Search Results (292)

Background/Objectives: Resting energy expenditure (REE) rises during critical illness, but its determinants and prognostic relevance remain incompletely characterized. Identifying a circulating signal that tracks REE could provide a bedside surrogate for metabolic demand where indirect calorimetry is unavailable. This prospective pilot study described longitudinal trajectories of indirect calorimetry-measured REE, Sequential Organ Failure Assessment (SOFA) score, serum cortisol and insulin-like growth factor-1 (IGF-1) over two weeks in the intensive care unit (ICU), examined whether the REE trajectory was attenuated by adjustment for these variables, and generated preliminary effect-size and variance estimates for mortality. Methods: This single-center pilot study enrolled 39 critically ill adults at Evangelismos General Hospital (Athens, Greece); sample size was pragmatic, not based on an a priori power calculation. REE (Q-NRG metabolic monitor), cortisol and IGF-1 were measured at admission and days 5–7, 10–11 and 13–14, alongside SOFA. Trajectories were modeled with linear mixed-effects models using all available repeated measures. Confounding was assessed by adding SOFA, cortisol and IGF-1 as covariates and evaluating attenuation of the time effect; no formal mediation analysis was performed. Causes of missing data were quantified and a completers-only sensitivity analysis was undertaken. Mortality was analyzed by Cox regression with ICU length of stay as the time variable. Estimation was emphasized throughout; point estimates and 95% confidence intervals (CIs) are reported in preference to significance testing. Results: Mean age was 54.6 ± 18.1 years; 69.2% were male; median admission SOFA was 6 (IQR 3–9). ICU and 28-day mortality were 20.5% (8/39) and 10.3% (4/39). REE/kg rose from 25.3 ± 3.7 to a peak of 27.2 ± 4.2 kcal/kg/day by days 10–11 (likelihood-ratio χ² = 17.2, p = 0.0006). Attrition was driven predominantly by discharge alive (18 of 23 patients missing at days 13–14) rather than death (n = 2), and the trajectory was preserved in a completers-only sensitivity analysis (χ² = 9.13, p = 0.028). Cortisol declined (21.1 to 13.4 μg/dL) and IGF-1 rose (80.0 to 105.4 ng/mL); SOFA was essentially unchanged. REE did not correlate with SOFA, cortisol or IGF-1 at any time-point, and the time effect was not attenuated by adjustment for them. Admission REE was not associated with ICU mortality (HR 1.00, 95% CI 1.00–1.00). Higher admission REE was associated with a longer ICU stay, and this persisted after adjustment for body mass index (p = 0.026) and fat-free mass (p = 0.001). Age (HR 1.04, 95% CI 1.00–1.09) and admission SOFA (HR 1.18, 95% CI 0.98–1.44) were the covariates most associated with ICU mortality. Conclusions: REE rose progressively over the first 10–11 days of critical illness. Its trajectory was not attenuated by adjustment for SOFA, cortisol or IGF-1, which is compatible with—but does not establish—independence from the adrenal and somatotropic markers measured here. Neither REE nor these hormones were associated with mortality; age and disease severity remained the dominant prognostic factors, supporting a larger confirmatory study. Full article

