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Record W2061917116 · doi:10.1097/bcr.0000000000000073

Pain and the Thermally Injured Patient—A Review of Current Therapies

2014· review· en· W2061917116 on OpenAlexaff
Helene Retrouvey, Shahriar Shahrokhi

Bibliographic record

VenueJournal of Burn Care & Research · 2014
Typereview
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsHealth Sciences CentreMcGill UniversityMcGill University Health CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineGabapentinDexmedetomidineKetamineIntensive care medicineAnalgesicIncidence (geometry)PopulationAnesthesiaClonidinePhysical therapySedationAlternative medicine

Abstract

fetched live from OpenAlex

Thermally injured patients experience tremendous pain from the moment of injury to months or years after their discharge from the hospital. Pain is therefore a critical component of proper management of burns. Although the importance of pain is well recognized, it is often undertreated. Acute uncontrolled pain has been shown to increase the incidence of mental health disorders and increase the incidence of suicide after discharge. Long-term poor pain control leads to an increase in the incidence of persistent pain. Most burn centers have used opioids as the mainstay analgesic, but recently, the significant side effects of opioids have led to the implementation of new and combined therapeutics. Pharmacological agents such as gabapentin, clonidine, dexmedetomidine, and ketamine have all been suggested as adjuncts to opioids in the treatment of burn pain. Nonpharmacological therapies such as hypnosis, virtual reality devices, and behavioral therapy are also essential adjuncts to current medications. This review aims at identifying the currently available pharmacological and nonpharmacological options for optimal pain management in the adult burn population.

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)0.022
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.784
Threshold uncertainty score0.866

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.088
GPT teacher head0.459
Teacher spread0.371 · 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
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

Citations78
Published2014
Admission routes1
Has abstractyes

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