Electrical spinal cord stimulation in the long‐term treatment of chronic painful diabetic neuropathy
Bibliographic record
Abstract
AIMS: Electrical spinal cord stimulation (ESCS) is a technique for the management of chronic painful diabetic neuropathy (CPDN) affecting the lower limbs. We assessed the efficacy and complication rate of ESCS implanted at least 7 years previously in eight patients. METHODS: After a trial period of percutaneous stimulation, eight male patients had been implanted with a permanent system. Mean age at implantation was 53.5 years and all patients were insulin treated with stage 3 severe disabling CPDN of at least 1 year's duration. The ESCS was removed from one patient at 4 months because of system failure and one patient died 2 months after implantation from a myocardial infarction. RESULTS: Six patients were reviewed a mean of 3.3 years post-implantation. With the stimulator off, McGill pain questionnaire (MPQ) scores (a measure of the quality and severity of pain) were similar to MPQ scores prior to ESCS insertion. Pain scores (visual analogue scale) were measured with the stimulator off and on, respectively: background pain [74.5 (63-79) mm vs. 25 (17-33) mm, median (interquartile range), P = 0.03), peak pain (85 (80-92) mm vs. 19 (11-47) mm, P = 0.03]. There were two further cardiovascular deaths (these patients had continued pain relief) and the four surviving patients were reassessed at 7.5 (range 7-8.5) years: background pain [73 (65-77) mm vs. 33 (28-36) mm, median (interquartile range)], peak pain [86 (81-94) mm vs. 42 (31-53) mm]. Late complications (> 6 months post-insertion) occurred in two patients; electrode damage secondary to trauma requiring replacement (n = 1), and skin peeling under the transmitter site (n = 1). One patient had a second electrode implanted in the cervical region which relieved typical neuropathic hand pains. CONCLUSIONS: ESCS can continue to provide significant pain relief over a prolonged period of time with little associated morbidity.
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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 | 0.001 |
| 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) | 0.001 | 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".