The Use of Transcutaneous Electrical Nerve Stimulation (TENS) in a Major Cancer Center for the Treatment of Severe Cancer-Related Pain and Associated Disability
Bibliographic record
Abstract
BACKGROUND: Cancer pain is difficult to treat, often requiring a multimodal approach. While medication management remains the mainstay for the treatment of cancer pain, medications are often associated with undesired side effects. Transcutaneous electrical nerve stimulation (TENS) provides a potential adjunctive method for treating cancer pain with minimal side effects. OBJECTIVE: Few studies have been performed evaluating the efficacy of TENS on cancer pain. We sought to examine the usefulness of TENS on all cancer patients and to specifically look at the use of TENS as a goal-directed therapy to improve functionality. DESIGN: Retrospective cohort study. METHODS: Since 2008, patients with chronic cancer pain and on multimodal pain regimens were trialed with TENS. Those patients who showed an improvement in pain symptoms or severity were educated about and provided with a TENS unit for use at home. Pain symptoms and scores were monitored with the visual analog scale (VAS), the numerical rating pain (NRP) scale, and Short-Form McGill Questionnaire at the start of TENS treatment and at 2 months follow-up. RESULTS: TENS proved beneficial in 69.7% of patients over the course of 2 months. In TENS responsive patients, VAS scores decreased by 9.8 on a 0-100 mm scale (P < 0.001), and NRP scores decreased by 0.8 on a 1-10 scale (P < 0.001). LIMITATIONS: Lack of placebo and lack of blinding of physician and patient. CONCLUSIONS: TENS provides a beneficial adjunct for the treatment of cancer pain, especially when utilized as a goal-directed therapy.
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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 | 0.001 | 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) | 0.000 | 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".