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Cost-effectiveness analysis of clinic-based chloral hydrate sedation versus general anaesthesia for paediatric ophthalmological procedures

2015· article· en· W1827811177 on OpenAlexaffabout
Heather Burnett, Rosemary G Lambley, Stephanie K. West, Wendy J. Ungar, Kamiar Mireskandari

Bibliographic record

VenueBritish Journal of Ophthalmology · 2015
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Sedative Agents
Canadian institutionsUniversity of TorontoInstitute for Clinical Evaluative SciencesSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsMedicineSedationChloral hydrateGeneral anaesthesiaCohortEmergency medicineRetrospective cohort studyPediatricsAnesthesiaSurgery

Abstract

fetched live from OpenAlex

BACKGROUND/AIMS: The inability of some children to tolerate detailed eye examinations often necessitates general anaesthesia (GA). The objective was to assess the incremental cost effectiveness of paediatric eye examinations carried out in an outpatient sedation unit compared with GA. METHODS: An episode of care cost-effectiveness analysis was conducted from a societal perspective. Model inputs were based on a retrospective cross-over cohort of Canadian children aged <7 years who had both an examination under sedation (EUS) and examination under anaesthesia (EUA) within an 8-month period. Costs ($CAN), adverse events and number of successful procedures were modelled in a decision analysis with one-way and probabilistic sensitivity analysis. RESULTS: The mean cost per patient was $406 (95% CI $401 to $411) for EUS and $1135 (95% CI $1125 to $1145) for EUA. The mean number of successful procedures per patient was 1.39 (95% CI 1.34 to 1.42) for EUS and 2.06 (95% CI 2.02 to 2.11) for EUA. EUA was $729 more costly on average than EUS (95% CI $719 to $738) but resulted in an additional 0.68 successful procedures per child. The result was robust to varying the cost assumptions. CONCLUSIONS: Cross-over designs offer a powerful way to assess costs and effectiveness of two interventions because patients serve as their own control. This study demonstrated significant savings when ophthalmological exams were carried out in a hospital outpatient clinic, although with slightly fewer procedures completed.

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)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.018
Threshold uncertainty score0.776

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
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 head0.164
GPT teacher head0.404
Teacher spread0.240 · 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

Citations20
Published2015
Admission routes2
Has abstractyes

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