A comparison of pain scores and medication use in patients undergoing single-bundle or double-bundle anterior cruciate ligament reconstruction
Bibliographic record
Abstract
BACKGROUND: No gold standard exists for the management of postoperative pain following anterior cruciate ligament reconstruction (ACLR). We compared the pain scores and medication use of patients undergoing single-bundle (SB) or double-bundle (DB) ACLR in the acute postoperative period. Pain and medication use was also analyzed for spinal versus general anesthesia approaches within both surgery types. METHODS: We assessed 2 separate cohorts of primary ACLR patients, SB and DB, for 14 days postoperatively. We used a standard logbook to record self-reported pain scores and medication use. Pain was assessed using a 100 mm visual analogue scale (VAS). Medications were divided into 3 categories: oral opioids, oral nonsteroidal anti-inflammatories and acetaminophen. RESULTS: A total of 88 patients undergoing SB and 41 undergoing DB ACLR were included in the study. We found no significant difference in VAS pain scores between the cohorts. Despite similar VAS pain scores, the DB cohort consumed significantly more opioid and analgesia medication (p = 0.011). Patients who underwent DB with spinal anesthesia experienced significantly less pain over the initial 14-day postoperative period than those who received general anesthesia (p < 0.001). CONCLUSION: Adequate pain relief was provided to all ACLR patients in the initial postoperative period. Patients in the DB cohort experienced more pain, as evidenced by the significant diffrence in consumption of opioids and acetaminophen, than the SB cohort. Patients who underwent spinal anesthesia experienced less pain in the acute postoperative period than those who received general anesthesia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".