Dorsal root ganglion stimulation for <scp>chemotherapy‐induced</scp> peripheral neuropathy
Bibliographic record
Abstract
BACKGROUND: Chemotherapy-induced peripheral neuropathy (CIPN) is a common consequence of cancer treatment that can be persistent and difficult to manage. Dorsal root ganglion stimulation (DRG-S) is a recently introduced but understudied treatment modality. This study explored the effect of DRG-S on pain and symptom burden associated with CIPN. METHODS: Patients with CIPN who underwent a DRG-S trial between January 2017 and August 2022 were identified through chart review after IRB approval was obtained. Demographic data, procedure details, pre-and postoperative scores, including the Numerical Rating Scale (NRS) and Edmonton Symptom Assessment System (ESAS), and duration of follow-up were recorded. Statistical analysis included descriptive statistics and paired t-tests to compare pre-and postoperative scores. RESULTS: Nine patients with an even mix of solid and hematologic malignancies underwent DRG-S trial and had a statistically significant decrease in NRS scores, with a mean reduction of 2.3 in their average pain (p = 0.014), 2.6 in worst pain (p = 0.023), and 2.1 in least pain (p = 0.018). Eight patients (88.9%) underwent permanent DRG-S implantation. Mean NRS scores remained lower than preoperative baselines through the first year of follow-up. Statistically significant reductions were noted at 3 months in average (2.1, p = 0.006) and least pain scores (1.9, p = 0.045), which further decreased after 6-12 months (average: 3.6, p = 0.049; least: 3.4, p = 0.023). Only the pain component of ESAS scores showed a significant reduction with DRG-S (2.0, p = 0.021). All patients endorsed improved sensation, 75% decreased their pain medication usage, and 37.5% reported complete pain relief by 2 years. CONCLUSION: Dorsal root ganglion stimulation can be an effective treatment for pain related to CIPN and deserves further investigation.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".