Resting energy expenditure in women with polycystic ovary syndrome.

STUDY QUESTION: Is resting energy expenditure (REE) altered in women with polycystic ovary syndrome (PCOS)? SUMMARY ANSWER: Women with PCOS have a reduction in REE, when corrected for fat-free mass, independent of PCOS clinical phenotypes and BMI categories. WHAT IS KNOWN ALREADY: Obesity is an important issue in women with PCOS, in terms of frequency and pathophysiological implications. It has been hypothesized that obesity may be favoured by alterations in REE, but the studies have been limited and conflicting. STUDY DESIGN, SIZE, DURATION: This case-control study was a comparison of 266 women with PCOS and 51 healthy controls, recruited in the Verona 3P study from 2010 to 2021. PARTICIPANTS/MATERIALS, SETTING, METHODS: Women with PCOS diagnosed by the Rotterdam criteria, with normal thyroid function and no interfering medications, were referred to the outpatient clinic of a tertiary care centre of endocrinology and metabolism for a measurement of REE. Healthy controls were recruited in the same period and submitted to the same procedure. In all subjects, REE was measured by indirect calorimetry and serum androgens were measured by LC-MS/MS. In women with PCOS, insulin sensitivity was assessed using the hyperinsulinemic-euglycemic clamp. MAIN RESULTS AND THE ROLE OF CHANCE: REE was similar in women with PCOS and controls. However, REE corrected for fat-free mass (REE/FFM) was significantly lower in women with PCOS than in controls (31.8 ± 4.0 vs 35.4 ± 3.9 kcal/kgFFM·day, P < 0.001). REE/FFM did not differ between normal-weight, overweight, or obese women with PCOS, and each of these subgroups showed lower REE/FFM values than controls. Reduced REE/FFM values were found in each phenotype of the syndrome. In multiple regression analysis, REE/FFM was independently associated with age and PCOS status, but not with fat mass. In PCOS women, REE/FFM was independently and directly associated with ovarian follicle number. LIMITATIONS, REASONS FOR CAUTION: Limitations of the study are the cross-sectional design, which limits the causal inference of the results, and the unavailability of precise information about lifestyle factors, which may be potential confounders. Further prospective studies are needed to establish the importance of this phenomenon in contributing to the weight excess of PCOS. WIDER IMPLICATIONS OF THE FINDINGS: A reduction of REE could potentially favour weight gain in women with PCOS and possibly contribute to the altered metabolic profile typical of this condition, even counteracting the therapeutic strategies aimed to reduce excess body fat in these women. Nevertheless, the presence of this abnormality in both obese/overweight and normal-weight patients suggests that other factors must play a role in this phenomenon. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by academic grants to PM from the University of Verona (FUR 2010-2022). All authors declare no conflict of interest. TRIAL REGISTRATION NUMBER: N/A.

Predictive Energy Equations Inaccurately Estimate Metabolic Demands of Older Adult Trauma Patients.

INTRODUCTION: Suboptimal nutrition promotes unfavorable outcomes in trauma patients, particularly among those aged 60 and over. While many institutions employ predictive energy equations to determine patients' energy requirements, mounting evidence shows these equations inaccurately estimate caloric needs. In this pilot randomized controlled trial, we sought to quantify the discrepancy between predictive equations and indirect calorimetry (IC)-the gold standard for determining energy requirements-in the older adult trauma population. METHODS: This is a nested cohort study within a pilot randomized control trial in which 32 older adult trauma patients were randomized 3:1 to receive IC-guided nutrition delivery versus standard of care. IC requirements of patients in the intervention arm were compared to Mifflin St. Jeor (MSJ), Harris-Benedict (HB), and the American Society for Parenteral and Enteral Nutrition-Society of Critical Care Medicine (ASPEN-SCCM) predictive energy equations. RESULTS: Twenty patients underwent IC to assess measured resting energy expenditure (mREE), yielding a mean (standard deviation) mREE of 23.1 ± 4.8 kcal/kg/d. MSJ and HB gave mean predictive resting energy expenditures of 17.5 ± 2.0 and 18.5 ± 2.0 kcal/kg/d in these patients, demonstrating that IC-derived values were 32.1% and 25.0% higher, respectively. When patients were stratified by body mass index (BMI), MSJ, and HB more severely underestimated caloric requirements in individuals with BMI <30 versus BMI 30-50. While the mean mREE fell within the mean predictive resting energy expenditure range prescribed by ASPEN-SCCM equations (21.4 ± 4.1 to 26.2 ± 4.3 kcal/kg/d), individuals' IC-derived values fell within their personal range in 8 of 20 cases. CONCLUSIONS: The MSJ and HB predictive energy equations consistently and significantly underpredict metabolic demands of older adult trauma patients compared to IC and perform worse in lower BMI individuals. ASPEN-SCCM equations frequently overpredict or underpredict resting energy expenditure. While these findings should be confirmed in a larger randomized control trial, this study suggests that institutions should prioritize IC to accurately identify the metabolic demands of older trauma patients.

