CNE Article: Pain After Lung Transplant: High-Frequency Chest Wall Oscillation vs Chest Physiotherapy
Bibliographic record
Abstract
Background Chest physiotherapy and high-frequency chest wall oscillation (HFCWO) are routinely used after lung transplant to facilitate removal of secretions. To date, no studies have been done to investigate which therapy is more comfortable and preferred by lung transplant recipients. Patients who have less pain may mobilize secretions, heal, and recover faster. Objectives To compare effects of HFCWO versus chest physiotherapy on pain and preference in lung transplant recipients. Methods In a 2-group experimental, repeated-measures design, 45 lung transplant recipients (27 single lung, 18 bilateral) were randomized to chest physiotherapy (10 AM, 2 PM) followed by HFCWO (6 PM, 10 PM; group 1, n=22) or vice versa (group 2, n=23) on postoperative day 3. A verbal numeric rating scale was used to measure pain before and after treatment. At the end of the treatment sequence, a 4-item patient survey was administered to assess treatment preference, pain, and effectiveness. Data were analyzed with χ(2) and t tests and repeated-measures analysis of variance. Results A significant interaction was found between mean difference in pain scores from before to after treatment and treatment method; pain scores decreased more when HFCWO was done at 10 AM and 6 PM (P =.04). Bilateral transplant recipients showed a significant preference for HFCWO over chest physiotherapy (11 [85%] vs 2 [15%], P=.01). However, single lung recipients showed no significant difference in preference between the 2 treatments (11 [42%] vs 14 [54%]). Conclusions HFCWO seems to provide greater decreases in pain scores than does chest physiotherapy. Bilateral lung transplant recipients preferred HFCWO to chest physiotherapy. HFCWO may be an effective, feasible alternative to chest physiotherapy. (American Journal of Critical Care. 2013;22:115-125).
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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 | 0.000 | 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) | 0.001 | 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".