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Record W4324121475 · doi:10.1071/hc12258

Viewpoint: From ladder to platform: a new concept for pain management

2012· article· en· W4324121475 on OpenAlexaff
Lawrence Leung

Bibliographic record

VenueJournal of Primary Health Care · 2012
Typearticle
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsQueen's University
Fundersnot available
KeywordsAnalgesicMedicineChronic painPerspective (graphical)Context (archaeology)Pain managementIntensive care medicinePhysical therapyComputer sciencePsychiatryArtificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND: Pain remains one of the top five reasons for consultations in general practice, presenting either alone or as comorbidity. The World Health Organization (WHO) analgesic ladder proposed in 1986 has been the cornerstone of pain management, but is often inadequate in daily practice, especially when dealing with the diverse nature and etiology of various pain conditions. There is a need for a better concept which is universally applicable that acknowledges the value of, and need for, other domains of treatment for pain. OBJECTIVE: This article reviews the original ideas of the WHO analgesic ladder and proposes its extension to a platform model in the context of pain management. DISCUSSION: Pain affects both the physical and psychological wellbeing of patients and should not be treated with pharmacotherapy alone. The model of WHO analgesic ladder provides guidelines for choosing the analgesic agents, but has its limitations. Incorporating the latest paradigm of neuromatrix theory, both acute and chronic pain should be best managed with a broader perspective incorporating multimodal non-pharmacological and supportive treatments, illustrated by the concept of interacting domains on a broad platform as presented in this article. Different levels of pain severity and chronicity necessitate different analgesic platforms of management, and the clinician should move up or down the appropriate platform to explore the various treatment options as per the status and needs of the patient. KEYWORDS: Analgesic ladder; pain management; analgesic platform

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 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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.700
Threshold uncertainty score0.545

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.043
GPT teacher head0.319
Teacher spread0.277 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations35
Published2012
Admission routes1
Has abstractyes

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