Weight History Correlates of Resting Energy Expenditure in Women With Bulimia Nervosa.

OBJECTIVE: Among those with bulimia nervosa, weight suppression has been associated with illness severity and treatment prognosis. Although significant weight loss is known to reduce metabolic rate, the relation between weight suppression and resting energy expenditure (REE) in bulimia nervosa has not been examined. This study tested the hypothesis of an inverse relation between weight suppression and REE in a sample of women with bulimia nervosa (N = 84). METHODS: In primary analyses, linear regressions were conducted between weight suppression and REE, corrected for fat-free mass. In follow-up, exploratory analyses, stepwise linear regressions were conducted to explore the main and interaction effects of weight history and weight suppression on REE. RESULTS: Neither traditional (TWS) nor developmental weight suppression (DWS) correlated with REE. Results from exploratory analyses, however, revealed a medium-to-large inverse relation between several weight history variables and REE (highest past weight, sr2 = 0.05; lowest postmorbid weight, sr2 = 0.07; current weight, sr2 = 0.05). Additionally, DWS interacted with current (sr2 = 0.08) and highest premorbid (sr2 = 0.05) z-BMI to influence REE with a medium-to-large effect. For individuals low in current and premorbid z-BMIs, higher DWS associated with lower REE levels. However, for individuals at higher premorbid z-BMIs, higher DWS unexpectedly associated with greater REE levels. DISCUSSION: In this sample of women with bulimia nervosa, reduced REE associated with higher weights across all timepoints. If the interaction effect between DWS and z-BMI history persists in future studies, this may indicate unique challenges faced by individuals low in z-BMI and high in DWS related to weight gain and normalization of eating.

Clarifying main nutritional aspects and resting energy expenditure in children with Smith-Magenis syndrome.

Our study aims to define resting energy expenditure (REE) and describe the main nutritional patterns in a single-center cohort of children with Smith-Magenis syndrome (SMS). REE was calculated using indirect calorimetry. Patients' metabolic status was assessed by comparing measured REE (mREE) with predictive REE (pREE). Patients also underwent multidisciplinary evaluation, anthropometric measurements and an assessment of average energy intake, using a 3-day food diary, which was reviewed by a specialized dietitian. Twenty-four patients (13 M) were included, the median age was 9 years (IC 95%, 6-14 years), 84% had 17p11.2 deletion, and 16% had RAI1 variants. REE was not reduced in SMS pediatric patients, and the mREE did not differ from the pREE. In patients with RAI1 variants (16%, n = 3/24), obesity was more prevalent than those with 17p11.2 deletion (100% vs 38%). Lower proteins intake and higher total energy intake were reported in obese and overweight patients, compared to healthy weight children. No significant difference was found between males and females in energy or macronutrient intake. CONCLUSIONS: In SMS, the onset of obesity is not explained by REE abnormalities, but dietary factors seem to be crucial. Greater concern should be addressed to patients with RAI1 variants. A better understanding of the molecular mechanisms causing obesity in SMS patients could set the basis for possible future targeted therapies. WHAT IS KNOWN: • More than 90% of SMS patients after the age of 10 are overweight or obese. WHAT IS NEW: • Onset of overweight and obesity in SMS pediatric patients is not explained by abnormal resting energy expenditure. • The development of syndrome-specific dietary guidelines for SMS patients should be of utmost relevance and are highly needed.

