THE MANAGEMENT OF HEART FAILURE IN CANADA AND WORLDWIDE:
Bibliographic record
Abstract
THE MANAGEMENT OF HEART FAILURE IN CANADA AND WORLDWIDE: Dr. Shehneela Dar (MD), Director, Medical Research The Canadian Journal of Scientific and Clinical Discovery (CJSCD) Toronto, Ontario, Canada www.cjscd.ca DOI:10.5281/zenodo.17930437 ORCID ID: https://orcid.org/0009-0004-8320-649X Google Scholar ID: https://myaccount.google.com/?hl=en Abstract: Heart failure (HF), a complex clinical syndrome characterized by the heart's inability to pump sufficient blood to meet the body's metabolic needs, remains a leading cause of morbidity, mortality, and healthcare expenditure globally. This review article synthesizes current established management strategies for heart failure, focusing on key differences and similarities between protocols utilized in Canada and those adopted worldwide. Canadian guidelines, influenced by bodies like the Canadian Cardiovascular Society (CCS), prioritize guideline-directed medical therapy (GDMT), including Sacubitril/Valsartan, SGLT2 inhibitors, beta-blockers, and mineralocorticoid receptor antagonists (MRA), tailored to the patient's ejection fraction (HFrEF, HFmrEF, HFpEF). Globally, while GDMT forms the foundation, challenges in resource accessibility, public health infrastructure, and adherence vary significantly, particularly in low- and middle-income countries. This paper reviews the progression of pharmacologic interventions, the increasing role of implantable devices (ICDs/CRTs), the importance of palliative care integration, and the critical need for coordinated care and patient education to improve outcomes in this chronic, progressive disease worldwide. Keywords: Heart Failure, Guideline-Directed Medical Therapy (GDMT), Canadian Cardiovascular Society (CCS), SGLT2 Inhibitors, Cardiac Resynchronization Therapy (CRT), Global Health, Healthcare Access.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".