Clinical trial NCT05337202: the Dutch-GERAF Study
Official title: The Dutch Multicentre Study Into Opportunistically Screening Geriatric Patients for Atrial Fibrillation Using a PPG Smartphone App; the Dutch-GERAF Study
Study type: OBSERVATIONAL
Overall status: ACTIVE_NOT_RECRUITING
Conditions: Atrial Fibrillation
Frailty
Major Bleed
Keywords: Atrial Fibrillation
Frailty
Major Bleed
Intra cranial Haemorrhage
Cognitive disorder
eHealth
Lead sponsor: Dijklander Ziekenhuis
Sponsor class: OTHER
First posted: 2022-04-20
Enrollment: 1075
Sex: ALL
Minimum age (years): 65
Standard ages: OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: All newly referred patients of 65 years and older that visit a geriatric outpatient service. These will form a cohort of very elderly individuals, with multi morbidity, polypharmacy, cognitive disorders, high frailty and high risk for falling. They can also be seen as a group at high risk of cardiovascular complication and/or the development of cognitive disorders.

Brief summary: Geriatric patients are at high risk of cardiovascular complications, and for the development of atrial fibrillation. Often atrial fibrillation exists in these patients without specific symptoms, and could therefore remain unknown. Furthermore, concerns exist about the bleeding profile of anticoagulation in the very elderly or frail patients.

This study applies opportunistic screening for atrial fibrillation as advised in the latest ESC Guideline on the diagnosis and management of atrial fibrillation. Furthermore, multiple bleeding risk scores will be applies, to better assess the bleeding risk in very elderly or frail patients.


Eligibility criteria: Inclusion Criteria:

All newly referred patients of 65 years and older that visit geriatric outpatient services are eligible (including Fall clinic, Memory clinic, Pre-operative geriatric assessment clinic, or any other geriatric outpatient clinics that are led by a geriatrician).

Exclusion Criteria:

* The patient has a pacemaker or implantable cardioverter defibrillator.
* The patient is known with a severe dementia, MoCA ≤ 15 points.
* The patient has a severe tremor, from whatever cause, and thus is unable to use the PPG based smartphone AF detection algorithm.

Primary outcomes:
measure: Newly identified cases of atrial fibrillation
timeFrame: The first 6 months after recruitment for the study
Secondary outcomes:
measure: Major bleeding
timeFrame: From recruitment until 3 years after the recruitment of the last participant
measure: Stroke
timeFrame: From recruitment until 3 years after the recruitment of the last participant
measure: Death
timeFrame: From recruitment until 3 years after the recruitment of the last participant
measure: Cognitive disorder
timeFrame: From recruitment until 3 years after the recruitment of the last participant
measure: New Atrial Fibrillation, developed after the screening period
timeFrame: From recruitment until 3 years after the recruitment of the last participant
Other outcomes:
Locations:
city: Arnhem
country: Netherlands
facility: Rijnstate
state: Gelderland
city: Hoorn
country: Netherlands
facility: Dijklander Ziekenhuis
state: Noord-Holland
city: Alkmaar
country: Netherlands
facility: Noordwest ziekenhuisgroep
city: Amersfoort
country: Netherlands
facility: Meander Medisch Centrum
city: Amsterdam
country: Netherlands
facility: Onze Lieve Vrouwe Gasthuis
city: Dordrecht
country: Netherlands
facility: Albert Schweitzer Ziekenhuis
Study officials:
affiliation: Northwest Hospital
name: René Jansen, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Zwart LAR, Germans T, Simsek S, Ruiter JH, Jansen RWMM. Atrial fibrillation, anticoagulation and major bleeding in geriatric patients at risk of falling. OBM Geriatrics 2019, Volume 3, Issue 3, doi:10.21926/obm.geriatr.1903071
citation: Mol D, Riezebos RK, Marquering HA, Werner ME, Lobban TCA, de Jong JSSG, de Groot JR. Performance of an automated photoplethysmography-based artificial intelligence algorithm to detect atrial fibrillation. Cardiovasc Digit Health J. 2020 Oct 22;1(2):107-110. doi: 10.1016/j.cvdhj.2020.08.004. eCollection 2020 Sep-Oct. No abstract available.
citation: Hindricks G, Potpara T, Dagres N, Arbelo E, Bax JJ, Blomstrom-Lundqvist C, Boriani G, Castella M, Dan GA, Dilaveris PE, Fauchier L, Filippatos G, Kalman JM, La Meir M, Lane DA, Lebeau JP, Lettino M, Lip GYH, Pinto FJ, Thomas GN, Valgimigli M, Van Gelder IC, Van Putte BP, Watkins CL; ESC Scientific Document Group. 2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS): The Task Force for the diagnosis and management of atrial fibrillation of the European Society of Cardiology (ESC) Developed with the special contribution of the European Heart Rhythm Association (EHRA) of the ESC. Eur Heart J. 2021 Feb 1;42(5):373-498. doi: 10.1093/eurheartj/ehaa612. No abstract available.
citation: Zwart LA, Jansen RW, Ruiter JH, Germans T, Simsek S, Hemels ME. Opportunistic screening for atrial fibrillation with a single lead device in geriatric patients. J Geriatr Cardiol. 2020 Mar;17(3):149-154. doi: 10.11909/j.issn.1671-5411.2020.03.007.
citation: Searle SD, Mitnitski A, Gahbauer EA, Gill TM, Rockwood K. A standard procedure for creating a frailty index. BMC Geriatr. 2008 Sep 30;8:24. doi: 10.1186/1471-2318-8-24.
citation: Rockwood K, Mitnitski A. Frailty in relation to the accumulation of deficits. J Gerontol A Biol Sci Med Sci. 2007 Jul;62(7):722-7. doi: 10.1093/gerona/62.7.722.
citation: Moraes JL, Rocha MX, Vasconcelos GG, Vasconcelos Filho JE, de Albuquerque VHC, Alexandria AR. Advances in Photopletysmography Signal Analysis for Biomedical Applications. Sensors (Basel). 2018 Jun 9;18(6):1894. doi: 10.3390/s18061894.