Clinical nutrition最新文献

{"title":"Both skeletal muscle index and muscle attenuation are associated with frailty in preoperative older patients with pancreatic cancer","authors":"Claudia J. Lucassen ,&nbsp;Yaren Zügül ,&nbsp;Anneke Droop ,&nbsp;Bert A. Bonsing ,&nbsp;Alexander L. Vahrmeijer ,&nbsp;Nynke Michiels ,&nbsp;Shirin Shahbazi Feshtali ,&nbsp;E.T. Daniël Souwer ,&nbsp;Johanneke E.A. Portielje ,&nbsp;J. Sven D. Mieog ,&nbsp;Frederiek van den Bos","doi":"10.1016/j.clnu.2025.11.004","DOIUrl":"10.1016/j.clnu.2025.11.004","url":null,"abstract":"<div><h3>Background and aims</h3><div>Frailty and sarcopenia are associated with morbidity and mortality in older patients with cancer. The aim of this study was to examine the association of frailty with skeletal muscle index (SMI) and muscle attenuation (MA) on preoperative CT-scans in older patients with pancreatic cancer.</div></div><div><h3>Methods</h3><div>A single-center retrospective study was performed in patients aged ≥70 years with pancreatic cancer. Frailty was assessed by an abbreviated GA screening. Preoperative SMI and MA were determined by computed tomography (CT) scan analysis. The association of frailty and individual frailty domains with SMI and MA was assessed using linear regression analyses.</div></div><div><h3>Results</h3><div>101 patients were included of which 15 (14.9 %) were frail. Frailty was associated with lower SMI (adjusted β: −5.07 cm²/m²; 95 % CI: −8.77–1.36) and MA (adjusted β: −5.70 HU; 95 % CI: −9.63–1.77). Both impaired functionality and risk of delirium were associated with lower SMI (adjusted β: −7.01 cm²/m²; 95 % CI: −11.69–2.33 and adjusted β: −4.58 cm²/m²; 95 % CI: −8.22–0.95, respectively). Impaired functionality was also associated with lower MA (adjusted β: −6.88 HU; 95 % CI: −11.89–1.87).</div></div><div><h3>Conclusion</h3><div>Frailty and impaired functionality were associated with lower SMI and MA. Risk of delirium was independently associated with lower SMI in preoperative older patients with pancreatic cancer. These results suggests that SMI and MA should be included in standard GA screening to better identify high-risk patients and enable more targeted treatment selection.</div></div>","PeriodicalId":10517,"journal":{"name":"Clinical nutrition","volume":"55 ","pages":"Pages 242-248"},"PeriodicalIF":7.4,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145620829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comment on “Effect of red meat consumption on cardiovascular risk factors: A systematic review and Bayesian network meta-analysis of randomized controlled trials”","authors":"Hamza Khan","doi":"10.1016/j.clnu.2025.11.003","DOIUrl":"10.1016/j.clnu.2025.11.003","url":null,"abstract":"","PeriodicalId":10517,"journal":{"name":"Clinical nutrition","volume":"55 ","pages":"Page 222"},"PeriodicalIF":7.4,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145620831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Does parenteral Omega-3 fatty acid administration increase the risk of atrial fibrillation? An analysis of the current evidence","authors":"Wolfgang H. Hartl ,&nbsp;Patrick Meybohm ,&nbsp;Matthias Pirlich ,&nbsp;Konstantin Mayer ,&nbsp;Gunnar Elke ,&nbsp;Christian Stoppe ,&nbsp;Christian von Loeffelholz","doi":"10.1016/j.clnu.2025.11.013","DOIUrl":"10.1016/j.clnu.2025.11.013","url":null,"abstract":"<div><h3>Background &amp; aims</h3><div>In 2023, the Pharmacovigilance Risk Assessment Committee (PRAC) of the European Medicines Agency (EMA) issued new safety information on oral fish oil (FO) pharmacotherapy. This information indicated a dose-related increased risk of atrial fibrillation (AF) with FO in patients with established cardiovascular disease (CVD). The aim of this study is to analyse the existing evidence on this risk and establish whether it can be extrapolated to FO-enriched intravenous lipid emulsions (FO-ILEs) or to other patient groups, such as critically ill patients with organ dysfunction.