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Record W2070485256 · doi:10.4021/jocmr1532w

Diastolic Heart Failure: A Concise Review

2013· review· en· W2070485256 on OpenAlexvenueno aff
Fahad Aziz

Bibliographic record

VenueJournal of Clinical Medicine Research · 2013
Typereview
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsnot available
Fundersnot available
KeywordsHeart failureMedicineDiastoleDiastolic heart failureCardiologyEjection fractionInternal medicineHeart failure with preserved ejection fractionBlood pressure

Abstract

fetched live from OpenAlex

The concept of "diastolic" heart failure grew out of the observation that many patients who have the symptoms and signs of heart failure had an apparently normal left ventricular (LV) ejection fraction. Thus it was assumed that since systolic function was "preserved" the problem must lie in diastole, although it is not clear by whom or when this assumption was made. Nevertheless, many guidelines followed on how to diagnose "diastolic" heart failure backed up by indicators of diastolic dysfunction derived from Doppler echoardiography. Diastolic heart failure is associated with a lower annual mortality rate of approximately 8% as compared to annual mortality of 19% in heart failure with systolic dysfunction, however, morbidity rate can be substantial. Thus, diastolic heart failure is an important clinical disorder mainly seen in the elderly patients with hypertensive heart disease. Early recognition and appropriate therapy of diastolic dysfunction is advisable to prevent further progression to diastolic heart failure and death. There is no specific therapy to improve LV diastolic function directly. Medical therapy of diastolic dysfunction is often empirical and lacks clear-cut pathophysiologic concepts. Nevertheless, there is growing evidence that calcium channel blockers, beta-blockers, ACE-inhibitors and ARB as well as nitric oxide donors can be beneficial. Treatment of the underlying disease is currently the most important therapeutic approach.

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)0.031
metaresearch head score (Gemma)0.051
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.540
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0310.051
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0120.006
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.009
Insufficient payload (model declined to judge)0.0040.001

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 head0.485
GPT teacher head0.618
Teacher spread0.132 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations47
Published2013
Admission routes1
Has abstractyes

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