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Obese-Inflammatory Phenotypes in Heart Failure With Preserved Ejection Fraction

2020· article· en· W3045989635 on OpenAlex
Michael S. Sabbah, Ahmed Fayyaz, Simon de Denus, G. Michael Felker, Barry A. Borlaug, Surendra Dasari, Rickey E. Carter, Margaret M. Redfield

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCirculation Heart Failure · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsUniversité de MontréalMontreal Heart Institute
FundersNational Center for Advancing Translational SciencesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood InstituteNational Institutes of HealthFondation Institut de Cardiologie de MontréalUniversité de MontréalInstitut de Cardiologie de MontréalMayo Clinic
KeywordsMedicineHeart failure with preserved ejection fractionHeart failureInternal medicineNatriuretic peptideEjection fractionInflammationCardiologyFibrosisPhenotypeEndocrinologyBioinformaticsBiology

Abstract

fetched live from OpenAlex

Background: Comorbidity-driven microvascular inflammation is posited as a unifying pathophysiologic mechanism for heart failure with preserved ejection fraction (HFpEF). Obesity is proinflammatory and common in HFpEF. We hypothesized that unique obesity-inflammation HFpEF phenotypes exist and are associated with differences in clinical features, fibrosis biomarkers, and functional performance. Methods: Patients (n=301) from 3 HFpEF clinical trials were studied. Unsupervised machine learning (hierarchical clustering) with obese status and 13 inflammatory biomarkers as input variables was performed. Associations of clusters with HFpEF severity and fibrosis biomarkers (PIIINP [procollagen III N-terminal peptide], CITP [C-telopeptide for type I collagen], IGFBP7 [insulin-like growth factor-binding protein-7], and GAL-3 [galectin-3]) were assessed. Results: Hierarchical clustering revealed 3 phenotypes: pan-inflammatory (n=129; 64% obese), noninflammatory (n=83; 55% obese), and obese high CRP (C-reactive protein; n=89; 98% obese). The pan-inflammatory phenotype had more comorbidities and heart failure hospitalizations; higher left atrial volume, NT-proBNP (N-terminal pro-B-type natriuretic peptide), and fibrosis biomarkers; and lower glomerular filtration rate, peak oxygen consumption, 6-minute walk distance, and active hours/day ( P <0.05 for all). The noninflammatory phenotype had the most favorable values for all measures. The obese high CRP phenotype resembled the noninflammatory phenotype except for isolated elevation of CRP and lower functional performance. Hierarchical cluster assignment was independent of CRP genotype combinations that alter CRP levels and more biologically plausible than other clustering approaches. Multiple traditional analytic techniques confirmed and extended the hierarchical clustering findings. Conclusions: Unique obesity-inflammation phenotypes exist in HFpEF and are associated with differences in comorbidity burden, HFpEF severity, and fibrosis. These data support comorbidity-driven microvascular inflammation as a pathophysiologic mechanism for many but not all HFpEF patients.

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)0.000
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 score0.256
Threshold uncertainty score0.769

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.016
GPT teacher head0.238
Teacher spread0.221 · 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