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Record W4388596051 · doi:10.1093/eurheartj/ehad655.007

Treatment with sacubitril/valsartan and improvement of ventricular-arterial coupling in heart failure with reduced ejection fraction

2023· article· en· W4388596051 on OpenAlexaff
Tina Stegmann, L Parentin, S H Schirmer, Andreas Hagendorff, Ulrich Laufs, Daniel Lavall

Bibliographic record

VenueEuropean Heart Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsPopulation Health Research Institute
FundersDeutsche Herzstiftung
KeywordsMedicineEjection fractionCardiologyInternal medicineHeart failureValsartanSacubitrilSacubitril, ValsartanBlood pressureStroke volume

Abstract

fetched live from OpenAlex

Abstract Background Treatment with the angiotensin receptor-neprilysin inhibitor sacubitril/valsartan (S/V) in patients with heart failure and reduced ejection fraction (HFrEF) reduces mortality and heart failure (HF) hospitalizations. The specific hemodynamic mechanisms underlying these beneficial effects are currently unclear. Purpose This study aimed to assess the effects of S/V treatment on left ventricular (LV) end-systolic elastance (Ees), effective arterial elastance (Ea), and the ventricular-arterial coupling ratio (Ea/Ees) in patients with HFrEF using non-invasive pressure-volume analysis. Methods 117 patients with symptomatic HF and LVEF <40% in whom treatment with S/V was initiated were enrolled in this multicenter German prospective study. We used transthoracic echocardiography with simultaneous arm-cuff blood pressure measurements for non-invasive pressure-volume loop analyses. Primary endpoints were changes in Ees, Ea, and Ea/Ees ratio after six months of S/V treatment. Results The mean age was 65 (±13) years and 30% were female. In 54.7% of the patients, the etiology of HF was ischemic, and 45.3% was non-ischemic. 58.4% had first HF diagnosis at baseline. 102 patients with complete clinical and echocardiographic data at baseline and after six months of follow-up were analyzed. Among those, 62% were on target dose of S/V. Six months of S/V treatment resulted in a significant increase of Ees (0.66 mmHg/ml, IQR [0.45;0.94] vs. 0.78 mmHg/ml [0.57;1.10], p=0.001) and decrease of Ea (1.76 mmHg/ml [1.48;2.13] vs. 1.62 mmHg/ml [1.36;1.96], p=0.014). Hence, the Ea/Ees ratio significantly improved (2.52 [1.88;4.05] vs. 1.93 [1.50;2.63], p<0.001). In addition, LV volumes and pressure improved significantly with a regression of the LV end-systolic volume (LVESV: 142 ml [115;180] vs. 96 ml [65;124]), end-diastolic volume (LVEDV: 216 ml [179;247] vs. 165 ml [132;200]) and LV end-diastolic pressure (LVEDP: 19.6 mmHg [18.2;22.4] vs. 17.8 mmHg [16.6;19.9]), p<0.001 respectively. The LVEF increased from a median of 33% (27;37) to 43% (36;49), p<0.001. NT-proBNP level decreased from (median) 1771 pg/ml [838;5211] to 724 pg/ml [300;1575] and mean 6-minute walking distance increased from 371m (±125) to 423 m (±122), p<0.001 respectively. The percentage of patients with NYHA class III changed from 25.6% to 5.9%. Conclusion In a 6-months treatment period, initiation of sacubitril/valsartan in patients with heart failure and reduced ejection fraction was associated with reduction of LV volumes, improved LV function, reduction in afterload and fewer heart failure symptoms. These new data indicate that beyond reverse LV remodeling, improvement of LV contractility and ventricular-arterial coupling may contribute to the favorable clinical outcomes on treatment with sacubitril/valsartan in chronic heart failure.

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)0.000
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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.018
GPT teacher head0.260
Teacher spread0.242 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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