Opioid Use Prior to Adult Spine Deformity Correction Surgery is Associated With Worse Pre- and Postoperative Back Pain and Prolonged Opioid Demands
Bibliographic record
Abstract
Study Design Prospective multicenter database post-hoc analysis. Objectives Opioids are frequently prescribed for painful spinal conditions to provide pain relief and to allow for functional improvement, both before and after spine surgery. Amidst a current opioid epidemic, it is important for providers to understand the impact of opioid use and its relationship with patient-reported outcomes. The purpose of this study was to evaluate pre-/postoperative opioid consumption surrounding ASD and assess patient-reported pain outcomes in older patients undergoing surgery for spinal deformity. Methods Patients ≥60 years of age from 12 international centers undergoing spinal fusion of at least 5 levels and a minimum 2-year follow-up were included. Patient-reported outcome scores were collected using the Numeric Rating Scale for back and leg pain (NRS-B; NRS-L) at baseline and at 2 years following surgery. Opioid use, defined based on a specific question on case report forms and question 11 from the SRS-22r questionnaire, was assessed at baseline and at 2-year follow-up. Result Of the 219 patients who met inclusion criteria, 179 (81.7%) had 2-year data on opioid use. The percentages of patients reporting opioid use at baseline (n = 75, 34.2%) and 2 years after surgery (n = 55, 30.7%) were similar ( P = .23). However, at last follow-up 39% of baseline opioid users (Opi) were no longer taking opioids, while 14% of initial non-users (No-Opi) reported opioid use. Regional pre- and postoperative opioid use was 5.8% and 7.7% in the Asian population, 58.3% and 53.1% in the European, and 50.5% and 40.2% in North American patients, respectively. Baseline opioid users reported more preoperative back pain than the No-Opi group (7.0 vs 5.7, P = .001), while NRS-Leg pain scores were comparable (4.8 vs 4, P = .159). Similarly, at last follow-up, patients in the Opi group had greater NRS-B scores than Non-Opi patients (3.2 vs 2.3, P = .012), but no differences in NRS-Leg pain scores (2.2 vs 2.4, P = .632) were observed. Conclusions In this study, almost one-third of surgical ASD patients were consuming opioids both pre- and postoperatively world-wide. There were marked international variations, with patients from Asia having a much lower usage rate, suggesting a cultural influence. Despite both opioid users and nonusers benefitting from surgery, preoperative opioid use was strongly associated with significantly more back pain at baseline that persisted at 2-year follow up, as well as persistent postoperative opioid needs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".