A Scoping Review of Cognitive Screening Among Older Adults With Heart Disease
Bibliographic record
Abstract
Abstract Strong associations exist between cognitive impairment (CI) and heart disease in older adults, and such conditions are often comorbid. Early identification of CI can improve health outcomes. However, standard screening protocols are lacking, and it is uncertain whether healthcare providers routinely conduct formal or informal assessments for CI. The purpose of this review was to better understand the extent to which healthcare providers screen for CI in older adults with heart disease within clinical settings and to identify which screening methods are used. A scoping review was conducted using Arksey and O’Malley’s systematic framework. Articles were included if they featured information about frequency, application, or other contextual factors about CI screening for adults with heart disease in clinical settings. Of 876 potential sources identified, 9 were included for the full review. The articles represented international screening practices, including the United States, Australia, the Netherlands, China, and Uganda. Most articles (n = 6) assessed healthcare providers’ practices and perspectives on cognitive screening. Results included a range of providers (e.g., nurses, psychologists, rehabilitation specialists, cardiologists) who routinely screen, 3% to 39%, and various screening measures (e.g., Montreal Cognitive Assessment, Mini-Mental Status Exam, Mini-Cog, and more). Barriers to regular screening were feasibility concerns and provider-specific attitudes and beliefs, among others. Recommendations included implementation of standardized screening protocols, increasing providers’ awareness of age-related considerations, and greater interdisciplinary collaboration, among others. Findings demonstrated that some providers recognize the importance of routine cognitive screening, but many lack adequate knowledge, training, and logistical support.
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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 | 0.016 | 0.077 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".