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GLP-1 Receptor Agonists and Musculoskeletal Outcomes: A Systematic Literature Review and Meta-Analysis.

INTRODUCTION: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are increasingly used for the treatment of type 2 diabetes and obesity, but their effects on musculoskeletal health remain completely misunderstood. OBJECTIVE: This systematic review/meta-analysis aims to synthesise clinical data on the effects of GLP-1 RAs on key relevant bone, muscle, and joint outcomes. METHODS: MEDLINE, Cochrane Central Register of Controlled Trials (CENTRAL) (both via Ovid&#xae; platform) and Embase were searched from inception to March 2025 to identify relevant randomised controlled trials (RCTs) or real-world evidence (RWE) studies to be included. This bibliographic search was completed manually. A random-effect model meta-analysis was performed for any outcome reported in at least 2 studies. Subgroup analyses were performed on the type of GLP-1 RAs, type of comparator used and study design. Sensitivity analyses (i.e., leave-out sensitivity analyses and analyses restricted to the most adjusted effect estimate) were performed to test the robustness of the data. The strength of evidence was assessed using GRADE. This work has been performed in adherence with PRISMA statement. (PROSPERO Record ID: CRD420251024082). RESULTS: From 1148 potentially relevant references, 60 articles (46 RCTs, 13 RWE studies and 1 pharmacovigilance study, comprising 1,250,717 individuals) met our inclusion criteria. Different GLP-1 RAs were represented across the panel of studies, i.e., semaglutide, liraglutide, exenatide, dulaglutide, tirzepatide (dual agonist gastric inhibitory polypeptide [GIP]/GLP-1) and others. No effect on bone outcomes (i.e., bone mineral density [all sites] and fractures [all sites]) were observed when the meta-analytical models included the most adjusted effect size. Regarding muscle outcomes, a significant decrease of lean body mass/fat-free mass was consistently observed with GLP-1 RAs in the global model (k = 28, standardised mean difference [SMD] 0.52, 95% confidence interval [CI] -0.8; -0.23, I2 88%, p-value for heterogeneity <0.0001), which remained robust in all sensitivity analyses. Subgroup analyses showed that the effect was mainly driven by liraglutide and semaglutide, with a decrease in lean body mass/fat-free mass observed when GLP-1 RAs were compared with placebo. No publication bias was found. Regarding joint outcome, models revealed no significant change in The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain, physical function and stiffness. CONCLUSIONS: This meta-analysis is the first to investigate the effects of GLP-1 RAs on a large panel of musculoskeletal health outcomes. While no significant effects were observed on bone- or joint-related outcomes, GLP-1 RAs were associated with reductions in lean body mass/fat-free mass, although the certainty of evidence was low and these changes appeared largely related to weight loss. Whether these changes translate into clinically meaningful impairments in muscle function or physical performance remains uncertain. Further studies in this field, including those looking at muscle function, strength or performance and using multivariate models considering confounding are needed to better reinforce the models and final findings.

Journal Article

A narrative systematic review of definitions and diagnostic criteria for disordered eating and eating disorders in type 1 diabetes.