</div></div><div><h3>Methods</h3><div>We searched for large (&gt;50,000 participants) systematic reviews analysing the effect of long-term (&gt;1 year) oral FO pharmacotherapy on the incidence of AF in non-critically ill patients with CVD. Reviews also had to include at least one large randomised study (&gt;1,000 participants) on this topic. We examined these reviews with regard to specific limitations. We also estimated on a theoretical basis the extent to which short-term use of FO-ILEs in critically ill patients might alter plasmatic EPA (eicosapentaenoic acid)/DHA (docosahexaenoic acid) concentrations or myocardial EPA/DHA content, and investigated how these changes might affect the cardiac conduction system. We identified six meta-analyses, which consistently showed an increased risk of AF (primary, secondary, exploratory or safety outcome). In these analyses, however, significant bias may arise from including studies that ignored informative censoring or competing risks, or that used highly variable methods to search for AF. The results of these meta-analyses also conflicted with those of controlled trials in which AF was the primary endpoint, investigating the effect of long-term oral FO pharmacotherapy on the frequency of AF recurrence in patients with paroxysmal or persistent AF. Based on our theoretical considerations, it is unlikely that short-term (&lt;4 weeks) use of FO-ILEs would increase EPA/DHA plasma concentrations or myocardial contents to levels that could induce AF in critically ill patients.</div></div><div><h3>Results and conclusions</h3><div>Short-term administration of FO-ILEs at the currently recommended dose (0.1–0.2 g/kg, corresponding to an average daily EPA/DHA intake of 4–6 g) can be considered safe from a critical care perspective in the setting of AF, especially when the duration of total parenteral nutrition is limited (&lt;4 weeks).</div></div>","PeriodicalId":10517,"journal":{"name":"Clinical nutrition","volume":"55 ","pages":"Pages 223-230"},"PeriodicalIF":7.4,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145621260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing protein in critical illness: Is g/fat-free mass the key?","authors":"Kensuke Nakamura ,&nbsp;Hidehiko Nakano ,&nbsp;Naoki Kanda","doi":"10.1016/j.clnu.2025.10.022","DOIUrl":"10.1016/j.clnu.2025.10.022","url":null,"abstract":"<div><h3>Background and aims</h3><div>One potential adverse effect of protein loading in critically ill patients is elevated blood urea nitrogen (BUN) concentrations. Along with kidney function, we hypothesized that muscle volume also affects the BUN trajectory with protein administration.</div></div><div><h3>Methods</h3><div>A post-hoc analysis was conducted of a prospective historical control study in which intensive care unit (ICU) patients were assigned to protein delivery targets of 0.9 and 1.8 g/kg/day over 10 days. Patients who received renal replacement therapy were excluded. Femoral muscle volume FMV was evaluated by computed tomography on ICU admission. Daily BUN and protein delivery were recorded throughout the 10 days.</div></div><div><h3>Results</h3><div>Eighty-two eligible patients were analyzed. The BUN trajectories were slightly higher in patients with a lower muscle volume. The relative ratio of total protein delivery over 10 days to FMV showed a positive correlation with the BUN concentration on day 10 (r = 0.37, p = 0.0007); while this relationship was not significant with protein intake to actual body weight (r = 0.22, p = 0.068). In the linear mixed-effects model, protein intake per FMV was significantly associated with higher blood BUN concentrations (coefficient 0.07, 95 % CI 0.01 to 0.13, p = 0.02). Simultaneously, age and baseline creatinine were also significant predictors of BUN concentrations.</div></div><div><h3>Conclusions</h3><div>In critically ill patients, the relative ratio of total protein delivery to muscle volume was associated with BUN elevations. Protein targets may be more appropriately set based on muscle volume, for example, by using the grams per fat-free mass calculation.