Energy Expenditure In Patients Research Articles

Energy expenditure and effort of patients with stroke during sit to stand: A pilot study.

Sit-to-stand (STS) is a mechanically demanding task. Little is known about the energy expenditure (EE) and the perceived effort of patients with stroke during STS. The objectives of our study were to assess the perceived effort and EE of patients with stroke when moving from STS and to determine whether an association between actual energy expended and patient-perceived effort exists. This descriptive cross-sectional pilot study assessed participants' EE and perceived effort during STS, with a triaxial accelerometer and the modified Borg scale (MBS), respectively. The team screened 428 individuals for potential inclusion, with nine participants (n = 5 female, 55.5%) meeting the criteria for our pilot study. Participants had a mean age of 52.77 (standard deviation [SD] ± 11.33) years, the majority had a haemorrhagic stroke (n = 6, 66.6%) and left hemiplegia (n = 6, 66.6%), and they were assessed 9.11 (SD ± 6.57) days post-stroke. The mean EE during STS was 2.82 (SD ± 1.9) kCal. Most participants (n = 7, 77.77%) perceived STS as more than a 'moderate' effort on the MBS. The correlation coefficient between the metabolic equivalent of task (METs) and MBS was r = 0.34 (p = 0.38). Our study found a fair positive correlation between METs and MBS for patients with stroke during STS. The increased EE shown can be a key point for rehabilitation to lessen the extent of EE during STS. Further research is warranted.

Comparison of pre- and posttransplant energy expenditure in patients undergoing hematopoietic stem cell transplantation and evaluation of associated factors

ObjectivesPatients undergoing hematopoietic stem cell transplantation may present with metabolic alterations that can have an effect on their energy expenditure and nutritional status. This project aimed to compare the pre- and posttransplant energy expenditures of patients undergoing hematopoietic stem cell transplantation as well as related factors. MethodsThis prospective study was conducted at a single center. Patients, undergoing autograft or allograft, were evaluated before transplantation and on the 10th and 17th d posttransplantation. Energy expenditure was measured by indirect calorimetry. Diet intake was assessed by a 24-h dietary recall. Infectious and noninfectious complications were analyzed between days 1 to 10 after transplantation and days 11 to 17 after transplantation. Paired model analyses were carried out to identify the pretransplantation and posttransplantation periods. ResultsTwenty patients were evaluated with a mean age of 45.6 ± 17.2 y; a majority were male sex (65%), and the most frequent diagnoses were chronic myeloid leukemia (25%) and multiple myeloma (25%). Energy expenditure increased by 15% posttransplantation, and the energy requirement per kilogram of weight was 23 kcal/kg at day 10 after transplantation. Throughout the posttransplantation period, 45% of the patients required nutritional therapy. Negative energy and negative protein balance were observed at all analyzed times. Phase angle (P = 0.018), fever (P = 0.014), mucositis grades I to II (P = 0.018), and the total number of infectious and noninfectious events (P = 0.043) were associated with an increase in energy expenditure at day 10 after transplantation. ConclusionsEnergy expenditure increased after transplantation compared with pretransplantation in 50% of patients. Phase angle, fever, grades I to II mucositis, and infectious and noninfectious events were associated with increased energy expenditure at day 10 after transplantation.

Does Accelerometry at the Centre of Mass Accurately Predict the Gait Energy Expenditure in Patients with Hemiparesis?

