MétaCan
Menu
← Back to cohort

CMR phenotypes and clinical outcomes in NYHA class I versus II-IV hypertrophic cardiomyopathy: identifying high-risk asymptomatic patients

2024· article· en· W4403807256 on OpenAlexaff
Dina Labib, Steven Dykstra, Farzaneh Hasanzadeh, Sandra Rivest, Jacqueline Flewitt, Theresa M. Beckie, Yanru Feng, Michael Bristow, Andrew G. Howarth, Carmen Lydell, R J H Miller, Louis Kolman, James A. White

Bibliographic record

VenueEuropean Heart Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsLibin Cardiovascular Institute of AlbertaUniversity of Calgary
FundersBristol-Myers Squibb
KeywordsMedicineHypertrophic cardiomyopathyAsymptomaticInternal medicineCardiologyPhenotypeCardiomyopathyHeart failureGeneticsGene

Abstract

fetched live from OpenAlex

Abstract Background Cardiac myosin inhibition therapy can deliver symptomatic benefit for NYHA class≥II patients with obstructive hypertrophic cardiomyopathy (HCM) and is being actively explored for non-obstructive phenotypes. However, expanding interest in clinical outcome reduction supports growing need to identify high risk cohorts across both symptomatic and asymptomatic cohorts. We aimed to examine phenotypic characteristics of NYHA-I versus NYHA≥II patients with HCM and their association with future outcomes. Methods 727 patients with HCM from the CIROC Registry who completed simultaneous CMR and patient health assessments, inclusive of NYHA evaluation and quality of life surveys, were studied. Baseline clinical and CMR characteristics were compared between NYHA-I and NYHA≥II cohorts, followed by risk modelling for the prediction of major adverse cardiovascular events (MACE), defined as: all-cause mortality, heart failure hospitalization, ventricular arrhythmia, new onset atrial fibrillation, or stroke. Cox models were constructed to identify independent predictors of MACE. Results Of the 727 patients, 546 (75%) reported NYHA-I and 181 (25%) NYHA≥II symptoms. Baseline characteristics are shown in Table 1. Compared to NYHA≥II, NYHA-I patients were younger, more likely male, and had a lower prevalence of diabetes and hypertension. No meaningful differences in CMR chamber volumes, function, left ventricular (LV) mass, or fibrosis burden were observed. Over a median follow up of 3.7 years, 109 patients (15%) experienced MACE: 12% in NYHA-I and 23% in NYHA≥II sub-groups (p<0.001). Baseline LV mass z-scores (determined from sex-matched, BSA-indexed SCMR healthy reference values) were independently associated with MACE by multivariable Cox modelling. An optimal LV mass z-score threshold of 3.9 for prediction of MACE was identified and combined with NYHA status to stratify patients into 4 categories. Kaplan-Meier curves showed patients with LV Mass z-scores >3.9 experienced worse event-free survival in both NYHA sub-groups (Figure 1a). Cox modelling in the overall cohort (Figure 1b) showed NYHA-I patients with LV Mass z-scores >3.9 experienced a 2.2-fold increased risk (p=0.007) of MACE, this exceeding the risk of NYHA ≥II patients below this threshold. Separate NYHA I and ≥II sub-group multivariable models showed LV Mass z-score >3.9 to remain a strong and independent predictor of MACE, providing respective hazards of 2.6 and 4.7 (p=0.001 and <0.001). Conclusions NYHA-I patients with HCM experience significantly lower rates of MACE versus NYHA≥II. However, LV mass z-scoring permits powerful sub-stratification of these sub-groups, identifying NYHA-I patients with higher LV mass who will experience worse outcomes versus NYHA≥II patients with lower LV mass. This simple yet powerful stratification offers unique potential to identify asymptomatic patients with HCM who may benefit from targeted therapeutics to reduce future MACE.

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)0.001
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.000
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 head0.048
GPT teacher head0.334
Teacher spread0.286 · 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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Heart Journal→Same topicCardiomyopathy and Myosin Studies→French-language works237,207→