Background: Anorexia Nervosa (AN) triggers profound metabolic and psychological adaptations during adolescence. This study investigated the relationships between resting energy expenditure (REE), body composition, physical activity (PA), and specific psychometric phenotypes in adolescent girls with AN compared to healthy, normal-weight (NW) peers. Methods: Sixteen adolescent girls with severe AN (16.1 ± 1.2 year) and 16 age-matched NW controls (15.6 ± 1.5 year) underwent clinical evaluations: anthropometry, bioelectrical impedance analysis for fat-free mass (FFM) and fat mass (FM), indirect calorimetry for REE, the short-form International Physical Activity Questionnaire (IPAQ), and the Eating Disorder Inventory-3 (EDI-3). Results: Girls with AN exhibited significantly lower BMI (−20.3%, ES: 1.94, large), FFM (−18.3%, ES: 1.92, large), and FM (−25.7%, ES: 0.79, medium) than controls (p < 0.003). Absolute REE was drastically lower (−40.4%, ES: 3.53, large, p < 0.001). This hypometabolic state persisted after adjusting REE for body weight (−34.9%) or FFM (−32.5%, p < 0.001), consistent with adaptive thermogenesis. The AN group displayed resting hypotension and 79.0% (ES: 1.84, large, p < 0.001) lower total PA energy expenditure due to a lack of structured moderate-to-vigorous exercise; however, walking expenditure did not differ. Psychometrically, the AN cohort showed significantly higher (p < 0.001) values for drive for thinness (+316.9%, ES: 3.16, large), body dissatisfaction (+232.3%, ES: 2.30, large), and severe general psychological maladjustment, including higher interoceptive deficits (+148.2%, ES: 1.26, large). Conclusions: Adolescents with AN exhibit profound metabolic suppression via adaptive thermogenesis, together with an apparent dissociation between walking-related activity and hypotension. Since cognitive distortions and distress vary independently of anthropometric severity, clinical recovery must extend beyond nutritional rehabilitation; targeted psychotherapy may therefore be necessary to address persistent psychological maladjustment. Full article

Introduction: Survival at high altitudes requires efficient energy management. Although hypobaric hypoxia alters thermodynamic efficiency, the independent impact of altitude versus demographic factors on basal and exertional caloric costs remains uncertain. We evaluated these variables in chronic residents across four Peruvian altitudes. Methodology: A cross-sectional study was conducted involving 141 healthy adults (aged 18–38 years) residing in Lima (154 m), Arequipa (2335 m), Puno (3827 m), and La Rinconada (5100 m). Resting energy expenditure (REE) and physical activity energy expenditure (PAEE) were estimated using continuous photoplethysmography; PAEE was assessed following the 6-min walk test (6MWT). Hemodynamic parameters, oxygen saturation (SpO₂), and hemoglobin (Hb) levels were evaluated. An analysis of covariance (ANCOVA) was employed to adjust metabolic variations for age, sex, and body mass index (BMI). Results: Unadjusted data demonstrated a progressive increase in REE and PAEE proportional to altitude. However, the ANCOVA revealed that the independent effect of the city of residence was no longer statistically significant after adjusting for anthropometric and demographic covariates. Physiologically, the SpO₂ deficit imposed a high metabolic demand (an increase of approximately 1.29 kcal in REE for every 1% drop in SpO₂). Hb concentrations above 18 g/dL were associated with an exponential increase in caloric cost driven by blood hyperviscosity. A positive correlation was identified between Hb levels and energy expenditure (EE), which proved to be statistically stronger in the female cohort. Under extreme hypoxia conditions (5100 m), men exhibited a significantly higher PAEE (50.60 ± 10.17 kcal vs. 40.78 ± 5.21 kcal). Despite the increased biological effort, mechanical performance in the 6MWT remained constant across cities. Conclusions: There is no independent relationship between REE and the altitude of residence. The initial unadjusted relationship between altitude and EE was negated by covariates, particularly body mass index (BMI). The preservation of functional capacity at the expense of the energy economy underscores the profound physiological burden of Andean acclimatization. Full article

Background/Objectives: Total or partial pancreatectomy is associated with significant metabolic stress and high risk of postoperative malnutrition. Accurate estimation of resting energy expenditure (REE) is essential, as predictive equations may not reflect true energy needs. Methods: A prospective study among patients undergoing total or partial pancreatectomy for pancreatic tumors was conducted. REE was measured by indirect calorimetry (mREE) and compared with the Harris–Benedict and Schofield equations and the weight-based approaches (25 and 30 kcal/kg). Agreement was assessed using linear regression and Bland–Altman analysis; accuracy indices included ±10%, Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE). Results: In 26 patients (mean age, 66.7 ± 8.7 years; 53.8% male) undergoing pancreatic resection (17 pancreaticoduodenectomies, 8 distal pancreatectomies, 1 total pancreatectomy), 60% were at preoperative malnutrition risk. The median measured REE was 1484 kcal/day, rising to 1706 kcal/day after activity adjustment (×1.15) within 14 postoperative days. At 3–6 months postoperatively, patients demonstrated significant declines in nutritional status with a median body weight reduction of −7.3% and a decrease in BMI of −2 kg/m². The 30 kcal/kg method showed the lowest accuracy (MAPE 23.2%, RMSE 416 kcal/day) and overestimated energy needs. Harris–Benedict underestimated mREE in 61.5% of cases, while the 25 kcal/kg approach showed more balanced performance. Conclusions: Postoperative energy expenditure in patients undergoing pancreatic resection appeared elevated relative to predictive equations. Predictive equations lack reliability, favoring indirect calorimetry for precision. Sustained weight loss underscores the need for prolonged nutritional surveillance. Full article

