Clinical nutrition ESPEN最新文献

Background: Among patients with esophageal adenocarcinoma, changing radiological metrics of body composition in the form of sarcopenia and myosteatosis are associated with postoperative complications and impaired survival. However, whether changes in these radiological metrics during neoadjuvant chemotherapy affect these outcomes remains unexplored.

Methods: From 01/2014-01/2023, a single center retrospective study was performed. Patients with locally advanced esophageal adenocarcinoma treated with neoadjuvant taxane based chemotherapy and en bloc resection were identified. Contrast infused pre-treatment and pre-surgery computed tomography scans were reviewed and skeletal muscle index (SMI) and skeletal muscle density (SMD) calculated. Pathological sarcopenia and myosteatosis were defined by the lowest sex-specific quartile of pre-treatment SMI/SMD values. Clinical and survival outcomes were compared between 'persistent'/'developed' sarcopenia and myosteatosis and the rest of the cohort. Data is reported with hazard ratio (HR).

Results: Of the 387 patients identified, 105 were included in the final analysis. 'Developed'/'persistent' sarcopenia and myosteatosis was identified in 36/105 (34.3%) and 33/105 (31.4%) patients respectively. Unlike sarcopenia, 'Developed'/'persistent' myosteatosis was associated with a higher incidence of major postoperative complications (11/72(15.3% vs 12/33(36.4%),p=0.009). On multivariate analysis pathologically positive lymph nodes (ypN1 HR 4.2, p=0.010, ypN2 HR 3.8, p=0.029 and ypN3 HR 9.1, p=<0.001), poor tumor differentiation (HR 3.4, p=0.001) and 'developed'/'persistent' myosteatosis (HR 2.1, p=0.046) were independently associated with impaired overall survival. Measurements of sarcopenia were not associated with these outcomes.

Conclusion: In patients with locally advanced esophageal adenocarcinoma treated with neoadjuvant chemotherapy and en bloc resection, radiological measurements of myosteatosis, rather than sarcopenia, seem to better predict postoperative and survival outcomes than sarcopenia.

Background & aims: Iodine is an essential micronutrient for thyroid hormone synthesis and neurological function. Despite long-standing salt iodization programs, both iodine deficiency and excess remain public health concerns. This study aimed to estimate daily iodine intake and identify sociodemographic and dietary factors associated with iodine intake among Chilean adults.

Methods: A cross-sectional analytical study was conducted using data from the 2016-2017 Chilean National Health Survey. Iodine intake (μg/day) was estimated from urinary iodine concentration adjusted for body weight. Linear regression models, accounting for complex survey design, were used to examine associations with sociodemographic, anthropometric, and dietary variables.

Results: Data from 1230 adults aged ≥18 years were analyzed. Mean iodine intake was adequate overall but higher in men than women (425 vs. 322 μg/day, p < 0.001). Iodine intake decreased significantly with age and was positively associated with waist circumference. Frequent dairy consumption was a key dietary determinant: those with frequent or moderate intake showed higher iodine intake than those with very frequent consumption (p = 0.006).

Conclusion: Although the average iodine intake among Chilean adults was adequate, women and older adults showed lower intake levels. Maintaining salt iodization policies and promoting iodine-rich foods, particularly dairy and fish, are essential to prevent reemerging deficiencies in vulnerable groups.

Objectives: This study aimed to evaluate the effects of an 8-h Time-Restricted Eating (TRE) intervention over 12 weeks on weight loss, body composition, and sleep in adults with Obstructive Sleep Apnea (OSA).

Methods: A randomized crossover clinical trial was conducted. Participants aged 30-65 years with a Body Mass Index (BMI) ≥30 kg/m², diagnosed with OSA, of both sexes, with eating windows from 11 to 14 h were included. The participants were randomized into an 8-h TRE intervention (meals between 11 AM and 7 p.m.) or control group (eating window >10 h and nutritional guidance). Twelve participants completed the intervention. Measurements included body weight, height, waist and neck circumference, and body composition (bioelectrical impedance). Sleep parameters were assessed using a Biologix® portable sleep monitor and questionnaires.

Results: The average age of the sample was 44.6 ± 7.84 years, 50% female. Adherence to the TRE intervention was 4.2 days per week. No significant effects of TRE were observed on body weight or anthropometric outcomes, body composition, or sleep parameters.

Conclusion: The findings of this study suggest that a 12-week 8-h time-restricted eating intervention was not associated with reductions in body mass or body composition and sleep parameters evaluated by a portable monitoring device. Brazilian Registry of Clinical Trials (REBEC) - protocol RBR-9rh56ph.

