Effect of Osteoarthritis on Work Participation and Loss of Working Life–years
Bibliographic record
Abstract
OBJECTIVE: To examine to what extent disabling osteoarthritis (OA), leading to a prolonged sickness absence (SA), interferes with work participation and shortens working life-years. METHODS: A total of 4704 wage earners aged 30 to 59 years, whose SA due to OA started in 2006, were followed until October 31, 2014. Kaplan-Meier analysis was used to plot sustained (at least 28 consecutive days) return-to-work curves. The associations of potential determinants with early exit from paid employment were examined applying Cox proportional hazards regression analysis. Years expected to be spent in different work participation statuses until statutory retirement age were estimated based on daily work participation statuses using adapted Sullivan method. RESULTS: Persons with knee OA showed the fastest, and persons with hip OA the slowest, sustained return to work. Although most participants typically were at work during the first year of followup, a considerable proportion was permanently retired. Male sex, older age, low education, long initial SA, and having not returned to work sustainably, as well as receiving vocational rehabilitation, predicted early exit from paid employment during the followup. Overall, only 45-53% of potential working life-years were estimated to be spent at work, being highest for the oldest age group. CONCLUSION: Our study showed a considerable effect of OA on work participation and working life duration. Clinicians should avoid prescription of long SA or temporary work disability due to OA without a clear treatment or return-to-work plan.
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 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.003 | 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".