One size does not fit all – a realist review of screening for asymptomatic atrial fibrillation in Indigenous communities in Australia, Canada, New Zealand and United States
Bibliographic record
Abstract
Abstract Background/Introduction Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and it is increasing in prevalence and incidence globally. True prevalence is underestimated because silent/asymptomatic AF is frequent and under-detected, but can cause stroke. Guidelines recommend opportunistic screening for AF in patients aged ≥65 years old. A growing body of evidence from hospital and community-based studies in Australia, New Zealand, Canada and United States indicates this age limit is lower for Indigenous people. Screening for AF meets the World Health Organisation (WHO) criteria for successful routine screening, yet little is known about successful implementation of AF screening in Indigenous communities in developed countries. Purpose The aim of this study is to use a realist approach to identify what works, how, for whom and under what circumstances for AF screening of Indigenous communities in Australia, Canada, New Zealand and United States. Methods In the realist review, eight databases were searched for studies targeted at AF screening in Indigenous communities. Realist analysis was used to identify context-mechanism-outcome configurations across 11 included records (reporting on 5 studies). Snowball referencing and grey literature were used to iteratively incorporate evidence to enhance the refined programme theory that was the product of the realist analysis. Results The realist review included studies using multiple screening strategies such as using tools to increase screening, using different screening environments and training screeners to provide culturally centred care. The realist analysis identified a number of mechanisms that can improve AF screening in Indigenous communities. The contextual factors enabling AF screening programs in Indigenous communities include wider community engagement, opportunistic non-clinical settings, using portable and easy to use devices, increasing knowledge, motivation and confidence in screening amongst Indigenous healthcare workers as well as improving follow-up protocols for abnormal results tailored to screen setting. Barriers to effective AF screening include time-poor working environments, conflicting cultural issues, navigating communication of abnormal results and logistical issues with device use (Figure 1). Conclusion(s) Since the life-course risk for AF in Indigenous population is different, a modified screening strategy needs to be put in place. This realist review provides lessons learned for successful implementation of AF screening programs for Indigenous communities. In order to tackle the gap in cardiovascular burden in Indigenous people, this study calls for action to develop AF screening guidelines for Indigenous populations and provides a guide for policy makers about timely and effective AF screening programs for Indigenous communities. Funding Acknowledgement Type of funding sources: None.
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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 | 0.083 | 0.252 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.023 | 0.019 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".