Chronic Gabapentinoid Use and Lumbar Fusion Outcomes
Bibliographic record
Abstract
STUDY DESIGN: Retrospective comparative cohort study. OBJECTIVES: To examine the effects of chronic use of gabapentinoids (GPs) (alone or with opioids) on the outcomes of lumbar fusions. SUMMARY OF BACKGROUND DATA: Opioids have historically been the mainstay medications for pain management, but the ongoing opioid epidemic led physicians to look for alternatives. GPs are used for various indications, and chronic use for any indication may lead to a higher risk of adverse events, especially when combined with opioids. MATERIALS AND METHODS: Patients aged 18 years and older who underwent posterior fusion of the lumbosacral spine and ≥1-year follow-up were included. Patients were grouped according to their preoperative chronic GP and opioid usage as GP and opioid nonuser (-/-), GP user opioid nonuser (+/-), GP nonuser and opioid user (-/+), and GP and opioid user (+/+). RESULTS: A total of 563 patients (M/F%=41/59, mean age 61.1 y) were included. Two hundred eighty (49%) patients were in the group -/-, while 110 (19%) were in +/-, 78 (15%) were in -/+, and 95 (17%) were in +/+. For ODI, back pain and leg pain, +/+ had the worst outcomes at all time points, while -/- had the best. Chronic GP users (+/-) showed back pain improvement similar to the -/- group; however, the improvements in leg pain and ODI were considerably less. GP use resulted in increased postoperative opioid requirements, although not as much as chronic opioid use. Complication rates were similar. CONCLUSIONS: Chronic preoperative use of GPs may lead to inferior outcomes when compared with GP-naive patients, and this is significantly accentuated when taken concurrently with opioids. Patients who are using both GPs and opioids had the worst results for almost every outcome measure. Given the significantly worse surgical outcomes documented in this study, concurrent use with opioids should be avoided.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".