Is the minimal clinically important difference (MCID) in acute pain a good measure of analgesic efficacy in regional anesthesia?
Bibliographic record
Abstract
In the field of acute pain medicine research, we believe there is an unmet need to incorporate patient related outcome measures that move beyond reporting pain scores and opioid consumption. The term "minimal clinically important difference" (MCID) defines the clinical benefit of an intervention as perceived by the patient, as opposed to a mathematically determined statistically significant difference that may not necessarily be clinically significant. The present article reviews the concept of MCID in acute postoperative pain research, addresses potential pitfalls in MCID determination and questions the clinical validity of extrapolating MCID determined from chronic pain and non-surgical pain studies to the acute postoperative pain setting. We further suggest the concepts of minimal clinically important improvement, substantial clinical benefit and patient acceptable symptom state should also represent aspirational outcomes for future research in acute postoperative pain management.
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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 | 0.017 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".