Caregiving for patients with atrial fibrillation: a systematic review of the scientific literature
Bibliographic record
Abstract
AIMS: Caregiving processes and outcomes have been increasingly articulated in the cardiovascular literature, particularly in heart failure and coronary artery disease, but there has been no synthesis on caregiving for a patient with atrial fibrillation (AF). This review synthesizes scientific evidence that describes caregiving in the context of AF, with the aim of informing future research priorities for AF caregiving or clinical approaches that may support caregivers. METHODS AND RESULTS: Informed by PRISMA guidelines, we conducted a mixed-methods systematic review with a data-based convergence design using a thematic synthesis approach. All studies that examined factors related to caregiving for patients with AF, as either a descriptive, predictor, or outcome variable, were included. After the search, data from 13 studies were abstracted; half of the studies (53%) were of low-to-moderate quality. Changes to the family unit and feelings of uncertainty are common post-AF; a subset of caregivers struggle with mental health challenges, particularly those who are unwell themselves or those who provide several hours of care to patients with more advanced symptoms or limitations. Informational support for caregivers appears to be lacking but is desired to better adapt to the changes or consequences incurred from AF. CONCLUSION: This review complements findings from previous reviews conducted in other cardiovascular disease subgroups. As there is still limited high-quality research on caregiving in an AF context, additional research is required to adequately inform supportive programming for caregivers of patients with AF, if indicated. REGISTRATION: PROSPERO: CRD4202339778.
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 | 0.014 | 0.059 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".