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Record W2075153095 · doi:10.1055/s-0033-1342973

Evaluation and Treatment of Pain in Critically Ill Adults

2013· review· en· W2075153095 on OpenAlexaff
Matt Hallman, Céline Gélinas, Daniel Herr, Kathleen Puntillo, Aaron M. Joffe

Bibliographic record

VenueSeminars in Respiratory and Critical Care Medicine · 2013
Typereview
Languageen
FieldMedicine
TopicAnesthesia and Sedative Agents
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineIntensive care medicineCritically illResource consumptionIntensive care unitOpiateIntensive care

Abstract

fetched live from OpenAlex

Pain is experienced by the overwhelming majority of patients during their intensive care unit stay, but it remains an underappreciated problem. To effectively treat pain, it must be detected and quantified using a validated assessment tool. It is acknowledged that optimal pain relief may be difficult to achieve given the complex interplay of coexisting medical conditions and the environment in which care is provided. Nonetheless, by following structured approaches to pain, resource consumption may be reduced, and even improved survival may be realized. This review covers practices and techniques specific to addressing and treating pain in the adult intensive care environment. Traditional pharmacological approaches including opiate and nonopiate medications are reviewed, as are regional anesthetic techniques and nonpharmacological approaches used for controlling 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.083
GPT teacher head0.410
Teacher spread0.327 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations34
Published2013
Admission routes1
Has abstractyes

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