Addressing the Opioid Crisis One Surgical Patient at a Time: Outcomes of a Novel Perioperative Pain Program
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Opioid prescriptions in the surgical setting have been implicated as contributors to the opioid epidemic. The authors hypothesized that a multidisciplinary approach to perioperative pain management for patients on chronic opioid therapy could decrease postoperative opioid requirements while reducing postoperative pain scores and improving functional outcomes. Therefore, a Perioperative Pain Program (PPP) for chronic opioid users was implemented. This study presents outcomes from the first 9 months of the PPP. Sixty-one patients met the inclusion criteria. Opioid consumption in morphine milligram equivalent (MME) was calculated and physical and health status of patients was assessed with the Brief Pain Inventory, Short-Form McGill Pain Questionnaire, and Short Form-12. Preliminary results showed significant reduction in MME, improved pain scores, and improved function for surgical patients on chronic opioids. PPP effectively reduced opioid usage without negatively influencing patient-reported outcomes, such as physical pain score assessment and health-related quality of life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it