Deprescribing Cardiovascular Medications in Older Adults Living with Frailty
Bibliographic record
Abstract
Certain medications have shown significant effectiveness in reducing the incidence of cardiovascular events and mortality, leading them to be among those that are prescribed most commonly for Canadian seniors. However, polypharmacy, which disproportionately affects older adults, is particularly concerning for frail individuals who are at higher risk for adverse medication-related events. The deprescribing process is the discontinuation, either immediate or gradual, of inappropriate medications, to address polypharmacy and improve outcomes. Nonetheless, the incorporation of deprescribing principles into clinical practice present challenges, including the limited amount of data available on the clinical benefits of deprescription, and a lack of consensus on how to deprescribe. The current narrative review explores frailty as a basis for deciding to deprescribe medication. The evidence regarding the benefits of use of medications prescribed for common cardiovascular conditions (including acetylsalicylic acid, statins, and antihypertensives) in older adults with frailty is reviewed. The review also examines the issue of who should initiate the deprescribing process, and the associated psychological implications. Although no one-size-fits-all approach to deprescription is available, patient goals should be prioritized. For older adults with frailty, healthcare professionals must consider carefully whether the benefits of use of a cardiovascular medication outweighs the potential harms. Ideally, the deprescribing process should involve shared decision-making among physicians, other health professionals, and patients and/or their substitute decision-makers, with the common goal of improving patient outcomes.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".