Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 11 appraisals
Journal of food science
Artificial Intelligence in Food-Nutrition-Health Research: From Multimodal Data Integration to Precision Intervention
Artificial intelligence (AI) is transforming food-nutrition-health research by enabling pattern recognition in complex, high-dimensional datasets that traditional hypothesis-driven approaches cannot address. This review systematically synthesizes research progress of AI across the food-nutrition-health continuum from 2020 to 2025. By examining 181 systematic reviews through PRISMA-guided selection, we provide a comprehensive overview and prospects across four dimensions: technical foundation, application scenarios, existing challenges, and future prospects. We propose a tripartite framework comprising (1) a data layer enabling multisource fusion of food composition, health monitoring, and individual characteristic data; (2) a technological layer of nondestructive testing (spectroscopy, nuclear magnetic resonance [NMR], imaging); and (3) an algorithmic layer progressing from machine learning to deep learning architecture. Key applications include food component analysis and safety detection; nutrition-disease association modeling; pathogen identification; and personalized dietary intervention systems. Despite rapid progress, critical challenges persist, insufficient model generalization across populations, algorithmic opacity limiting clinical trust, data privacy vulnerabilities, and lack of standardized multi-omics integration protocols. Future directions emphasize multimodal fusion models, explainable artificial intelligence (XAI), federated learning for privacy-preserving collaboration, gene-guided precision nutrition, and development of intelligent wearable devices and functional food. This review provides a roadmap for transitioning from population-averaged guidelines to dynamic, individualized health optimization through AI-enabled food system.
1 Aug 2026
Read appraisal →Current obesity reports
A Systematic Review of Community-based Interventions to Promote Physical Activity or Reduce Sedentary Behavior among Adults in Low- and Middle-Income Countries
PURPOSE OF REVIEW: Community-based interventions (CBIs) are widely used to address behavioral risk factors for non-communicable diseases, yet evidence of their effectiveness in low- and middle-income countries (LMICs) remains limited. This study systematically reviewed evidence on the effectiveness of CBIs promoting physical activity (PA) and/or reducing sedentary behavior (SB) among community-dwelling adults in LMICs. We searched PubMed, Embase, Scopus, and the Cochrane Library (2000-2024) for CBIs in LMICs. Primary outcomes were changes in PA and/or SB. Descriptive and graphical depictions were used to draw inferences. RECENT FINDINGS: We selected 24 studies (11 RCTs) from 15,396 for review. Most studies (n = 16) reported significant improvements in PA outcomes. Changes were observed in Metabolic Equivalents (+ 100 - +2,700), moderate-to-vigorous PA (+ 7 to + 60 min/week), and steps/day (+ 3,000). Broadly, interventions were delivered using digital/technology format (n = 10), peer-led/community health worker-facilitated (n = 8), and Environmental restructuring (n = 6), with the digital interventions depicting the most consistent significant improvements. Two studies directly measured SB as a primary outcome. Short- (≤ 6 months; n = 11) and medium-duration (6-12 months; n = 4) interventions more frequently reported significant PA improvements than long-duration interventions (> 12 months; n = 9). PA/SB-focused CBI demonstrated proportions of significant effects similar to those of broader lifestyle interventions (88.9% and 53.3%, respectively). CBIs can be effective in improving PA in LMICs, although evidence is heterogeneous and SB is less addressed. Digital interventions show more consistent positive signals, but high heterogeneity in studies precludes firm conclusions. The impact of duration on effectiveness looks counterintuitive but underscores the need for more rigorous evaluation of longer-duration interventions and SB outcomes. PROSPERO registration number: CRD42024579461.
23 July 2026
Read appraisal →Analytical chemistry
Large Language Model-Generated Dietary Metabolite Biomarker Database Drives Deep Annotation of the Human Diet Metabolome
The annotation of dietary biomarkers is crucial for nutritional epidemiology. While untargeted liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is a powerful analytical approach, the annotation of dietary biomarkers is hampered by the low specificity of existing public databases, which limits annotation coverage and accuracy. To address this limitation, we developed a novel database construction strategy and a dual-annotation workflow. We first employed an automated, large language model (LLM)-based text-mining pipeline to parse 7339 scientific articles and supplementary materials, creating the Dietary Metabolite Biomarker Database (DMBDB), which contains 4983 nonredundant biomarkers. The LLMs workflow demonstrated high performance, achieving an F1 score of 0.9269 for biomarker name recognition. Subsequently, two complementary annotation strategies were designed: (i) a specialized LC-MS database derived from DMBDB, incorporating predicted retention times and experimental MS/MS spectra for high-confidence matching, and (ii) a structure-guided molecular networking strategy (SGMNS) that uses DMBDB as background knowledge to annotate dietary biomarkers and their metabolites lacking spectral evidence. The framework was validated using untargeted LC-HRMS analysis of urine samples. LC-MS database directly annotated 566 metabolites, and the integration with SGMNS expanded the total number of annotations to 2078. The LLM-driven database construction combined with the dual-strategy annotation framework provides a powerful paradigm for achieving high-coverage and high-accuracy dietary metabolomics.
