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Record W6950470332 · doi:10.5683/sp3/niuc86

Données de réplication pour : Postoperative complication rate and owner satisfaction comparison of enucleation versus evisceration

2024· dataset· en· W6950470332 on OpenAlexaffabout

Bibliographic record

VenueBorealis · 2024
Typedataset
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsEnucleationEvisceration (ophthalmology)ComplicationPatient satisfactionMedical recordEye Enucleation

Abstract

fetched live from OpenAlex

This study aims to compare complication rates and owner satisfaction following enucleation versus EIOP in order to increase literature knowledge on both procedures. A review was conducted of medical records of 138 dogs, presented to the ophthalmology service of the Faculty of Veterinary Medicine, University of Montreal, Quebec, Canada that underwent enucleation from 2015 to 2022 and EIOP from 2008 to 2022. A survey was conducted with the owners by email or by telephone. This study found a significant effect of procedure choice on the complication rate with EIOP being much more prone to complications than enucleation (54.1 vs 15.3%). A glaucoma (primary or secondary) diagnosis before an evisceration procedure significantly increased the complication rate (p < 0.05). No other variable tested had a significant effect (age, size, sex, comorbidities, brachycephalic syndrome). The duration of administration of topical medication after an EIOP was much higher in this study compared to intervals mentioned in the literature (0.49 years). The owner survey revealed a similar level of satisfaction regarding the post-operative outcome of both procedures. Both procedures are viable options, but it is important to communicate the complication risk clearly with the owner and the personal implication necessary for postoperative care after an EIOP. The results of this study put in perspective the fact that the EIOP can be considered equally safe as enucleation. The survey results of this study show enucleation can have a very satisfactory cosmetic result with much less postoperative burden, while the choice of procedure remains the owner’s preference.

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)0.089
metaresearch head score (Gemma)0.473
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.089
Threshold uncertainty score0.471

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0890.473
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0040.005
Science and technology studies0.0020.002
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0150.003

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 head0.043
GPT teacher head0.292
Teacher spread0.249 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2024
Admission routes2
Has abstractyes

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