Study on the Effectiveness of AF Analysis Software in AF Rhythm Monitoring

Atrial Fibrillation Clinical Trial

— PPG-AF  

Official title:

Study on the Effectiveness of Atrial Fibrillation Analysis Software in Atrial Fibrillation Rhythm Monitoring

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05333380
• Other study ID #: 2022-PPG-AF
• Status: Recruiting
• Start date: August 29, 2022
• Est. completion date: July 2023

Study information

• Verified date: October 2022
• Source: Beijing Anzhen Hospital
• Contact: Chang Sh Ma, Dr.
• Phone: 86-010-64412431
• Email: chshma[@]vip.sina.com
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Atrial fibrillation (AF) is a serious public health problem because of its increasing incidence and prevalence in the aging population. ECG is the most commonly used gold standard for clinical diagnosis of arrhythmias, but conventional ECG examinations are not adequate for long-term ECG follow-up measurements in patients with AF.

In this study, the AF patients will wear an watch and ECG patch to continuously monitor ECG and PPG. The software uses an integrated diagnostic mechanism of "AF burden + AF segments" to efficiently analyze ECG and PPG data, which can quickly and accurately identify the occurrence of AF and analyze AF burden in real-time, facilitating physicians' diagnosis and treatment and efficacy assessment.

Description:

PPG-AF study is a Cohort randomized observational study.The trial will include patients with AF who meet the study requirements from Beijing Anzhen Hospital within 2 months. Each participant will wear an watch and ECG monitor after admission to hospital until Radiofrequency ablation for AF, and after AF ablation until discharge. And more than 18 hours in each period.

1. Primary endpoint. The ECG and PPG data are automatically analyzed by the AF analysis software. The results are compared with expert-annotated gold standard results to verify the sensitivity and specificity.

2. Secondary endpoints. The AF burden calculated from PPG data is compared with that from ECG monitoring, to verify the feasibility of daily monitoring of AF burden using PPG analysis.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 266
• Est. completion date: July 2023
• Est. primary completion date: June 2023
• Gender: All
• Age group: 18 Years to 80 Years

Eligibility

Inclusion Criteria:

• Be at least 18 years of age.

• Have clear ECG-recorded atrial fibrillation in the past and will undergo atrial fibrillation ablation in the current hospitalization.

• Patients who agree to wear both the watch and the ECG recorder.

Exclusion Criteria:

• Inability to wear the watch due to limited mobility or other problems.

• Severe skin diseases such as skin allergies or skin ulcers.

• Chronic insomnia not treated with medication.

• Patients with severe cardiovascular disease who may be resuscitated at any time.

• Previous history of Parkinson's, schizophrenia, epilepsy.

• Black people and those with excessively dark skin.

Related Conditions & MeSH terms

• Atrial Fibrillation
• Atrial Fibrillation Paroxysmal

Intervention

Device:
• ECG/PPG monitoring
The enrolled patients will wear an "ECG patch" and watch at the same time to collect ECG and PPG data respectively. The data collection time is from the day of hospitalization to before the ablation operation, and from 2 hours after the removal of ECG monitoring equipment to before leaving the hospital. The monitoring duration of each patient shall not be less than 18 hours.

Locations

Country	Name	City	State
China	Beijing Anzhen Hospital	Beijing	Beijing
China	Beijing Anzhen Hospital	Beijing	Beijing

Sponsors (2)

Lead Sponsor	Collaborator
Beijing Anzhen Hospital	Heart Health Research Center

Country where clinical trial is conducted

China, 

References & Publications (9)

Andrew NE, Thrift AG, Cadilhac DA. The prevalence, impact and economic implications of atrial fibrillation in stroke: what progress has been made? Neuroepidemiology. 2013;40(4):227-39. doi: 10.1159/000343667. Epub 2013 Jan 24. Review. — View Citation

Freedman B, Camm J, Calkins H, Healey JS, Rosenqvist M, Wang J, Albert CM, Anderson CS, Antoniou S, Benjamin EJ, Boriani G, Brachmann J, Brandes A, Chao TF, Conen D, Engdahl J, Fauchier L, Fitzmaurice DA, Friberg L, Gersh BJ, Gladstone DJ, Glotzer TV, Gwynne K, Hankey GJ, Harbison J, Hillis GS, Hills MT, Kamel H, Kirchhof P, Kowey PR, Krieger D, Lee VWY, Levin LÅ, Lip GYH, Lobban T, Lowres N, Mairesse GH, Martinez C, Neubeck L, Orchard J, Piccini JP, Poppe K, Potpara TS, Puererfellner H, Rienstra M, Sandhu RK, Schnabel RB, Siu CW, Steinhubl S, Svendsen JH, Svennberg E, Themistoclakis S, Tieleman RG, Turakhia MP, Tveit A, Uittenbogaart SB, Van Gelder IC, Verma A, Wachter R, Yan BP; AF-Screen Collaborators. Screening for Atrial Fibrillation: A Report of the AF-SCREEN International Collaboration. Circulation. 2017 May 9;135(19):1851-1867. doi: 10.1161/CIRCULATIONAHA.116.026693. Review. — View Citation

