Minimally Invasive vs. Open Surgery for Lumbar Spinal Stenosis in Patients with Diabetes – A Canadian Spine Outcomes and Research Network Study
Bibliographic record
Abstract
Study Design Retrospective cohort. Objectives To compare outcomes of minimally invasive surgery (MIS) vs open surgery (OPEN) for lumbar spinal stenosis (LSS) in patients with diabetes. Methods Patients with diabetes who underwent spinal decompression alone or with fusion for LSS within the Canadian Spine Outcomes and Research Network (CSORN) database were included. MIS vs OPEN outcomes were compared for 2 cohorts: (1) patients with diabetes who underwent decompression alone (N = 116; MIS n = 58 and OPEN n = 58), (2) patients with diabetes who underwent decompression with fusion (N = 108; MIS n = 54 and OPEN n = 54). Modified Oswestry Disability Index (mODI) and back and leg pain were compared at baseline, 6–18 weeks, and 1-year post-operation. The number of patients meeting minimum clinically important difference (MCID) or minimum pain/disability at 1-year was compared. Results MIS approaches had less blood loss (decompression alone difference 100 mL, P = .002; with fusion difference 244 mL, P < .001) and shorter length of stay (LOS) (decompression alone difference 1.2 days, P = .008; with fusion difference 1.2 days, P = .026). MIS compared to OPEN decompression with fusion had less patients experiencing adverse events (AEs) (difference 13 patients, P = .007). The MIS decompression with fusion group had lower 1-year mODI (difference 14.5, 95% CI [7.5, 21.0], P < .001) and back pain (difference 1.6, 95% CI [.6, 2.7], P = .002) compared to OPEN. More patients in the MIS decompression with fusion group exceeded MCID at 1-year for mODI (MIS 75.9% vs OPEN 53.7%, P = .028) and back pain (MIS 85.2% vs OPEN 70.4%, P = .017). Conclusions MIS approaches were associated with more favorable outcomes for patients with diabetes undergoing decompression with fusion for LSS.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".