Age as an Independent Predictor of Adult Spinal Cord Stimulation Pain Outcomes
Bibliographic record
Abstract
INTRODUCTION: Spinal cord stimulation (SCS) is an efficacious chronic pain treatment most commonly used in middle-aged patients. Results from previous studies that investigated SCS' effects in older patient populations have been equivocal. We examine whether SCS outcomes correlate with age. METHODS: We retrospectively examined prospectively collected outcomes from 189 patients who underwent SCS at Albany Medical Center between 2012 and 2020. The patients completed the Numerical Rating Scale (NRS), McGill Pain Questionnaire (MPQ), Oswestry Disability Index (ODI), Beck Depression Inventory (BDI), and Pain Catastrophizing Scale (PCS) preoperatively and 1 year postoperatively. The mean percent change in each outcome was determined and compared via a regression analysis to determine relationships between patient age and each respective outcome metrics. Demographics were compared between patients aged under 65 versus those aged 65 and older via χ2 tests. RESULTS: All subjects demonstrated the expected improvement on NRS, BDI, PCS, and MPQ from baseline to 1-year follow-up, with several demonstrating statistically significant changes: NRS-worst pain (18.66%, p < 0.001), NRS-least pain (26.9%, p < 0.001), NRS-average pain (26.9%, p < 0.01), NRS-current pain (26.4%, p < 0.001), ODI (19.6%, p < 0.001), PCS (29.8%, p < 0.001), and MPQ (29.4%, p < 0.001). There was no significant difference between patients aged under 65 versus those aged 65 and older based on lead type (p = 0.454). Six patients (3.1%) had lead migration, one of whom was 65 or older. Regression analysis revealed improvements in MPQ-sensory and MPQ-affective scores as age increased (p < 0.001, R2 = 0.09; p = 0.046, R2 = 0.05, respectively). Age did not correlate with NRS, ODI, BDI, or PCS. Diagnosis, spinal level of SCS, and lead type were not found to influence any respective outcome measure based on covariate analysis. CONCLUSION: This study represents the largest study where age was correlated to specific pain, depression, and disability outcomes following SCS. We provide evidence that SCS outcomes are equivalent, or better, in older patients following SCS. Based on these findings, SCS is a viable option for treatment of chronic pain in elderly patient populations.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".