducted. Patients enrolled will be randomized with an allocation rate of 1:1 at standard diet versus protein-fortified diet. The estimated sample size is 19 per arm, for a total of 38 patients to be randomized.

RESULTS

Enrollment began in January 2017. In the feasibility study, 14 patients were enrolled. Protein administration increased significantly (P<.001) over time but was significantly lower compared to that recommended (P<.001). Blood urea nitrogen significantly increased (P<.03) over the period of observation. Such increased catabolism resulted in negative cumulative nitrogen balance (NB) in all patients, and some patients presented with a more negative NB compared to the others.

CONCLUSIONS

Results of the feasibility study clearly confirmed that protein provision in ICU patients is below that recommended and that this results in impaired NB. The emerging of an interindividual variability in NB will be further analyzed in the RCT.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02990065; https://clinicaltrials.gov/ct2/show/NCT02990065 (Archived by WebCite at http://www.webcitation.org/6prsqZdRM).

Energy Expenditure and Protein Requirements After Traumatic Injury

Traumatic injury induces hypermetabolism. The degree of hypermetabolism can be variable, depending on the type of injury, the degree of inflammation, body composition, age, and treatment regimens. To estimate metabolic rate in some types of injury, predictive equations have been published. Some of these equations have been tested in validation studies. For other types of injury, equations do not exist. Some expert panels have recommended measuring in lieu of estimating metabolic rate, though studies have not been performed to determine whether clinical outcome is affected by the method used to determine energy requirements. Traumatically injured patients are usually catabolic, but protein needs after traumatic injury continue to be debated. Some suggest that 1.5 g protein per kg body weight is adequate and that any additional protein is simply oxidized, adding to the nitrogen load to be excreted. Alternately, protein intake >2.0 g/kg body weight increases the absolute rate of body protein synthesis, and achievement of nitrogen balance has been associated with survival. Thus, provision of high-protein feeding to achieve nitrogen balance might be worthwhile, even if that balance is achieved at the cost of additional nitrogen production.

Nutritional Alterations Associated with Neurological and Neurosurgical Diseases

Neurological and neurosurgical diseases lead to complications producing malnutrition increasing pathology and mortality. In order to avoid complications because of malnutrition or overcome deficiencies in nutrients supplements are often used for these subjects. The physiopathological mechanisms of malnutrition, methods of nutritional assessment and the supplemental support are reviewed in this paper based on the assumption that patients need to receive adequate nutrition to promote optimal recovery, placing nutrition as a first line treatment and not an afterthought in the rehabilitation.

Influence of different dialysis modalities in the measurement of resting energy expenditure in patients with acute kidney injury in ICU

BACKGROUND

Currently, the execution of indirect calorimetry, which is considered the gold standard for measuring energy expenditure, is not indicate during dialysis, and it may interfere on nutritional therapy of these patients. This study aimed to evaluate the resting energy expenditure (REE) in patients with severe acute kidney injury treated by different modalities of dialysis and to identify whether dialysis influences on REE.

METHODS

This was a prospective cohort study that evaluated patients admitted in intensive care units with diagnosis of acute kidney injury AKIN-3, mechanically ventilated, and submitted to conventional hemodialysis (CHD), extended hemodialysis (EHD) or high volume peritoneal dialysis (HVPD). Indirect calorimetry was performed at pre dialysis time and during the dialysis procedure. Parameters that could change REE were also evaluated.

RESULTS

One-hundred patients undergoing 290 dialysis sessions were evaluated, with mean age 60.3 ± 17 years, 69% were male and 74% have died. There was no significant difference between REE of predialysis time and during dialysis time (2156 ± 659 kcal vs. 2100 ± 634 kcal, respectively, p = 0.15). No difference was observed in the REE before and during dialysis of different modalities. There were no differences between parameters pre and during dialysis of each modality. There was only a difference in norepinephrine dose, which was higher in pre dialysis time in HVPD and EHD modalities, compared with CHD modality. Moreover, during dialysis time, EHD modality had significantly higher VAD compared to other dialysis modalities.

CONCLUSION

The three evaluated modalities did not change REE. Indirect calorimetry can be performed during dialysis procedures and there was no difference between ventilation parameters, sedatives use, body temperature and VAD in both moments.