AIMS/HYPOTHESIS: Type 1 diabetes and disordered eating (T1DE) affects 8-37.1% of adults and is associated with high rates of morbidity and mortality. The absence of a standardised case definition of T1DE and its severity hinders effective screening, diagnosis and treatment. This systematic review aimed to (1) synthesise existing case definitions and diagnostic criteria for T1DE in adults and (2) identify key characteristics to inform consensus for future diagnostic criteria. METHODS: A systematic review was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) guidelines. Eligible studies involved adults (&#x2265;18 years) with type 1 diabetes assessing disordered eating; paediatric studies, mixed samples without disaggregated data, non-empirical designs and non-English publications were excluded. PubMed, MEDLINE, EMBASE, CINAHL and PsycINFO were searched up to November 2025 for peer-reviewed studies involving adults with T1DE. Qualitative and quantitative data on definitions, diagnostic criteria and assessment tools were extracted. Study quality was appraised using a modified Graphical Appraisal Tool for Epidemiological studies (GATE) checklist. Due to heterogeneity of data, a narrative synthesis of findings was performed to describe current definitions of T1DE. RESULTS: Sixty-one studies met the inclusion criteria, with a pooled sample of 111,208 participants (76% women) from over 22 countries. T1DE was defined using a heterogeneous array of terms, diagnostic frameworks and assessment tools (29 distinct methods). The Diabetes Eating Problem Survey-Revised (DEPS-R) was the most used questionnaire, but many studies relied on criteria adapted from general eating disorder classifications or generic questionnaires. Approximately three-quarters of the studies assessed insulin omission behaviours, but the operationalisation of the cognitions for insulin omission varied widely. Beyond physiological markers such as HbA1c and BMI, studies explored various diabetes-related and psychological constructs, although often considering diabetes and disordered eating separately rather than as an integrated condition. CONCLUSIONS/INTERPRETATION: This systematic review highlights the lack of a unified, evidence-based definition of T1DE, resulting in inconsistent screening, diagnostic and reporting practices. Establishing clear, consistent, evidence-based diagnostic criteria and screening questionnaires for T1DE is critical to improving early detection and developing targeted interventions. These findings provide a foundation for refining T1DE definitions as a stepping stone to an international consensus definition. STUDY REGISTRATION: PROSPERO registration no. CRD420250223622 FUNDING: King's College London and King's College Hospital through the KMRT KCH Joint Research Committee studentship. This work was also conducted as part of the National Institute for Health Research (NIHR; CS-2017-17-023)-funded STEADY project (Safe management of people with Type 1 diabetes and EAting Disorders studY). NZ's salary was part-funded by the NIHR via the NIHR Clinician Scientist award to MS; JT and KI are part-funded by the NIHR Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. MS was funded through her NIHR Clinician Scientist Fellowship (CS-2017-17-023).

Humans

Using the OPTIMAL Theory to Optimize Aerodynamics in Respiratory Training for Healthy Adults and Individuals With Parkinson's Disease.

BACKGROUND: The OPTIMAL (Optimizing Performance Through Intrinsic Motivation and Attention for Learning) theory is a motor learning framework proposing that optimizing intrinsic motivation enhances motor performance and learning. The theory identifies three key components-Enhanced Expectancies (EE), Autonomy Support (AS) and External Focus of Attention (EF)-which facilitate more efficient, goal-directed movement. These components have been shown to improve motor outcomes in limb-based tasks; however, their application to respiratory training, particularly in clinical contexts such as voice and swallowing therapy in patients with Parkinson's disease (pwPD), has not yet been systematically explored. AIMS: This study aimed to investigate whether implementing OPTIMAL theory strategies during a respiratory muscle strength training (RMST) task improves immediate respiratory motor performance in healthy adults and pwPD. Additionally, we aimed to examine the effects of these strategies on motivation and cognitive engagement. METHODS: This quasi-randomized, single-session trial included 47 participants: Healthy CONTROL (n = 17), Healthy OPTIMAL (n = 16) and PD OPTIMAL (n = 14). Healthy participants were quasi-randomly assigned to either intervention or control conditions, whereas pwPD completed the intervention only. All participants completed a single respiratory session that included baseline, practice and retention phases. Outcome measures included peak expiratory flow, cough peak expiratory flow, cognitive engagement (EEG-based Cognitive Engagement Index) and self-administered motivation questionnaire. OUTCOMES AND RESULTS: Exhalation force improved from baseline to retention in the Healthy OPTIMAL group (baseline: M = 296 L/min; retention: M = 338 L/min; p < 0.001) and the PD OPTIMAL group (baseline: M = 315 L/min; retention: M = 370 L/min; p < 0.0001), but not in the Healthy CONTROL group (p > 0.05). No significant changes in cough strength were observed in any group. No correlations were found between cognitive engagement and exhalation force or motivation scores. However, motivation increased more in the Healthy OPTIMAL group (Questionnaire 1: M = 57.2; Questionnaire 2: M = 60.7) and the PD OPTIMAL group (Questionnaire 1: M = 60.1; Questionnaire 2: M = 62.8) than in the Healthy CONTROL group (Questionnaire 1: M = 61.1; Questionnaire 2: M = 62.5). CONCLUSIONS AND IMPLICATIONS: Implementing the OPTIMAL theory enhances immediate respiratory motor performance in both healthy participants and pwPD. OPTIMAL theory has clinical value in voice and swallowing therapy, although further research is needed to establish long-term efficacy and clinical impact. WHAT THIS PAPER ADDS: What is already known on the subject Motivation is a critical factor in rehabilitation. The OPTIMAL theory has been shown to improve both motivation and motor performance in limb-based tasks. Its impact on respiratory training, however, has not been previously examined. What this paper adds to the existing knowledge This study shows that applying OPTIMAL strategies during a respiratory muscle strength training task significantly improved peak expiratory flow in both healthy adults and people with Parkinson's disease. What are the potential or clinical implications of this work? Integrating the OPTIMAL theory principles into respiratory therapy may enhance motor outcomes, supporting voice, swallowing and cough rehabilitation.

