MétaCan
Menu
Back to cohort
Record W3112519947 · doi:10.1161/jaha.120.017870

Comparison of Early Surgical or Transcatheter Aortic Valve Replacement Versus Conservative Management in Low‐Flow, Low‐Gradient Aortic Stenosis Using Inverse Probability of Treatment Weighting: Results From the TOPAS Prospective Observational Cohort Study

2020· article· en· W3112519947 on OpenAlexafffund
Mohamed‐Salah Annabi, Nancy Côté, Abdellaziz Dahou, Philipp E. Bartko, Jutta Bergler‐Klein, Ian G. Burwash, Stefan Orwat, Helmut Baumgartner, Julia Mascherbauer, Gerald Mundigler, Miho Fukui, João L. Cavalcante, Henrique Barbosa Ribeiro, Josep Rodés‐Cabau, Marie‐Annick Clavel, Philippe Pîbarot

Bibliographic record

VenueJournal of the American Heart Association · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversity of OttawaUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
FundersCanadian Institutes of Health Research
KeywordsMedicineStenosisObservational studyAortic valve replacementProspective cohort studyCardiologyInternal medicineRadiologyValve replacementCohortSurgery

Abstract

fetched live from OpenAlex

Background No randomized comparison of early (ie, ≤3 months) aortic valve replacement (AVR) versus conservative management or of transcatheter AVR (TAVR) versus surgical AVR has been conducted in patients with low‐flow, low‐gradient (LFLG) aortic stenosis (AS). Methods and Results A total of 481 consecutive patients (75±10 years; 71% men) with LFLG AS (aortic valve area ≤0.6 cm 2 /m 2 and mean gradient <40 mm Hg), 72% with classic LFLG and 28% with paradoxical LFLG, were prospectively recruited in the multicenter TOPAS (True or Pseudo Severe Aortic Stenosis) study. True‐severe AS or pseudo‐severe AS was adjudicated by flow‐independent criteria. During follow‐up (median [IQR] 36 [11–60] months), 220 patients died. Using inverse probability of treatment weighting to address the bias of nonrandom treatment assignment, early AVR (n=272) was associated with a major overall survival benefit (hazard ratio [HR], 0.34 [95% CI, 0.24–0.50]; P <0.001). This benefit was observed in patients with true‐severe AS but also with pseudo‐severe AS (HR, 0.38 [95% CI, 0.18–0.81]; P =0.01), and in classic (HR, 0.33 [95% CI, 0.22–0.49]; P <0.001) and paradoxical LFLG AS (HR, 0.42 [95% CI, 0.20–0.92]; P =0.03). Compared with conservative management in the conventional multivariate model, trans femoral TAVR was associated with the best survival (HR, 0.23 [95% CI, 0.12–0.43]; P <0.001), followed by surgical AVR (HR, 0.36 [95% CI, 0.23–0.56]; P <0.001) and alternative‐access TAVR (HR, 0.51 [95% CI, 0.31–0.82]; P =0.007). In the inverse probability of treatment weighting model, trans femoral TAVR appeared to be superior to surgical AVR (HR [95% CI] 0.28 [0.11–0.72]; P =0.008) with regard to survival. Conclusions In this large prospective observational study of LFLG AS, early AVR appeared to confer a major survival benefit in both classic and paradoxical LFLG AS. This benefit seems to extend to the subgroup with pseudo‐severe AS. Our findings suggest that TAVR using femoral access might be the best strategy in these patients. Registration URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01835028.

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)0.010
metaresearch head score (Gemma)0.009
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.077
GPT teacher head0.373
Teacher spread0.295 · 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

Citations44
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the American Heart AssociationSame topicCardiac Valve Diseases and TreatmentsFrench-language works237,207