Advances in the Management of Acute Postsurgical Pain: A Review
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
Despite the millions of surgeries performed every year around the world, postoperative pain remains prevalent and is often addressed with inadequate or suboptimal treatments. Chronic postsurgical pain is surprisingly prevalent, and its rate varies with the type of surgery, as well as with certain patient characteristics. Thus, better clinical training is needed as well as patient education. As pain can be caused by more than one mechanism, multimodal or balanced postsurgical analgesia is appropriate. Pharmacological agents such as opioid and nonopioid pain relievers, as well as adjuvants and nonpharmacologic approaches, can be combined to provide better and opioid-sparing pain relief. Many specialty societies have guidelines for postoperative pain management that emphasize multimodal postoperative analgesia. These guidelines are particularly helpful when dealing with special populations such as pregnant patients or infants and children. Pediatric pain control, in particular, can be challenging as patients may be unable to communicate their pain levels. A variety of validated assessment tools are available for diagnosis. Related to therapy, most guidelines agree on the fact that codeine should be used with extreme caution in pediatric patients as some may be "rapid metabolizers" and its use may be life-threatening. Prehabilitation is a preoperative approach that prepares patients in advance of elective surgery with conditioning exercises and other interventions to optimize their health. Prehabilitation may have aerobic, strength-training, nutritional, and counseling components. Logistical considerations and degree of patient adherence represent barriers to effective prehabilitation programs. Notwithstanding all this, acute postoperative pain represents a clinical challenge that has not yet been well addressed.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it