The aim of this study was to compare energy expenditure (EE) predicted by accelerometery (EEAcc) with indirect calorimetry (EEMETA) in individuals with hemiparesis. Twenty-four participants (12 with stroke and 12 healthy controls) performed a six-minute walk test (6MWT) during which EEMETA was measured using a portable indirect calorimetry system and EEACC was calculated using Bouten's equation (1993) with data from a three-axis accelerometer positioned between L3 and L4. The median EEMETA was 9.85 [8.18;11.89] W·kg-1 in the stroke group and 5.0 [4.56;5.46] W·kg-1 in the control group. The median EEACC was 8.57 [7.86;11.24] W·kg-1 in the control group and 8.2 [7.05;9.56] W·kg-1 in the stroke group. The EEACC and EEMETA were not significantly correlated in either the control (p = 0.8) or the stroke groups (p = 0.06). The Bland-Altman method showed a mean difference of 1.77 ± 3.65 W·kg-1 between the EEACC and EEMETA in the stroke group and -2.08 ± 1.59 W·kg-1 in the controls. The accuracy of the predicted EE, based on the accelerometer and the equations proposed by Bouten et al., was low in individuals with hemiparesis and impaired gait. This combination (sensor and Bouten's equation) is not yet suitable for use as a stand-alone measure in clinical practice for the evaluation of hemiparetic patients.

Relation of parathyroid hormone with malnutrition in peritoneal dialysis patients

Aims: Protein-energy wasting syndrome is a risk factor specific to ESRD is protein-energy wasting (PEW) syndrome. Clinical and experimental studies have suggested that secondary hyperparathyroidism plays a vital role in increasing energy expenditure in patients with ESRD. The geriatric nutritional risk index (GNRI) is used to evaluate nutritional status in various pathological conditions. Considering the effect of parathormone on malnutrition and studies indicating that parathyroid hormone causes weight loss, we aimed to investigate the relationship between malnutrition and parathyroid hormone (PTH) in our patients using GNRI.
 Methods: Forty-nine patients without known malignancy, liver disease, or chronic inflammatory disease who underwent peritoneal dialysis were included in the study. Patient data were recorded from these files. Height and weight were measured. GNRI was calculated by the formula 14.89 × serum albumin (g/dL) + [41.7 × bodyweight/ideal body weight
 Results: Forty-nine patients (29 females, 59.2%) were included in the study. Three (6.1%), seven (14.3%), and seven (14.3%) patients had severe, moderate, and mild malnutrition, respectively. GNRI was positively correlated with albumin, hematocrit, and calcium levels (r=0.757, r=0.355, r=0.423; p

Abnormal lipid metabolism in cancer-associated cachexia and potential therapy strategy.

Cancer-associated cachexia (CAC) is a major characteristic of advanced cancer, associates with almost all types of cancer. Recent studies have found that lipopenia is an important feature of CAC, and it even occurs earlier than sarcopenia. Different types of adipose tissue are all important in the process of CAC. In CAC patients, the catabolism of white adipose tissue (WAT) is increased, leading to an increase in circulating free fatty acids (FFAs), resulting in " lipotoxic". At the same time, WAT also is induced by a variety of mechanisms, browning into brown adipose tissue (BAT). BAT is activated in CAC and greatly increases energy expenditure in patients. In addition, the production of lipid is reduced in CAC, and the cross-talk between adipose tissue and other systems, such as muscle tissue and immune system, also aggravates the progression of CAC. The treatment of CAC is still a vital clinical problem, and the abnormal lipid metabolism in CAC provides a new way for the treatment of CAC. In this article, we will review the mechanism of metabolic abnormalities of adipose tissue in CAC and its role in treatment.

Modified Indirect Calorimetry To Measure Energy Expenditure In Patients Receiving Venoarterial Extracorporeal Membrane Oxygenation

Modified Indirect Calorimetry To Measure Energy Expenditure In Patients Receiving Venoarterial Extracorporeal Membrane Oxygenation

Effects of sevoflurane and propofol on hemodynamics during cardiac surgery: A randomized controlled clinical trial

