<p>Postoperative analgesic effect of hydromorphone in patients undergoing single-port video-assisted thoracoscopic surgery: a randomized controlled trial</p>
Bibliographic record
Abstract
Objective: To study the general efficacy of hydromorphone as a systemic analgesic in postoperative pain management following single-port video-assisted thoracoscopic surgery (VATS) and to explore the optimal administration regimen. Methods: A prospective, randomized, double-blind study was designed and conducted in a tertiary hospital. In total, 157 valid patients undergoing single-port VATS were randomly allocated into three groups. A total of 53 patients received morphine bolus only for postoperative analgesia (Group Mb); 51 patients received a hydromorphone background infusion plus bolus (Group Hb + i), and 53 patients received a hydromorphone bolus only (Group Hb). The primary outcomes were patient-reported static and dynamic pain levels; the secondary outcomes included side effects, sleep quality, and recovery indexes. Results: Patients in Group Hb + i experienced lower pain intensity (approximately 10 out of 100 on the visual analog scale) in both static pain and dynamic pain in the days following surgery ( P <0.01), better sleep quality during the first night only ( P =0.002), and a higher satisfaction level than those in the other two groups ( P =0.006). A comparison of these variables in Group Mb and Group Hb resulted in no significant differences. Lastly, side effects and recovery indexes remained the same among bolus-only groups and bolus-plus-background-infusion groups. Conclusion: There is no advantage to administering hydromorphone over morphine using bolus only mode. Within 24 h after surgery, a background infusion should be considered as a part of a standard protocol for patient-controlled intravenous analgesia. At 24 h after surgery, the background infusion should be adjusted in accordance with patient preferences and pain intensity. Keywords: morphine, background infusion, sleep quality, patient satisfaction
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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 | 0.070 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".