Indirect calorimetry in nutritional therapy. A position paper by the ICALIC study group

BACKGROUND & AIMS

This review aims to clarify the use of indirect calorimetry (IC) in nutritional therapy for critically ill and other patient populations. It features a comprehensive overview of the technical concepts, the practical application and current developments of IC.

METHODS

Pubmed-referenced publications were analyzed to generate an overview about the basic knowledge of IC, to describe advantages and disadvantages of the current technology, to clarify technical issues and provide pragmatic solutions for clinical practice and metabolic research. The International Multicentric Study Group for Indirect Calorimetry (ICALIC) has generated this position paper.

RESULTS

IC can be performed in in- and out-patients, including those in the intensive care unit, to measure energy expenditure (EE). Optimal nutritional therapy, defined as energy prescription based on measured EE by IC has been associated with better clinical outcome. Equations based on simple anthropometric measurements to predict EE are inaccurate when applied to individual patients. An ongoing international academic initiative to develop a new indirect calorimeter aims at providing innovative and affordable technical solutions for many of the current limitations of IC.

CONCLUSION

Indirect calorimetry is a tool of paramount importance, necessary to optimize the nutrition therapy of patients with various pathologies and conditions. Recent technical developments allow broader use of IC for in- and out-patients.

Supplemental Parenteral Nutrition Is the Key to Prevent Energy Deficits in Critically Ill Patients

This review emphasizes the role of a timely supplemental parenteral nutrition (PN) for critically ill patients. It contradicts the recommendations of current guidelines to avoid the use of PN, as it is associated with risk. Critical illness results in severe metabolic stress. During the early phase, inflammatory cytokines and mediators induce catabolism to meet the increased body energy demands by endogenous sources. This response is not suppressed by exogenous energy administration, and the early use of PN to reach the energy target leads to overfeeding. On the other hand, early and progressive enteral nutrition (EN) is less likely to cause overfeeding because of variable gastrointestinal tolerance, a factor frequently associated with significant energy deficit. Recent studies demonstrate that adequate feeding is beneficial during and after the intensive care unit (ICU) stay. Supplemental PN allows for timely adequate feeding, if sufficient precautions are taken to avoid overfeeding. Indirect calorimetry can precisely define the adequate energy prescription. Our pragmatic approach is to start early EN to progressively test the gut tolerance and add supplemental PN on day 3 or 4 after ICU admission, only if EN does not meet the measured energy target. We believe that supplemental PN plays a pivotal role in the achievement of adequate feeding in critically ill patients with intolerance to EN and does not cause harm if overfeeding is avoided by careful prescription, ideally based on energy expenditure measured by indirect calorimetry.

Energy expenditure in critically ill patients estimated by population-based equations, indirect calorimetry and CO2-based indirect calorimetry

Background

Indirect calorimetry (IC) is the reference method for measurement of energy expenditure (EE) in mechanically ventilated critically ill patients. When IC is unavailable, EE can be calculated by predictive equations or by VCO₂-based calorimetry. This study compares the bias, quality and accuracy of these methods.

Methods

EE was determined by IC over a 30-min period in patients from a mixed medical/postsurgical intensive care unit and compared to seven predictive equations and to VCO₂-based calorimetry. The bias was described by the mean difference between predicted EE and IC, the quality by the root mean square error (RMSE) of the difference and the accuracy by the number of patients with estimates within 10 % of IC. Errors of VCO₂-based calorimetry due to choice of respiratory quotient (RQ) were determined by a sensitivity analysis, and errors due to fluctuations in ventilation were explored by a qualitative analysis.

Results

In 18 patients (mean age 61 ± 17 years, five women), EE averaged 2347 kcal/day. All predictive equations were accurate in less than 50 % of the patients with an RMSE ≥ 15 %. VCO₂-based calorimetry was accurate in 89 % of patients, significantly better than all predictive equations, and remained better for any choice of RQ within published range (0.76–0.89). Errors due to fluctuations in ventilation are about equal in IC and VCO₂-based calorimetry, and filtering reduced these errors.

Conclusions

This study confirmed the inaccuracy of predictive equations and established VCO₂-based calorimetry as a more accurate alternative. Both IC and VCO₂-based calorimetry are sensitive to fluctuations in respiration.