The anaesthetic support for various types of cardiac surgery such as coronary artery bypass grafting, heart valve repair or replacement is essential for success of a surgery. The planning of anaesthesia depends on the intended surgical procedure. The traditional approach is total intravenous anesthesia with propofol and inhalation with sevoflurane.<br /> <b>Objectives: </b>To identify the advantages and disadvantages of propofol and sevoflurane when cardiac surgery in adults.  <br /> <b>Material and methods: </b>A total of<b> </b>40 patients were assigned randomly into two groups to receive: in Group 1 - propofol and in Group 2 - sevoflurane. The induction to general anesthesia started with intravenous fractional administration of 1-1.5 mg/kg propofol, 5-7 µg/kg fentanyl and 1.5-2 mg/kg ketamine. Pipecuronium bromide 0.07-0.1 mg/kg was used as a myorelaxant in all patients in both groups. The anaesthesia in group P was supported with propofol 4-6 mg/kg/min intravenously by means of a perfusor as anaesthetic. In group 2, sevoflurane at a dose of 1.7-1.9 MAC was used as an anaesthetic. To maintain anaesthesia in both groups, there was a fractional administration of fentanyl at a dose of 100 µg intravenously when the heart rate and blood pressure increase, piperonium bromide in a dose of 2 mg intravenously was used for muscle relaxation.<br /> <b>Results: </b>The mean arterial pressure, oxygen demand, energy expenditure, cardiac index, total peripheral resistance showed statistically significant differences between propofol and sevoflurane groups. Through the correlation analysis, the relationship between cardiac index and oxygen consumption was moderately relevant, as R was 0.4 and P>0.05.<br /> <b>Conclusion</b>: When the use of sevoflurane for anesthesia, the hemodynamic parameters were stable. The oxygen consumption, energy expenditure in patients were significantly lower compared to propofol using the sevoflurane anesthesia.

Comparison of three different measurement methods to determine resting energy expenditure in patients with decompensated hepatitis B cirrhosis

Objective: To compare the differences to determine resting energy expenditure (REE) measured with indirect calorimetry and REE predicted by formula method and body composition analyzer in patients with decompensated hepatitis B cirrhosis, so as to provide theoretical guidance for the implementation of precision nutrition intervention. Methods: Patients with decompensated hepatitis B cirrhosis who were admitted to Henan Provincial People's Hospital from April 2020 to December 2020 were collected. REE was determined by the body composition analyzer and the H-B formula method. Results: were analyzed and compared to REE measured by the metabolic cart. Results A total of 57 cases with liver cirrhosis were included in this study. Among them, 42 were male, aged (47.93 ± 8.62) years, and 15 were female aged (57.20 ± 11.34) years. REE measured value in males was (1 808.14 ± 201.47) kcal/d, compared with the results calculated by the H-B formula method and the measured result of body composition, and the difference was statistically significant (P = 0.002 and 0.003, respectively). REE measured value in females was (1 496.60 ± 131.28) kcal/d, compared with the results calculated by the H-B formula method and the measured result of body composition, and the difference was statistically significant (P = 0.016 and 0.004, respectively). REE measured with the metabolic cart had correlation with age and area of visceral fat in men (P = 0.021) and women (P = 0.037). Conclusion: Metabolic cart use will be more accurate to obtain resting energy expenditure in patients with decompensated hepatitis B cirrhosis. Body composition analyzer and formula method may underestimate REE predictions. Simultaneously, it is suggested that the effect of age on REE in H-B formula should be fully considered for male patients, while the area of visceral fat may have a certain impact on the interpretation of REE in female patients.

