The impact of an educational pain management booklet intervention on postoperative pain control after cardiac surgery
Bibliographic record
Abstract
BACKGROUND: Relevant discharge information about the use of analgesic medication and other strategies may help patients to manage their pain more effectively and prevent postoperative persistent pain. AIMS: To examine patients' pain characteristics, analgesic intake and the impact of an educational pain management booklet intervention on postoperative pain control after cardiac surgery. Concerns about pain and pain medication prior to surgery will also be described. METHODS: From March 2012 to September 2013, 416 participants (23% women) were consecutively enrolled in a randomized controlled trial. The intervention group received usual care plus an educational booklet at discharge with supportive telephone follow-up on postoperative day 10, and the control group received only usual care. The primary outcome was worst pain intensity (The Brief Pain Inventory - Short Form). Data about pain characteristics and analgesic use were collected at 2 weeks and at 1, 3, 6 and 12 months post-surgery. General linear mixed models were used to determine between-group differences over time. RESULTS: Twenty-nine percent of participants reported surgically related pain at rest and 9% reported moderate to severe pain at 12 months post-surgery. Many participants had concerns about pain and pain medication, and analgesic intake was insufficient post-discharge. No statistically significant differences between the groups were observed in terms of the outcome measures following surgery. CONCLUSION: Postoperative pain and inadequate analgesic use were problems for many participants regardless of group allocation, and the current intervention did not reduce worst pain intensity compared with control. Further examination of supportive follow-up monitoring and/or self-management strategies post-discharge is required.
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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 | 0.019 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.000 | 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".