|
1
|
Lawin D, Kuhn S, Schulze Lammers S, Lawrenz T, Stellbrink C. Use of digital health applications for the detection of atrial fibrillation. Herzschrittmacherther Elektrophysiol 2022; 33:373-379. [PMID: 35960358 DOI: 10.1007/s00399-022-00888-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/18/2022] [Indexed: 06/15/2023]
Abstract
The advances in health care technologies over the last decade have led to improved capabilities in the use of digital health applications (DiHA) for the detection of atrial fibrillation (AFib). Thus, home-based remote heart rhythm monitoring is facilitated by smartphones or smartwatches alone or combined with external sensors. The available products differ in terms of type of application (wearable vs. handheld) and the technique used for rhythm detection (electrocardiography [ECG] vs. photoplethysmography [PPG]). While ECG-based algorithms often require additional sensors, PPG utilizes techniques integrated in smartphones or smartwatches. Algorithms based on artificial intelligence allow for the automated diagnosis of AFib, enabling high diagnostic accuracy for both ECG-based and PPG-based DiHA. Advantages for clinical use result from the widespread accessibility of rhythm monitoring, thereby permitting earlier diagnosis and higher AFib detection rates. DiHA are also useful for the follow-up of patients with known AFib by monitoring the success of therapeutic interventions to restore sinus rhythm, e.g. catheter ablation. Although some studies strongly suggest a potential benefit for the use of DiHA in the setting of AFib, the overall evidence for an improvement in hard, clinical endpoints and positive effects on clinical care is scarce. To enhance the acceptance of DiHA use in daily practice, more studies evaluating their clinical benefits for the detection of AFib are required. Moreover, most of the applications are still not reimbursable, although the German Digital Health Care Act (Digitale-Versorgung-Gesetz, DVG) made reimbursement possible in principle in 2019.
Collapse
Affiliation(s)
- Dennis Lawin
- Department of Cardiology and Intensive Care Medicine, University hospital OWL of Bielefeld University, Campus Klinikum Bielefeld, Teutoburger Str. 50, 33604, Bielefeld, Germany.
- Department of Digital Medicine, Medical Faculty OWL, Bielefeld University, Bielefeld, Germany.
| | - Sebastian Kuhn
- Department of Digital Medicine, Medical Faculty OWL, Bielefeld University, Bielefeld, Germany
| | - Sophia Schulze Lammers
- Department of Cardiology and Intensive Care Medicine, University hospital OWL of Bielefeld University, Campus Klinikum Bielefeld, Teutoburger Str. 50, 33604, Bielefeld, Germany
| | - Thorsten Lawrenz
- Department of Cardiology and Intensive Care Medicine, University hospital OWL of Bielefeld University, Campus Klinikum Bielefeld, Teutoburger Str. 50, 33604, Bielefeld, Germany
| | - Christoph Stellbrink
- Department of Cardiology and Intensive Care Medicine, University hospital OWL of Bielefeld University, Campus Klinikum Bielefeld, Teutoburger Str. 50, 33604, Bielefeld, Germany
| |
Collapse
|
|
2
|
Lawin D, Albrecht UV, Oftring ZS, Lawrenz T, Stellbrink C, Kuhn S. [Mobile health for detection of atrial fibrillation-Status quo and perspectives]. Internist (Berl) 2022; 63:274-280. [PMID: 35147711 PMCID: PMC8832086 DOI: 10.1007/s00108-022-01267-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/13/2022] [Indexed: 11/24/2022]
Abstract
Mobile health (mHealth) for the detection of atrial fibrillation is an innovative domestic monitoring of the heart rhythm. The use of mHealth in the context of atrial fibrillation increases the availability of diagnostic technologies and facilitates the integration into telemedical treatment concepts as well as the active participation of patients in the treatment process. The detection of atrial fibrillation with mHealth applications is usually based on electrocardiography (ECG) or by detection of the pulse wave using photoplethysmography (PPG). Some applications require additional sensors, others make use of sensors integrated into smartphones or smartwatches. A high diagnostic accuracy for the detection of atrial fibrillation has been shown for most mHealth applications regardless of the underlying technology (analytical validation); however, the evidence on positive care effects and improvement of medical endpoints (clinical validation) is so far scarce. Screening of symptomatic or asymptomatic patients and the follow-up care after antiarrhythmic measures are possibilities for the integration into the reality of care. The preventive detection of atrial fibrillation is an attractive field of application for mHealth with great potential for the future. Nevertheless, at present mHealth is only integrated to a limited extent into the reality of patient care. Adequate reimbursement and medical remuneration as well as opportunities to derive information and qualification are prerequisites in order to be able to guarantee a comprehensive implementation in the future. The Digital Health Care Act passed in 2019, regulates the reimbursement of digital healthcare applications but issues of primary preventive applications have not yet been included.
