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Record W2077390079 · doi:10.1177/0036933013482641

Evaluation of the utility of hospital databases to provide data in assessing the quality of strabismus surgery

2013· article· en· W2077390079 on OpenAlexfundno aff
Jacob S. Heng, Liying Low, JR MacKinnon, T Lavy, Gordon N. Dutton

Bibliographic record

VenueScottish Medical Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Eye Disorders
Canadian institutionsnot available
FundersHospital for Sick ChildrenUniversity of Dundee
KeywordsMedicineStrabismusStrabismus surgeryConfidence intervalPopulationPediatricsSurgeryDatabaseInternal medicine

Abstract

fetched live from OpenAlex

AIMS AND BACKGROUND: Rates of re-operation, which may be related to an unsatisfactory surgical outcome, can provide a long-term index of the quality of strabismus surgery. This study aims to evaluate the utility of the Scottish Morbidity Records (SMR1) in determining nature and rates of re-operation for strabismus at the Royal Hospital for Sick Children (RHSC), Glasgow. METHODS: SMR1 data on strabismus surgery performed on children aged between 0 and 17 years at the RHSC, Glasgow, between January 2000 and March 2009 were analysed. RESULTS: In total, 1376 strabismus procedures were carried out on 1274 individuals. The median time between first and subsequent procedures was 19 months; the commonest reasons being under-correction or recurrence. The Kaplan-Meier rate of undergoing re-operation was 7.4% after 9 years with a 95% confidence interval of 5.4-9.9%. CONCLUSIONS: The SMR1 is a useful source of hospital-based and population data. With supplementation from parallel databases, routine administrative databases like the SMR1 can provide better quality data to inform practice.

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)0.017
metaresearch head score (Gemma)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.187
GPT teacher head0.461
Teacher spread0.274 · 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 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

Citations2
Published2013
Admission routes1
Has abstractyes

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