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Record W2762542652 · doi:10.1093/eurheartj/ehx502.1998

1998Long-term hemodynamic improvement after percutaneous mitral valve repair in the noninvasive pressure-volume analysis

2017· article· en· W2762542652 on OpenAlexfundno aff
Daniel Lavall, Manuel Mehrer, Stephan H. Schirmer, Jan-C Reil, Michael Böehm, Ulrich Laufs

Bibliographic record

VenueEuropean Heart Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsMedicineCardiologyHemodynamicsPercutaneousInternal medicineMitral valveTerm (time)

Abstract

fetched live from OpenAlex

Background: The long-term hemodynamic adaptations of the cardiovascular system after percutaneous mitral valve repair (PMVR) are poorly understood. Purpose: We studied patients before and 12 months after PMVR using noninvasive pressure-volume analysis. Methods: 80 patients with severe (grade 3+ and 4+) and symptomatic (82.5% NYHA functional class III and IV) mitral regurgitation (MR) were treated with PMVR (Mitraclip). 45 patients (56%) were male, mean age was 74±11 years. 24 patients (30%) had primary and 56 patients (70%) secondary MR. Mean ejection fraction was 43±14%. Arm-cuff blood pressure was measured simultaneously with echocardiography at baseline and at 12 months to calculate pressure-volume parameters. Results: 12 months after PMVR, outcome data were available for 74 patients, 5 patients withdraw consent for participation and one patient was lost to follow-up. 14 patients (17.5%) had died, 12 of them had secondary MR. During the follow-up, 13 patients (16.3%) were hospitalized because of decompensated heart failure. 12 months after PMVR, MR grade was 0+ to 2+ in 90.5% of surviving patients and 75.5% were in NYHA functional class I and II. Left ventricular (LV) end-diastolic volume decreased from (mean±SD) 167±81ml to 147±79ml (p<0.0001), end-systolic volume changed from 103±70ml to 95±72ml (p=0.01). Thereby, total stroke volume (SV) was reduced from 64±23ml to 52±15ml (p<0.0001). Total ejection fraction and global longitudinal peak systolic strain remained similar to baseline, whereas forward ejection fraction increased (31±14% vs. 41±20%, p<0.0001). Since forward SV increased (43±12ml vs. 49±17ml, p=0.01) and HR remained unchanged cardiac index improved from 1.7±0.4l/min/m2 to 1.9±0.5ml/min/m2 (p=0.01) at 12 months. The peak power index reflecting LV contractility increased (220±116mmHg/s vs. 282±152mmHg/s, p=0.001). High baseline total peripheral resistance was reduced at 12 months (2423±666dynes×sec×cm5 vs. 2122±749dynes×sec×cm5, p=0.02). Stroke work of the LV was diminished (5941±2430mmHg×ml vs. 4515±1535mmHg×ml, p=0.0002) at 12 months while pressure-volume area representing total myocardial work was similar to baseline. Cardiac output relative to the pressure-volume area in one minute indicating efficacy of the operating heart improved (0.024±0.015 mmHg–1 vs. 0.031±0.019 mmHg–1, p=0.003). Glomerular filtration rate decreased from baseline to 12 months (41±17ml/1.73m2/min to 35±16ml/1.73m2/min, p<0.0001) without correlation to any hemodynamic parameter.

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)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
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 head0.015
GPT teacher head0.322
Teacher spread0.307 · 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
Published2017
Admission routes1
Has abstractyes

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