Humans

Methods for defining equity-stratifying variables: a systematic review of validation studies.

BACKGROUND AND OBJECTIVE: Disease burden is often disproportionally higher among those who are socially disadvantaged by factors defined in the PROGRESS-Plus framework (ie, Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, and Social capital, with "Plus" covering features like age and disability). The accuracy and applicability of case definitions to identify these variables from administrative and clinical health data are unknown. We conducted a systematic review to explore how equity-stratifying variables, as categorized by the PROGRESS-Plus framework, have been defined and validated in epidemiologic studies using administrative health, population-level, or electronic health record (EHR) data. METHODS: Medline, EMBASE, CINAHL, Web of Science, and Google Scholar were searched from the inception of the databases to 2024 for validation studies of equity-stratifying variables in adults using administrative health datasets, health registries, or EHR data. Titles and abstracts, followed by relevant full-text articles, were screened in duplicate by two reviewers for eligibility. The data sources utilized, algorithms employed, and their associated performance measures were extracted and synthesized from included studies. Given substantial heterogeneity in study design, equity-stratifying variable definition, and performance metrics, meta-analysis was not possible. RESULTS: Of the 9099 unique citations screened, 188 full texts were reviewed and 116 were included in this review. Most studies were published between 2019 and 2024 (n = 64, 55%) and were validation studies of race/ethnicity definitions that used race/ethnicity codes or surname list algorithms (n = 66, 57%). No studies examined religion. Regarding the reported performance measure estimates, the race/ethnicity/culture/language equity-stratifying variables category had the largest variability across sensitivity, positive predictive value (PPV), and Cohen's Kappa. Occupation validation studies had the lowest variation in sensitivity and PPV. CONCLUSION: Despite an increasing number of publications reporting on the validation of equity-stratifying variables relevant to the PROGRESS-Plus framework, performance measures varied widely across studies. The significant heterogeneity in equity-stratifying variable definitions and methods used to validate them support the need for further rigorous validation of equity-stratifying variables in administrative and clinical health data. PLAIN LANGUAGE SUMMARY: Disease burden is often higher in people who experience financial hardships, lower level of education, discrimination due to race/ethnicity, and unstable housing. These social factors can be considered health equity factors and are important for understanding health inequalities. Health researchers often use large datasets, such as hospital or electronic health records (EHRs), to study these health equity factors. However, it is not clear how accurately these data sources capture information about people's social circumstances and how these factors are defined. In this study, we reviewed existing research to understand how health equity factors have been defined across health data sources and how accurate they are at measuring aspects of health equity and social disadvantage. Of the more than 9000 studies we identified, we included 116 that met our criteria for this systematic review. Most included studies focused on identifying race and ethnicity, often using codes or surname-based methods. We found that the accuracy of these methods varied widely across studies, meaning results may not always be reliable or comparable. Overall, our findings show that there are inconsistencies in how social factors are defined and measured in health data. This makes it difficult to fully understand and address health inequalities using routinely collected health data. More work is needed to develop and validate better quality and more consistent methods for capturing these important social factors.

Humans