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Record W3181894442 · doi:10.1016/j.jcin.2021.03.069

Prosthesis-Patient Mismatch After Aortic Valve Replacement in the PARTNER 2 Trial and Registry

2021· article· en· W3181894442 on OpenAlexafffund
Julien Ternacle, Philippe Pîbarot, Howard C. Herrmann, Susheel Kodali, Jonathon Leipsic, Philipp Blanke, Wael A. Jaber, Michael J. Mack, Marie‐Annick Clavel, Erwan Salaün, Ezéquiel Guzzetti, Mohamed‐Salah Annabi, Mathieu Bernier, Jonathan Beaudoin, Omar Khalique, Neil J. Weissman, Pamela S. Douglas, Jeroen J. Bax, Abdellaziz Dahou, Ke Xu, Maria Alu, Erin Rogers, Martin B. Leon, Vinod H. Thourani, Amr E. Abbas, Rebecca T. Hahn

Bibliographic record

VenueJACC: Cardiovascular Interventions · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversity of British ColumbiaSt. Paul's HospitalUniversité Laval
FundersEdwards LifesciencesUniversité LavalMedtronic
KeywordsMedicineAortic valve replacementCardiologyCardiac skeletonInternal medicineBody surface areaValve replacementProsthesisAortic valveIncidence (geometry)Body mass indexSurgeryStenosis

Abstract

fetched live from OpenAlex

This study aimed to compare incidence and impact of measured prosthesis-patient mismatch (PPMM) versus predicted PPM (PPMP) after surgical aortic valve replacement (SAVR) and transcatheter aortic valve replacement (TAVR). TAVR studies have used measured effective orifice area indexed (EOAi) to body surface area (BSA) to define PPM, but most SAVR series have used predicted EOAi. This difference may contribute to discrepancies in incidence and outcomes of PPM between series. The study analyzed SAVR patients from the PARTNER (Placement of Aortic Transcatheter Valves) 2A trial and TAVR patients from the PARTNER 2 SAPIEN 3 Intermediate Risk registry. PPM was classified as moderate if EOAi ≤0.85 cm2/m2 (≤0.70 if obese: body mass index ≥30 kg/m2) and severe if EOAi ≤0.65 cm2/m2 (≤0.55 if obese). PPMM was determined by the core lab–measured EOAi on 30-day echocardiogram. PPMP was determined by 2 methods: 1) using normal EOA reference values previously reported for each valve model and size (PPMP1; n = 929 SAVR, 1,069 TAVR) indexed to BSA; and 2) using normal reference EOA predicted from aortic annulus size measured by computed tomography (PPMP2; n = 864 TAVR only) indexed to BSA. Primary endpoint was the composite of 5-year all-cause death and rehospitalization. The incidence of moderate and severe PPMP was much lower than PPMM in both SAVR (PPMP1: 28.4% and 1.2% vs. PPMM: 31.0% and 23.6%) and TAVR (PPMP1: 21.0% and 0.1% and PPMP2: 17.0% and 0% vs. PPMM: 27.9% and 5.7%). The incidence of severe PPMM and severe PPMP1 was lower in TAVR versus SAVR (P < 0.001). The presence of PPM by any method was associated with higher transprosthetic gradient. Severe PPMP1 was independently associated with events in SAVR after adjustment for sex and Society of Thoracic Surgeons score (hazard ratio: 3.18;95% CI: 1.69-5.96; P < 0.001), whereas no association was observed between PPM by any method and outcomes in TAVR. EOAi measured by echocardiography results in a higher incidence of PPM following SAVR or TAVR than PPM based on predicted EOAi. Severe PPMP is rare (<1.5%), but is associated with increased all-cause death and rehospitalization after SAVR, whereas it is absent following TAVR.

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)0.004
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 score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.335
Teacher spread0.309 · 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

Citations104
Published2021
Admission routes2
Has abstractyes

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