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Record W4310962987 · doi:10.1001/jamacardio.2022.4427

Associations Between New York Heart Association Classification, Objective Measures, and Long-term Prognosis in Mild Heart Failure

2022· article· en· W4310962987 on OpenAlexaff
Luís Eduardo Paim Rohde, André Zimerman, Muthiah Vaduganathan, Brian Claggett, Milton Packer, Akshay S. Desai, Michael R. Zile, Jean L. Rouleau, Karl Swedberg, Martin Lefkowitz, Victor Shi, John J.V. McMurray, Scott D. Solomon

Bibliographic record

VenueJAMA Cardiology · 2022
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsUniversité de MontréalMontreal Heart Institute
Fundersnot available
KeywordsMedicineHeart failureValsartanInternal medicineCardiologyRandomizationAsymptomaticLogistic regressionProportional hazards modelNatriuretic peptideRandomized controlled trialBlood pressure

Abstract

fetched live from OpenAlex

Importance: Heart failure (HF) treatment recommendations are centered on New York Heart Association (NYHA) classification, such that most apparently asymptomatic patients are not eligible for disease-modifying therapies. Objectives: To assess within-patient variation in NYHA classification over time, the association between NYHA class and an objective measure of HF severity (N-terminal pro-B-type natriuretic peptide [NT-proBNP] level), and their association with long-term prognosis in the PARADIGM-HF trial. Design, Setting, and Participants: All patients in PARADIGM-HF were in NYHA class II or higher at baseline and were treated with sacubitril-valsartan during a 6- to 10-week run-in period before randomization. Patients classified as NYHA class I, II, and III in PARADIGM-HF were compared at randomization. Exposures: NYHA class at randomization after 6 to 10 weeks of the run-in period. Main Outcomes and Measures: Primary outcome was cardiovascular death or first HF hospitalization. Logistic regression models, areas under the receiver operating characteristic curve (AUC), kernel density estimation overlaps, and Cox proportional hazards models were used. Results: The analysis included 8326 patients with known NYHA classification at randomization. Of 389 patients in NYHA class I, 228 (58%) changed functional class during the first year after randomization. Level of NT-proBNP was a poor discriminator of NYHA classification: for NYHA class I vs II, the AUC was 0.51 (95% CI, 0.48-0.54). For NT-proBNP level, estimated kernel density overlap was 93% between NYHA class I vs II, 79% between NYHA I vs III, and 83% between NYHA II vs III. Patients classified as NYHA III displayed a distinctively higher rate of cardiovascular events (NYHA III vs I, hazard ratio [HR], 1.84; 95% CI, 1.44-2.37; NYHA III vs II, HR, 1.49; 95% CI, 1.35-1.64). Patients in NYHA class I and II revealed lower event rates (NYHA II vs I, HR, 1.24; 95% CI, 0.97-1.58). Stratification by NT-proBNP level (<1600 pg/mL or ≥1600 pg/mL) identified subgroups with distinctive risk, such that NYHA class I patients with high NT-proBNP levels (n = 175) had a numerically higher event rate than patients with low NT-proBNP levels from any NYHA class (vs I, HR, 3.43; 95% CI, 2.03-5.87; vs II, HR, 2.12; 95% CI, 1.58-2.86; vs III, HR, 1.37; 95% CI, 1.00-1.88). Conclusions and Relevance: In this study, patients in NYHA class I and II overlapped substantially in objective measures and long-term prognosis. Physician-defined "asymptomatic" functional class concealed patients who were at substantial risk for adverse outcomes. NYHA classification might be limited to differentiate mild forms of HF. Trial Registration: ClinicalTrials.gov Identifier: NCT01035255.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.674

Codex and Gemma teacher scores by category

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

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 head0.045
GPT teacher head0.287
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 teacher head, 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

Citations42
Published2022
Admission routes1
Has abstractyes

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