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Record W1589540853 · doi:10.1186/1472-6947-6-8

Utilities of the Post-anesthesia State derived by the Standard Gamble method in surgical patients

2006· article· en· W1589540853 on OpenAlexaff
Saifudin Rashiq, Diane Edlund, Bruce Dick

Bibliographic record

VenueBMC Medical Informatics and Decision Making · 2006
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineNauseaVomitingAnesthesiaUrinary retentionmyalgiaComplicationIncidence (geometry)SurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: There are no published utilities for the post-anesthesia state obtained by the standard gamble method (SG). METHODS: We obtained utilities for postoperative pain, nausea, vomiting, urinary retention and myalgia from 100 adults prior to elective surgery using SG. RESULTS: 20% of volunteer participants could not demonstrate a satisfactory understanding of the SG process. Median utilities for each adverse effect were all very close to 1.0, and no statistically significant differences were found between them. CONCLUSION: Our results suggest that the avoidance of anesthesia related side effects and pain is not viewed by patients prior to surgery as being worthy of the taking of even a miniscule risk of death. This may affect the decision to utilize anesthesia techniques that trade a lower incidence of common side effects for a very low but finite risk of a catastrophic complication.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.540
Threshold uncertainty score0.290

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.013
GPT teacher head0.306
Teacher spread0.293 · 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

Citations6
Published2006
Admission routes1
Has abstractyes

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