MétaCan
Menu
Back to cohort

Short-term Ketamine Infusion for Acute Pain in an Opioid-tolerant Patient: a Case Report

2017· article· en· W3016429134 on OpenAlexaffvenue
Landon Berger, Mark McLean

Bibliographic record

VenueThe Canadian Journal of Addiction · 2017
Typearticle
Languageen
FieldMedicine
TopicAlcoholism and Thiamine Deficiency
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
Fundersnot available
KeywordsKetamineMedicineAcute painOpioidAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

Physicians are increasingly likely to encounter opioid tolerant patients suffering from acute pain. In the opioid tolerant patient, low-dose ketamine can provide safe, effective analgesia. However, hospital policies and unfamiliarity with ketamine have limited its use. We report a case of a patient who was tolerant to opioids as a result of opioid use disorder and who received ketamine by infusion, on a regular hospital ward, as an effective treatment for acute pain. We suggest that an internist or hospitalist can use low dose ketamine by infusion to treat acute, reversible pain in the opioid tolerant patient. Les médecins sont de plus en plus susceptibles de rencontrer des patients tolérants aux opioïdes souffrant de douleurs aiguës. Chez le patient tolérant les opioïdes, la dose faible de kétamine peut fournir une analgésie efficace et sûre. Cependant, les politiques des hôpitaux et la méconnaissance de la kétamine ont limité leur utilisation. Nous rapportons le cas d'un patient qui était tolérant aux opioïdes, qui, à la suite d'un trouble de l'utilisation des opioïdes, a reçu de la kétamine par perfusion, dans un milieu hospitalier régulier, comme traitement efficace pour la douleur aiguë. Nous suggérons qu'un interniste ou practicien hospitalier peut utiliser une dose faible de kétamine par perfusion pour traiter une douleur aiguë et réversible chez le patient tolérant les opioïdes.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.938

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.029
GPT teacher head0.303
Teacher spread0.274 · 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 designObservational
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

Citations0
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueThe Canadian Journal of AddictionSame topicAlcoholism and Thiamine DeficiencyFrench-language works237,207