Preventing and Managing Falls in Adults With Cardiovascular Disease: A Scientific Statement From the American Heart Association
Bibliographic record
Abstract
Falls and fear of falling are a major health issue and associated with high injury rates, high medical care costs, and significant negative impact on quality of life. Adults with cardiovascular disease are at high risk of falling. However, the prevalence and specific risks for falls among adults with cardiovascular disease are not well understood, and falls are likely underestimated in clinical practice. Data from surveys of patient-reported and medical record-based analyses identify falls or risks for falling in 40% to 60% of adults with cardiovascular disease. Increased fall risk is associated with medications, structural heart disease, orthostatic hypotension, and arrhythmias, as well as with abnormal gait and balance, physical frailty, sensory impairment, and environmental hazards. These risks are particularly important among the growing population of older adults with cardiovascular disease. All clinicians who care for patients with cardiovascular disease have the opportunity to recognize falls and to mitigate risks for falling. This scientific statement provides consensus on the interdisciplinary evaluation, prevention, and management of falls among adults with cardiac disease and the management of cardiovascular care when patients are at risk of falling. We outline research that is needed to clarify prevalence and factors associated with falls and to identify interventions that will prevent falls among adults with cardiovascular disease.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".