Efficacy and safety of local ozone injection through the surgical incision for postoperative pain in patients undergoing VATS-assisted pulmonary lobectomy：a randomized controlled trial
Bibliographic record
Abstract
Abstract Background Perioperative analgesia can improve the quality of postoperative recovery in thoracoscopic patients. Nevertheless, traditional analgesic effects are not ideal. Therefore, we intend to afford a fresh approach to managing postoperative pain in patients by dint of probe into the efficacy and safety of local ozone injection.Methods The sequence marked 87 patients subject to downwards video-assisted thoracoscopic lobectomy, divided into the ozone group (n = 44) and control group (n = 43). Primary observation indexes included the resting pain visual analog scale at 6 h, 24 h, 48 h, and 72 h as well as the postoperative three-month simplified McGill pain questionnaire. The statistical software SPSS 20.0 was used to analyse the similarity and dissimilarity in data.Results The Visual Analogue Scale scores (6 h, 24 h, 48 h, 72 h) of the ozone group after surgery were allegedly lower than those of the control group (p < 0.01). However, there were no significant differences in the sensory item score and affective item score in Pain Rating Index, Visual Analogue Scale score, or Present Pain Intensity score between the two groups in the third month after surgery (p > 0.05).Conclusions Local ozone injection for video-assisted thoracoscopic pulmonary lobectomy effectively lowers postoperative pain scores, facilitates incision healing, reduces postoperative acute adverse reactions, and enhances patients' short-term quality of life after surgery. Therefore, local ozone injection through a surgical incision is practical, safe, and feasible for postoperative pain relief in patients undergoing thoracoscopic lobectomy.Trial Registration ChiCTR2000037691(http://www.chictr.org.cn/showproj.aspx?proj=59038)registered on 30/8/2020
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".