Utilization of Evidence-Based Therapies for Heart Failure in the Institutionalized Elderly
Bibliographic record
Abstract
OBJECTIVES: Heart failure (HF) is a major source of morbidity and mortality in elderly populations. A significant proportion of the elderly with HF are living in long-term care facilities. Little is known about their management. The aim of this study was to evaluate the use of evidence-based therapies in institutionalized elderly patients with HF. DESIGN, SETTING AND PARTICIPANTS: Retrospective chart review conducted at 15 long-term care facilities in the Capital Health Region (Edmonton, Alberta). Residents > or =65 years of age with HF were identified using a pharmacy database. RESULTS: Overall prevalence of HF was 15% (313/2062 residents). Mean age was 87 years, median duration of residence was 1.8 years. Utilization of ACE-inhibitors, beta-blockers and spironolactone was 51%, 16% and 10%, respectively. Use of these medications was not significantly different between subgroups of those with and without contraindications to the therapies, different advance directive levels, gender or age. Sodium and fluid restricted diets were prescribed in only 11.0% and 3.8% of residents. Weight was not regularly monitored. Influenza and pneumococcal vaccination were administered to 60.4% and 81.2% of the residents. CONCLUSION: The use of evidence-based therapies in institutionalized elderly patients with HF is low, and unexplained by contraindications or advance directives. Efforts to increase the utilization of evidence-based therapies and improve monitoring are warranted.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".