Carbon Footprint of Clinical Photon Therapy: Initial Estimates

<h3>Purpose/Objective(s)</h3> There is an increasing concern about rising carbon dioxide (CO2) levels and its hazardous impact on human health and climate change. Radiation oncology uses high energy machines; however, their carbon footprint is not well understood. This study estimates the energy utilization of photon therapy, and estimates corresponding carbon footprint. Additionally, the study evaluates possible ways to offset CO2 with planting new trees. <h3>Materials/Methods</h3> Patients treated between 07/2020 and 06/2021 using a technology company's medical linear accelerator system at one of our satellite locations were evaluated. A technology company data sheet was used to estimate power draw of the system. BeamOn mode was specified as 39 kVA, Ready mode as 15 kVA, On mode as 11 kVA, and Standby mode as 7 kVA; these were converted to kW. This is likely the worst-case power use scenario, with power factor typically 0.75 – 1.0. Patients treated were reviewed for dose, number of fractions, number of fields, and duration of beam during each fraction. Field delivery durations were obtained from the EMR, and kWh power consumption was estimated per fraction and per treatment course. EPA web calculator was used to convert power consumption to tons of CO2, and the number of new trees required to potentially offset it. <h3>Results</h3> There were 176 patients treated for 191 treatment courses. Total of 4,517 fractions were delivered (average 23.6 fractions per treatment course). Total BeamOn time was 710,606 seconds (197.4 hours), average 157 seconds per fraction. Total BeamOn power consumption would be 7,698 kWh, or ∼1.7 kWh per fraction and ∼40 kWh per treatment course. Annual power consumption including standby mode would be ∼81,250 kWh; BeamOn consumption would account for 9.5% of total machine power usage. The corresponding carbon footprint for BeamOn time would be 5.46 metric tonnes of CO2, or 29 kg of CO2 per patient course. Carbon footprint for the annual machine power consumption would be 57.6 tonnes of CO2. Attributed footprint would thus be 57.6 / 191 = 301 kg CO2 per patient treatment course. The carbon offset required for patient BeamOn time would be 90 new trees planted (average 0.5 trees per patient course). The corresponding offset required to operate the medical linear accelerator system for a year would be 952 new trees planted. The attributed carbon offset per treatment course would thus be 5 new trees planted. <h3>Conclusion</h3> Carbon footprint of the technology company's medical linear accelerator system is likely to be ∼30 kg of CO2 equivalent for direct BeamOn treatment course energy used, ∼300 kg of CO2 equivalent per overall patient energy expenditure, and ∼5.5 metric tonnes of CO2 in total to operate per year. The corresponding number of new trees to be planted to offset the power use would be 0.5 new trees, 5 new trees, and 952 new trees respectively. We are working on measuring the actual power draw during various treatment modes, which could be 5-15% lower than the kVA specification, and calculating the actual carbon footprint of clinical radiation therapy for our next study.

Possible association of high-density lipoprotein cholesterol levels with trunk muscle deficits and decrease in energy expenditure in patients with or at risk for COPD: A pilot study.

Chronic obstructive pulmonary disease (COPD) is associated with low muscle mass and function caused by malnutrition and physical inactivity. We aimed to investigate possible associations between serum biomarkers and clinical traits including computed tomography-derived muscle measurements and energy expenditure indices in COPD. Total energy expenditure (TEE) was measured by the doubly labeled water method, while physical activity level (PAL) was calculated as TEE/basal metabolic rate. Cross-sections and densities of pectoralis, rectus abdominis, and erector spinae muscles were measured. Serum biomarkers included adiponectin, insulin-like growth factor-1, and high-density lipoprotein (HDL)- and low-density lipoprotein (LDL)-cholesterol (C). HDL-C levels were significantly correlated with all muscle areas, densities, and TEE. Only LDL-C levels were correlated with PAL. HDL-C level was a potential biomarker for trunk muscle volumes and functions, as well as total energy expenditure in COPD.

Clinical Correlates of Measured and Predicted Resting Energy Expenditure in Patients with Anorexia Nervosa: A Retrospective Cohort Study.

