Short-term Effect of Transcutaneous Electrical Nerve Stimulation (TENS) on Pain in Patients with Bone Metastasis: An Uncontrolled Pretest-Posttest Study
Bibliographic record
Abstract
Objective: To evaluate the short-term effect of TENS on pain for patients with bone metastasis.Methods: An experimental descriptive study of 25 eligible advanced cancer patients with bone metastasis. Patients were enrolled in the study from June 1, 2018 to December 31, 2019. Pain intensity measurements were recorded at baseline prior to TENS application, then after 30 minutes and 60 minutes of TENS while the device was switched on. TENS was applied prior to radiotherapy at the same time every day for 5 days. Pain score was evaluated with the Visual Analogue Scale (VAS). Symptom assessment was measured by a Thai version of the Edmonton symptom assessment system (ESAS-Thai) on the first day prior to and five days after TENS application began. The paired t-test and Generalized Estimating Equations (GEE) were used analysis.Results: Mean VAS scores decreased by 1.08 (-1.08; 95% CI; -1.66 to 0.50, p < 0.001) and 1.82 (-1.82; 95 CI; -2.40 to 1.24, p < 0.001) after 30 and 60 minutes, respectively, compared to the baseline. Lower VAS scores were also correlated to the number of TENS visits. Mean ESAS scores showed a statistically significant difference before and after TENS application (before: 4.32 (95% CI: 3.60–5.03); after: 3.08 (95% CI: 2.61–3.54), p = 0.004). During TENS application there was a reduction in VAS pain scores over time.Conclusion: TENS is non-invasive, inexpensive and safe. It may be a useful adjunct to the multimodality treatment of pain and may reduce the need for morphine.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 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".