Collapse
Affiliation(s)
- Dennis Lawin
- Arbeitsgruppe für Digitale Medizin, Medizinische Fakultät OWL der Universität Bielefeld, Universitätsstraße 25, 33615, Bielefeld, Deutschland.
- Klinik für Kardiologie und internistische Intensivmedizin, Universitätsklinikum OWL der Universität Bielefeld, Campus Klinikum Bielefeld, Teutoburger Straße 50, 33604, Bielefeld, Deutschland.
| | - Urs-Vito Albrecht
- Arbeitsgruppe für Digitale Medizin, Medizinische Fakultät OWL der Universität Bielefeld, Universitätsstraße 25, 33615, Bielefeld, Deutschland
| | - Zoe Sophie Oftring
- Arbeitsgruppe für Digitale Medizin, Medizinische Fakultät OWL der Universität Bielefeld, Universitätsstraße 25, 33615, Bielefeld, Deutschland
| | - Thorsten Lawrenz
- Klinik für Kardiologie und internistische Intensivmedizin, Universitätsklinikum OWL der Universität Bielefeld, Campus Klinikum Bielefeld, Teutoburger Straße 50, 33604, Bielefeld, Deutschland
| | - Christoph Stellbrink
- Klinik für Kardiologie und internistische Intensivmedizin, Universitätsklinikum OWL der Universität Bielefeld, Campus Klinikum Bielefeld, Teutoburger Straße 50, 33604, Bielefeld, Deutschland
| | - Sebastian Kuhn
- Arbeitsgruppe für Digitale Medizin, Medizinische Fakultät OWL der Universität Bielefeld, Universitätsstraße 25, 33615, Bielefeld, Deutschland
| |
Collapse
|
|
3
|
Gao Z, Shi H, Xu W, Guan Z, Su X, Guo N, Ma H. Hyperuricemia Increases the Risk of Atrial Fibrillation: A Systematic Review and Meta-Analysis. Int J Endocrinol 2022; 2022:8172639. [PMID: 36046801 PMCID: PMC9420608 DOI: 10.1155/2022/8172639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Accepted: 08/02/2022] [Indexed: 11/17/2022] Open
Abstract
Association between hyperuricemia (HUA) and atrial fibrillation (AF) remains unclear. We reviewed clinical evidence and aimed to determine whether hyperuricemia leads to a high risk of atrial fibrillation. Most studies were identified through databases online. Keywords used in literature search were hyperuricemia, atrial fibrillation, metabolic disorder, endocrine disorder, or uric acid. Three studies were provided by the authors. Literature search was performed without any data or language restriction. Observational studies, including cohort studies and cross-sectional studies, were used. Study type should be clearly defined. Cross-sectional studies should clearly introduce the sources of epidemiological data. Studies were excluded if with too many complications unrelated to AF enrolled. Data were independently extracted by three individuals. Data synthesis was conducted by R version 4.1.2. Prevalence of atrial fibrillation was the main outcome. Results of meta-analysis were presented as risk ratio (RR) for different prevalence of AF between individuals with and without HUA. All data included were obtained after follow-up work is completed. Data from 608,810 participants showed that patients with hyperuricemia were easier to suffer from atrial fibrillation (RR, 2.42; 95% CI, 1.24-3.03). And the meta-regressions suggested growth of linear proportion between the ratio of current drinkers and hyperuricemia (QM = 41.0069, P < 0.001). Subgroup analyses demonstrated consistent results in different countries. And design of the observational studies brought heterogeneity, but no uncertainties. Patients with hyperuricemia were easier to suffer from atrial fibrillation. Treatment of hyperuricemia or gout may bring potential benefits for AF patients.
