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Record W4386705477 · doi:10.1002/ejhf.3031

Heart Failure Patients with Improved Ejection Fraction: Insights from the MECKI Score Database

2023· article· en· W4386705477 on OpenAlexaff
Piergiuseppe Agostoni, Francesca Pluchinotta, Elisabetta Salvioni, Massimo Mapelli, Arianna Galotta, Alice Bonomi, Damiano Magrì, Enrico Perna, Stefania Paolillo, Ugo Corrà, Rosa Raimondo, Rocco Lagioia, Roberto Badagliacca, Pasquale Perrone Filardi, Anna Apostolo, Michele Senni, Michele Correale, Jeness Campodonico, Pietro Palermo, Mariantonietta Cicoira, Marco Metra, Marco Guazzi, Giuseppe Limongelli, Mauro Contini, Beatrice Pezzuto, Gianfranco Sinagra, Gianfranco Parati, Gaia Cattadori, Cosimo Carriere, Marco Cittar, Maria Vittoria Matassini, Andrea Salzano, Antonio Cittadini, Marco Masè, Francesco Bandera, Maurizio Bussotti, Irene Mattavelli, Federica Re, Carlo Vignati, Carlo Lombardi, Angela Beatrice Scardovi, Susanna Sciomer, Andrea Passantino, Michele Emdin, Andrea Di Lenarda, Claudio Passino, Caterina Santolamazza, Federica Moscucci, Denise Zaffalon, Massimo Piepoli

Bibliographic record

VenueEuropean Journal of Heart Failure · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsSurgical Specialties (Canada)
FundersMinistero della SaluteAstraZeneca
KeywordsEjection fractionMedicineHeart failureCardiologyInternal medicineClinical endpointNatriuretic peptideRenal functionHeart transplantationTransplantationKidney diseaseDatabaseClinical trial

Abstract

fetched live from OpenAlex

AIMS: Improvement of left ventricular ejection fraction is a major goal of heart failure (HF) treatment. However, data on clinical characteristics, exercise performance and prognosis in HF patients who improved ejection fraction (HFimpEF) are scarce. The study aimed to determine whether HFimpEF patients have a distinct clinical phenotype, biology and prognosis than HF patients with persistently reduced ejection fraction (pHFrEF). METHODS AND RESULTS: A total of 7948 patients enrolled in the Metabolic Exercise Cardiac Kidney Indexes (MECKI) score database were evaluated (median follow-up of 1490 days). We analysed clinical, laboratory, electrocardiographic, echocardiographic, exercise, and survival data from HFimpEF (n = 1504) and pHFrEF (n = 6017) patients. The primary endpoint of the study was the composite of cardiovascular death, left ventricular assist device implantation, and urgent heart transplantation. HFimpEF patients had lower HF severity: left ventricular ejection fraction 44.0 [41.0-47.0] versus 29.7 [24.1-34.5]%, B-type natriuretic peptide 122 [65-296] versus 373 [152-888] pg/ml, haemoglobin 13.5 [12.2-14.6] versus 13.7 [12.5-14.7] g/dl, renal function by the Modification of Diet in Renal Disease equation 72.0 [56.7-89.3] versus 70.4 [54.5-85.3] ml/min, peak oxygen uptake 62.2 [50.7-74.1] versus 52.6 [41.8-64.3]% predicted, minute ventilation-to-carbon dioxide output slope 30.0 [26.9-34.4] versus 32.1 [28.0-38.0] in HFimpEF and pHFrEF, respectively (p < 0.001 for all). Cardiovascular mortality rates were 26.6 and 46.9 per 1000 person-years for HFimpEF and pHFrEF, respectively (p < 0.001). Kaplan-Meier analysis showed that HFimpEF had better a long-term prognosis compared with pHFrEF patients. After adjustment for variables differentiating HFimpEF from pHFrEF, except echocardiographic parameters, the Kaplan-Meier curves showed the same prognosis. CONCLUSIONS: Heart failure with improved ejection fraction represents a peculiar group of HF patients whose clinical, laboratory, electrocardiographic, echocardiographic, and exercise characteristics parallel the recovery of systolic function. Nonetheless, these patients remain at risk for adverse outcome.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.221
Teacher spread0.208 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations26
Published2023
Admission routes1
Has abstractyes

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