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Record W4225632118 · doi:10.1159/000521241

Definition and Diagnostic Criteria for Sarcopenic Obesity: ESPEN and EASO Consensus Statement

2022· article· en· W4225632118 on OpenAlexaff
Lorenzo M. Donini, Luca Busetto, Stephan C. Bischoff, Tommy Cederholm, María D. Ballesteros‐Pomar, John A. Batsis, Yves Boirie‌, Alfonso J. Cruz‐Jentoft, Dror Dicker, Stefano Frara, Gema Frühbeck, Laurence Genton, Yftach Gepner, Marı́a Cristina González, Ho‐Seong Han, Steven B. Heymsfield, Takashi Higashiguchi, Alessandro Laviano, Andrea Lenzi, Ibolya Nyulasi, Edda Parrinello, Eleonora Poggiogalle, Carla M. Prado, Javier Salvador, Yves Rolland, Ferruccio Santini, Mireille J. Serlie, Hanping Shi, Cornel Sieber, Mario Siervo, Roberto Vettor, Dennis T. Villareal, Dorothee Volkert, Jianchun Yu, Mauro Zamboni, Rocco Barazzoni

Bibliographic record

VenueObesity Facts · 2022
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversity of Alberta
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsSarcopenic obesityMedicineSarcopeniaObesityWaistBody mass indexInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Loss of skeletal muscle mass and function (sarcopenia) is common in individuals with obesity due to metabolic changes associated with a sedentary lifestyle, adipose tissue derangements, comorbidities (acute and chronic diseases) and during the ageing process. Co-existence of excess adiposity and low muscle mass/function is referred to as sarcopenic obesity (SO), a condition increasingly recognized for its clinical and functional features that negatively influence important patient-centred outcomes. Effective prevention and treatment strategies for SO are urgently needed, but efforts are hampered by the lack of a universally established SO definition and diagnostic criteria. Resulting inconsistencies in the literature also negatively affect the ability to define prevalence as well as clinical relevance of SO for negative health outcomes. AIMS AND METHODS: The European Society for Clinical Nutrition and Metabolism (ESPEN) and the European Association for the Study of Obesity (EASO) launched an initiative to reach expert consensus on a definition and diagnostic criteria for SO. The jointly appointed international expert panel proposes that SO is defined as the co-existence of excess adiposity and low muscle mass/function. The diagnosis of SO should be considered in at-risk individuals who screen positive for a co-occurring elevated body mass index or waist circumference, and markers of low skeletal muscle mass and function (risk factors, clinical symptoms, or validated questionnaires). Diagnostic procedures should initially include assessment of skeletal muscle function, followed by assessment of body composition where presence of excess adiposity and low skeletal muscle mass or related body compartments confirm the diagnosis of SO. Individuals with SO should be further stratified into stage I in the absence of clinical complications or stage II if cases are associated with complications linked to altered body composition or skeletal muscle dysfunction. CONCLUSIONS: ESPEN and EASO, as well as the expert international panel, advocate that the proposed SO definition and diagnostic criteria be implemented into routine clinical practice. The panel also encourages prospective studies in addition to secondary analysis of existing data sets, to study the predictive value, treatment efficacy and clinical impact of this SO definition.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.036
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.036
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0100.004
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0070.005
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0030.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.086
GPT teacher head0.355
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations880
Published2022
Admission routes1
Has abstractyes

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