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E048 Obesity is related to poorer functional outcomes among individuals with radiographic knee osteoarthritis: findings from the Hertfordshire Cohort Study

2025· article· en· W4409899119 on OpenAlexaboutno aff
Faidra Laskou, Leo D. Westbury, Fiona Kirkham-Wilson, Gregorio Bevilacqua, Elaine Dennison

Bibliographic record

VenueLara D. Veeken · 2025
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsOsteoarthritisMedicineCohortObesityCohort studyPhysical therapyRadiographyInternal medicineSurgeryAlternative medicinePathology

Abstract

fetched live from OpenAlex

Abstract Background/Aims Osteoarthritis (OA) is one of the most prevalent musculoskeletal conditions and a major contributor to years lived with disability. Obesity is an established risk factor for OA. Although OA patients are advised to maintain a healthy weight, this is often challenging, especially when pain limits activity. We examined relationships between obesity and functional outcomes in older community-dwelling adults with radiographic knee OA. Methods We studied 101 men and 115 women, aged 71-80, from the UK Hertfordshire Cohort Study. Participants completed a questionnaire that ascertained information on health-related quality of life (EuroQol-5D) and pain (Western Ontario and McMaster Universities Osteoarthritis Index [WOMAC]). Knee radiographs were taken and classified according to Kellgren and Lawrence (K&L) criteria; analysis was restricted to individuals with radiographic knee OA (K&L score ≥2 on either knee). Balance, walking, and chair rise scores were assigned, depending on performance, and used to derive the Guralnik physical performance score. Logistic and ordinal logistic regression were used to examine obesity status in relation to functional outcomes after adjustment for age and sex. Results Prevalence of obesity (BMI≥30kg/m2) was 26.7% among men and 44.3% among women. Odds of having a higher Guralnik score were lower among obese participants compared to those who were not (p < 0.001). Obesity (yes vs no) was associated with greater odds of reporting at least some problems in the following EuroQol domains: mobility (odds ratio [95% CI]: 4.73 [2.52, 8.85], p < 0.001); self-care (3.40 [1.44, 8.02], p = 0.005); usual activities (4.38 [2.31, 8.30], p < 0.001); and pain (2.27 [1.24, 4.15], p = 0.008). Obesity was also related to increased odds of having a WOMAC pain score > 0 (2.21 [1.24, 3.95], p = 0.007). Conclusion These findings highlight the strong relationships between obesity and functional outcomes in individuals with OA. These results stress the crucial need for support in managing excess adiposity, to reduce the potential degree of resulting disability. Disclosure F. Laskou: Grants/research support; NIHR Southampton Biomedical Research Centre, Nutrition, and the University of Southampton. L. Westbury: None. F. Kirkham-Wilson: None. G. Bevilacqua: None. N.O. Fuggle: None. E. Dennison: Consultancies; Pfizer, UCB and Lilly.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.215

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.008
GPT teacher head0.234
Teacher spread0.226 · 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 designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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