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Record W2066791439 · doi:10.1089/jpm.2005.8.49

Parenteral Ketamine as an Analgesic Adjuvant for Severe Pain: Development and Retrospective Audit of a Protocol for a Palliative Care Unit

2005· review· en· W2066791439 on OpenAlexaff
Edward Fitzgibbon, Raymond Viola

Bibliographic record

VenueJournal of Palliative Medicine · 2005
Typereview
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsQueen's UniversityCanadian Hospice Palliative Care Association
Fundersnot available
KeywordsKetamineMedicineAnalgesicAnesthesiaCancer painNeuropathic painOpioidPain ladderCancerInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Ketamine is an effective analgesic agent for treating a variety of neuropathic and cancer pain syndromes. Recent studies indicate that ketamine may have a particular role in the management of patients with neuropathic and/or pain syndromes that are poorly responsive to opioids. OBJECTIVE: To develop, implement, and subsequently assess a protocol designed to maximize the analgesic effect of ketamine while minimizing its side effects. DESIGN: A retrospective chart audit of 16 patients who had used the ketamine protocol over a 12-month period. Criteria for assessing the effectiveness of ketamine were defined. RESULTS: Ketamine was an effective, well-tolerated analgesic adjuvant for 11 of 16 patients with previously uncontrolled pain. Pain scores were reduced by at least 4 of 10 in 15 of the 16 patients. Median opioid dose reduction on starting ketamine was 25%. CONCLUSION: The audit confirmed the safety and effectiveness of ketamine as an analgesic adjuvant for patients with severe pain. Baseline opioid dose reduction and prophylactic use of haloperidol or benzodiazepine were effective in minimizing psychotomimetic side effects.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.928
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.151
GPT teacher head0.461
Teacher spread0.310 · 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.

Study designOther design
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

Citations68
Published2005
Admission routes1
Has abstractyes

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