Resting energy expenditure (REE; i.e., the calorie amount required for 24 h during a non-active period) is an important parameter in nutritional rehabilitation of patients with anorexia nervosa (AN). This study determined whether age, body mass index, AN duration/subtype/specific symptoms/clinical severity, cognitive function alterations, and psychiatric comorbidities influenced REE or the difference between the calculated and estimated REE. Patients with AN who were followed at a daycare treatment facility between May 2017 and January 2020 (n = 138) underwent a complete assessment that included the MINI, Eating Disorder Examination Questionnaire, d2 test of attention, body fat composition by bioelectrical impedance analysis (BIA) and REE measurement by indirect calorimetry (REEIC). AN subtype (N = 66 for restrictive subtype and N = 69 for non-restrictive subtype; p = 0.005), free-fat mass (<0.001), and fat mass (<0.001) were associated with REEIC. Age (p < 0.001), height (p = 0.003), and AN duration (N = 46 for <3 years and N = 82 for ≥3 years; p = 0.012) were associated with the difference between estimated REE (using the Schebendach equation) and measured REEIC. Therefore, the Schebendach equation was adjusted differently in the two patients’ subgroups (AN duration ≤ or >3 years). Overall, REE was higher in patients with restrictive than non-restrictive AN. In the absence of BIA measures, REE-estimating equations should take into account AN duration.

Effect of age on resting energy expenditure in patients with cancer

ObjectiveBecause older patients with cancer are at high risk for developing malnutrition, it is critical to understand their energy needs and to feed them appropriately. The aim of this study was to determine whether there are differences in resting energy expenditure between younger and older adults with cancer and in various age groups of older patients. MethodsThis retrospective, observational, and descriptive study from a single center included adult (≥18 to <60 y) and older (≥60 y) outpatients with gastrointestinal tract and head and neck cancers. According to the World Health Organization classification for adults and Pan American Health Organization for older individuals, nutritional status was estimated using body mass index. Nutritional risk screening was used to assess the nutritional risk and Patient-Generated Subjective Global Assessment for those at risk. Resting energy expenditure (REE) was measured by indirect calorimetry coupled to a gas exchange canopy. Bodystat and Quadscan 4000 multifrequency electrical bioimpedance devices were used to assess body composition at four frequencies (5, 50, 100, and 200 kHz). ResultsThe study included 326 patients of whom 197 were older (60.4%), 244 were men (74.8%), 197 had gastric cancer (60.4%), and 129 had head and neck cancer (39.6%). Most patients had advanced cancer (stages III and IV) and had not undergone cancer treatment in the previous 3 mo. Compared with the younger adults, patients ≥60 y had a higher rate of malnutrition (88.4 versus 54.3%; P < 0.001), a higher percentage of fat-free mass deficit (88.3 versus 74.4%; P < 0.001), and higher percentage of fat mass (91.4 versus 58.9% adult; P < 0.001). The REE of older patients (1263.3 [234.1] kcal/d) was lower than that of patients ≥18 to <60 y (1382.5 [210.5] kcal/d; P < 0.001), for women (1055.2 kcal/d for the older adults versus 1214.3 kcal/d for younger adults), and men (1337.9 versus 1433 kcal/d; P = 0.001). The REE comparison categorized by decades has shown that for patients <60 y, an REE greater than those for individuals 60 to 69 y, 70 to 79 y, and ≥80 y (P < 0.001). REE in patients 60 to 69 y was greater than for those ≥80 y (P < 0.001). When compared with the Harris–Benedict formula, the REE intraclass correlation coefficient for all older patients was 0.514 (95% confidence interval [CI], 0.064–0.736); for ages 60 to 69 y it was 0.527 (95% CI, 0.126–0.733), and for ages >70 y, it was 0.466 (95% CI, –0.080 to –0.756). ConclusionMeasured REE in patients with cancer decreases with age. This finding is critical for appropriate caloric provision for older patients with cancer.

Nutritional Status and Other Clinical Variables Are Associated to the Resting Energy Expenditure in Patients With Chronic Kidney Disease: A Validity Study.