</div></div><div><h3>Registration</h3><div>The present study is registered at the University Hospital Medical Information Network-clinical trials registry (UMIN000040290, Registration date: May 7, 2020); <span><span>https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000045970</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":10517,"journal":{"name":"Clinical nutrition","volume":"55 ","pages":"Pages 189-195"},"PeriodicalIF":7.4,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145511665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Longitudinal associations of serum fatty acids derived from dairy consumption with early prediabetes phenotypes: The PROspective Metabolism and ISlet cell Evaluation (PROMISE) cohort","authors":"Nagam A. Yehia ,&nbsp;Ingrid Santaren ,&nbsp;Luke W. Johnston ,&nbsp;John L. Sievenpiper ,&nbsp;Adria Giacca ,&nbsp;Ravi Retnakaran ,&nbsp;Stewart B. Harris ,&nbsp;Richard P. Bazinet ,&nbsp;Anthony J. Hanley","doi":"10.1016/j.clnu.2025.10.012","DOIUrl":"10.1016/j.clnu.2025.10.012","url":null,"abstract":"<div><h3>Background</h3><div>Dairy derived saturated and trans fatty acids may contribute to inverse associations of dairy intake with type 2 diabetes mellitus (T2DM) risk. Longitudinal studies examining this association are limited. This study investigated longitudinal associations of 15:0, <em>trans</em>-16:1n9, <em>trans</em>-18:1n11, and c9, <em>trans</em>-11 conjugated linoleic acid (CLA) in four serum fractions with insulin sensitivity, beta cell function and glucose concentrations.</div></div><div><h3>Methods</h3><div>Data were obtained from the Prospective Metabolism Islet Cell Evaluation (PROMISE) cohort (n = 418) from 4 separate evaluations over 9 years. Insulin sensitivity was assessed using Matsuda's insulin sensitivity index (ISI) and the homeostasis model assessment of insulin sensitivity (HOMA2_S). Beta cell function was determined using the insulinogenic index divided by HOMA insulin resistance (IGI/IR) and the Insulin Secretion-Sensitivity Index-2 (ISSI-2). Baseline serum fatty acids (mol%) were analyzed using gas chromatography flame-ionization detection. Longitudinal associations were analyzed using covariate-adjusted generalized estimating equations with false discovery adjusted <em>P</em> values.</div></div><div><h3>Results</h3><div>In the phospholipid (PL) pool, 15:0 was positively associated with logISSI2 (β = 6.54, CI: [2.84, 10.37], p &lt; 0.01) and logIGI/IR (β = 14.75, CI: [6.92, 23.15], p &lt; 0.01), and significantly inversely associated with logGlucose120 (β = −3.45, CI: [-5.63, −1.22], p &lt; 0.05) and logGlucose Area Under the Curve (AUC) (β = −2.84, CI: [-4.38, −1.40], p &lt; 0.01). <em>Trans</em>-16:1n9was significantly associated with logISI (β = 8.08, CI: [2.06, 14.45], p &lt; 0.05) and inversely associated with logGlucose120 (β = −3.11, CI: [-5.50, −0.66], p &lt; 0.05) and logGlucoseAUC (β = −2.16, CI: [-3.75, −0.55], p &lt; 0.05).</div></div><div><h3>Conclusions</h3><div>Our findings extend the literature on the potential role of dairy derived saturated and trans conjugate fatty acids in cardiometabolic phenotypes underlying T2DM, specifically in the PL fraction.</div></div>","PeriodicalId":10517,"journal":{"name":"Clinical nutrition","volume":"55 ","pages":"Pages 124-133"},"PeriodicalIF":7.4,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145470735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dairy products intake and its association with cognitive function in older adults: A systematic review and dose–response meta-analysis","authors":"Ting Gao ,&nbsp;Yan Li ,&nbsp;Li Niu ,&nbsp;Zihan Wang ,&nbsp;Shenjun Li ,&nbsp;Yunmeng Niu ,&nbsp;Ye Li ,&nbsp;Yuhan Meng ,&nbsp;Xiaohui Gao ,&nbsp;Xinyi Xu","doi":"10.1016/j.clnu.2025.09.020","DOIUrl":"10.1016/j.clnu.2025.09.020","url":null,"abstract":"<div><h3>Background &amp; aims</h3><div>Emerging evidence suggests a possible association between dairy product intake and cognitive function in older adults; however, previous findings remain inconsistent. This study aimed to systematically evaluate the association between dairy intake and cognitive outcomes in older adults, and explore potential dose-response relationships and regional differences.</div></div><div><h3>Methods</h3><div>We searched PubMed, MEDLINE, Embase, Cochrane Library, Scopus, and CINAHL from their inception to 31 December 2024. Dose–response analysis was performed for cohort studies to assess the impact of different types and quantities of dairy intake on cognitive subdomains. Meta-regression was used to explore sources of heterogeneity. The results were presented as relative risks (RRs), odds ratios (ORs), and mean differences (MDs) with 95 % confidence intervals (CIs). The methodology followed the PRISMA guidelines for systematic reviews and meta-analyses.