Background and aims: Hip fractures are common among older adults and are associated with functional decline and increased mortality. Body mass index (BMI) is a known prognostic factor for adverse outcomes. However, evidence on nonlinear associations across the entire BMI spectrum remains limited. This study aimed to examine the association between BMI at admission and in-hospital mortality, complications, and changes in functional status as measured by the Barthel Index.

Methods: This retrospective observational study used data from a nationwide inpatient database in Japan between 2014 and 2024. This study included patients aged 65-99 years who had undergone surgery for hip fractures. BMI at admission was categorized according to the World Health Organization Asian criteria: underweight (<18.5 kg/m²), normal (18.5-22.9 kg/m²), overweight (23.0-27.4 kg/m²), and obese (≥27.5 kg/m²). The primary outcome was in-hospital mortality, and the secondary outcomes were in-hospital complications and changes in the Barthel Index. Cox proportional hazards and linear regression models were applied and nonlinear associations were assessed using restricted cubic splines.

Results: In total, 146,699 patients were included in the analysis (mean age 84.5 ± 7.5 years; 78.4% female). In-hospital mortality occurred in 2554 patients (1.7%). The associations of BMI at admission with in-hospital mortality and complications showed L-shaped patterns in the spline curves. The hazard ratio for in-hospital mortality at a BMI of 18.5 kg/m² was 1.83 (95% CI: 1.69-1.99), compared with a BMI of 23.0 kg/m² as the reference. A similar L-shaped pattern was observed for complications (BMI 18.5 kg/m²: HR = 1.06, 95% CI: 1.04-1.09). No substantial changes were observed for BMI ≥23.0 kg/m². Changes in Barthel Index showed a reverse J-shaped pattern, decreasing progressively below 23.0 kg/m² (18.5 kg/m²: β = -4.44, 95% CI: -4.92 to -3.96) and increasing above this threshold (27.5 kg/m²: β = 1.45, 95% CI: 0.78-2.12).

Conclusion: BMI at admission is an important prognostic factor of clinical outcomes in patients with hip fractures. Maintaining an adequate BMI through nutritional management before injury may improve survival and functional recovery. However, the exclusion of patients with missing BMI data and the absence of information on surgical delay and other potential confounders should be considered when interpreting these results.

Background & aims: Nutritionally rehabilitating children admitted to hospitals with severe acute malnutrition (SAM) and acute illness can pose significant challenges. Understanding the predictors of weight gain in this vulnerable group remains limited. Advanced analytical methods leveraging machine learning (ML) approaches adeptly handle the complexity of the data involved and identify predictors of clinical outcomes in a comprehensive and interpretable manner. This work aimed to predict weight gain in hospitalized children with SAM using explainable ML approaches.

Methods: We included 2183 children aged 0-59 months with SAM hospitalized in the Dhaka Hospital at the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) between 2011 and 2019. Service data were collected during hospitalization and analyzed retrospectively. Seven ML models were developed to predict weight gain from hospital admission to discharge (continuous outcome) and 5% or 15% weight gain during hospitalization (binary outcomes). Explainability analysis was conducted using Shapley values to interpret the most important predictors.

Results: Among the ML algorithms evaluated, Random Forest and XGBoost demonstrated consistently superior performance across both continuous and binary outcomes. The ML models identified MUAC at admission, age, baseline height-for-age z-score (HAZ), and admission weight as the most important predictors of weight gain when analyzed as a continuous outcome. When weight gain was treated as a binary outcome, admission anthropometry, including MUAC, WHZ, and WAZ, followed by age, formula feeding, and family income, were found among the most important predictors of weight gain during hospitalization. Shapley explainability analysis revealed that baseline anthropometric measurements (e.g., MUAC and weight), duration of formula feeding, and household roof condition, had a positive contribution, while age had a negative contribution on>15% weight gain. Weight gain models had moderate-low performance (RMSE=0.38-0.63, MAE=0.24-0.34). For weight gain categories of >5% or >15% during hospitalization, the average accuracy was 60% (50%-70%), while sensitivity, specificity, AUC, and positive and negative predictive values also varied between 50% and 70%.

Conclusions: Tree-based ensemble methods showed the greatest potential for future clinical application. This analysis, using explainable ML models, provided valuable insights into the role of baseline anthropometry and the importance of feeding practices in attaining weight from hospital admission to discharge in children under five treated for SAM. This finding has important implications for future research on childhood feeding practices, developing personalized nutrition strategies, and community-based detection of children with SAM.