BackgroundEstimating energy requirements (ER) is crucial for nutritional attention to chronic kidney disease (CKD) patients. Current guidelines recommend measuring ER with indirect calorimetry (IC) when possible. Due to clinical settings, the use of simple formulas is preferred. Few studies have modeled equations for estimating ER for CKD. Nevertheless, variables of interest such as nutritional status and strength have not been explored in these models. This study aimed to develop and validate a model for estimating REE in patients with CKD stages 3–5, who were not receiving renal replacement therapy (RTT), using clinical variables and comparing it with indirect calorimetry as the gold standard.MethodsIn this study 80 patients with CKD participated. Indirect calorimetry (IC) was performed in all patients. The calorimeter analyzed metabolic measurements every minute for 15 min after autocalibration with barometric pressure, temperature, and humidity. Bioelectrical Impedance Analysis (BIA) was performed. Fat-free mass (FFM) was registered among other bioelectrical components. Handgrip strength (HGS) was evaluated and an average of 3 repetitions was recorded. Nutritional status was assessed with the subjective global assessment (SGA). Patients categorized as B or C were then considered as having malnutrition.ResultsWe analyzed 71 patients and 3 models were generated. Model 1a included FFM; Model 2a included weight; Model 3c included handgrip strength (HGS). All other variables were stepwise, computer-selected with a p < 0.01 significance level; Malnutrition was consistently associated with ER among other clinical variables in all models (p < 0.05). The model that included BIA-FFM had R2 adjusted = 0.46, while the model that included weight (Kg) had an adjusted R2 adjusted = 0.44. The models had moderate concordance, LC = 0.60–0.65 with the gold standard, whereas other energy expenditure estimation equations had LC = 0.36 and 0.55 with indirect calorimetry. Using these previously validated equations as a reference, our models had concordance values ranging from 0.66 to 0.80 with them.ConclusionModels incorporating nutritional status and other clinical variables such as weight, FFM, comorbidities, gender, and age have a moderate agreement with REE. The agreement between our models and others previously validated for the CKD patient is good; however, the agreement between the latter and IC measurements is moderate. The KDOQI lowest recommendation (25 Kcals/kg body weight) considering the 22% difference with respect to the IC for total energy expenditure rather than for REE.

Resting and total energy expenditure of patients with long-chain fatty acid oxidation disorders (LC-FAODs)

Resting and total energy expenditure of patients with long-chain fatty acid oxidation disorders (LC-FAODs)

Assessment of resting energy expenditure in patients with cirrhosis.

BACKGROUNDMalnutrition affects 20% to 50% of patients with cirrhosis. It may be associated with serious complications and has a direct impact on prognosis. Resting energy expenditure (REE) is an important parameter to guide the optimization of therapy and recovery of nutritional status in patients with cirrhosis. However, the REE of patients with cirrhosis is still unclear, casting doubt upon the optimal nutritional management approach. AIMTo identify the best method that predicts the REE of cirrhotic patients, using indirect calorimetry (IC) as the gold standard.METHODSAn observational study was performed on 90 patients with cirrhosis. REE was assessed by IC, bioelectrical impedance analysis (BIA), and predictive formulas, which were compared using Bland-Altman plots and the Student’s t-test.RESULTSREE values measured by IC (1607.72 ± 257.4 kcal) differed significantly from those determined by all other methods (BIA: 1790.48 ± 352.1 kcal; Harris & Benedict equation: 2373.54 ± 254.9 kcal; IOM equation: 1648.95 ± 185.6 kcal; Cunningham equation: 1764.29 ± 246.2 kcal), except the Food and Agriculture Organization of the United Nations, World Health Organization, and United Nations University (FAO/WHO/UNU) (1616.07 ± 214.6 kcal) and McArdle (1611.30 ± 241.8 kcal) equations. We found no significant association when comparing IC and 24-h dietary recall among different Child-Pugh classes of cirrhosis.CONCLUSIONThe IOM and FAO/WHO/UNU equations have the best agreement with the CI. These results indicate a possibility of different tools for the clinical practice on cirrhotic patients.

