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Record W2551848894 · doi:10.1155/2016/1424193

Day of Surgery Admission in Total Joint Arthroplasty: Why Are Surgeries Cancelled? An Analysis of 3195 Planned Procedures and 114 Cancellations

2016· article· en· W2551848894 on OpenAlexaff
David Dalton, Enda Kelly, Terence Patrick Murphy, Gerry F. McCoy, Aaron Glynn

Bibliographic record

VenueAdvances in Orthopedics · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsSunnybrook Hospital
Fundersnot available
KeywordsMedicineArthroplastyJoint arthroplastySpecialtySurgeryAlgorithmDatabaseMathematicsFamily medicineComputer science

Abstract

fetched live from OpenAlex

Background . Day of surgery admission (DOSA) is becoming standard practice as a means of reducing cost in total joint arthroplasty. Aims . The aim of our study was to audit the use of DOSA in a specialty hospital and identify reasons for cancellation. Methods . A retrospective study of patients presenting for hip or knee arthroplasty between 2008 and 2013 was performed. All patients were assessed at the preoperative assessment clinic (PAC). Results . Of 3195 patients deemed fit for surgery, 114 patients (3.5%) had their surgery cancelled. Ninety-two cancellations (80%) were due to the patient being deemed medically unsuitable for surgery by the anaesthetist. Cardiac disease was the most common reason for cancellation ( n = 27 ), followed by pulmonary disease ( n = 22 ). 77 patients (67.5%) had their operation rescheduled and successfully performed in our institution at a later date. Conclusion . DOSA is associated with a low rate of cancellations on the day of surgery. Patients with cardiorespiratory comorbidities are at greatest risk of cancellation.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.283
Teacher spread0.265 · 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 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

Citations17
Published2016
Admission routes1
Has abstractyes

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