Acute Pain Medicine in the United States: A Status Report
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
BACKGROUND: Consensus indicates that a comprehensive,multimodal, holistic approach is foundational to the practice of acute pain medicine (APM),but lack of uniform, evidence-based clinical pathways leads to undesirable variability throughout U. S. healthcare systems. Acute pain studies are inconsistently synthesized to guide educational programs. Advanced practice techniques involving regional anesthesia assume the presence of a physician-led, multidisciplinary acute pain service,which is often unavailable or inconsistently applied.This heterogeneity of educational and organizational standards may result in unnecessary patient pain and escalation of healthcare costs. METHODS: A multidisciplinary panel was nominated through the APM Shared Interest Group of the American Academy of Pain Medicine. The panel met in Chicago, IL, in July 2014, to identify gaps and set priorities in APM research and education. RESULTS: The panel identified three areas of critical need: 1) an open-source acute pain data registry and clinical support tool to inform clinical decision making and resource allocation and to enhance research efforts; 2) a strong professional APM identity as an accredited subspecialty; and 3) educational goals targeted toward third-party payers,hospital administrators, and other key stake holders to convey the importance of APM. CONCLUSION: This report is the first step in a 3-year initiative aimed at creating conditions and incentives for the optimal provision of APM services to facilitate and enhance the quality of patient recovery after surgery, illness, or trauma. The ultimate goal is to reduce the conversion of acute pain to the debilitating disease of chronic pain.
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 | 0.029 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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