The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Mobile Health Technology for Atrial Fibrillation Management Integrating Decision Support, Education, and Patient Involvement: mAF App Trial
Open accessAbstract
Background Mobile Health technology for the management of patients with atrial fibrillation is unknown. Methods The simple mobile AF (mAF) App was designed to incorporate clinical decision-support tools (CHA 2 DS 2 -VASc [Congestive heart failure, Hypertension, Age ≥75 years, Diabetes Mellitus, Prior Stroke or TIA, Vascular disease, Age 65–74 years, Sex category], HAS-BLED [Hypertension, Abnormal renal/liver function, Stroke, Bleeding history or predisposition, Labile INR, Elderly, Drugs/alcohol concomitantly], SAMe-TT 2 R 2 [Sex, Age <60 years, Medical history, Treatment, Tobacco use, Race] scores), educational materials, and patient involvement strategies with self-care protocols and structured follow-up. Patients with atrial fibrillation were randomized into 2 groups (mAF App vs usual care) in a cluster randomized design pilot study. Patients' knowledge, quality of life, drug adherence, and anticoagulation satisfaction were evaluated at baseline, 1 month, and 3 months. Usability, feasibility, and acceptability of the mAF App were assessed at 1 month. Results A total of 113 patients were randomized to mAF App intervention (mean age, 67.4 years; 57.5% were male; mean follow-up, 69 days), and 96 patients were randomized to usual care (mean age, 70.9 years; 55.2% were male; mean follow-up, 95 days). More than 90% of patients reported that the mAF App was easy, user-friendly, helpful, and associated with significant improvements in knowledge compared with the usual care arm ( P values for trend <.05). Drug adherence and anticoagulant satisfaction were significantly better with the mAF App versus usual care (all P < .05). Quality of life scores were significantly increased in the mAF App arm versus usual care, with anxiety and depression reduced (all P < .05). Conclusions The pilot mAFA Trial is the first prospective randomized trial of Mobile Health technology in patients with atrial fibrillation, demonstrating that the mAF App, integrating clinical decision support, education, and patient-involvement strategies, significantly improved knowledge, drug adherence, quality of life, and anticoagulation satisfaction.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Worldwide Epidemiology of Atrial Fibrillation: A Global Burden of Disease 2010 Study
Chugh, S. S., Havmoeller, R., Narayanan, K., Singh, D., Rienstra, M., Benjamin, E. J., Gillum, R. F., Kim, Y.-H., McAnulty, J. H., Zheng, Z.-J., et al. (2014) · Circulation · doi:10.1161/circulationaha.113.005119 · Cited by 4,506
Lifetime Risk for Development of Atrial Fibrillation: The Framingham Heart Study
Lloyd-Jones, D. M., Wang, T. J., Leip, E. P., Larson, M. G., Levy, D., Vasan, R. S., D’Agostino, R. B., Massaro, J. M., Beiser, A., Wolf, P. A., et al. (2004) · Circulation · doi:10.1161/01.cir.0000140263.20897.42 · Cited by 2,041
Prevalence, incidence and lifetime risk of atrial fibrillation: the Rotterdam study
Heeringa, J., van der Kuip, D. A. M., Hofman, A., Kors, J. A., van Herpen, G., Stricker, B. H. C., Stijnen, T., Lip, G. Y. H., & Witteman, J. C. M. (2006) · European Heart Journal · doi:10.1093/eurheartj/ehi825 · Cited by 1,939
Self-citationSchnabel, R. B., Yin, X., Gona, P., Larson, M. G., Beiser, A. S., McManus, D. D., Newton-Cheh, C., Lubitz, S. A., Magnani, J. W., Ellinor, P. T., et al. (2015) · The Lancet · doi:10.1016/s0140-6736(14)61774-8 · Cited by 1,746
Burke, L. E., Ma, J., Azar, K. M. J., Bennett, G. G., Peterson, E. D., Zheng, Y., Riley, W., Stephens, J., Shah, S. H., Suffoletto, B., et al. (2015) · Circulation · doi:10.1161/cir.0000000000000232 · Cited by 516
Prevalence, Incidence, and Lifetime Risk of Atrial Fibrillation in China
Guo, Y., Tian, Y., Wang, H., Si, Q., Wang, Y., & Lip, G. Y. H. (2015) · Chest · doi:10.1378/chest.14-0321 · Cited by 255
Self-citationClarkesmith, D. E., Pattison, H. M., Lip, G. Y. H., & Lane, D. A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0074037 · Cited by 209
Self-citationLane, D. A., Aguinaga, L., Blomström-Lundqvist, C., Boriani, G., Dan, G.-A., Hills, M. T., Hylek, E. M., LaHaye, S. A., Lip, G. Y. H., Lobban, T., et al. (2015) · Europace · doi:10.1093/europace/euv233 · Cited by 142
Cited by
Hindricks, G., Potpara, T., Dagres, N., Arbelo, E., Bax, J. J., Blomström-Lundqvist, C., Boriani, G., Castella, M., Dan, G.-A., Dilaveris, P. E., et al. (2021) · European Heart Journal · doi:10.1093/eurheartj/ehaa612 · Cited by 9,971
Self-citationSteffel, J., Verhamme, P., Potpara, T. S., Albaladejo, P., Antz, M., Desteghe, L., Haeusler, K. G., Oldgren, J., Reinecke, H., Roldan-Schilling, V., et al. (2018) · European Heart Journal · doi:10.1093/eurheartj/ehy136 · Cited by 2,123
Self-citationMobile Photoplethysmographic Technology to Detect Atrial Fibrillation
Guo, Y., Wang, H., Zhang, H., Liu, T., Liang, Z., Xia, Y., Yan, L., Xing, Y., Shi, H., Li, S., et al. (2019) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2019.08.019 · Cited by 489
Self-citationAtrial fibrillation: epidemiology, screening and digital health
Linz, D., Gawalko, M., Betz, K., Hendriks, J. M., Lip, G. Y. H., Vinter, N., Guo, Y., & Johnsen, S. (2024) · The Lancet Regional Health - Europe · doi:10.1016/j.lanepe.2023.100786 · Cited by 441
Self-citationMobile Health Technology to Improve Care for Patients With Atrial Fibrillation
Guo, Y., Lane, D. A., Wang, L., Zhang, H., Wang, H., Zhang, W., Wen, J., Xing, Y., Wu, F., Xia, Y., et al. (2020) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2020.01.052 · Cited by 369
Self-citation
Metadata
- Authors
- Guo, Y., Chen, Y., Lane, D. A., Liu, L., Wang, Y., & Lip, G. Y. H.
- Venue
- The American Journal of Medicine
- Publisher
- Elsevier BV
- Published
- 2017-12
- Volume
- 130
- Issue
- 12
- Pages
- 1388-1396.e6
- ISSN
- 0002-9343 (ISSN-L)
- OpenAlex
- W2745811192
- Cited by
- 230
- References
- 8
- FWCI
- 32.66
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Mobile Health Technology for Atrial Fibrillation Management Integrating Decision Support, Education, and Patient Involvement: mAF App Trial. https://app.cochat.ai/papers/10.1016/j.amjmed.2017.07.003
- The paper
- Guo, Y., Chen, Y., Lane, D. A., Liu, L., Wang, Y., & Lip, G. Y. H. (2017). Mobile Health Technology for Atrial Fibrillation Management Integrating Decision Support, Education, and Patient Involvement: mAF App Trial. The American Journal of Medicine. https://doi.org/10.1016/j.amjmed.2017.07.003
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
