Association Between Osteoarthritis and Social Isolation: Data From the EPOSA Study
Bibliographic record
Abstract
OBJECTIVE: To determine whether there is an association between osteoarthritis (OA) and incident social isolation using data from the European Project on OSteoArthritis (EPOSA) study. DESIGN: Prospective, observational study with 12 to 18 months of follow-up. SETTING: Community dwelling. PARTICIPANTS: Older people living in six European countries. MEASUREMENTS: Social isolation was assessed using the Lubben Social Network Scale and the Maastricht Social Participation Profile. Clinical OA of the hip, knee, and hand was assessed according to American College of Rheumatology criteria. Demographic characteristics, including age, sex, multijoint pain, and medical comorbidities, were assessed. RESULTS: Of the 1967 individuals with complete baseline and follow-up data, 382 (19%) were socially isolated and 1585 were nonsocially isolated at baseline; of these individuals, 222 (13.9%) experienced social isolation during follow-up. Using logistic regression analyses, after adjustment for age, sex, and country, four factors were significantly associated with incident social isolation: clinical OA, cognitive impairment, depression, and worse walking time. Compared to those without OA at any site or with only hand OA, clinical OA of the hip and/or knee, combined or not with hand OA, led to a 1.47 times increased risk of social isolation (95% confidence interval = 1.03-2.09). CONCLUSION: Clinical OA, present in one or two sites of the hip and knee, or in two or three sites of the hip, knee, and hand, increased the risk of social isolation, adjusting for cognitive impairment and depression and worse walking times. Clinicians should be aware that individuals with OA may be at greater risk of social isolation. J Am Geriatr Soc 68:87-95, 2019.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".