Pain intensity and opioid consumption after temporary and permanent peripheral nerve stimulation: a 2-year multicenter analysis
Bibliographic record
Abstract
OBJECTIVE: Peripheral nerve stimulation (PNS) is an emerging neuromodulation modality, yet there remains limited data highlighting its long-term effectiveness. The objective of this study was to report real-world data on pain intensity and opioid consumption after temporary and permanent PNS for chronic pain up to 24 months postimplantation. METHODS: A retrospective study was conducted on all patients who received PNS implants at a multi-centered enterprise between January 1, 2014 and February 24, 2022. The two co-primary outcomes were: (1) change in pain intensity (11-point Numerical Rating Scale) from baseline to 12 months postimplant; and (2) comparison of the change in pain intensity between temporary and permanent PNS cohorts 12 months postimplant. RESULTS: 126 patients were included in this analysis. Pain intensity significantly decreased 12 months postimplant in the overall cohort (mean difference (MD) -3.0 (95% CI -3.5 to -2.4), p<0.0001). No significant difference in this reduction was identified between temporary and permanent PNS cohorts (MD 0.0 (95% CI -1.1 to 1.0), p=1.00) 12 months postimplantation. Pain intensity significantly decreased in the overall, temporary, and permanent cohorts at all secondary time points (3, 6, and 24 months). No change in daily opioid consumption was observed at 6 and 12 months postimplant in the overall cohort. CONCLUSION: This study found that both temporary and permanent PNS may be effective for reducing pain intensity in patients with chronic pain up to 24 months postimplantation, although no changes in opioid consumption were observed. The decrease in pain intensity was comparable between patients receiving temporary versus permanent implants, highlighting that temporary PNS may achieve long-lasting clinical benefits. However, given the substantial loss to follow-up, further large-scale studies are needed to solidify conclusions about the efficacy of PNS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| 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) | 0.000 | 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".