Resting energy expenditure, body composition, and metabolic alterations in breast cancer survivors vs. healthy controls: a cross-sectional study.

PURPOSE: This study aimed to investigate the difference in absolute and fat free mass (FFM)-adjusted resting energy expenditure (mREE) and body composition (body weight, fat mass (FM), FFM) between breast cancer survivors (BCs) and controls. Correlations with body composition were analyzed. We examined if survival year, or being metabolically dysfunctional were predictive variables. METHODS: A cross-sectional analysis was conducted on 32 BCs ≤5 years post treatment and 36 healthy controls. Indirect calorimetry measured absolute mREE. Body composition was determined by BOD POD. FFM-adjusted mREE was calculated (mREE/FFM). The Harris-Benedict equation was used to predict REE and determine hyper-/hypometabolism (mREE/pREE). The database of the multidisciplinary breast clinic of the University Hospital of Antwerp was consulted for survival year and metabolic dysfunctions. RESULTS: BCs have similar absolute mREE and greater FFM-adjusted mREE compared to controls. Absolute mREE and body composition between BCs differed; adjusted mREE was similar. FFM correlated significantly with absolute mREE in BCs. A significant interaction term was found between survival year and FM for absolute mREE. CONCLUSION: BCs have similar absolute mREE, but higher FFM-adjusted mREE. Differences in body composition between BCs are suggested to cause inter-individual variations. We suggest that increased FFM-adjusted mREE is caused by metabolic stress related to cancer/treatment. Accurate measurement of REE and body composition is advised when adapting nutritional strategies, especially in patients at risk for developing metabolic dysfunctions.

Resting energy expenditure in patients with liver cirrhosis: Indirect calorimetry vs. predictive equations.

BACKGROUND AND OBJECTIVES: The objective of our study was to explore the accuracy of previously published prediction equations in predicting resting energy expenditure (REE) in patients with liver cirrhosis (LC). We also aimed to develop a novel equation to estimate REE for Chinese patients with LC. METHODS AND STUDY DESIGN: In 90 patients with LC, the agreement between REE measured by Indirect calorimetry (IC) and predictive equations was quantified using paired T-test and visualized using a Bland-Altman Plot. Pearson correlation coefficient (R) was used to measure a linear correlation between REE measured by IC and different predictive equations. Stepwise multiple regression analysis was used to create a new REE equation. RESULTS: The estimated REEs of previous equations were underestimated against REE measured by IC (1610 ± 334 kcal). Lean body mass (LBM) was positively correlated with REE measured by IC (r = 0.723, p < 0.01). The newly derived estimation equation for REE (kcal) was 1274.3 - 209.0 * sex - 5.73 * age + 3.69 * waist circumference + 22.89 * LBM. The newly derived estimation equation was found to have a Pearson-r value of 0.765 compared with REE measured by IC. CONCLUSIONS: REE in liver cirrhosis was underestimated by using predictive equations. The new predictive equation developed by using age, sex, waist circumference, and LBM may help estimate REE in Chinese patients with LC accurately and easily.

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

The basis of medical nutrition therapy for patients with LC-FAODs is to provide adequate energy to maintain anabolism and prevent catabolism. In practice, energy needs are estimated based on formulas derived from normal populations but it is unknown if energy expenditure among patients with LC-FAODs is similar to the normal population. We measured resting energy expenditure (REE), total energy expenditure (TEE) and body composition in 31 subjects with LC-FAODs ranging in age from 7 to 64 years. Measured REE was lower than estimated REE by various prediction equations and measured TEE was lower than estimated TEE. It is possible that the lower energy expenditure based on prediction formulas from the normal population is due to differences in body composition; we compared body composition to normal data from the 2017-18 National Health and Nutrition Examination Survey (NHANES). Fat free mass and fat mass was similar between subjects with an LC-FAOD and NHANES normal data suggesting no difference in body composition. We then compared measured REE and TEE to normal published data from the Dietary Reference Intakes (DRI). Measured REE and TEE were significantly lower among subjects with LC-FAODs compared to normal published energy expenditure data. Our results suggests patients with a LC-FAOD exhibit a lower REE and therefore actually have a slightly lower TEE than estimated. Current prediction equations may overestimate energy expenditure of patients with a LC-FAOD.

