Effect of Cryotherapy on Pain Quality and Intensity among Patients with Thoracotomy after Chest Tube Removal
Bibliographic record
Abstract
Background: Chest tubes removal (CTR) described as one of the worst feeling for critical ill patients after thoracotomy. Unrelieved pain causes undesired consequences that had adverse effects on patient quality of care. CTR pain usually managed by analgesics, but patient showed different responses to drugs and might not provide complete relaxation.Aim: This study aims to assess the effect of cryotherapy on pain quality and intensity among patients with thoracotomy after chest tube removal. Methods: Quasi-experimental design (study & control) was utilized in this study. This study conducted in the cardio-thoracic critical care units at Cardiovascular and Thoracic Academy affiliated to Ain Sham University Hospital. A purposive sample of patients undergoing thoracotomy was included in this study. They were divided into control group and study group (70 patients in each group). Data were collected using three tools; a structured interviewing questionnaire, Standardized Linear Scale for Pain Assessment and Modified McGill Pain Questionnaire-Short Form (MPQ-SF).Results: The results reveals that 50%, 67.1% of the control and study group patients were in age group from 51-≥60 years. 62.9 and 81.4% of the control and study group were males. 42.9% of both groups were highly educated. A statistically significant differences were found between study and control group regarding pain quality immediately and after 30 minutes of cryotherapy applied after chest tube removal in terms of sensory and affective descriptors. Also, a highly significant difference was found between study and control groups regarding pain intensity immediately and 30 minutes after cryotherapy applied after chest tube removal. Conclusion: cryotherapy application was useful for improving pain quality and relieving intensity of pain among patients with thoracotomy after application of cryotherapy following chest tube removal. Recommendations: Encourage nurses in critical care settings to make decision about applying cryotherapy as a nonpharmacological modality for reliving chest tube removal pain
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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 | 0.000 |
| 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) | 0.000 | 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".