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Record W2808277411 · doi:10.4212/cjhp.v51i4.1962

Addition of sevoflurane to the formulary: Impact on a surgical daycare unit

2018· article· en· W2808277411 on OpenAlexvenueno aff
Luciana Frighetto, Carlo A. Marra, Patricia Gerber, Cathy MacDougall, John Dolman, Peter J. Jewesson

Bibliographic record

VenueThe Canadian Journal of Hospital Pharmacy · 2018
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Sedative Agents
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSevofluraneAnestheticAnesthesiaFormularyGynecologyNursing

Abstract

fetched live from OpenAlex

ABSTRACT Objectives: To determine the impact of sevoflurane on anesthetic-related patient outcomes an on anesthetic acquisition costs in a surgical daycare unit (SDU). Methods: A retrospective observational study comparing 50 historic controls from August 1995 – October 1995 (Phase 1) to 50 patients who received sevoflurane for dental or gynecologic procedures from August 1996 – October 1996 (Phase 2) in the SDU. From the health record, we obtained information on patient characteristics, procedure characteristics, anesthetic regimen characteristics, toxicities, ancillary drug, and time interval outcomes related to admission, recovery and duration of stay. From total SDU anesthetic expenditures we estimated the mean anesthetic expenditure per procedure in the SDU prior to and after introduction of sevoflurane. Results: There were no apparent differences in toxicities, ancillary drug use and time interval outcomes between the sevoflurane group and the control group with the exception of median time interval between recovery room admission and conscious-drowsy state for gynecology patients. Mean anesthetic costs per SDU procedure were $10.23 in Phase 1 and $12.30 in Phase 2. Conclusions: The use of sevoflurane in outpatient anesthesia did not permit quicker recovery or earlier discharge of patients undergoing dental or gynecologic procedures nor did it result in any cost advantage over other agents. Its role, therefore, appears limited to an inhalational alternative to propofol for induction anesthesia in the outpatient setting. RESUME Objectifs : Connaitre les effets du sevoflurane sur les resultats de l'anesthesie pour les patients ainsi que sur le cout des anesthesiques dans un service de chirurgie de jour (SCJ). Methodes : Etude retrospective par observation consistant a comparer, parmi des patients du SCJ, 50 patients temoins traites entre aout et octobre 1995 (Phase 1) a 50 patients ayant recu du sevoflurane pour une intervention dentaire ou gynecologique entre aout et octobre 1996 (Phase 2). Nous avons tire des dossiers de sante les renseignements suivants : caracteristiques des patients, de l'intervention et de l'anesthesique utilise, toxicites, medicament auxiliaire, periode ecoulee entre l'admission et le retablissement, duree du sejour. A partir des depenses totales du SCJ, nous avons estime le cout moyen de l'anesthesique par intervention avant et apres l'adoption du sevoflurane. Resultats : Nous n'avons constate aucune difference apparente entre les resultats relatifs aux toxicites, a l'utilisation de medicament auxiliaire et aux durees entre le groupe traite au sevoflurane et le groupe temoin, exception faite de la periode mediane ecoulee entre l'admission a la salle de reveil et l'atteinte de l'etat « conscient-somnolent » chez les patientes ayant subi une intervention gynecologique. Le cout moyen de l'anesthesique par intervention au SCJ s'est eleve a 10,23 $ en Phase 1 et a 12,30 $ en Phase 2. Conclusions : Par rapport aux autres agents anesthesiques, le sevoflurane utilise comme anesthesique en chirurgie externe n'a pas accelere le retablissement ou la liberation ni procure d'avantages sur le plan des couts. Son role semble donc limite a offrir une solution de rechange au propofol comme anesthesique inhale pour provoquer l'anesthesie en contexte de chirurgie externe.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.031
GPT teacher head0.339
Teacher spread0.309 · 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 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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