Impact of methods for data selection on the day-to-day reproducibility of resting metabolic rate assessed with four different metabolic carts.

BACKGROUND AND AIMS: Accomplishing a high day-to-day reproducibility is important to detect changes in resting metabolic rate (RMR) and respiratory exchange ratio (RER) that may be produced after an intervention or for monitoring patients' metabolism over time. We aimed to analyze: (i) the influence of different methods for selecting indirect calorimetry data on RMR and RER assessments; and, (ii) whether these methods influence RMR and RER day-to-day reproducibility. METHODS AND RESULTS: Twenty-eight young adults accomplished 4 consecutive RMR assessments (30-min each), using the Q-NRG (Cosmed, Rome, Italy), the Vyntus CPX (Jaeger-CareFusion, Höchberg, Germany), the Omnical (Maastricht Instruments, Maastricht, The Netherlands), and the Ultima CardiO2 (Medgraphics Corporation, St. Paul, Minnesota, USA) carts, on 2 consecutive mornings. Three types of methods were used: (i) short (periods of 5 consecutive minutes; 6-10, 11-15, 16-20, 21-25, and 26-30 min) and long time intervals (TI) methods (6-25 and 6-30 min); (ii) steady state (SSt methods); and, (iii) methods filtering the data by thresholding from the mean RMR (filtering methods). RMR and RER were similar when using different methods (except RMR for the Vyntus and RER for the Q-NRG). Conversely, using different methods impacted RMR (all P ≤ 0.037) and/or RER (P ≤ 0.009) day-to-day reproducibility in all carts. The 6-25 min and the 6-30 min long TI methods yielded more reproducible measurements for all metabolic carts. CONCLUSION: The 6-25 min and 6-30 min should be the preferred methods for selecting data, as they result in the highest day-to-day reproducibility of RMR and RER assessments.

Validation of predictive equations for resting energy expenditure in children and adolescents with different body mass indexes.

BACKGROUND: Accurate estimation of resting energy expenditure (REE) in children and adolescents is important to establish estimated energy requirements. The objective of this study was to assess the validity of existing equations in literature and a newly developed equation in estimating REE in children and adolescents. METHODS: 275 participants (148 boys, 127 girls) aged 6-18 years included in the study were classified as normal-weighted, overweight, obese based on BMI z-scores for age according to WHO-2007 growth curves for 5-19 years of age. REEs were measured using an indirect calorimeter, with various equations, and a newly established equation [REE = 505.412+(24.383*FFM);Adjusted R2 = 0.649] were compared with REE measured using Bland-Altman and further validation parameters. RESULTS: When the predicted REEs were compared with the measured REEs, the highest prediction accuracy was achieved using the new Eq. (64.8%) and IOM (63.8%) for normal-weight participants, Müller FFM and new Eq. (59.6%) for overweight participants and Lazzer (44.9%) for obese participants. In normal and overweight participants, lowest root mean squared error (RMSE) values were acquired from Schmelzle's equation (respectively 136.2;159.9 kcal/d), and the highest values were found in Kim's Eq. (315.2; 295.2 kcal/d respectively). RMSE value of the new equation was 174.7 kcal/d for normal-weight children and adolescents, and 201.9 kcal/d for overweight ones. In obese participants, the lowest RMSE value was obtained from Schmelzle's Eq. (305.4 kcal/d) and the new Eq. (317.4 kcal/d), while the highest value was obtained from IOM Eq. (439.9 kcal/d). RMSE was higher in obese groups compared to the other BMI groups. CONCLUSION: Indirect-calorimeter is the most suitable method for REE measurement in especially obese children and adolescents. The new equation and Schmelzle's equation appear to be most accurate equations for normal and overweight children and adolescents.

