MétaCan
Menu
← Back to cohort
Record W93658926

Treatment of congestive heart failure: present and future.

2005· article· en· W93658926 on OpenAlexaffabout
Jean‐Lucien Rouleau

Bibliographic record

VenuePubMed · 2005
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsMedicineHeart failureCardiac resynchronization therapyIntensive care medicineCardiologyPsychological interventionPopulationInternal medicineEjection fraction
DOInot available

Abstract

fetched live from OpenAlex

The treatment of patients with congestive heart failure has markedly improved over the past 25 years. The most successful therapy has been attenuation of neurohumoral overactivation with antagonists of the renin-angiotensin-aldosterone system, as well as beta-adrenergic blockade. Cardiac surgical interventions, which include not only aortocoronary artery bypass surgery but also interventions that remodel the heart and repair the mitral valve, have also been advocated. However, randomized clinical trials to prove their benefit and to identify which patients could derive the most benefit from these interventions are lacking. Cardiac devices, such as biventricular pacemakers (for cardiac resynchronization) and implantable cardiac defibrillators, have proved useful in improving survival and quality of life. The treatment of sleep apnea with continuous positive airway pressure has shown some promise, as has immune modulation therapy, but more research to conclusively prove their efficacy is necessary. Cell therapy with skeletal myoblasts or pluripotential stem cells is an interesting and emerging area of research that shows enormous promise. However, fundamental questions regarding the optimal use of this therapy remain unanswered. Finally, although exciting, these developments, along with the changing demographics of the Canadian population, will require a change in the way we provide care for patients with congestive heart failure. These changes will require greater involvement of health care professionals other than physicians, and greater emphasis on outpatient care, early detection and prevention, and evidence-based practice.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.002

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 head0.019
GPT teacher head0.256
Teacher spread0.237 · 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 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

Citations9
Published2005
Admission routes2
Has abstractyes

Explore more

Same venuePubMed→Same topicCongenital Heart Disease Studies→French-language works237,207→