New Zealand working farm dogs can struggle to maintain their body weight and condition during periods of high workload, despite substantial energy intake, highlighting the need to optimise energy balance. One potential strategy for reducing overall energy demands is to reduce energy expenditure for thermoregulation, particularly during colder conditions, which may improve both recovery and energy utilisation. This study investigated whether wearing coats influenced the sleep behaviour, activity, and apparent nutrient digestibility of outdoor-kennelled dogs. Eight adult working-breed dogs (n = 8) were studied using a randomised cross-over design, in which dogs wore a coat or no coat during overnight periods (15:00–09:00 h). Behaviour was monitored using triaxial accelerometers and classified using a validated machine learning model, while apparent nutrient digestibility was determined from pooled faecal samples. Dogs spent more time sleeping when wearing a coat compared to no coat (48.1% vs. 40.0%, p = 0.008), with the effect being most evident during cooler evening hours. Time spent resting and being active was reduced when coats were worn (p < 0.05), while overall activity did not differ (p = 0.856). No differences were observed in apparent digestibility of energy or nutrients (p > 0.05), although protein digestibility tended to be higher when coats were worn (p = 0.079). These findings suggest that coats can improve sleep behaviour, likely through improved thermal comfort. While this study was conducted in research dogs under relatively mild temperature conditions, the results indicate the potential welfare and functional benefits for working farm dogs. Full article

Background/Objective: Huntington’s disease (HD) is an autosomal dominant neurodegenerative disorder characterized by motor dysfunction, cognitive impairment, and psychiatric symptoms. As the disease progresses, weight loss, cachexia, and musculoskeletal atrophy are common, reducing quality of life, decreasing their autonomy in their activities of daily living (ADLs), and increasing morbidity and mortality risk. To describe and compare energy expenditure (EE) during ADLs and resting conditions in individuals with HD and healthy controls, and to examine its associations with quality of life, cognitive status, motor function, and functional capacity. Methods: A cross-sectional observational study was conducted with 16 people with manifest HD and 10 healthy controls. Participants completed five ADLs: resting, dressing, combing hair, feeding, and walking under laboratory conditions. EE during ADLs was measured using a portable indirect calorimetry system. Results: Statistically significant between-group differences in EE were found only during feeding, with individuals with HD showing higher EE than controls (p = 0.021). In the exploratory correlation analysis, cognitive status was significantly associated with EE during dressing (p = 0.033). Conclusions: This exploratory study contributes to the limited evidence on EE during ADLs in adults with HD. The findings suggest that individuals with HD may expend more energy than healthy controls during specific daily activities, particularly feeding. However, these results should be interpreted with caution due to the small sample size and preliminary nature of the study. Larger, multicenter, and longitudinal studies are needed to confirm these findings and determine their clinical relevance. Full article

