Cryoanalgesia in Lung Transplantation – A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Background: Lung transplantation is a crucial treatment for end-stage lung diseases. However, postoperative pain management remains a significant challenge. Therefore, this study aims to examine the implications of adoption cryoanalgesia on lung transplantation pain control protocol. Methods: Three databases were searched for studies comparing cryoanalgesia versus standard of care analgesia in patients after lung transplantation. The primary outcome was opioid consumption throughout the entire hospitalization, at postoperative day (POD) 7 and at POD 14 addressed with Morphine Milligram Equivalents (MME). The secondary outcomes were maximum reported pain score at POD 7, hospital length of stay (LOS) and time until extubation. Mean differences (MDs) with 95% confidence intervals (CIs) were calculated for continuous outcomes. Results: A total of 5 studies encompassing 485 patients undergoing lung transplantation were included, of whom 228 underwent cryoanalgesia. Compared to standard of care, cryoanalgesia demonstrated significant reduction in opioid consumption at POD 7 (MD: -96.79 MME, 95% CI -183.40 to -10.18, p=0.03), at POD 14 (MD -225,26 MME; 95% CI -366.58 to -83.94; p<0.01) and throughout the entire hospitalization (MD: -307.76 MME, 95% CI -461.72 to -153.79, p<0.01). In addition, there was a significant reduction in pain scores in the cryoanalgesia group (MD: -1.10 points, 95% CI -1.77 to -0.43, p<0.01). However, no significant differences were found regarding hospital LOS or time until extubation. Conclusions: This meta-analysis indicates that cryoanalgesia effectively reduces opioid requirements and pain levels in lung transplant patients.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| 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".