110 Pain Medication Prescription Patterns and the American Burn Association 2020 Guidelines on the Management of Acute Pain in the Adult Burn Patient
Bibliographic record
Abstract
Abstract Introduction In September 2020, the American Burn Association released new pain guidelines following a rigorous literature review and input from experts. These guidelines were last updated 14 years ago and represent a multitude of changes including increased importance for non-opioid pain medication use and non-pharmacologic adjuncts given the current opioid crisis. Specifically, the main recommendations were to use opioid medication sparingly and always with adjuncts; acetaminophen utilized in all patients; NSAID use depending on baseline comorbidities and kidney function; neuropathic pain therapy for those with such pain/refractory to standard therapy; and ketamine for procedural sedation/adjunct for opioid consumption. Further, nonpharmacologic treatments include cognitive-behavioural therapy (‘CBT’), hypnosis, and virtual reality should be considered. The objective of this study is to describe current pain medication prescription habits at one ABA-verified centre and how well they are in compliance with these new guidelines. Methods We conducted phase one of a quality improvement retrospective study of 514 patients admitted to an ABA-verified centre over a two-year period. Data included demographics and pain medication use which was compared against the new ABA American Burn Association 2020 Guidelines on the Management of Acute Pain in the Adult Burn Patient. Pain medication contraindications were defined using UpToDate Drug Information. Statistical analysis was descriptive in nature. Results 422 patients were admitted for acute burns. 65.9% were male with an average age of 46.4 (st dev 17.6,range 15–96). Flame burns were most common(n=209,49.5%) with average TBSA of 11.9%(st dev 16.5,range 0–98%) and 54 inhalation injuries(12.8%) covering an average length of stay of 15.6 days in the burn centre (st dev 16.8,range 1–146 days). A total of 3549 pain medications were prescribed: 1792 opioid(50.5%) and 1757 non-opioid(49.5%). Of those admitted, 93.8% were prescribed opioids, 72.5% NSAIDs, 87.2% acetaminophen, 74.4% nerve pain medications, and 25.3% ketamine. Opioids were not prescribed in 26 patients(6.2%) and only prescribed in 29 patients(6.9%). Regarding adjuncts, 4(0.94%) had documented contraindications to NSAIDs and 3(0.71%) to acetaminophen. No referrals were completed for CBT. Virtual reality and hypnosis are not available at this centre. Conclusions This work represents the first known study examining compliance to the new pain guidelines in an ABA-verified burn centre. There is significant room for improvement for the use of adjuncts specifically NSAIDs and acetaminophen as both were under prescribed. In addition, nonpharmacologic treatments are largely not available or not used and may be an untapped resource for better pain control.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".