Establishing Minimal Clinically Important Difference of Spinal Cord Stimulation Therapy in Post-Laminectomy Syndrome
Bibliographic record
Abstract
BACKGROUND: The concept of minimum clinically important difference (MCID) has been shown to be effective in spine surgery to differentiate between clinically insignificant and significant improvements as determined by the patient. OBJECTIVE: The MCID for spinal cord stimulation (SCS) to date has not been established. We sought to determine the MCID for SCS therapy for failed laminectomy syndromes. METHODS: Preoperative and 6-mo outcomes were assessed prospectively, including the Oswestry Disability Index (ODI), Beck Depression Inventory (BDI), and McGill and Visual Analog Survey questionnaires. Patients were asked: (1) are you satisfied with SCS therapy and (2) would you have the surgery again. Four methods of calculating the MCID were utilized. RESULTS: Forty-eight patients who underwent placement of an SCS between 2012 and 2014 were reviewed. The 4 calculation methods yielded a range of outcome scores (ODI 8.2-13.3, BDI 3.2-7, McGill 0.3-1.3, and Visual Analog Scale [VAS] 1.2-3.7). The maximum area under the curve was observed for the ODI, BDI, and VAS (0.73, 0.81, and 0.89, respectively), which signifies acceptable accuracy in distinguishing responders from nonresponders with the receiver operating characteristic method and suggests that VAS may be the most sensitive in determining meaningful change for the patient. CONCLUSION: The MCID for SCS placement was calculated using 4 different methods. The results are similar to calculations for the MCID for many lumbar and cervical procedures done for pain. Our results suggest that an improvement of 1.2 to 3.7 points on the VAS scale and 8.2 to 13.3 points on the ODI is clinically meaningful to the patient. Further defining the MCID for SCS therapy will remain of utmost importance in order to justify the cost of the procedure.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".