Early Prescription Opioid Use for Musculoskeletal Disorders and Work Outcomes
Bibliographic record
Abstract
OBJECTIVES: Musculoskeletal disorders (MSDs) are a common source of work disability. Opioid prescribing for MSDs has been on the rise, despite a lack of data on effectiveness. The objective of this study was to conduct a systematic review to determine whether early receipt of opioids is associated with future work outcomes among workers with MSDs compared with other analgesics, no analgesics, or placebo. METHODS: MEDLINE, EMBASE, CINAHL, and CENTRAL were searched from inception to 2014 and reference lists were scanned. Studies were included if opioids were prescribed within 12 weeks of MSD onset. Eligible outcomes included absenteeism, work status, receiving disability payments, and functional status. Two reviewers independently reviewed articles for relevance, risk of bias, and data extraction using standardized forms. Data synthesis using best evidence synthesis methods was planned. RESULTS: Five historical cohort studies met the inclusion criteria, all including workers filing wage compensation claims. Four studies demonstrated a significant association between early opioids and prolonged work disability. One study found a shorter time between prescriptions to be associated with shorter work disability. However, all studies were found to be at a high risk of bias and a best evidence synthesis could not be conducted. The main limitations identified were with exposure measurement and control of confounding. DISCUSSION: Current literature suggests that opioids provided within the first 12 weeks of onset of an MSD are associated with prolonged work disability. However, the conclusions of these studies need testing in a high-quality study that addresses the methodological shortcomings identified in the current review.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".