Background: Evidence comparing the effects of novel alternative dietary strategies on resting energy expenditure (REE) with a hypocaloric standard Mediterranean diet (MedDiet) with continuous caloric restriction remains limited. This study aimed to evaluate the effects of diets with varying ketogenic potentials—including a very-low-carbohydrate diet (ketogenic diet, KD), time-restricted eating (TRE), and modified alternate-day fasting (mADF)—on the REE of individuals with obesity compared to those of a standard MedDiet. Methods: This was a secondary post hoc sub-analysis of a three-month, parallel-arm, randomized clinical trial (RCT) including 160 adults with obesity (body mass index > 30 kg/m²). The participants were randomly assigned to one of five calorie-restricted dietary interventions: control (MedDiet), KD, early time-restricted eating (eTRE), late time-restricted eating (lTRE), or mADF. All interventions featured an individualized energy deficit of 600 kcal/day. In this sub-analysis, a total of 102 participants with valid baseline measures were included. The REE was assessed by indirect calorimetry, and longitudinal trajectories were evaluated using Linear Mixed Models (LMMs) in 98 participants to account for baseline variability and to maximize data retention. Results: The mean age of participants in this sub-analysis was 45.3 years (SD 10.8), and 73.1% were women. The longitudinal modeling confirmed no statistically significant differences in the adjusted REE trajectories among the five dietary groups over the 3-month intervention (Group × Time interaction, p = 0.506). Furthermore, the LMMs showed that total body weight (p < 0.001) and biological sex (p < 0.001) were the variables most strongly associated with REE within the model. No independent associations between circulating beta-hydroxybutyrate levels and REE trajectories were detected. Conclusions: Hypocaloric diets with varying macronutrient distributions and fasting windows did not show statistically significant differences in REE trajectories over the 3-month intervention. In this exploratory sub-analysis, the REE trajectories were more closely associated with individual biological characteristics, particularly body weight and sex, than with the specific dietary strategy employed. Given the modest sample size and exploratory nature of the study, these findings should be interpreted cautiously and require confirmation in larger, adequately powered prospective trials. Full article

Background/Objectives: Multi-strain Limosilactobacillus fermentum supplementation has been reported to promote weight loss outcomes in free-living conditions, but limited evidence exists on these probiotic strains added to an energy-restricted diet and walking program in overweight adults. Methods: In a double-blind, placebo-controlled, parallel-arm randomized trial, overweight adults (35.2 ± 13.2 years old, 167.6 ± 8.6 cm, 79.9 ± 11.8 kg, 28.4 ± 2.7 kg/m² body mass index, 36.1 ± 6.6% body fat) completed a 12-week weight loss program that included a 500 kcal/day energy deficit and walking 10 k steps/d. Participants ingested one daily capsule containing a three-strain probiotic blend (L. fermentum K7-Lb1, L. fermentum K8-Lb1, L. fermentum K11-Lb3; 6 billion CFU/day) (PRO) or maltodextrin placebo (PLA). Assessments were performed at baseline, week 6, and week 12 and included body composition, resting energy expenditure, substrate utilization, peak oxygen uptake, dietary intake, step counts, blood biomarkers, quality of life, and side effects. Data were analyzed using multivariate and univariate repeated-measures general linear models (GLM), with mean changes from baseline presented alongside 95% confidence intervals. Results: All participants significantly reduced body weight, fat mass, body fat percentage, and waist circumference. At 12 weeks, PRO reduced fat mass more than PL (−2680.7 ± 1276.7 g; p = 0.039). In PRO, android and gynoid fat percentage decreased at 6 weeks (p < 0.001; p = 0.008) and 12 weeks (p = 0.004; p < 0.001), respectively. Visceral adipose tissue mass, volume, and area were lower at 6 weeks and trended lower at 12 weeks. In PRO, bone mineral content and bone mineral area decreased at 12 weeks, while bone mineral density paradoxically increased (0.007 ± 0.003 g/cm²; p = 0.024). Conclusions: During a 12-week weight loss program, supplementation of a multi-strain L. fermentum probiotic significantly reduced body fat and central adiposity. Full article

