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Record W7133077734

Association of Preoperative Echocardiographic Right Ventricular Function with Outcomes after Cardiac Surgery: A Retrospective Cohort Study

2024· dissertation· W7133077734 on OpenAlexaff
Neeki Alavi

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsVentricular functionRetrospective cohort studyCohortCohort studyCardiac function curveSystoleIncidence (geometry)
DOInot available

Abstract

fetched live from OpenAlex

Quantitative measures of right ventricular (RV) function, such as RV fractional area change (RVFAC) and tricuspid annular plane systolic excursion (TAPSE), are recommended in preoperative echocardiography for cardiac surgery. This thesis investigated the association of quantitative RV function and outcomes in cardiac surgical patients. Preoperative TAPSE and RVFAC were reported in 2,275 and 1,379 patients, respectively. Adjusting for confounders, lower TAPSE was significantly associated with mortality (OR per 1 mm increase: 0.92, 95% CI: 0.87-0.97) and hospital length of stay (HLOS) (OR per 1 mm: 0.99, 95% CI: 0.99-0.99), but not acute kidney injury (AKI). Lower RVFAC was also significantly associated with mortality (OR per 1% decrease: 0.95, 95% CI: 0.92-0.98) and HLOS (OR per 1%: 0.99, 95% CI: 0.99-0.99), but not AKI. Discharges home with support or transferred to other facilities was not significantly associated with RV function. TAPSE<17mm and RVFAC<35% were also significantly associated with mortality and HLOS.

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)0.002
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.008
GPT teacher head0.291
Teacher spread0.283 · 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
Published2024
Admission routes1
Has abstractyes

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