15 July 2026
Read appraisal →Metabolomics : Official journal of the Metabolomic Society
A metabolomic signatures in hyperuricemia: a systematic review
BACKGROUND: Hyperuricemia (HUA) is traditionally viewed as a disorder of purine metabolism. However, its broader metabolic alterations remain incompletely understood. Metabolomics provides a useful approach for exploring metabolite changes associated with HUA, but a comprehensive synthesis of existing findings is still lacking. AIM OF REVIEW: This systematic review and meta-analysis aimed to characterize the systemic metabolic signature of HUA beyond purine pathways. By synthesizing data from 27 metabolomics studies involving 12,335 participants, the study sought to identify consistent metabolite biomarkers and key dysregulated pathways to provide new insights for diagnosis and therapeutic targeting. KEY SCIENTIFIC CONCEPTS OF REVIEW: This review included 27 metabolomics studies involving 12,335 participants and identified 1,187 metabolites reported in association with HUA. Qualitative synthesis showed 54 consistently elevated and 20 consistently decreased blood metabolites, mainly involving amino acids, lipid-related metabolites, energy-related compounds, vitamins and their derivatives, and purine nucleoside metabolites. The meta-analysis was limited to two eligible studies, with one study contributing most of the statistical weight; it suggested higher levels of Alanine, Leucine, Phenylalanine, and Tyrosine and lower Histidine levels in HUA. Pathway enrichment analysis highlighted "One carbon pool by folate," "Arginine biosynthesis," "Glutathione metabolism," and related amino acid and energy metabolism pathways. Overall, these findings suggest that HUA may be associated with metabolic perturbations beyond purine metabolism alone, but the candidate metabolites and pathways require further validation in longitudinal, standardized, and mechanistic studies.
13 July 2026
Read appraisal →European journal of pediatrics
Feasibility of image-based 3D avatar anthropometry assessment of pediatric obesity: a pilot study.
UNLABELLED: The purpose of this study is to evaluate the feasibility and validity of 3D avatar-based anthropometry for assessing anthropometric indicators of overweight and obesity in children based on artificial intelligence-derived 3D body reconstruction. This cross-sectional study included 171 children aged 8-10 years from five primary schools in southern Spain. Due to technical constraints of the reconstruction software, 75 children meeting predefined image quality and body weight requirements (≥ 30 kg) were eligible for 3D avatar analysis. Manual anthropometric measurements were obtained following International Society for the Advancement of Kinanthropometry (ISAK) standards and compared with avatar-derived circumferences. Agreement was assessed by using Wilcoxon tests, Spearman correlations, Bland-Altman analyses, and false discovery rate-adjusted comparisons. Avatar-derived circumferences were consistently greater than manual measurements, although waist-to-hip and waist-to-stature ratios demonstrated no significant differences. Avatar and manual circumferences were moderately to strongly correlated (Spearman's ρ = 0.62-0.72; adjusted p < 0.05). However, the mean absolute errors ranged from 6.21 to 7.11 cm, and Bland-Altman analysis revealed systematic overestimation with wide limits of agreement, particularly for waist and hip circumferences. Despite these discrepancies, both methods similarly discriminated between weight status categories. CONCLUSION: Image-based 3D avatar anthropometry is a feasible, noninvasive approach for population-level screening and research in pediatric settings. Although the system reliably captures relative differences and body proportions, its current accuracy is insufficient for individual-level clinical assessment. Further algorithmic refinement and validation in lighter and more diverse pediatric populations are needed before clinical implementation. WHAT IS KNOWN: • Childhood obesity remains a major public health challenge requiring accurate monitoring. • Anthropometric assessment still relies mainly on manual measurements, while AI-based 3D body modeling offers a promising non-invasive alternative. WHAT IS NEW: • Image-based 3D avatar anthropometry is feasible in school settings but is constrained by technical requirements. • Avatar measurements are correlated with manual anthropometry and preserve weight status discrimination but demonstrate systematic overestimation and limited agreement.
29 June 2026
Read appraisal →Medicine
Clinical outcome of revisional gastrectomy postgastric banding failure: A systematic review.