Introduction: Patients with psoriasis, a non-contagious, chronic, systemic inflammatory skin disease, often suffer from carbohydrate metabolism disorders, which can exacerbate systemic inflammation. Methods: This randomized, double-blind, placebo-controlled trial (RCT) evaluated the effects of chicory-derived inulin-type fructans (ITFs) on body composition, energy expenditure, and carbohydrate metabolism in patients with mild psoriasis (PS), using a healthy control (n = 32) group as a baseline reference. PS participants (n = 56) were randomized to receive 15 g/day of ITFs (n = 29) or a placebo (n = 27) for 8 weeks. Body composition using bioelectrical impedance analysis (BIA), carbohydrate metabolism (fasting glucose, insulin, glycated hemoglobin, Oral Glucose Tolerance Test (OGTT)) and resting energy expenditure (resting metabolic rate (RMR), oxygen consumption (VO₂), carbon dioxide production (VCO₂)) via indirect calorimetry were determined. Results: At baseline, patients with PS had significantly (p < 0.01) higher body mass index and visceral fat levels, and abnormal levels of selected parameters of carbohydrate metabolism, compared with healthy controls. Following the intervention, the ITFs group maintained stable fasting glucose levels, while the placebo group showed an undesirable increase (Δ_glucose = +5.7 mg/dL; p < 0.01). The energy expenditure analysis revealed a significant treatment effect on RMR and VO₂ parameters (p < 0.01), with a decrease in the placebo group (p < 0.01) while remaining stable in the prebiotic group. There was no significant effect of the intervention on body composition and anthropometric parameters. Conclusions: Patients with PS exhibit a higher metabolic risk than healthy controls. Although no significant changes were observed within the intervention groups, the deterioration of metabolic indices in the placebo group may indicate an unfavorable effect of the maltodextrin. Consequently, the stabilization of parameters in the prebiotic group should be interpreted with great caution. This RCT was registered at ClinicalTrials.gov (NCT05971992). Full article

GLP-1 receptor agonists and dual GLP-1/GIP agonists have significantly transformed the treatment of obesity, enabling clinically meaningful weight reduction and improvements in cardiometabolic parameters. However, clinical trial data indicate that cessation of therapy is associated with biologically driven weight regain and a partial loss of metabolic benefits. This phenomenon underscores the chronic nature of obesity and the limited durability of effects achieved through pharmacotherapy alone. Nevertheless, structured clinical frameworks describing how to maintain satiety and metabolic stability after GLP-1/GIP dose reduction or discontinuation remain limited. The aim of this narrative review is to discuss the mechanisms underlying weight regain following dose reduction or discontinuation of GLP-1/GIP pharmacotherapy and to present strategies supporting long-term metabolic stabilisation. Weight regain is driven in part by persistent metabolic adaptations, including a reduction in resting energy expenditure (adaptive thermogenesis), alterations in the hunger–satiety axis (increased ghrelin, reduced leptin signalling), and potentially incomplete restoration of adipose tissue and liver-related metabolic function, although direct evidence in this specific setting remains limited. Weight loss is often accompanied by a reduction in fat-free mass, which further lowers energy expenditure and increases susceptibility to a positive energy balance after treatment cessation. It remains unclear whether pharmacological suppression of appetite results in sustained normalisation of endogenous satiety regulation after treatment cessation, and its effects on gut microbiota function remain uncertain. In clinical practice, key priorities include preserving muscle mass (adequate protein intake, resistance training), maintaining dietary nutrient density, stabilising postprandial glycaemia, and ensuring sufficient intake of fermentable fibre to support short-chain fatty acid production and gut–brain signalling. GLP-1/GIP pharmacotherapy should be viewed as a component of an integrated model of obesity treatment. We propose that long-term weight stabilisation may require a transition from pharmacologically induced satiety to satiety supported by diet quality, preserved fat-free mass, and metabolic stability. Further research is needed to define optimal post-treatment strategies and to identify patients in whom therapy can be safely reduced or discontinued. This transition should be regarded as a conceptual framework and forward-looking hypothesis requiring validation in prospective studies. Full article

