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Record W3005401792 · doi:10.1111/vsu.13393

Predicting the duration of surgery and procedures in a veterinary referral center

2020· article· en· W3005401792 on OpenAlexaff
Michelle M. M. Hasiuk, Daniel Pang

Bibliographic record

VenueVeterinary Surgery · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Operations and Scheduling Optimization
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineTechnicianLimits of agreementDuration (music)ReferralObservational studySurgeryGeneral surgeryFamily medicineNuclear medicineInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the ability of veterinary personnel to predict the duration of surgery and associated procedures in a referral center. STUDY DESIGN: Prospective observational study. SAMPLE POPULATION: Experienced surgeons (ES; n = 2, board certified for 10+ years), inexperienced surgeons (IS; n = 2, residency completed, not board certified), anesthesia animal health technicians (AAHT; n = 3) and surgery animal health technicians (SAHT; n = 2). METHODS: Surgeons and technicians predicted surgery duration (skin incision to final stitch/staple) and total procedure duration (TPD; from induction of anesthesia to extubation). Predictions were compared to actual durations with Bland-Altman plots to assess agreement (accuracy) as indicated by bias (mean of observed differences) and limits of agreement (LOA; bias ±1.96 SD). RESULTS: All groups underestimated TPD. Experienced surgeons predicted their own TPD more accurately (bias -20.1 ± 30.4 minutes [±SD]) and more consistently (narrower LOA) than IS for their own TPD (-40.1 ± 41.0 minutes). Experienced surgeon TPD predictions by AAHT were more accurate than those by ES (bias -16.0 ± 28.9 minutes, LOA 5% narrower). Inexperienced surgeon TPD predictions by AAHT were less consistent (wider LOA) than those by IS. Own surgery duration predictions by surgeons were similar in magnitude (ES surgery duration [ESSD] 8.3 ± 18.3, IS surgery duration [ISSD] surgery duration -7.9 ± 27.2 minutes), with greater consistency by ES (LOA 30% narrower). Anesthesia animal health technician predictions were similar to those of surgeons (ESSD 3.0 ± 19.3, ISSD -9.0 ± 28.7 minutes). Surgery animal health technician predictions were similar to those of AAHT for ESSD but were less accurate for ISSD. CONCLUSION: Surgery duration was more accurately predicted than TPD, which was most accurately predicted by anesthesia technicians. CLINICAL SIGNIFICANCE: Surgical procedure planning should involve personnel best able to predict total procedure durations; in this case, anesthesia technicians. Accurate planning will promote efficient operating room and personnel use.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.389

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.000
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 head0.248
GPT teacher head0.408
Teacher spread0.160 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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