Universal Precautions Revisited: Managing the Inherited Pain Patient
Bibliographic record
Abstract
"Universal Precautions in Pain Medicine: A Rational Approach to the Treatment of Chronic Pain" was published in 2005. In it, a unified 10-step approach to the assessment and management of patients suffering from chronic pain was proposed. As well, a triage scheme of risk stratification was offered. By placing patients into risk categories of low, medium, or high (Groups I, II, and III), it became possible to recommend to primary care practitioners those patients whom they might confidently manage on their own, comanage with specialty support, or refer to specialty clinics with more experience and resources to tackle these often challenging cases. It is important to note that Universal Precautions is not simply about opioid prescribing, although the use of opioids does highlight the value inherent in managing risk in all patients. Moreover, it should serve to remind health care professionals that the presence of significant psychiatric comorbidities, including substance-use disorders, may represent treatable conditions that must be addressed in order to optimize outcomes. Universal Precautions as a concept should be based upon mutual trust and respect between patient and practitioner, both of whom should be committed to setting and achieving realistic goals in both cancer and noncancer pain patients. The goal of this article is to explore the application of a Universal Precautions approach to manage the care of patients with chronic pain who no longer have an appropriate source of the medications upon which they have become physically dependent-so-called inherited pain patients.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".