Background/Objectives: Traditional predictive equations derived from regression analyses exhibit varying degrees of accuracy in estimating resting energy expenditure (REE). AI models can increase the predictability of such equations, even for population-specific ones. This work aimed to improve the prediction of REE in a dataset of Saudi population-specific equations using suitable AI tools. Methods: The dataset from the previously published Saudi population-specific equation by Almajwal and Abulmeaty (AA) in 2019 was used to develop an artificial neural network (ANN)-based version to better predict REE in the adult population. Anthropometric and body composition parameters were used as proposed features. The proposed hybrid prediction model underwent an extensive two-stage, iterative training process. First, the Extreme Gradient Boosting (XGBoost) model is used to compute feature importance scores. Then, the most prominent features were identified and incorporated into the ANN model. These significant features were used to train the ANN model to capture nonlinear correlations among them and make accurate predictions. Subsequently, XGBoost and Convolutional Neural Network-Recurrent Neural Network (CNN-RNN) are used for their ability to provide a multi-layer abstraction of complex input data. Results: A total of 423 participants (208 male, 215 female) were divided into three non-overlapping sets: training (295, 70%), validation (64, 15%), and testing (64, 15%). The ANN model, combined with XGBoost, helped us to develop two equations: AA_ANN1= 2.47 × BMI + 11.9 × AdjBW + 962.5 and AA_ANN2 = 4.29 × age + 9.4 × fat mass + 15.71 × FFMI + 1289.3, where BMI is Body Mass Index (kg/m²), AdjBW is Adjusted Body Weight (kg), and FFMI is Fat Free Mass Index (kg/m²). The AA_ANN1 presented a Root Mean Square Error (RMSE) of 215 and an accuracy of 66.2%, whereas AA_ANN2 presented a lower RMSE of 193 and a higher accuracy of 71.4%. The ANN model was trained on the top 10 features ranked by XGBoost, achieving an average accuracy of 90.2%. Conclusions: The two new predictive equations, developed using an ANN combined with XGBoost, significantly improved REE prediction accuracy to 90.2%, achieved only with the full ANN model. Future external validation in an independent cohort is essential before clinical application of these equations. Full article

Purpose: Recent studies have shown that high-intensity interval training (HIIT) can improve cardiometabolic health in individuals with spinal cord injury (SCI); however, many barriers remain for individuals with spinal cord injury to participate in exercise such as lack of time, accessible equipment and facilities, and transportation. The use of telehealth interventions may be a form of exercise delivery that can ease the burden on the participant and lead to greater exercise participation. Thus, the purpose of this study was to determine the feasibility and efficacy of a home-based telehealth HIIT arm crank exercise training program for individuals with spinal cord injury. Methods: Participants were randomly assigned to 16 weeks of telehealth HIIT arm crank exercise training or a no-exercise control group. Body composition, resting energy expenditure (REE), blood lipids, insulin sensitivity, blood pressure, aerobic capacity (VO₂ max), and a qualitative interview were assessed at baseline and at 16 weeks post intervention. Results: Six individuals (four male and two female, mean age 52.7 ± 10.2 years) with spinal cord injury were recruited for this study. Four out of five HIIT participants showed improvements in aerobic capacity, insulin sensitivity, and resting energy expenditure. Three qualitative themes emerged: (1) convenience and perceived benefits were critical elements of engagement; (2) high-intensity exercise elicited time-sensitive responses; and (3) trainers played a key role in promoting strong program adherence. Conclusions: Overall, we found that this program could be easily implemented and per-formed at home in individuals with spinal cord injury. We also found that participants enjoyed the 1:1 training sessions with a telecoach and that the intervention was easy to adhere to, as demonstrated by participant attendance. There is a need for future randomized controlled trials to determine the efficacy of telehealth exercise training for improving cardiometabolic health in spinal cord injury. Full article

Background/Objective: Accurate resting energy expenditure (REE) estimation is paramount for the nutritional management of older Asian adults with multimorbidity. However, standard predictive equations (PEs) lack precision for this cohort. This study aimed to recalibrate PEs using BMI-stratified, slope-only regression to enhance bedside accuracy. Methods: REE was measured via indirect calorimetry in 400 hospitalized patients (age ≥ 65). Sensitivity analyses identified significant proportional bias in existing models. Models were recalibrated and validated using 1000-iteration bootstrap resampling. Results: Standard PEs exhibited significant bias, particularly overpredicting requirements for 68% of underweight patients. The new Singapore Older Adults Resting energy expenditure (SOAR) PE 1 (963.67 + 8.56 × weight − 5.6 × age) eliminated weight-dependent systematic errors. The recalibrated models utilizing actual body weight achieved accuracy rates of up to 64% in obese cohorts, comparable to complex adjusted-weight protocols. Conclusions: Population-specific recalibration is essential to mitigate the bidirectional risks of malnutrition and overfeeding in geriatric rehabilitation. The BMI-stratified multipliers provided offer a robust, clinically efficient framework for individualized nutritional care. Full article

