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Record W2127284306 · doi:10.1097/aln.0b013e3181e7d626

Efficacy and Safety of Melatonin as an Anxiolytic and Analgesic in the Perioperative Period

2010· review· en· W2127284306 on OpenAlexaff
Farhanah Yousaf, Edwin Seet, Lashmi Venkatraghavan, Amir Abrishami, Frances Chung, David S. Warner

Bibliographic record

VenueAnesthesiology · 2010
Typereview
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineMelatoninPremedicationAnxiolyticAnalgesicPerioperativeAnesthesiaPlaceboSedativeHypnoticRegimenAnxietySurgeryInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Melatonin possesses sedative, hypnotic, analgesic, antiinflammatory, antioxidative, and chronobiotic properties that distinguish it as an attractive alternative premedicant. A qualitative systematic review of the literature concerning the perioperative use of melatonin as an anxiolytic or analgesic in adult patients was carried out using the recommended guidelines provided by the Cochrane Handbook for Systematic Reviews of Interventions. Nine of the 10 studies showed statistically significant reduction of preoperative anxiety with melatonin premedication compared with placebo. An opioid-sparing effect or reduced pain scores were evident in five studies whereas three studies were contradictory. Thus, melatonin premedication is effective in ameliorating preoperative anxiety in adults, but its analgesic effects remain controversial in the perioperative period. Additional well designed randomized controlled trials are necessary to compare melatonin premedication with other pharmacological interventions, investigate its effect on more varied surgical populations, and to delineate its optimal dosing regimen.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.054
GPT teacher head0.398
Teacher spread0.344 · 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 designSystematic review
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

Citations138
Published2010
Admission routes1
Has abstractyes

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