ArticlePloS one2022
Blood-biomarkers and devices for atrial fibrillation screening: Lessons learned from the AFRICAT (Atrial Fibrillation Research In CATalonia) study.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07441759 (Economic, Clinical, and Societal Impact of Early Thromboembolic -Risk Detection in High-Risk Atrial Fibrillation), which is not on this map. Cited by 9 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Economic, Clinical, and Societal Impact of Early Thromboembolic -Risk Detection in High-Risk Atrial Fibrillation: A Model -Based Evaluation of the MATHIAS Strategy.
Who cites it
9 citing papers in PubMed, 12 citations in OpenAlex.
- Long non-coding RNA NPPA-AS1 acts as a potential novel biomarker and promotes atrial fibrillation progression via the miR-302e/TGFBR2 axis.Journal of thrombosis and thrombolysis · 2026Article
- Sex-Specific Health and Economic Benefits in Older Women at Risk of Atrial Fibrillation: A Proof-of-Concept Evaluation of an AI-Enabled Strategy for Early Thromboembolic Risk Detection.Journal of clinical medicine · 2026Article
- Recent advances in the tools and techniques for AI-aided diagnosis of atrial fibrillation.Biophysics reviews · 2025Review
- Evidence Gaps and Lessons in the Early Detection of Atrial Fibrillation: A Prospective Study in a Primary Care Setting (PREFATE Study).Biomedicines · 2025Article
- Echocardiography and Electrocardiography in Detecting Atrial Cardiomyopathy: A Promising Path to Predicting Cardioembolic Strokes and Atrial Fibrillation.Journal of clinical medicine · 2023Article
- Accuracy of Artificial Intelligence-Based Technologies for the Diagnosis of Atrial Fibrillation: A Systematic Review and Meta-Analysis.Journal of clinical medicine · 2023Review
- Associations of Cardiac Biomarkers With Peripheral Artery Disease and Peripheral Neuropathy in US Adults Without Prevalent Cardiovascular Disease.Arteriosclerosis, thrombosis, and vascular biology · 2023Article
- Electrocardiogram Devices for Home Use: Technological and Clinical Scoping Review.JMIR cardio · 2023Article
- Early Diagnosis of Atrial Fibrillation and Stroke Incidence in Primary Care: Translating Measurements into Actions-A Retrospective Cohort Study.Biomedicines · 2023Article
Corrections and comments
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Authors and funding
15 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectiveAFRICAT is a prospective cohort study intending to develop an atrial fibrillation (AF) screening program through the combination of blood markers, rhythm detection devices, and long-term monitoring in our community. In particular, we aimed to validate the use of NT-proBNP, and identify new blood biomarkers associated with AF. Also, we aimed to compare AF detection using various wearables and long-term Holter monitoring.
methods359 subjects aged 65-75 years with hypertension and diabetes were included in two phases: Phase I (n = 100) and Phase II (n = 259). AF diagnosis was performed by baseline 12-lead ECG, 4 weeks of Holter monitoring (NuuboTM), and/or medical history. An aptamer array including 1310 proteins was measured in the blood of 26 patients. Candidates were selected according to p-value, logFC and biological function to be tested in verification and validation phases. Several screening devices were tested and compared: AliveCor, Watch BP, MyDiagnostick and Fibricheck.
resultsAF was present in 34 subjects (9.47%). The aptamer array revealed 41 proteins with differential expression in AF individuals. TIMP-2 and ST-2 were the most promising candidates in the verification analysis, but none of them was further validated. NT-proBNP (log-transformed) (OR = 1.934; p<0.001) was the only independent biomarker to detect AF in the whole cohort. Compared to an ECG, WatchBP had the highest sensitivity (84.6%) and AUC (0.895 [0.780-1]), while MyDiagnostick showed the highest specificity (97.10%).
conclusionThe inclusion and monitoring of a cohort of primary care patients for AF detection, together with the testing of biomarkers and screening devices provided useful lessons about AF screening in our community. An AF screening strategy using rhythm detection devices and short monitoring periods among high-risk patients with high NT-proBNP levels could be feasible.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.