P.133 Minimally invasive MetrX microdiskectomy for lumbar disc herniation: review of long-term outcomes
Bibliographic record
Abstract
Background: Lumbar microdiskectomy is amongst the most common neurosurgical techniques. In Saskatoon, minimally invasive microdiskectomy using the MetrX tubular retractor system has become a routinely performed procedure. While the outcomes of microdiskectomy are known to be similar to open technique, long term outcomes have not been reported. Methods: We performed a retrospective study of 160 minimally invasive microdiskectomies. We excluded subjects with cauda equina syndrome, redo surgery, fusions, and multi-level decompressions. We used one-way ANOVA to compare VAS, ODI, SF36, and EQ5D scores at pre-operative, 6-week postoperative, and long-term timepoints. Results: The mean pre-operative back pain VAS score was 6.23+/−2.63, 6-week post-operative follow-up VAS was 3.21+/−2.49, and long-term follow-up VAS was 2.56+/−2.45. The mean preoperative leg pain VAS score was 7.66+/−1.99, 6-week follow-up VAS was 3.56+/−2.79, final follow-up VAS was 2.20+/−2.57. The mean preoperative ODI score was 60.41+/−13.97; falling to 32.54+/−20.57 at 6-week follow up, and further to 24.50+/−20.97 at long term follow up. The mean baseline EQ5D quality of life score was 46.4+/−18.1, 68.9+/−20.2 at 6-week follow up and 69.3+/−20.3 at final review. Data reached statistical significance. Conclusions: We report good outcomes for minimally invasive microdiskectomy that are as durable as published results using open technique.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".