Survey of lumbar discectomy practices: 10 years in the making
Bibliographic record
Abstract
Background: Lumbar discectomy is a common spinal procedure. The purpose of this survey is to ascertain neurosurgeons’ practices in the surgical management of one-level lumbar discectomies in the Canadian adult population and to determine changes over a 10-year period. Methods: One-page questionnaire distributed electronically to neurosurgeons in Canada and results were compared with similarly completed survey from 2007. Results: A total of 109 completed surveys were returned representing 43.8% response rate. This is compared to 112 completed surveys in 2007 reaching 64.4% response rate. Statistically significant differences between the two points in time were noted. There was an increase in spine fellowship training [26 (33.3%) 2017 vs. 15 (15.3%) 2007 (P=0.007)], use of pre-operative magnetic resonance imaging (MRI) [65 (83.3%) 2017 vs. 27 (27.6%) 2007] (P<0.001), use of intramuscular injection [58 (74.4%) 2017 vs. 43 (43.9%) 2007 (P<0.001)], use of both microscope and loupes [20 (25.6%) 2017 vs. 3 (3.1%) 2007 (P<0.001)], use of tubular retraction [26 (33.3%) 2017 vs. 12 (12.2%) 2007 (P=0.001)], use of fibrin glue for a durotomy [72 (92.3%) 2017 vs. 75 (76.5%) 2007 (P=0.007)]. There was an increased rate of same-day discharge in 2017 [46 (59.0%) vs. 18 (18.4%) 2007 (P<0.001)], and quicker return to work [62.8% in 6 weeks or less vs. 39.7% (P=0.003)]. No statistical differences were noted with pre-incision localization, pre-op antibiotics, pre-incision local anesthetic use, use of fat graft or epidural steroids. In either survey the majority would not perform lumbar discectomy on a patient whose primary complaint is back pain. Conclusions: Our survey identified changes in practice patterns amongst Canadian neurosurgeons with respect to performing one-level lumbar discectomy over the past 10 years. These changes include increased preference for minimally invasive surgical technique, same-day discharge and sooner return to work. Randomized trials would be helpful to provide evidence regarding which practices are associated with better outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".