MétaCan
Menu
Back to cohort
Record W4304759237 · doi:10.1016/j.jchf.2022.08.012

Hemodynamically-Guided Management of Heart Failure Across the Ejection Fraction Spectrum

2022· article· en· W4304759237 on OpenAlex
Michael R. Zile, Mandeep R. Mehra, Anique Ducharme, Samuel F. Sears, Akshay S. Desai, Alan S. Maisel, Sara Paul, Frank W. Smart, Gillian Grafton, Sachin Kumar, Tareck O. Nossuli, Nessa Johnson, John Henderson, Philip B. Adamson, Maria Rosa Costanzo, JoAnn Lindenfeld

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJACC Heart Failure · 2022
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsMontreal Heart InstituteUniversité de Montréal
FundersAbbott Laboratories
KeywordsEjection fractionHeart failureCardiologyFraction (chemistry)Internal medicineSpectrum (functional analysis)MedicinePhysicsChemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Hemodynamically-guided management using an implanted pulmonary artery pressure sensor is indicated to reduce heart failure (HF) hospitalizations in patients with New York Heart Association (NYHA) functional class II-III with a prior HF hospitalization or those with elevated natriuretic peptides. OBJECTIVES: The authors sought to evaluate the effect of left ventricular ejection fraction (EF) on treatment outcomes in the GUIDE-HF (Hemodynamic-GUIDEd management of Heart Failure) randomized trial. METHODS: The GUIDE-HF randomized arm included 1,000 NYHA functional class II-IV patients (with HF hospitalization within the prior 12 months or elevated natriuretic peptides adjusted for EF and body mass index) implanted with a pulmonary artery pressure sensor, randomized 1:1 to a hemodynamically-guided management group (treatment) or a control group (control). The primary endpoint was the composite of HF hospitalizations, urgent HF visits, and all-cause mortality at 12 months. The authors assessed outcomes by EF in guideline-defined subgroups ≤40%, 41%-49%, and ≥50%, within the trial specified pre-COVID-19 period cohort. RESULTS: There were 177 primary events (0.553/patient-year) in the treatment group and 224 events (0.682/patient-year) in the control group (HR: 0.81 [95% CI: 0.66-1.00]; P = 0.049); HF hospitalization was lower in the treatment vs control group (HR: 0.72 [95% CI: 0.57-0.92]; P = 0.0072). Within each EF subgroup, primary endpoint and HF hospitalization rates were lower in the treatment group (HR <1.0 across the EF spectrum). Event rate reduction by EF in the treatment groups was correlated with reduction in pulmonary artery pressures and medication changes. CONCLUSIONS: Hemodynamically-guided HF management decreases HF-related endpoints across the EF spectrum in an expanded patient population of patients with HF. (Hemodynamic-GUIDEd Management of Heart Failure [GUIDE-HF]; NCT03387813).

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.351
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.287
Teacher spread0.273 · 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