Marini C, De Santis F, Sacco S, Russo T, Olivieri L, Totaro R, Carolei A. Contribution of atrial fibrillation to incidence and outcome of ischemic stroke: results from a population-based study. Stroke. 2005 Jun;36(6):1115-9. Epub 2005 May 5. — View Citation

McManus DD, Lee J, Maitas O, Esa N, Pidikiti R, Carlucci A, Harrington J, Mick E, Chon KH. A novel application for the detection of an irregular pulse using an iPhone 4S in patients with atrial fibrillation. Heart Rhythm. 2013 Mar;10(3):315-9. doi: 10.1016/j.hrthm.2012.12.001. Epub 2012 Dec 6. — View Citation

Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, de Ferranti S, Després JP, Fullerton HJ, Howard VJ, Huffman MD, Judd SE, Kissela BM, Lackland DT, Lichtman JH, Lisabeth LD, Liu S, Mackey RH, Matchar DB, McGuire DK, Mohler ER 3rd, Moy CS, Muntner P, Mussolino ME, Nasir K, Neumar RW, Nichol G, Palaniappan L, Pandey DK, Reeves MJ, Rodriguez CJ, Sorlie PD, Stein J, Towfighi A, Turan TN, Virani SS, Willey JZ, Woo D, Yeh RW, Turner MB; American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics--2015 update: a report from the American Heart Association. Circulation. 2015 Jan 27;131(4):e29-322. doi: 10.1161/CIR.0000000000000152. Epub 2014 Dec 17. Erratum in: Circulation. 2015 Jun 16;131(24):e535. Circulation. 2016 Feb 23;133(8):e417. — View Citation

Perez MV, Mahaffey KW, Hedlin H, Rumsfeld JS, Garcia A, Ferris T, Balasubramanian V, Russo AM, Rajmane A, Cheung L, Hung G, Lee J, Kowey P, Talati N, Nag D, Gummidipundi SE, Beatty A, Hills MT, Desai S, Granger CB, Desai M, Turakhia MP; Apple Heart Study Investigators. Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation. N Engl J Med. 2019 Nov 14;381(20):1909-1917. doi: 10.1056/NEJMoa1901183. — View Citation

Wang Z, Chen Z, Wang X, Zhang L, Li S, Tian Y, Shao L, Hu H, Gao R; for China Hypertension Survey Group. The Disease Burden of Atrial Fibrillation in China from a National Cross-sectional Survey. Am J Cardiol. 2018 Sep 1;122(5):793-798. doi: 10.1016/j.amjcard.2018.05.015. Epub 2018 Jun 2. — View Citation

Wasserlauf J, You C, Patel R, Valys A, Albert D, Passman R. Smartwatch Performance for the Detection and Quantification of Atrial Fibrillation. Circ Arrhythm Electrophysiol. 2019 Jun;12(6):e006834. doi: 10.1161/CIRCEP.118.006834. — View Citation

Witassek F, Springer A, Adam L, Aeschbacher S, Beer JH, Blum S, Bonati LH, Conen D, Kobza R, Kühne M, Moschovitis G, Osswald S, Rodondi N, Sticherling C, Szucs T, Schwenkglenks M; Swiss-AF study investigators. Health-related quality of life in patients with atrial fibrillation: The role of symptoms, comorbidities, and the type of atrial fibrillation. PLoS One. 2019 Dec 23;14(12):e0226730. doi: 10.1371/journal.pone.0226730. eCollection 2019. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	The ECG and PPG data are automatically analyzed by the AF analysis software.	The results are compared with expert-annotated gold standard results to verify the sensitivity and specificity.	Two months after enrollment of the first subject
Secondary	The AF burden calculated from PPG data is compared with that from ECG monitoring.	The AF burden calculated from PPG data is compared with that from ECG monitoring, to verify the feasibility of daily monitoring of AF burden using PPG analysis.	Two months after enrollment of the first subject