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Prognostic Implications of Congestion on Physical Examination Among Contemporary Patients With Heart Failure and Reduced Ejection Fraction

2019· article· en· W2972899652 on OpenAlexaff
Senthil Selvaraj, Brian Claggett, Andrea Pozzi, John J.V. McMurray, Pardeep S. Jhund, Milton Packer, Akshay S. Desai, Eldrin F. Lewis, Muthiah Vaduganathan, Martin Lefkowitz, Jean L. Rouleau, Victor Shi, Michael R. Zile, Karl Swedberg, Scott D. Solomon

Bibliographic record

VenueCirculation · 2019
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsMontreal Heart Institute
FundersNational Center for Advancing Translational Sciences
KeywordsMedicineHeart failureValsartanInternal medicineEjection fractionCardiologySacubitril, ValsartanSacubitrilPeripheral edemaPhysical examinationAngiotensin receptorAngiotensin IIBlood pressureAdverse effect

Abstract

fetched live from OpenAlex

Background: The contemporary prognostic value of the physical examination— beyond traditional risk factors including natriuretic peptides, risk scores, and symptoms—in heart failure (HF) with reduced ejection fraction is unknown. We aimed to determine the association between physical signs of congestion at baseline and during study follow-up with quality of life and clinical outcomes and to assess the treatment effects of sacubitril/valsartan on congestion. Methods: We analyzed participants from PARADIGM-HF (Prospective Comparison of Angiotensin Receptor-Neprilysin Inhibitor With Angiotensin Converting Enzyme Inhibitor to Determine Impact on Global Mortality and Morbidity in HF) with an available physical examination at baseline. We examined the association of the number of signs of congestion (jugular venous distention, edema, rales, and third heart sound) with the primary outcome (cardiovascular death or HF hospitalization), its individual components, and all-cause mortality using time-updated, multivariable-adjusted Cox regression. We further evaluated whether sacubitril/valsartan reduced congestion during follow-up and whether improvement in congestion is related to changes in clinical outcomes and quality of life, assessed by Kansas City Cardiomyopathy Questionnaire overall summary scores. Results: Among 8380 participants, 0, 1, 2, and 3+ signs of congestion were present in 70%, 21%, 7%, and 2% of patients, respectively. Patients with baseline congestion were older, more often female, had higher MAGGIC risk scores (Meta-Analysis Global Group in Chronic Heart Failure) and lower Kansas City Cardiomyopathy Questionnaire overall summary scores ( P <0.05). After adjusting for baseline natriuretic peptides, time-updated Meta-Analysis Global Group in Chronic Heart Failure score, and time-updated New York Heart Association class, increasing time-updated congestion was associated with all outcomes ( P <0.001). Sacubitril/valsartan reduced the risk of the primary outcome irrespective of clinical signs of congestion at baseline ( P =0.16 for interaction), and treatment with the drug improved congestion to a greater extent than did enalapril ( P =0.011). Each 1-sign reduction was independently associated with a 5.1 (95% CI, 4.7–5.5) point improvement in Kansas City Cardiomyopathy Questionnaire overall summary scores. Change in congestion strongly predicted outcomes even after adjusting for baseline congestion ( P <0.001). Conclusions: In HF with reduced ejection fraction, the physical exam continues to provide significant independent prognostic value even beyond symptoms, natriuretic peptides, and Meta-Analysis Global Group in Chronic Heart Failure risk score. Sacubitril/valsartan improved congestion to a greater extent than did enalapril. Reducing congestion in the outpatient setting is independently associated with improved quality of life and reduced cardiovascular events, including mortality. Clinical Trial Registration: https://www.clinicaltrials.gov . Unique 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)0.000
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 score0.005
Threshold uncertainty score0.322

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.015
GPT teacher head0.251
Teacher spread0.236 · 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

Citations109
Published2019
Admission routes1
Has abstractyes

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