The Association between Early Opioids Prescribing and the Length of Disability in Acute Lower Back Pain: A Systematic Review and Narrative Synthesis
Bibliographic record
Abstract
BACKGROUND: There is conflicting evidence with respect to whether early opioid prescribing (EOP) within the first two weeks of acute Low Back Pain (LBP) onset is associated with the length of disability (LOD). The aim of this systematic review was to examine the relationship between EOP and LOD in individuals with acute LBP. METHODS: A systematic search of Medline, EMBASE, and CINAHL was conducted. The Newcastle-Ottawa scale was used to assess the methodological quality of included studies. A narrative synthesis of findings was used owing to between-study heterogeneity. RESULTS: Six cohort studies using workers' compensation administrative data on 178,130 adults with LBP were included. Most studies were of good methodological quality. One study reported that LBP cases with EOP had higher LOD by 4 days than cases without EOP. Two studies reported that each 100 mg morphine equivalent amount (MEA) was associated with an increase in mean LOD by 0.4 day (95% confidence interval (CI): 0.3, 0.5) and 0.4 day (95% CI: 0.3, 0.4). One study showed that LBP cases with EOP had a higher hazard of continuation of time loss benefits by 1.94 (95% CI 1.86, 2.02). One study reported a dose-response relationship between MEA of EOP and LOD ranging between 5.2 days (95% CI 14.6, 25.0) for 1-140 mg MEA and 69.1 (95% CI 49.3, 89.0) for 450+ mg MEA. One study reported that LBP cases with EOP had a higher mean LOD by 3.8 days, but there was no statistically significant relationship between EOP and LOD (Hazard ratio 1.02; 95% CI 0.91, 1.13). CONCLUSIONS: The use of early opioid in the management of acute uncomplicated LBP is associated with prolonged disability duration. Further research on factors influencing inadequate adherence to evidence-based guidelines and optimal strategies to modify such factors may improve disability outcomes among patients presenting with acute LBP.
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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 | 0.016 | 0.079 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".