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Universal Precautions in Pain Medicine: A Rational Approach to the Treatment of Chronic Pain

2005· article· en· W2044783221 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePain Medicine · 2005
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsCentre for Addiction and Mental HealthMount Sinai Hospital
Fundersnot available
KeywordsMedicineBiopsychosocial modelChronic painTriageReferralPain managementHealth carePhysical therapyIntensive care medicinePsychiatryFamily medicine

Abstract

fetched live from OpenAlex

The heightened interest in pain management is making the need for appropriate boundary setting within the clinician-patient relationship even more apparent. Unfortunately, it is impossible to determine before hand, with any degree of certainty, who will become problematic users of prescription medications. With this in mind, a parallel is drawn between the chronic pain management paradigm and our past experience with problems identifying the "at-risk" individuals from an infectious disease model. By recognizing the need to carefully assess all patients, in a biopsychosocial model, including past and present aberrant behaviors when they exist, and by applying careful and reasonably set limits in the clinician-patient relationship, it is possible to triage chronic pain patients into three categories according to risk. This article describes a "universal precautions" approach to the assessment and ongoing management of the chronic pain patient and offers a triage scheme for estimating risk that includes recommendations for management and referral. By taking a thorough and respectful approach to patient assessment and management within chronic pain treatment, stigma can be reduced, patient care improved, and overall risk contained.

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.874
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.281
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it