Does diet and activity lead to difference in resting energy expenditure in obese women?

BACKGROUND: Obesity is considered as a risk factor for metabolic and chronic diseases. Reduction in resting energy expenditure (REE) may increase risk of obesity. Our study was carried out to investigate dietary, biochemical, anthropometric and body composition parameters and physical activity in obese women with normal and low resting energy expenditure. METHODS: A total forty nine subjects (women, 30-50 years old) were enrolled and divided into three groups. Anthropometric, body composition parameters, resting energy expenditure, Fasting blood lipid profile, dietary intake and physical activity were measured. RESULTS: Although, fat mass and fat-free mass were significantly increased in obese groups, there was no significant difference in body composition between two obese groups (p-value = 0.10, 0.27). Measured resting energy expenditure was significantly decreased in obese with low REE compare to other groups (p-value < 0.001). There was no significant difference in energy intake and macronutrients between groups. There was a significant difference in T3 between obese subjects with low REE compared to obese group with normal REE (p-value < 0.001). There was no significant difference in lipid profile between two obese groups. Also there was a significant difference in LDL, cholesterol and triacylglycerol between obese subjects with low REE compared to normal weight group. Moreover, there was a significant difference in cholesterol and triacylglycerol between obese subjects with normal REE compared to normal weight group. Our finding showed there was no significant difference in physical activity between three groups. CONCLUSIONS: Dietary intake and physical activity may relate to metabolism and energy expenditure. It is interesting that in some obese people resting energy expenditure was much lower compared to other obese people; however, there was no significant difference in their body composition, age, sex, dietary intake, lipid profile and physical activity. Thus it should investigate the role of other factors involved in different REE in subjects with obesity.

Optimization of VO2 and VCO2 outputs for the calculation of resting metabolic rate using a portable indirect calorimeter.

This study aimed to compare the Cosmed K5 portable indirect calorimeter, using the mixing chamber mode and face mask, with a stationary metabolic cart when measuring the resting metabolic rate (RMR) and to derive fitting equations if discrepancies are observed. Forty-three adults (18-84 years) were assessed for their RMR for two 30-min consecutive and counterbalanced periods using a Cosmed K5 and an Oxycon Pro. Differences among devices were tested using paired sample Student's t-tests, and correlation and agreement were assessed using Pearson's correlation coefficients, intraclass correlation coefficient and Bland-Altman plots. Forward stepwise multiple linear regression models were performed to develop fitting equations for estimating differences among devices when assessing oxygen uptake (VO2 diff , mL·min-1 ) and carbon dioxide production (VCO2 diff , mL·min-1 ). Furthermore, the Oxycon Pro was tested before being confirmed as a reference device. Significant differences between devices were found in most metabolic and ventilatory parameters, including the primary outcomes of VO2 and VCO2 . These differences showed an overestimation of the Cosmed K5 in all metabolic outcomes, except for Fat, when compared to the Oxycon Pro. When derived fitting equations were applied (VO2 diff - 139.210 + 0.786 [weight, kg] + 1.761 [height, cm] - 0.941 [Cosmed K5 VO2 , mL·min-1 ]; VCO2 diff - 86.569 + 0.548 [weight, kg] + 0.915 [height, cm] - 0.728 [Cosmed K5 VCO2 , mL·min-1 ]), differences were minimized, and agreement was maximized. This study provides fitting equations which allow the use of the Cosmed K5 for reasonably optimal RMR determinations.

Accuracy of equations for estimating resting energy expenditure in children and adolescents living with phenylketonuria.

