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Abstract 12636: Association Between Pre-Operative Specialist Assessment and Adverse Outcomes Among Patients Scheduled for Major Vascular Surgery

2022· article· en· W4380794251 on OpenAlexaffabout
Charles de Mestral, Husam M Abdel Qadir, Peter C. Austin, Alice Chong, McAlister Finlay, Thomas F. Lindsay, Heather J. Ross, George Oreopoulos, Duminda N. Wijeysundera, Douglas S. Lee

Bibliographic record

VenueCirculation · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsUniversity of AlbertaInstitute for Clinical Evaluative SciencesUniversity of Toronto
Fundersnot available
KeywordsMedicineMyocardial infarctionHazard ratioStroke (engine)Internal medicineAmbulatoryVascular surgeryPopulationCohortCardiologyProportional hazards modelConfoundingCardiac surgerySurgeryConfidence interval

Abstract

fetched live from OpenAlex

Background: The impact of pre-operative specialist assessment on outcomes following high-risk vascular surgery remains uncertain. Our objective was to characterize the association between pre-operative cardiology or general internal medicine (GIM) assessment and post-operative outcomes following scheduled major vascular surgery. Methods: This is a population-based cohort study of all adult scheduled major vascular surgery patients in Ontario, Canada (April 1, 2004-March 31, 2019). Those who underwent an ambulatory cardiology and/or GIM assessment within 6 months prior to surgery were compared to those who did not. The primary outcome was 30-day mortality. Secondary outcomes included 30-day mortality, myocardial infarction or stroke; 30-day cardiovascular death; 1-year mortality; 1-year mortality, myocardial infarction or stroke; and 1-year cardiovascular death. Multivariable cox proportional hazard regression using inverse probability of treatment weighting (IPTW) was used to mitigate confounding by indication. Results: Among 50,228 scheduled major vascular surgery patients, 20,484 underwent pre-operative ambulatory specialist assessment: 11,074 (54.1%) with cardiology, 8,071 (39.4%) with GIM and 1,339 (6.5%) with both. Patients who underwent cardiology or GIM assessment had a higher Revised Cardiac Risk Index (N with Index over 2= 4,989 [24.4%] vs. 4,587 [15.4%], p<0.001) and more frequent pre-operative cardiac testing (N=7,772 [37.9%] vs. 6,113 [20.6%], p<0.001) but had lower crude 30-day mortality (N=551 [2.7%] vs. 970 [3.3%], p<0.001). After application of IPTW, pre-operative specialist assessment remained associated with a lower rate of 30-day mortality (Hazard Ratio [95%CI] = 0.73 [0.65-0.82]) and a lower rate of all secondary outcomes (Figure). Conclusion: Pre-operative ambulatory cardiology or GIM assessment is associated with improved outcomes following scheduled major vascular surgery

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)0.000
metaresearch head score (Gemma)0.002
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 score0.151
Threshold uncertainty score0.300

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.296
Teacher spread0.277 · 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

Citations0
Published2022
Admission routes2
Has abstractyes

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