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Abstract 3172: Impact of Prosthesis-Patient Mismatch on Long-Term Survival After Aortic Valve Replacement

2007· article· en· W94958738 on OpenAlexaffabout
Dania Mohty, Jean G. Dumesnil, Najmeddine Echahidi, Patrick Mathieu, François Dagenais, Pierre Voisine, Philippe Pîbarot

Bibliographic record

VenueCirculation · 2007
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsMedicineAortic valve replacementProsthesisBody surface areaInternal medicineCardiologyAortic valveSurvival rateSurgeryOverall survivalStenosis

Abstract

fetched live from OpenAlex

Background: We recently reported that Prosthesis-Patient Mismatch (PPM) is an independent predictor of operative mortality in patients undergoing aortic valve replacement (AVR). The objective of this study was to evaluate the impact of PPM on late postoperative survival. Methods and Results: Between 1992 and 2005, 2653 patients (age: 68±10 years; 61% of males) underwent AVR in our institution. Patients who died at the time of operation or within 30 days were excluded from this study. The projected indexed effective orifice area (EOAi) was derived from the published normal in vivo EOA values for each model and size of prosthesis and PPM was classified as severe if the EOAi was ≤0.65 cm 2 /m 2 , moderate if it was > 0.65 cm 2 /m 2 and ≤ 0.85 cm 2 /m 2 , or not clinically significant if >0.85 cm 2 /m 2 . PPM was severe in 40 patients (2%), moderate in 797 (31%), and not significant in 1739 (67%). Patients with severe PPM had higher proportion of female gender (67% vs. 38%; P=0.0002) and hypertension (68% vs. 55%, p=0.02) and larger body surface (1.86±0.25 vs. 1.77±0.20, p=0.02). For patients with severe PPM, 5-year survival rate (74±8%) and 10-year survival rate (40±10%) were significantly (p=0.008) less than for patients with moderate PPM (5-yr: 81±2% and 10-yr: 57±3%) or no significant PPM (5-yr: 84±1% and 10-yr: 61±2%). On multivariate analysis after adjustment for other predictors of outcome, severe PPM was associated with increased overall mortality (Hazard ratio 1.38, [95% Confidence Interval 1.04 –1.75]; (p=0.02) Conclusion: In our previous study, we reported that severe PPM is a powerful risk factor for operative mortality. The results of the present study now suggest that severe PPM is also an independent predictor of long-term mortality. Hence, for the patients who are identified to be at risk of severe PPM at the time of operation, every effort should be made to implant a prosthesis with a larger EOA. Funded by: Canadian Institutes of Health Research

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)0.003
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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.341
Teacher spread0.323 · 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
Published2007
Admission routes2
Has abstractyes

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