BACKGROUND: Measuring resting energy expenditure (REE) in individuals living with phenylketonuria (PKU) using indirect calorimetry (IC) is unusual in healthcare facilities because it requires specific protocols and expensive equipment. Considering that determining REE is crucial for devising nutritional strategies for the management of PKU, the aim of this study was to identify the predictive equations that provide the best estimates of REE in children and adolescents living with PKU and to propose a predictive equation for determining REE in this population. METHODS: An REE concordance study was conducted with children and adolescents living with PKU. Anthropometric and body composition assessments using bioimpedance and REE assessment using IC were performed. The results were compared to 29 predictive equations. RESULTS: Fifty-four children and adolescents were evaluated. The REE obtained using IC differed from all estimated REE, except Henry's equation for male children (p = 0.058). Only this equation showed good agreement (0.900) with IC. Eight variables were associated with the REE obtained using IC with emphasis on fat-free mass (kg) (r = 0.786), weight (r = 0.775), height (r = 0.759) and blood phenylalanine (r = 0.503). With these variables, three REE equations were suggested, with R2 = 0.660, 0.635 and 0.618, respectively, and the third equation, which involves weight and height, showed adequate sample size for a statistical power of 0.942. CONCLUSION: Most equations, not specific for individuals living with PKU, overestimate the REE of this population. We propose a predictive equation for assessing REE for children and adolescents living with PKU to be used in settings where IC is not available.

Resting energy expenditure based on equation estimation can predict renal outcomes in patients with type 2 diabetes mellitus and biopsy-proven diabetic kidney disease.

AIMS: The aim of this study was to investigate the relationship between resting energy expenditure (REE) based on equation estimation and renal outcomes in patients with diabetes kidney disease (DKD). METHODS: A total of 124 patients were enrolled from a retrospective cohort of Type 2 Diabetes mellitus (T2DM) patients with biopsy-proven DKD. Renal outcome defined as End-Stage Renal Disease (ESRD). To compare the predictive ability of different REE estimation equations on ESRD. Patients' REE was assessed according to the estimating equation with the best predictive power, and then the relationship between REE and ESRD risk was fitted using a restricted cubic spline curve (RCS) plot and REE cutoff values were obtained. Grouping using cutoff values, and ultimately evaluate the relationship between REE and the risk of ESRD using a Multivariate Cox regression model. RESULTS: The strongest predictive validity for renal outcomes was the NDCKD-equation. The patients were divided into the higher-REE group (n = 78) and the lower-REE group (n = 46), based on the cutoff value. During the follow-up, 30 of 124 patients (24.2%) proceeded to ESRD. Multivariate Cox regression models showed that the risk of ESRD in patients with lower REE was 6.08 times increased compared with that in those with higher REE (HR = 6.08; 95% CI, 1.28-28.80, p = 0.023). CONCLUSION: These findings suggested that the lower REE was an independent risk factor for unfavorable renal outcomes in patients with DKD.

Indirect Calorimetry in Spontaneously Breathing, Mechanically Ventilated and Extracorporeally Oxygenated Patients: An Engineering Review.

Indirect calorimetry (IC) is considered the gold standard for measuring resting energy expenditure (REE). This review presents an overview of the different techniques to assess REE with special regard to the use of IC in critically ill patients on extracorporeal membrane oxygenation (ECMO), as well as to the sensors used in commercially available indirect calorimeters. The theoretical and technical aspects of IC in spontaneously breathing subjects and critically ill patients on mechanical ventilation and/or ECMO are covered and a critical review and comparison of the different techniques and sensors is provided. This review also aims to accurately present the physical quantities and mathematical concepts regarding IC to reduce errors and promote consistency in further research. By studying IC on ECMO from an engineering point of view rather than a medical point of view, new problem definitions come into play to further advance these techniques.

Predicted estimates of resting energy expenditure have limited clinical utility in patients with cirrhosis.

