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Record W2806113917 · doi:10.1097/aap.0000000000000806

Consensus Guidelines on the Use of Intravenous Ketamine Infusions for Acute Pain Management From the American Society of Regional Anesthesia and Pain Medicine, the American Academy of Pain Medicine, and the American Society of Anesthesiologists

2018· article· en· W2806113917 on OpenAlexaff
Eric S. Schwenk, Eugene R. Viscusi, Asokumar Buvanendran, Robert W. Hurley, Ajay D. Wasan, Samer Narouze, Anuj Bhatia, Fred Davis, W. Michael Hooten, Steven P. Cohen

Bibliographic record

VenueRegional Anesthesia & Pain Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsUniversity of Toronto
FundersUniformed Services University of the Health Sciences
KeywordsMedicineKetamineAcute painPerioperativePain medicineChronic painOpioidEmergency departmentAnesthesiaIntensive care medicineAnesthesiologyPhysical therapyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Ketamine infusions have been used for decades to treat acute pain, but a recent surge in usage has made the infusions a mainstay of treatment in emergency departments, in the perioperative period in individuals with refractory pain, and in opioid-tolerant patients. The widespread variability in patient selection, treatment parameters, and monitoring indicates a need for the creation of consensus guidelines. METHODS: The development of acute pain ketamine guidelines grew as a corollary from the genesis of chronic pain ketamine guidelines. The charge for the development of acute pain ketamine guidelines was provided by the Boards of Directors of both the American Society of Regional Anesthesia and Pain Medicine and the American Academy of Pain Medicine, who approved the document along with the American Society of Anesthesiologists' Committees on Pain Medicine and Standards and Practice Parameters. The committee chair developed questions based on input from the committee during conference calls, which the committee then refined. Groups of 3 to 5 panel members and the committee chair were responsible for answering individual questions. After preliminary consensus was achieved, the entire committee made further revisions via e-mail and conference calls. RESULTS: Consensus guidelines were prepared in the following areas: indications, contraindications for acute pain and whether they differ from those for chronic pain, the evidence for the use of ketamine as an adjunct to opioid-based therapy, the evidence supporting patient-controlled ketamine analgesia, the use of nonparenteral forms of ketamine, and the subanesthetic dosage range and whether the evidence supports those dosages for acute pain. The group was able to reach consensus on the answers to all questions. CONCLUSIONS: Evidence supports the use of ketamine for acute pain in a variety of contexts, including as a stand-alone treatment, as an adjunct to opioids, and, to a lesser extent, as an intranasal formulation. Contraindications for acute pain are similar to those for chronic pain, partly based on the observation that the dosage ranges are similar. Larger studies evaluating different acute pain conditions are needed to enhance patient selection, determine the effectiveness of nonparenteral ketamine alternatives, define optimal treatment parameters, and develop protocols optimizing safety and access to care.

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)0.104
metaresearch head score (Gemma)0.167
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.104
Threshold uncertainty score0.550

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1040.167
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0100.007
Science and technology studies0.0030.003
Scholarly communication0.0060.004
Open science0.0090.006
Research integrity0.0110.013
Insufficient payload (model declined to judge)0.0050.005

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 head0.115
GPT teacher head0.351
Teacher spread0.236 · 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
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

Citations576
Published2018
Admission routes1
Has abstractyes

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