Validity study of a triaxial accelerometer for measuring energy expenditure in stroke inpatients of a physical medicine and rehabilitation center

ABSTRACT Purpose Establish the validity of a triaxial accelerometer (Dynaport®) for evaluating the energy expenditure of patients with stroke sequelae at a rehabilitation hospital Methods This is a cross-sectional study with 24 stroke inpatients of a rehabilitation hospital. The participants were assessed on energy expenditure by an ergospirometer system and the triaxial accelerometer simultaneously during a walk test. The data collected by both devices were compared by intraclass correlation coefficient (ICC) and Bland-Altman limits of agreement Results An almost perfect agreement (ICC = 0,94) in the energy expenditure measured by the accelerometer compared to the results of the ergospirometer system was found during the exercise test. The Bland-Altman analysis has shown suitable limits of agreement. Post hoc analyses with the maximum volume of oxygen and the total energy expenditure measured by the ergospirometer system evidenced significant correlation with the energy expenditure measurements by the accelerometer Conclusion Our results evidence that the triaxial accelerometer Dynaport® and its built-in software are valid for estimating the energy expenditure of stroke sequelae during a walk exercise.

Current methods for developing predictive energy equations in maintenance dialysis are imprecise

Purpose For individuals receiving maintenance dialysis, estimating accurate resting energy expenditure (REE) is essential for achieving energy balance, and preventing protein-energy wasting. Dialysis-specific, predictive energy equations (PEEs) offer a practical way to calculate REE. Three PEEs have been formulated via similar methods in different demographic samples; the Maintenance Haemodialysis Equation (MHDE REE), Vilar et al. Equation (Vilar REE) and the Fernandes et al. Equation (Cuppari REE). We compared them in a US cohort and assessed precision relative to measured REE (mREE) from indirect calorimetry. Because of expected imprecision at the extremes of the weight distribution, we also assessed the PEEs stratified by body mass index (BMI) subgroups. Methods This analysis comprised of 113 individuals from the Rutgers Nutrition and Kidney Database. Estimated REE (eREE) was calculated for each PEE, and agreement with mREE was set at > 50% of values within the limits of ±10%. Reliability and accuracy were determined using intraclass correlation (ICC) and a Bland Altman plot, which analysed the percentage difference of eREE form mREE. Results Participants were 58.4% male and 81.4% African American. Mean age was 55.8 ± 12.2 years, and the median BMI was 28.9 (IQR = 25.3 − 34.4) kg/m2. The MHDE REE achieved 58.4% of values within ±10% from mREE; Cuppari REE achieved 47.8% and Vilar REE achieved 46.0% agreement. Reliability was good for the MHDE REE (ICC = 0.826) and Cuppari REE (ICC = 0.801), and moderate for the Vilar REE (ICC = 0.642) (p < .001 for all). The equations performed poorly at the lowest and highest BMI categories. Conclusion Dialysis-specific energy equations showed variable accuracy. When categorized by BMI, the equations performed poorly at the extremes, where individuals are most vulnerable. Innovation is needed to understand these variances and correct the imprecision in PEEs for clinical practice. KEY MESSAGES Potentially impacting over millions of patients worldwide, our long-term goal is to understand energy expenditure (EE) across the spectrum of CKD (stages 1–5) in adults and children being treated with dialysis or transplantation, with the intent of providing tools for the health professional that will improve the delivery of quality care. Our research has identified and focussed on disease-specific factors which account for 60% of the variance in predicting EE in patients on MHD, but significant gaps remain. Thus, our central hypotheses are that (1) there are unique disease-specific determinants of EE and (2) prediction of EE for individuals diagnosed with CKD can be vastly improved with a model that combines these factors with more sophisticated approaches.