BACKGROUND & AIMS: Malnutrition is associated with adverse clinical outcomes in patients with cirrhosis. Accurate assessment of energy requirements is needed to optimize dietary intake. Resting energy expenditure (REE), the major component of total energy expenditure, can be measured using indirect calorimetry (mREE) or estimated using prediction equations (pREE). This study assessed the usefulness of predicted estimates of REE in this patient population. METHODS: Individual mREE data were available for 900 patients with cirrhosis (mean [±1 SD] age 55.7±11.6 years-old; 70% men; 52% south-east Asian) and 282 healthy controls (mean age 36.0±12.8 years-old; 52% men; 18% south-east Asian). Metabolic status was classified using thresholds based on the mean ± 1 SD of the mREE in the healthy controls. Comparisons were made between mREE and pREE estimates obtained using the Harris-Benedict, Mifflin, Schofield and Henry equations. Stepwise regression was used to build 3 new prediction models which included sex, ethnicity, body composition measures, and model for end-stage liver disease scores. RESULTS: The mean mREE was significantly higher in patients than controls when referenced to dry body weight (22.4±3.8 cf. 20.8±2.6 kcal/kg/24 hr; p <0.001); there were no significant sex differences. The mean mREE was significantly higher in Caucasian than Asian patients (23.1±4.4 cf. 21.7±2.9 kcal/kg/24 hr; p <0.001). Overall, 37.1% of Caucasian and 25.3% of Asian patients were classified as hypermetabolic. The differences between mREE and pREE were both statistically and clinically relevant; in the total patient population, pREE estimates ranged from 501 kcal/24 hr less to 548 kcal/24 hr more than the mREE. Newly derived prediction equations provided better estimates of mREE but still had limited clinical utility. CONCLUSIONS: Prediction equations do not provide useful estimates of REE in patients with cirrhosis. REE should be directly measured. LAY SUMMARY: People with cirrhosis are often malnourished and this has a detrimental effect on outcome. Provision of an adequate diet is very important and is best achieved by measuring daily energy requirements and adjusting dietary intake accordingly. Prediction equations, which use information on age, sex, weight, and height can be used to estimate energy requirements; however, the results they provide are not accurate enough for clinical use, particularly as they vary according to sex and ethnicity.

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.

Analysis of Resting Energy Consumption and Its Influencing Factors in Stroke Patients with Severe Neurological Diseases: A Retrospective Clinical Study.

BACKGROUND: This study aimed to observe the changes of resting energy metabolism in patients with severe neurological diseases, and to explore the effects of tracheostomy status, stroke severity, and complications on resting energy expenditure (REE) and respiratory quotient (RQ). METHODS: A retrospective study was conducted in 105 patients with neurological rehabilitation who were hospitalized in the Rehabilitation Department of the Affiliated Jiangning Hospital of Nanjing Medical University from August 2018 to October 2021. REE was measured by Italian Cosmed k4b2 indirectly, and white blood cell count and C-reactive protein (CRP) were collected. RESULTS: Among the 105 patients, there were 18 cases of mild stroke, 45 cases of moderate stroke, and 42 cases of severe stroke. The difference between predicted REE and actual REE among different degrees of stroke patients was statistically significant (p < 0.05); there was no significant difference in RQ values among different degrees of stroke patients (p > 0.05). Hemoglobin, albumin, and body mass index were significantly and positively correlated with predicted REE and actual REE, while CRP was significantly negatively correlated with predicted REE and actual REE. There was no significant difference in predicted REE, actual REE, and RQ between renal insufficiency, type 2 diabetes mellitus, and chronic obstructive pulmonary disease (p > 0.05). The CRP level could affect the REE of stroke patients. CONCLUSION: Metabolic vehicle assay has a certain clinical value in accurately evaluating the metabolic needs and feeding level of patients.

Effects of a 4-month active weight loss phase followed by weight loss maintenance on adaptive thermogenesis in resting energy expenditure in former elite athletes.

