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Record W1834397104 · doi:10.1503/cmaj.150174

Preoperative testing before low-risk surgical procedures

2015· article· en· W1834397104 on OpenAlexafffundvenueabout
Kyle R. Kirkham, Duminda N. Wijeysundera, Ciara Pendrith, Ryan Ng, Jack V. Tu, Andreas Laupacis, Michael J. Schull, Wendy Levinson, R. Sacha Bhatia

Bibliographic record

VenueCanadian Medical Association Journal · 2015
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare cost, quality, practices
Canadian institutionsSunnybrook HospitalInstitute for Clinical Evaluative SciencesWomen's College HospitalSunnybrook Health Science CentreToronto Rehabilitation InstituteToronto Western HospitalToronto General HospitalUniversity Health NetworkSt. Michael's Hospital
FundersCanadian Institutes of Health ResearchOntario Ministry of Health and Long-Term Care
KeywordsMedicineOdds ratioConfidence intervalLogistic regressionCohortRetrospective cohort studySurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: There is concern about increasing utilization of low-value health care services, including preoperative testing for low-risk surgical procedures. We investigated temporal trends, explanatory factors, and institutional and regional variation in the utilization of testing before low-risk procedures. METHODS: For this retrospective cohort study, we accessed linked population-based administrative databases from Ontario, Canada. A cohort of 1 546 223 patients 18 years or older underwent a total of 2 224 070 low-risk procedures, including endoscopy and ophthalmologic surgery, from Apr. 1, 2008, to Mar. 31, 2013, at 137 institutions in 14 health regions. We used hierarchical logistic regression models to assess patient- and institution-level factors associated with electrocardiography (ECG), transthoracic echocardiography, cardiac stress test or chest radiography within 60 days before the procedure. RESULTS: Endoscopy, ophthalmologic surgery and other low-risk procedures accounted for 40.1%, 34.2% and 25.7% of procedures, respectively. ECG and chest radiography were conducted before 31.0% (95% confidence interval [CI] 30.9%-31.1%) and 10.8% (95% CI 10.8%-10.8%) of procedures, respectively, whereas the rates of preoperative echocardiography and stress testing were 2.9% (95% CI 2.9%-2.9%) and 2.1% (95% CI 2.1%-2.1%), respectively. Significant variation was present across institutions, with the frequency of preoperative ECG ranging from 3.4% to 88.8%. Receipt of preoperative ECG and radiography were associated with older age (among patients 66-75 years of age, for ECG, adjusted odds ratio [OR] 18.3, 95% CI 17.6-19.0; for radiography, adjusted OR 2.9, 95% CI 2.8-3.0), preoperative anesthesia consultation (for ECG, adjusted OR 8.7, 95% CI 8.5-8.8; for radiography, adjusted OR 2.2, 95% CI 2.1-2.2) and preoperative medical consultation (for ECG, adjusted OR 6.8, 95% CI 6.7-6.9; for radiography, adjusted OR 3.6, 95% CI 3.5-3.6). The median ORs for receipt of preoperative ECG and radiography were 2.3 and 1.6, respectively. INTERPRETATION: Despite guideline recommendations to limit testing before low-risk surgical procedures, preoperative ECG and chest radiography were performed frequently. Significant variation across institutions remained after adjustment for patient- and institution-level factors.

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)0.001
metaresearch head score (Gemma)0.005
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: Other · Consensus signal: none
Teacher disagreement score0.058
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.316
GPT teacher head0.485
Teacher spread0.169 · 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
GenreOther

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".

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Citations87
Published2015
Admission routes4
Has abstractyes

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