</div></div><div><h3>Results</h3><div>A total of 38 studies were included, comprising 21 cohort studies, 15 cross-sectional studies, and 2 randomized controlled trials. We stratified dairy products intake levels, and higher total dairy intake was associated with a reduced risk of cognitive decline and improved global cognitive function (Cohort: medium vs low, RR: 0.92, 95 % CI: 0.85, 0.99; high vs low, RR: 0.85, 95 % CI: 0.73, 0.98; Cross-sectional: high vs low, OR: 0.64, 95 % CI: 0.49, 0.82). Fermented dairy products were associated with improved verbal memory and executive function, whereas higher milk intake showed a potential association with poorer verbal memory in certain instances (medium vs low, MD: −0.04; 95 % CI: −0.09, 0.01; high vs low, MD: −0.05; 95 % CI: −0.09, −0.01). Evidence showed nonlinear associations, with the lowest risk of cognitive decline associated with a daily intake of 150 g of dairy products (<em>p</em>-nonlinear = 0.009, RR: 0.86, 95 % CI: 0.78, 0.95), and 30 g/day of whole-fat dairy (<em>p</em>-nonlinear = 0.007, RR: 0.83, 95 % CI: 0.74, 0.94). Regional differences were observed, with cognitive outcomes varying between European and Asian populations, possibly reflecting dietary habits and cultural contexts.</div></div><div><h3>Conclusions</h3><div>Dairy intake, especially fermented products and moderate total intake, may support cognitive health in older adults, though associations vary by region and dairy type. More high-quality studies are needed to clarify these relationships and guide dietary recommendations.</div></div>","PeriodicalId":10517,"journal":{"name":"Clinical nutrition","volume":"55 ","pages":"Pages 24-41"},"PeriodicalIF":7.4,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145444098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using artificial intelligence models to generate dietary recommendations for chronic kidney disease patients: A comparative cross-sectional study","authors":"Binyu Yang ,&nbsp;Wei Wei ,&nbsp;Caihong Liu ,&nbsp;Yongxiu Huang ,&nbsp;Jinglei Ren ,&nbsp;Ya Yuan ,&nbsp;Ping Fu ,&nbsp;Yuliang Zhao","doi":"10.1016/j.clnu.2025.10.014","DOIUrl":"10.1016/j.clnu.2025.10.014","url":null,"abstract":"<div><h3>Background &amp; aims</h3><div>Artificial intelligence (AI) models are increasingly being used to assist in chronic kidney disease (CKD) dietary guidance, but concerns about their accuracy remain. This study aimed to assess the performance of three AI models (ChatGPT, DeepSeek, Gemini) in accordance with the Kidney Disease: Improving Global Outcomes (KDIGO) 2024 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease.</div></div><div><h3>Methods</h3><div>We compared ChatGPT, DeepSeek, and Gemini with the KDIGO 2024 guidelines through expert and cross-AI assessments. Outputs were scored across five domains: accuracy, clarity, completeness, practicality, and safety.</div></div><div><h3>Results</h3><div>The AI models were able to generate well-structured dietary advice for CKD patients. DeepSeek received a higher score (7.625) for practicality compared to ChatGPT (6.5) and Gemini (7.0) (p = 0.041). ChatGPT showed numerically higher accuracy scores than the other two models, although there was no statistically significant difference (ChatGPT: 7.25, DeepSeek: 6.875, Gemini: 6.875; p = 0.715). Similarly, scores for clarity (p = 0.489), completeness (p = 0.432) and safety (p = 0.413) were not significantly different. The AI models share several common limitations: they might overlook contraindications (such as recommending a low-protein diet for patients with severe hypoalbuminemia), neglect age-specific needs, and lack real-time knowledge updates.</div></div><div><h3>Conclusions</h3><div>While AI shows clinical potential, its outputs still require expert validation, real-time updates, and enhanced safety protocols to ensure reliable clinical integration.