Collapse
Affiliation(s)
- Zheng Gao
- Department of Physiology, Hebei Medical University, Shijiazhuang, China
- Department of First Affiliated Hospital of Hebei Medical University, Shijiazhuang, China
| | - Hekai Shi
- Department of Physiology, Hebei Medical University, Shijiazhuang, China
- Department of Second Affiliated Hospital of Hebei Medical University, Shijiazhuang, China
| | - Wei Xu
- Department of Physiology, Hebei Medical University, Shijiazhuang, China
- Department of Second Affiliated Hospital of Hebei Medical University, Shijiazhuang, China
| | | | - Xiuxiu Su
- College of Physical Education, Hebei Normal University, Shijiazhuang, China
| | - Nuojin Guo
- Department of Physiology, Hebei Medical University, Shijiazhuang, China
- Department of Third Affiliated Hospital of Hebei Medical University, Shijiazhuang, China
| | - Huijie Ma
- Department of Physiology, Hebei Medical University, Shijiazhuang, China
| |
Collapse
|
|
4
|
Boriani G, Palmisano P, Malavasi VL, Fantecchi E, Vitolo M, Bonini N, Imberti JF, Valenti AC, Schnabel RB, Freedman B. Clinical Factors Associated with Atrial Fibrillation Detection on Single-Time Point Screening Using a Hand-Held Single-Lead ECG Device. J Clin Med 2021; 10:729. [PMID: 33673209 PMCID: PMC7917757 DOI: 10.3390/jcm10040729] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 02/05/2021] [Accepted: 02/08/2021] [Indexed: 02/07/2023] Open
Abstract
Our aim was to assess the prevalence of unknown atrial fibrillation (AF) among adults during single-time point rhythm screening performed during meetings or social recreational activities organized by patient groups or volunteers. A total of 2814 subjects (median age 68 years) underwent AF screening by a handheld single-lead ECG device (MyDiagnostick). Overall, 56 subjects (2.0%) were diagnosed with AF, as a result of 12-lead ECG following a positive/suspected recording. Screening identified AF in 2.9% of the subjects ≥ 65 years. None of the 265 subjects aged below 50 years was found positive at AF screening. Risk stratification for unknown AF based on a CHA2DS2VASc > 0 in males and >1 in females (or CHA2DS2VA > 0) had a high sensitivity (98.2%) and a high negative predictive value (99.8%) for AF detection. A slightly lower sensitivity (96.4%) was achieved by using age ≥ 65 years as a risk stratifier. Conversely, raising the threshold at ≥75 years showed a low sensitivity. Within the subset of subjects aged ≥ 65 a CHA2DS2VASc > 1 in males and >2 in females, or a CHA2DS2VA > 1 had a high sensitivity (94.4%) and negative predictive value (99.3%), while age ≥ 75 was associated with a marked drop in sensitivity for AF detection.
Collapse
Affiliation(s)
- Giuseppe Boriani
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (E.F.); (M.V.); (N.B.); (J.F.I.); (A.C.V.)
| | - Pietro Palmisano
- Cardiology Unit, “Card. G. Panico” Hospital, 73039 Tricase, Italy;
| | - Vincenzo Livio Malavasi
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (E.F.); (M.V.); (N.B.); (J.F.I.); (A.C.V.)
| | - Elisa Fantecchi
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (E.F.); (M.V.); (N.B.); (J.F.I.); (A.C.V.)
| | - Marco Vitolo
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (E.F.); (M.V.); (N.B.); (J.F.I.); (A.C.V.)
- Clinical and Experimental Medicine PhD Program, University of Modena and Reggio Emilia, 41125 Modena, Italy
| | - Niccolo’ Bonini
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (E.F.); (M.V.); (N.B.); (J.F.I.); (A.C.V.)
| | - Jacopo F. Imberti
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (E.F.); (M.V.); (N.B.); (J.F.I.); (A.C.V.)
| | - Anna Chiara Valenti
- Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Policlinico di Modena, 41125 Modena, Italy; (V.L.M.); (E.F.); (M.V.); (N.B.); (J.F.I.); (A.C.V.)
| | - Renate B. Schnabel
- German Cardiovascular Research Center (DZHK), Partner Site Hamburg/Kiel/Lübeck, University Heart and Vascular Centre, 20251 Hamburg, Germany;
| | - Ben Freedman
- Heart Research Institute, Charles Perkins Centre, and Concord Hospital Cardiology, University of Sydney, Sydney 2006, Australia;
| |
Collapse
|