Association of Serum Adipokines and Resting Energy Expenditure in Patients With Chronic Kidney Disease

Background and AimMetabolic disorders are prevalent in patients with chronic kidney disease (CKD) and may lead to protein energy wasting (PEW). Adipokines improve connections between PEW and energy metabolism. We aimed to determine the relationship between adipokine levels and resting energy expenditure (REE) in patients with CKD.MethodsA total of 208 patients in non-dialyzed CKD stages 3–5 were enrolled in this cross-sectional study. Serum adipokines (leptin, adiponectin, and interleukin 6 (IL-6) were measured using enzyme-linked immunosorbent assay. Patient's REE was measured using indirect calorimetry. Fat mass (FM) and lean tissue mass (LTM) were measured using multiple-frequency bioimpedance analysis. Spearman correlation analyses and multivariate linear regression models were used to assess the association between serum adipokines and REE.ResultsThe mean age was 52.7 ± 14.6 years, and 26.9, 26.4, and 46.7% of our participants had CKD stages 3, 4, and 5, respectively. The median values of serum adiponectin, leptin, and IL-6 were 470.4 (range, 291.1–802.2), 238.1 (range, 187.9–418.4), and 4.0 (range, 2.4–9.5) pg/mL, respectively. The male participants had significantly lower FM% (P = 0.001) and lower leptin levels (P < 0.001) than the female participants. After adjusting for age, diabetes, high-sensitivity C-reactive protein, intact parathyroid hormone, LTM, and FM, multiple linear regression analysis revealed that serum leptin levels were significantly positively associated with REE in men rather than in women (P < 0.05). Serum adiponectin levels were inversely associated with REE in men, but this association disappeared while FM was additionally adjusted. Adiponectin levels in women were not correlated with REE (P > 0.05). IL-6 was not significantly associated with REE in either men or women.ConclusionsA sex-specific relationship between serum adipokines (leptin and adiponectin) and REE was observed in patients with CKD stages 3–5, which was partly confounded by FM.

Poor performance of predictive equations to estimate resting energy expenditure in patients with Crohn's disease.

Studies exploring the accuracy of equations calculating Resting Energy Expenditure (REE) in patients with Crohn's disease are lacking. The aim of this study was to investigate the accuracy of REE predictive equations against indirect calorimetry in Crohn's disease patients. REE was measured using indirect calorimetry (mREE) after an overnight fasting. Fourteen predictive equations, with and without body composition analysis parameters, were compared with mREE using different body weight approaches. Body composition analysis was performed using dual X-ray absorptiometry. 186 Crohn's disease outpatients (102 males) with mean age 41.3±14.1 years and 37.6% with active disease were evaluated. Mean mREE in the total sample was 1734±443 kcal/day. All equations under-predicted REE and showed moderate correlations with mREE (Pearson's r or Spearman's rho 0.600-0.680 for current weight, all p-values<0.001). Accuracy was low for all equations at the individual level (28-42% and 25-40% for current and adjusted body weight, respectively, 19-33% for equations including body composition parameters). At the group level, accuracy showed wide limits of agreement and proportional biases. Accuracy remained low when sample was studied according to disease activity, sex, body mass index and medication use. All predictive equations underestimated REE and showed low accuracy. Indirect calorimetry remains the best method for estimating REE of patients with Crohn's disease.

Methodological Aspects of Indirect Calorimetry in Patients with Sepsis-Possibilities and Limitations.

The aim of the review was to analyse the challenges of using indirect calorimetry in patients with sepsis, including the limitations of this method. A systematic review of the literature was carried out. The analysis concerned the methodology and presentation of research results. In most studies assessing energy expenditure, energy expenditure was expressed in kcal per day (n = 9) and as the mean and standard deviation (n = 7). Most authors provided a detailed measurement protocol, including measurement duration (n = 10) and device calibration information (n = 7). Ten papers provided information on the day of hospitalisation when the measurements were obtained, nine on patient nutrition, and twelve on the criteria for inclusion and exclusion of participants from the study. Small study group sizes and study at a single centre were among the most cited limitations. Studies assessing energy expenditure in patients with sepsis by indirect calorimetry differ in the methodology and presentation of results, and their collective analysis is difficult. A meta-analysis of the results could enable multi-site and large patient evaluation. Standardisation of protocols and presentation of all collected data would enable their meta-analysis, which would help to achieve greater knowledge about metabolism in sepsis.