Effectiveness of an Intervention (Effleurage and Petrissage) on severity of Chemotherapy Induced Peripheral Neuropathy (CIPN) among patients : a pilot randomized controlled trial
Bibliographic record
Abstract
Background: Chemotherapy-induced peripheral neuropathy (CIPN) is a dose-dependent, nerve-damaging adverse reaction with reported prevalence rates of 68.1% at the first month after starting chemotherapy; 60.0 % at the third month; and 30% at the sixth month. Purpose: To determine the effectiveness of an intervention (effleurage and petrissage) on severity of CIPN among patients receiving platinum-based chemotherapy. Methods: Sixty patients receiving either a third or fourth cycle of platinum-based chemotherapy were randomly assigned to one of two groups with a pre- and post-test design. The interventional group received effleurage and petrissage prior to chemotherapy for a period of one month. Comparisons of CIPN levels among both groups were done at Day 7, 14, 21, and 1 month using the FACT/ GOG-Ntx subscale. Results: Prior to intervention, the mean score (+SD) of CIPN in the intervention group was 17.17 (+4.907) and 17.10 (+ 4.421) in the control group (T = 0.055, P value 0.956). The post-test scores following intervention at 1 month, was a mean score (+SD) for CIPN in the intervention group of 10.70 (±2.855) and 16.27 (±3.039) in the control group (P value 0.000). Conclusions: This pilot result supports that the intervention (effleurage and petrissage) can be effective in reducing CIPN severity levels among patients receiving platinum-based chemotherapy.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".