Low-back pain after lumbar discectomy for disc herniation: what can you tell your patient?
Bibliographic record
Abstract
OBJECTIVE: Lumbar discectomy (LD) is frequently performed to alleviate radicular pain resulting from disc herniation. While this goal is achieved in most patients, improvement in low-back pain (LBP) has been reported inconsistently. The goal of this study was to characterize how LBP evolves following discectomy. METHODS: The authors performed a retrospective analysis of prospectively collected patient data from the Canadian Spine Outcomes and Research Network (CSORN) registry. Patients who underwent surgery for lumbar disc herniation were eligible for inclusion. The primary outcome was a clinically significant reduction in the back pain numerical rating scale (BPNRS) assessed at 12 months. Binary logistic regression was used to model the relationship between the primary outcome and potential predictors. RESULTS: There were 557 patients included in the analysis. The chief complaint was radiculopathy in 85%; 55% of patients underwent a minimally invasive procedure. BPNRS improved at 3 months by 48% and this improvement was sustained at all follow-ups. LBP and leg pain improvement were correlated. Clinically significant improvement in BPNRS at 12 months was reported by 64% of patients. Six factors predicted a lack of LBP improvement: female sex, low education level, marriage, not working, low expectations with regard to LBP improvement, and a low BPNRS preoperatively. CONCLUSIONS: Clinically significant improvement in LBP is observed in the majority of patients after LD. These data should be used to better counsel patients and provide accurate expectations about back pain improvement.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".