BACKGROUND: Laparoscopic adjustable gastric banding (LAGB) has been widely used for obesity management; however, its long-term failure, due to complications such as band erosion, slippage, and inadequate weight loss, has necessitated revisional bariatric procedures. Revisional laparoscopic sleeve gastrectomy has emerged as a common alternative, yet its safety and efficacy remain debated. METHODS: A systematic review was conducted in accordance with PRISMA guidelines; this review was prospectively registered with Prospective Register of Systematic Reviews (CRD42024568094). A comprehensive search of PubMed, Scopus, Web of Science, and Cochrane databases was performed up to July 19, 2024. Studies published in English that reported postoperative outcomes following revisional laparoscopic sleeve gastrectomy after failed LAGB were included. Data were extracted independently by 2 reviewers, focusing on patient demographics, complication rates (including leaks, bleeding, and infections), and nutritional outcomes. Quality assessment was performed using a standardized tool for observational studies, cohort and cross-sectional studies. RESULTS: Fifty studies involving a total of 16,192 patients were analyzed. Patients had a mean age between 30 and 50 years and a revision body mass index ranging from 33 to 52 kg/m2. Infection was reported in 9 studies, though incidence was low. Bleeding was examined in 30 studies, with mostly isolated cases; thrombosis was reported in only 1 study. Leak rates were reported in 39 studies, ranging from 0% to 8.1%, with stage-specific rates between 2.8% and 5.8%. Four studies noted nutritional deficiencies, including increased ferritin deficiency and some cases contributing to readmission. Overall complication rates were reported in 22 studies, averaging 9.95% and ranging from 0% to 37.5%. CONCLUSION: Revisional laparoscopic sleeve gastrectomy following failed LAGB appears to offer a safe and effective alternative, with acceptable complication rates and favorable weight loss outcomes. However, heterogeneity in study designs and patient characteristics underscores the need for standardized reporting and further research to optimize clinical protocols.
28 June 2026
Read appraisal →PloS one
Determinants of dropout from lifestyle interventions for overweight polycystic ovary syndrome: An exploratory analysis of randomized controlled trial.
OBJECTIVE: This exploratory analysis of a randomized controlled trial aimed to identify baseline predictors of dropout in overweight women with polycystic ovary syndrome (PCOS) participating in a lifestyle intervention program. METHODS: An exploratory analysis was conducted using data from a randomized controlled trial involving overweight or insulin-resistant women with PCOS aged 18-45. All participants received cyclic progestin, metformin, and a structured lifestyle intervention. Dropout was defined as proactive withdrawal, missing two consecutive visits, or loss of contact for more than six months. Univariate and adjusted multivariable logistic regression models were used to identify factors associated with dropout. RESULTS: Among the participants, 61.06% (n = 69) dropped out within one year. No significant differences were observed in baseline demographic, clinical, biochemical, psychological, or dietary characteristics between completers and dropouts. However, baseline physical activity level (PAL), objectively measured using an accelerometer, was identified as the strongest predictor of dropout. Each 0.3-unit increase in PAL was associated with a 29.6% reduction in the likelihood of dropout. CONCLUSION: Baseline PAL is strongly associated with the risk of dropout. Screening for PAL in women with PCOS is recommended, and those with lower PAL should receive personalized support in addition to lifestyle interventions to improve adherence and promote weight loss.
28 June 2026
Read appraisal →Journal of global health
Habitual physical activity and sarcopenia: a systematic review and meta-analysis of prospective cohort studies
BACKGROUND: Habitual physical activity (HPA) has been associated with a lower risk of sarcopenia by enhancing skeletal muscle protein synthesis and suppressing systemic inflammation. However, the evidence for a long-term protective association remains inconclusive. Therefore, we conducted a systematic review and meta-analysis to quantify the association between HPA and sarcopenia. METHODS: We searched PubMed, the Cochrane Library, EMBASE, Cumulative Index to Nursing and Allied Health Literature, Web of Science, and the China National Knowledge Infrastructure for prospective cohort studies on the relationship between physical activity (PA) and sarcopenia. We selected English and Chinese-language literature published before 6 October 2025, and assessed study quality using the Newcastle-Ottawa Scale. Data were statistically synthesised by calculating pooled relative risks (RRs) and 95% confidence intervals (CIs) using a random-effects model with the generic inverse-variance method. RESULTS: This meta-analysis included nine prospective cohort studies involving 21 265 participants. High levels of HPA were associated with a significantly lower risk of sarcopenia compared to the low levels (RR = 0.55; 95% CI = 0.44-0.67). This protective association remained consistent in subgroup analyses stratified by gender and by compliance with international PA guidelines. Furthermore, moderate HPA was also associated with a reduced risk compared to low HPA levels (RR = 0.73; 95% CI = 0.50-0.96). CONCLUSIONS: Our analysis indicates that moderate to high levels of HPA are independently associated with a lower risk of sarcopenia, serving as a significant protective factor. However, given the methodological heterogeneity in PA measurement, further high-quality prospective studies are needed to clarify the optimal PA dose while accounting for potential reverse causality. REGISTRATION: PROSPERO: CRD420251162529.
