Physiotherapy intervention on changes in post-chemotherapy sensibility with taxanes
Bibliographic record
Abstract
Abstract OBJECTIVE: Evaluate the presence of changes in post-chemotherapy sensibility with Taxane and the efficiency of a physiotherapy intervention that aims at the improvement of this condition. METHODS: We conducted an uncontrolled, longitudinal quantitative and prospective study on 23 patients. Four were not included in the study for not showing changes in sensibility or having a skin condition that rendered the evaluation impossible. The patients responded to the McGill and FACT G-Taxane questionnaires after the sensibility evaluation with a Semmes-Weinstein esthesiometer, an intervention session using a Peridell® therapeutic massager and a subsequent sensibility revaluation. RESULTS: Two regions with the best responses to the intervention were the dermatomes L5 and S1, with initial means of 5.33 and 5.53 and final means of 5.64 and 5.78, respectively (p = 0.012 e 0.020). The general analysis for both superior and inferior limbs showed an increase in the means, with an initial mean of 5.69 and a final mean of 5.81 (p = <0.001). There was a negative correlation between FACT G-Taxane and the McGill Questionnaire (-0.738 e p = <0.001). CONCLUSION: Vibratory stimulus of Peridell® therapeutic massager showed a significant improvement of changes in sensibility on the region of the dermatomes L5 and S1, especially on milder changes. The correlation between FACT G-Taxane and the McGill questionnaire suggests that the more pain the patient feels, there is less life quality and there are more symptoms of toxicity.
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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 | 0.002 |
| 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) | 0.003 | 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".