Introduction: Accurately meeting the energy requirements of patients in intensive care units (ICUs) is crucial to prevent catabolism, muscle loss, and complications. We assessed their energy needs in this study using indirect calorimetry (IC) and predictive formulas, comparing the results with delivered energy intake and evaluating agreement. Materials and Methods: A total of 38 mechanically ventilated patients in seven ICUs at Kayseri City Hospital were included; eligible patients were ≥18 years old and mechanically ventilated for at least 24 h. Disease severity and nutritional risk were evaluated using validated indices (prognostic nutritional index (PNI) and Modified Nutrition Risk in the Critically Ill (mNUTRIC)), and basal energy expenditure (BEE) was measured by IC and calculated using the Harris–Benedict (HB) and ESPEN formulas. IC measurements lasted 15 min under resting conditions in conscious patients and, according to acute phase criteria, in unconscious patients in a quiet, temperature-controlled environment. Nutrition was provided enterally or parenterally based on patient condition and disease severity. Agreement between IC and predictive formulas was assessed using Bland–Altman analysis, a statistical method that evaluates agreement between two measurement techniques. Results: Estimated energy requirements differed significantly from delivered energy intake (p < 0.001). IC-derived values were significantly lower than those estimated by the HB equation and ESPEN recommendations (p < 0.001), suggesting that predictive equations may overestimate energy requirements in this population. By contrast, delivered energy intake was lower than IC-measured values, with a mean difference of approximately 503 kcal, indicating a potential risk of underfeeding in clinical practice. Weak correlations were observed between methods (IC vs. HB: r = 0.35, p = 0.003; IC vs. ESPEN: r = −0.21, p = 0.02), indicating limited agreement between predictive equations and IC measurements, and Passing–Bablok regression analysis further supported this lack of agreement between methods. Conclusions: The energy intake delivered to patients was lower than the calculated values. Indirect calorimetry is important for accurately monitoring and determining energy requirements based on delivered energy intake, and further research in this area is needed. These findings highlight the importance of individualized monitoring of energy expenditure in critically ill patients and suggest that reliance solely on predictive equations may lead to clinically relevant discrepancies in energy delivery. Full article

The menstrual cycle represents a dynamic infradian rhythm characterized by coordinated fluctuations in ovarian steroids that extend beyond reproductive function and influence systemic metabolism. This narrative review synthesizes current evidence on how menstrual cycle phase modulates energy balance, macronutrient metabolism, micronutrient handling, and responses to dietary bioactive compounds. Across phases, small-to-moderate but consistent differences emerge in energy intake, resting energy expenditure, substrate utilization, and protein turnover, with a tendency toward increased energy intake and lipid oxidation during the mid-luteal phase compared with the early follicular and peri-ovulatory phases. Emerging metabolomics data further reveal coordinated cyclical variation in amino acids, B vitamins, and lipid species, suggesting temporally sensitive windows in which low energy availability or micronutrient insufficiency may more readily impair performance, recovery, or symptom burden. Importantly, menstrual cycle-related metabolic variability reflects not only estradiol and progesterone oscillations but also integrated adaptations across the hypothalamic–pituitary–adrenal axis, autonomic nervous system, immune signaling, and gut microbiota. These interconnected systems contribute to inter- and intra-individual heterogeneity in metabolic phenotype. From a clinical and applied perspective, the evidence supports “cycle-aware” but non-dogmatic nutritional strategies, particularly in contexts of metabolic dysfunction, high training loads, or reproductive disorders. Future research should systematically verify cycle phase, incorporate multi-system biomarkers, and adopt sex-specific analytical frameworks to improve translational relevance. Recognizing the menstrual cycle as a biologically meaningful metabolic variable may enhance precision nutrition, exercise prescription, and metabolic risk assessment in women. Full article