28 June 2026
Read appraisal →Science advances
Smart contact lens-trained digital twin for device-free personalized uric acid prediction
Tears contain valuable biomarkers and offer potential for noninvasive disease monitoring. However, the lack of correlation analysis between serum uric acid (SUA) and tear uric acid (TUA) has limited their clinical application in personalized medicine. Here, we present a wireless smart contact lens capable of real-time, noninvasive monitoring of TUA as an alternative to blood-based UA testing. We validated the device through correlation analysis in rabbits and human participants, including individuals with hyperuricemia and gout. Daily-life monitoring enabled personalized characterization of TUA fluctuations in response to food intake and physical activity, together with individualized lag time profiling. A strong linear relationship allowed development of a regression model to derive estimated SUA from TUA. Building on these temporal profiles, lifestyle-informed digital twins were constructed to predict daily uric acid dynamics without continuous lens wear. This digital twin-enabled, device-free framework provides a practical route toward unobtrusive and personalized metabolic health monitoring.
27 June 2026
Read appraisal →JMIR research protocols
Cross-Cultural Perspectives on Metabolic Syndrome Management and Attitudes Toward Using Digital Health Tools in Two Distinct Populations: Protocol for a Qualitative Descriptive Study
BACKGROUND: Metabolic syndrome (MetS) is defined by the presence of at least 3 out of 5 clinical risk factors, including abdominal obesity, elevated blood pressure, high fasting glucose, elevated triglycerides, and low high-density lipoprotein cholesterol. Individuals with MetS face significantly increased risks of cardiovascular disease, type 2 diabetes, and all-cause mortality. OBJECTIVE: This study aims to explore the multilevel factors influencing individuals' engagement in self-management of MetS. Specifically, it seeks to identify key barriers and facilitators to effective self-management and to assess participants' attitudes toward the use of digital health tools in supporting disease management. METHODS: This qualitative descriptive study will be conducted at 2 international sites: the University of Memphis (United States) and King Saud bin Abdulaziz University for Health Sciences (Saudi Arabia), in collaboration with local primary care clinics. Participants will be recruited using purposive sampling with a maximum variation strategy, aiming for 20 to 30 individuals per site who meet eligibility criteria. Data will be collected through semi-structured, 60-minute one-on-one interviews. An abductive thematic analysis approach (integrating both inductive and deductive reasoning) will be used to analyze the data with NVivo 15 software. RESULTS: This study will begin participant enrollment in August 2026. Thematic analysis will be used to examine barriers and facilitators to MetS self-management and participants' views on digital health tools across 2 international sites. CONCLUSIONS: Findings will offer culturally grounded insights into how social, dietary, and familial factors influence chronic disease management. This knowledge can inform the design of equitable, context-sensitive digital health interventions. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/91903.
27 June 2026
Read appraisal →Food & function
Impact of tomatoes and tomato-derived products on obesity and cardiometabolic health: a systematic review and meta-analysis
Tomatoes and tomato-based products are central components of the Mediterranean diet and have been associated with improved cardiometabolic health, but their effects on anthropometric parameters remain unclear. This review aimed to assess the potential effects of tomato-based interventions on obesity-related and cardiometabolic outcomes in individuals with overweight or obesity. We conducted a PRISMA-compliant systematic review and meta-analysis. Eligible studies included populations with a mean BMI ≥ 25 kg m-2, evaluated tomatoes, tomato-based products, or tomato extracts (excluding isolated lycopene) and reported at least one anthropometric outcome. The risk of bias was assessed using RoB 2 for randomized controlled trials (RCTs). Epidemiological and preclinical evidence was synthesized qualitatively. Forty-seven studies met the inclusion criteria: 11 clinical trials (RCTs), 5 epidemiological studies, and 31 preclinical studies. In the RCTs, tomato-based interventions produced a small but significant reduction in waist circumference (MD: -1.153 cm, 95% CI: -2.27 to -0.04, p = 0.0432), with no consistent effects on body weight or BMI. Meta-regression analyses indicated that supplementation type influenced blood pressure-related outcomes. Epidemiological studies consistently linked higher tomato intake to more favorable cardiometabolic profiles, whereas preclinical models showed reduced visceral adiposity, inflammation, and oxidative stress, together with improved glucose and lipid homeostasis. Tomato-based interventions confer modest but biologically consistent benefits, targeting visceral adiposity and cardiometabolic pathways rather than overall weight loss. The absence of a lycopene dose response and the efficacy of lycopene-free matrices support a food-matrix synergy rather than lycopene as the primary bioactive compound. Combined clinical, epidemiological, and preclinical evidence suggests potential beneficial effects of tomatoes and tomato-based products on cardiometabolic health, which deserve further investigation. This review underscores the need to standardize tomato-derived interventions to improve comparability and strengthen the evidence base.
24 June 2026
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