</div></div>","PeriodicalId":10517,"journal":{"name":"Clinical nutrition","volume":"55 ","pages":"Pages 76-80"},"PeriodicalIF":7.4,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145457984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Determining body composition using different bioimpedance technologies: Is an agreement possible?","authors":"Francesco Campa ,&nbsp;A. Sampieri ,&nbsp;G. Cerullo ,&nbsp;L. Zoffoli ,&nbsp;G. Coratella ,&nbsp;Antonio Paoli","doi":"10.1016/j.clnu.2025.10.021","DOIUrl":"10.1016/j.clnu.2025.10.021","url":null,"abstract":"<div><h3>Background and aims</h3><div>Disagreement between bioelectrical impedance analysis (BIA) technologies in measuring resistance (R), reactance (Xc), and phase angle (PhA) is well documented and mainly due to device-specific features. Whether such a variability translates into differences in body composition estimates remains uncertain. This study evaluated agreement in fat-free mass (FFM) estimates from different BIA technologies against dual-energy X-ray absorptiometry (DXA), while accounting for the role of predictive equations. Additionally, agreement of BIA-based fat mass (FM), indirectly calculated from FFM, was assessed.</div></div><div><h3>Methods</h3><div>A total of 288 adults (167 men, 37.2 ± 18.7 y, BMI 23.0 ± 3.1 kg/m²; 121 women, 33.8 ± 16.8 y, BMI 25.1 ± 3.3 kg/m²) participated in this study. Whole-body foot-to-hand and direct segmental BIA at 50 kHz measured R, Xc, and PhA. DXA served as the reference. Predictive equations for FFM were developed by stepwise regression in two-thirds of the sample and validated in the remaining third. Agreement was evaluated between BIA technologies and against DXA using Bland–Altman and Lin's concordance correlation coefficient.</div></div><div><h3>Results</h3><div>Foot-to-hand BIA yielded lower R (p &lt; 0.001) but higher Xc and PhA (p &lt; 0.001) than direct segmental BIA. Despite these differences, no significant bias (p &gt; 0.05) was observed in FFM estimation across devices. Concordance analyses indicated high agreement without systematic deviations. FM derived from FFM agreed with DXA at a group level but showed systematic trends at the individual level.</div></div><div><h3>Conclusions</h3><div>Although raw bioelectrical parameters differ between technologies, FFM estimates can be comparable when equations are derived within the same population and reference method. However, FM indirectly obtained from FFM lacks accuracy at the individual level.</div></div>","PeriodicalId":10517,"journal":{"name":"Clinical nutrition","volume":"55 ","pages":"Pages 180-188"},"PeriodicalIF":7.4,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145475504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From prediction of personalized metabolic responses to foods to computational nutrition: Concepts of an emerging interdisciplinary field","authors":"Ruixin Zhu ,&nbsp;Yu Dong ,&nbsp;Jie Guo ,&nbsp;Jingjing He ,&nbsp;Huiyu Chen ,&nbsp;Ran Wang ,&nbsp;Fazheng Ren ,&nbsp;Anne Raben ,&nbsp;J. Alfredo Martinez","doi":"10.1016/j.clnu.2025.10.009","DOIUrl":"10.1016/j.clnu.2025.10.009","url":null,"abstract":"<div><div>Recent advances in artificial intelligence, wearable biosensors, and multi-omics technologies, combined with interdisciplinary translational collaborations, are transforming the landscape of nutrition, particularly by enabling precision nutrition. We propose computational nutrition as an emerging interdisciplinary field that aims to address complex challenges in nutrition and health and drive paradigm shifts in nutrition research through computational methods in statistics and computer science (e.g., statistical modeling, simulation, causal inference, machine learning, and deep learning) and multi-modal data. Computational nutrition employs epidemiology and data science as its methodologies and integrates expertise from nutrition, food science, computer science, statistics, systems biology, and public health. The main research directions of computational nutrition are: 1) prediction of personalized metabolic responses to foods and establishment of individualized dietary reference intakes; 2) causal inference in nutrition and diseases and evaluation of individualized treatment effects of nutritional interventions; 3) precise and dynamic assessment and monitoring of diet-related disease risks; 4) simulation and evaluation of public health nutrition policies and sustainability assessment of dietary patterns. Critical challenges such as the reliability of wearable biosensors, trade-offs in feature selection, ethics of algorithms and health equity, and interpretability of algorithms are raised, which must be addressed to ensure human well-being and rights.