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Record W4211048968 · doi:10.1097/aap.0000000000000808

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

2018· review· en· W4211048968 on OpenAlexaff
Steven P. Cohen, Anuj Bhatia, Asokumar Buvanendran, Eric S. Schwenk, Ajay D. Wasan, Robert W. Hurley, Eugene R. Viscusi, Samer Narouze, Fred Davis, Elspeth Cameron Ritchie, Timothy R. Lubenow, W. Michael Hooten

Bibliographic record

VenueRegional Anesthesia & Pain Medicine · 2018
Typereview
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsToronto Western HospitalUniversity of Toronto
FundersUniformed Services University of the Health Sciences
KeywordsMedicineKetamineDosingConsensus conferenceChronic painClinical trialAlternative medicineNarrative reviewIntensive care medicineAnesthesiaPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

Background Over the past 2 decades, the use of intravenous ketamine infusions as a treatment for chronic pain has increased dramatically, with wide variation in patient selection, dosing, and monitoring. This has led to a chorus of calls from various sources for the development of consensus guidelines. Methods In November 2016, the charge for developing consensus guidelines was approved by the boards of directors of the American Society of Regional Anesthesia and Pain Medicine and, shortly thereafter, the American Academy of Pain Medicine. In late 2017, the completed document was sent to the American Society of Anesthesiologists9 Committees on Pain Medicine and Standards and Practice Parameters, after which additional modifications were made. Panel members were selected by the committee chair and both boards of directors based on their expertise in evaluating clinical trials, past research experience, and clinical experience in developing protocols and treating patients with ketamine. Questions were developed and refined by the committee, and the groups responsible for addressing each question consisted of modules composed of 3 to 5 panel members in addition to the committee chair. Once a preliminary consensus was achieved, sections were sent to the entire panel, and further revisions were made. In addition to consensus guidelines, a comprehensive narrative review was performed, which formed part of the basis for guidelines. Results Guidelines were prepared for the following areas: indications; contraindications; whether there was evidence for a dose-response relationship, or a minimum or therapeutic dose range; whether oral ketamine or another N-methyl-D-aspartate receptor antagonist was a reasonable treatment option as a follow-up to infusions; preinfusion testing requirements; settings and personnel necessary to administer and monitor treatment; the use of preemptive and rescue medications to address adverse effects; and what constitutes a positive treatment response. The group was able to reach consensus on all questions. Conclusions Evidence supports the use of ketamine for chronic pain, but the level of evidence varies by condition and dose range. Most studies evaluating the efficacy of ketamine were small and uncontrolled and were either unblinded or ineffectively blinded. Adverse effects were few and the rate of serious adverse effects was similar to placebo in most studies, with higher dosages and more frequent infusions associated with greater risks. Larger studies, evaluating a wider variety of conditions, are needed to better quantify efficacy, improve patient selection, refine the therapeutic dose range, determine the effectiveness of nonintravenous ketamine alternatives, and develop a greater understanding of the long-term risks of repeated treatments.

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)0.080
metaresearch head score (Gemma)0.211
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: Review · Consensus signal: none
Teacher disagreement score0.080
Threshold uncertainty score0.422

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0800.211
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0070.005
Science and technology studies0.0030.002
Scholarly communication0.0050.005
Open science0.0070.005
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0090.007

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 head0.204
GPT teacher head0.383
Teacher spread0.179 · 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

Citations341
Published2018
Admission routes1
Has abstractyes

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