Neuropathic pain (NP) is caused by damage to the peripheral or central nervous system and is associated with adverse complex sensory and affective symptoms. There are few current treatment options for NP, and opioid analgesics have severe side effects which can lead to opioid abuse. Therefore, the development of innovative, effective, and safe alternatives is urgently needed. This study will assess the effects of ginger root extract's anti-inflammatory and anti-oxidant properties on individuals with sciatica via the microbiome-gut-brain axis. Eighty participants (18-85 years) with chronic sciatica, classified as lean (n=40, BMI <25 kg/m²) or obese (n=40, BMI ≥30 kg/m²), will be stratified by age, sex, and BMI to receive 2,000 mg/day of ginger extract or placebo for eight weeks. Primary outcomes are pain-associated outcomes and brain neuroplasticity by assessing functional (resting state-fMRI) and structural (Diffusion Tensor Imaging) connectivity. Secondary outcomes include gut function (gut microbiota composition using 16S rRNA sequencing analysis, intestinal permeability assessing concentrations of plasma lipopolysaccharide binding protein and fecal zonulin, and fecal metabolites using LC-MS/MS analysis) and neuroinflammation: nCounter® Neuroinflammation Panel analysis. We will evaluate outcomes at baseline and end of study. We will employ intention-to-treat principle and per-protocol for data analysis. Hierarchical linear modeling is utilized to estimate ginger supplementation's effects while properly accounting for data dependency and identified covariates. This study was approved by the Bioethics Committee of the Texas Tech University Health Sciences Center, Lubbock, TX. Participants will sign an informed consent form before enrolling in the study. Our team will actively disseminate the results from this trial through academic conference presentations and peer-reviewed journals. We are now actively recruiting subjects for this study. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT06817018.

Background and aims: Although the prognostic significance of low muscle mass has been established in cancer outcomes, standardizing cutoff values remains challenging. Various criteria based on the skeletal muscle index (SMI) have been proposed. The Z-score derived from the body-size-adjusted skeletal muscle area (SMA) has been proposed (Derstine's Z-score), which offers the potential for unbiased assessments across diverse body sizes. However, large-scale cohort validation of clinical outcomes using this approach has not been conducted. This study aimed to validate Derstine's Z-score in a different race than the original paper.

Methods: This single-center study included 2869 patients with gastrointestinal or genitourinary cancers who underwent radical surgery. The SMA on computed tomography at the third lumbar level was used to calculate Derstine's Z-scores by normalizing the ratio of the SMA to height- or height-squared with the body size-adjusted mean and sex-specific standard deviation. We employed Z-score cutoffs of -2 and -3, the nearest whole number to the optimal cutoff, calculated using maximally selected rank statistics with several p-value approximations. The effects of Derstine's Z-scores on cancer-specific survival (CSS) and overall survival (OS) were calculated and compared with the previously proposed SMI definition.

Results: Kaplan-Meier analysis demonstrated significant discrimination of CSS and OS based on Derstine's Z-scores. A -3 cutoff for Derstine's Z-score, rather than the conventional -2, achieved the highest hazard ratio, with values of 1.61 for CSS and 1.94 for OS. Multivariate analysis revealed that low muscle mass, as defined by Derstine's Z-scores, was associated with poor prognosis, with hazard ratios of 1.42 for CSS and 1.62 for OS, enhancing the predictive capability of survival models comparable to the SMI definition.

Conclusion: The Derstine Z-score is a valuable prognostic indicator in patients with cancer. A cutoff value of -3 may better capture low muscle mass in a different race than the original paper.

Introduction: Skeletal muscle mass (SMM) is a relevant factor in oncology because of its association with treatment tolerance, efficacy, and survival. However, its characterization in patients with diffuse large B-cell lymphoma (DLBCL) remains limited, particularly in the Latin American population.

Objective: To characterize total and muscle group-specific SMM in newly diagnosed DLBCL patients and define age- and sex-adjusted cut-off values based on overall survival (OS).

Methods: A secondary analysis was conducted using data from a retrospective cohort of 242 patients aged ≥18 years between 2015 and 2024 at a referral center in Mexico City. SMM was assessed using computed tomography (CT) at the L3 vertebra. The skeletal muscle index (SMI) was calculated and correlated with clinical and functional parameters. OS was defined as the time from the date of diagnosis to the date of the last follow-up or death.

Results: Low SMI was observed in 57.4 % of patients, showing a weak correlation with age and a moderate correlation with handgrip strength. Proposed SMI cut-off values were as follows: women <60 years, 30.28 cm²/m², and ≥60 years, 37.87 cm²/m²; for men <60 years, 55.82 cm²/m², and ≥60 years, 49.96 cm²/m².

Conclusions: Comprehensive assessment of SMM, incorporating all regional muscle groups, provides a more accurate representation of body composition than isolated muscle analyses. The high prevalence of low SMM in this cohort underscores its clinical relevance and supports the applicability of the proposed cut-offs to improve SMI-based evaluations in Latin American patients with DLBCL.