</div></div>","PeriodicalId":10517,"journal":{"name":"Clinical nutrition","volume":"55 ","pages":"Pages 11-23"},"PeriodicalIF":7.4,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145430521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How to define low muscle mass: A critical exploration of current definitions supports a reference equation-based approach","authors":"R. Reiter ,&nbsp;B. Wernly ,&nbsp;J. Oswald ,&nbsp;J. Gomahr ,&nbsp;J. Eberhardt ,&nbsp;D. Schaffler-Schaden ,&nbsp;B. Iglseder","doi":"10.1016/j.clnu.2025.10.016","DOIUrl":"10.1016/j.clnu.2025.10.016","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Background and aims&lt;/h3&gt;&lt;div&gt;Current definitions of low muscle mass rely on ratios in combination with gender-specific cut-offs. While these approaches aim to adjust for differences in body metrics, their mathematical validity has not been systematically examined and may introduce bias—not only in relation to muscle mass itself, but also in relation to adiposity.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;In the National Health and Nutrition Examination Survey (NHANES) cohort 1999–2006 (n = 8325) DXA-based definitions for low muscle mass of the European Working Group on Sarcopenia in Older People (ALST/height&lt;sup&gt;2&lt;/sup&gt;), of the Foundation for the National Institutes of Health sarcopenia project (ALST/BMI) and of the ESPEN and EASO consensus for sarcopenic obesity (ALST/weight) were analyzed for proportional (isometric) scaling by regression analysis, calculation of scaling exponents of the denominators and graphical illustrations. The complex relationship between muscle mass, fat mass and BMI was analyzed and the adiposity related bias, cut-offs entail, explored. To illustrate the clinical relevance, we examined the relationship between low muscle mass and fatty liver disease in a second NHANES cohort (2017–2018, n = 673).&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;While ALST/height&lt;sup&gt;2&lt;/sup&gt; approximated isometric scaling, ALST/BMI and ALST/weight showed a major mathematical bias. Instead of the assumed β = 1, BMI scaled to ALST with β = 0.6 and weight with β = 0.7. In addition to the increase with BMI, variation of muscle mass at a given BMI was tightly linked to adiposity: age and BMI adjusted standard deviation scores for muscle and fat mass correlated with r = 0.833 and r = 0.799 in men and women, respectively (p &lt; 0.001). As none of the ratio-based definitions correctly adjusted for these associations, cut-offs unmasked a major, adiposity-related bias. Using ALST/height&lt;sup&gt;2&lt;/sup&gt; the group with low muscle mass had a ∼7 kg/m&lt;sup&gt;2&lt;/sup&gt; lower BMI, opposed by ALST/BMI and ALST/weight with a ∼6 kg/m&lt;sup&gt;2&lt;/sup&gt; and ∼7 kg/m&lt;sup&gt;2&lt;/sup&gt; higher BMI. In line, fatty liver disease was less prevalent in subjects with low muscle mass following the ALSTI/height&lt;sup&gt;2&lt;/sup&gt; definition (PR = 0.30; CI 0.09–0.97), but more prevalent following the ALST/BMI and ALST/weight definitions (PR = 1.92; CI 1.38–2.67 and PR = 2.20; CI 1.58–3.06). Latter associations were no longer statistically significant when BMI and weight were corrected for β values (BMI&lt;sup&gt;0.6&lt;/sup&gt; and weight&lt;sup&gt;0.7&lt;/sup&gt;).&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusion&lt;/h3&gt;&lt;div&gt;In contrast to ALST/height&lt;sup&gt;2&lt;/sup&gt;, ALST/BMI and ALST/weight were not mathematically valid. Normalization of muscle mass by these ratios cannot correctly account for the complex association of muscle mass with fat mass, BMI and age and therefore potentially confounds results when cut-offs are applied. Reference equations that adjust for age and BMI and yield standard deviation scores may offer a more valid and clinically m","PeriodicalId":10517,"journal":{"name":"Clinical nutrition","volume":"55 ","pages":"Pages 104-112"},"PeriodicalIF":7.4,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145470708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}