PURPOSE: Despite adaptive thermogenesis (AT) being studied as a barrier to weight loss (WL), few studies assessed AT in the resting energy expenditure (REE) compartment after WL maintenance. The aim of this study was twofold: (1) to understand if AT occurs after a moderate WL and if AT persists after a period of WL maintenance; and (2) if AT is associated with changes in body composition, hormones and energy intake (EI). METHODS: Ninety-four participants [mean (SD); BMI, 31.1(4.3)kg/m2; 43.0(9.4)y; 34% female] were randomized to intervention (IG, n = 49) or control groups (CG, n = 45). Subjects underwent a 1-year lifestyle intervention, divided in 4 months of an active WL followed by 8 months of WL maintenance. Fat mass (FM) and fat-free mass (FFM) were measured by dual-energy X-ray absorptiometry and REE by indirect calorimetry. Predicted REE (pREE) was estimated through a model using FM, FFM. EI was measured by the "intake-balance" method. RESULTS: For the IG, the weight and FM losses were - 4.8 (4.9) and - 11.3 (10.8)%, respectively (p < 0.001). A time-group interaction was found between groups for AT. After WL, the IG showed an AT of -85(29) kcal.d-1 (p < 0.001), and remained significant after 1 year [AT = - 72(31)kcal.d-1, p = 0.031]. Participants with higher degrees of restriction were those with an increased energy conservation (R = - 0.325, p = 0.036 and R = - 0.308, p = 0.047, respectively). No associations were found between diet adherence and AT. Following a sub-analysis in the IG, the group with a higher energy conservation showed a lower WL and fat loss and a higher initial EI. CONCLUSION: AT in REE occurred after a moderate WL and remained significant after WL maintenance. More studies are needed to better clarify the mechanisms underlying the large variability observed in AT and providing an accurate methodological approach to avoid overstatements. Future studies on AT should consider not only changes in FM and FFM but also the FFM composition.

Adaptive thermogenesis after moderate weight loss: magnitude and methodological issues.

PURPOSE: The aim of this study was (1) to assess AT through 13 different mathematical approaches and to compare their results; and (2) to understand if AT occurs after moderate WL. METHODS: Ninety-four participants [mean (SD); BMI, 31.1 (4.3) kg/m2; age, 43.0 (9.4) years; 34% females] underwent a 1-year lifestyle intervention (clinicaltrials.gov ID: NCT03031951) and were randomized to intervention (IG, n = 49) or control groups (CG, n = 45), and all measurements were made at baseline and after 4 months. Fat mass (FM) and fat-free mass (FFM) were measured by dual-energy X-ray absorptiometry and REE by indirect calorimetry. AT was assessed through 13 different approaches, varying in how REE was predicted and/or how AT was assessed. RESULTS: IG underwent a mean negative energy balance (EB) of 270 (289) kcal/day, p < 0.001), resulting in a WL of - 4.8 (4.9)% and an FM loss of - 11.3 (10.8)%. Regardless of approach, AT occurred in the IG, ranging from ~ - 65 to ~ - 230 kcal/day and three approaches showed significant AT in the CG. CONCLUSIONS: Regardless of approach, AT occurred after moderate WL in the IG. AT assessment should be standardized and comparisons among studies with different methodologies to assess AT must be avoided.

Resting energy expenditure in Parkinson's disease patients under dopaminergic treatment.

Background: Weight homeostasis is complex in Parkinson's disease (PD) and body weight changes substantially throughout the course of the disease. We designed a case-control study to (i) investigate whether PD is associated with changes in resting energy expenditure (REE), (ii) to assess how accurately REE could be predicted for individuals with PD utilizing the equations constructed for healthy individuals, and (iii) to eventually construct a new equation.Materials & Methods: Measured REE (mREE) was compared between 122 PD patients and 122 gender and body mass index (BMI)-matched controls. The accuracy of estimated REE by 5 common equations (Harris/Benedict-1919, Roza/Shizgal-1984, Mifflin St. Jeor, WHO/FAO and aggregate formula) was investigated in PD using Bland-Altman analysis and reported as the frequency of accurate predictions (±10%). Concordance correlation coefficients (CCC) were also calculated. Then, we regressed a new REE equation - using gender, age, weight, height and Hoehn-Yahr stage - and validated it in an independent sample (N = 100).Results: No significant difference in mREE was recorded between the whole PD sample and healthy controls. However, mREE was increased in patients with BMI ≥ 30 kg/m2 and Hoehn-Yahr stage ≥ 3. Limited accuracy was present in the available REE equations (accurate prediction [±10%] frequency, <60% for all). For the new equation, the proportion of accurate prediction was 67.0% (overestimation, 24.0%) and CCC was 0.77.Conclusion: PD patients are not commonly characterized by an increase in REE. This is limited to patients suffering from obesity and more severe disease. Common REE equations appear to be inaccurate. The new predictive equation proposed in this study provided better REE estimates.