Patient‐Controlled Oral Analgesia for Postoperative Pain Management Following Total Knee Replacement
Bibliographic record
Abstract
PURPOSE: To investigate whether patient-controlled oral analgesia (PCOA) used by individuals receiving a total knee replacement could reduce pain, increase patient satisfaction, reduce opioid use and/or reduce opioid side effects when compared with traditional nurse (RN)-administered oral analgesia. METHODS: Patients who underwent an elective total knee replacement at a quaternary care centre (Toronto Western Hospital, Toronto, Ontario) were randomly assigned to either PCOA or RN-administered short-acting oral opioids on postoperative day 2. Subjects in the RN group called the RN to receive their prescribed short-acting opioid. Subjects in the PCOA group kept a single dose of their prescribed oral opioid at their bedside and took this dose when they felt they needed it, to a maximum of one dose every 2 h. Study outcomes, collected on postoperative day 2, included pain (measured by the Brief Pain Inventory - Short Form), patient satisfaction (measured by the Pain Outcome Questionnaire Satisfaction subscale - component II), opioid use (oral morphine equivalents), opioid side effects (nausea, pruritus and/or constipation) and knee measures (maximum passive knee flexion and pain at maximum passive knee flexion, performed on the operative knee). RESULTS: Study outcomes were analyzed twice. First, for a subset of 73 subjects who remained in their randomly assigned group (PCOA group, n=36; RN group, n=37), randomized analyses were performed. Second, for the larger sample of 88 subjects who were categorized by their actual method of receiving oral opioids (PCOA group, n=41; RN group, n=47), as-treated analyses were performed. There were no differences in study outcomes between the PCOA and RN groups in either analysis. CONCLUSION: PCOA was not superior to RN administration on study outcomes. However, PCOA did not increase opioid use or pain. PCOA remains an important element in the patient-centred care facility.
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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 | 0.016 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".