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Record W2996598812 · doi:10.4037/aacnacc2019285

Evidence-Based Strategies for the Prevention of Chronic Post–Intensive Care and Acute Care–Related Pain

2019· article· en· W2996598812 on OpenAlexaff
Mélanie Berube

Bibliographic record

VenueAACN Advanced Critical Care · 2019
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMedicineChronic painPsychological interventionIntensive care medicineAcute careIntensive careAcute painMEDLINEEpidemiologyHealth carePhysical therapyNursingInternal medicineAnesthesia

Abstract

fetched live from OpenAlex

Chronic pain is prevalent in intensive care survivors and in patients who require acute care treatments. Many adverse consequences have been associated with chronic post-intensive care and acute care-related pain. Hence, interest in interventions to prevent these pain disorders has grown. To improve the understanding of the mechanisms of action of these interventions and their potential impacts, this article outlines the pathophysiology involved in the transition from acute to chronic pain, the epidemiology and consequences of chronic post-intensive care and acute care- related pain, and risk factors for the development of chronic pain. Pharmacological, nonpharmacological, and multimodal preventive interventions specific to the targeted populations and their levels of evidence are presented. Nursing implications for preventing chronic pain in patients receiving critical and acute care are also discussed.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.881
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.016
GPT teacher head0.342
Teacher spread0.326 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations5
Published2019
Admission routes1
Has abstractyes

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