Risk factor management of atrial fibrillation using mHealth: The Atrial Fibrillation – Helping Address Care with Remote Technology (AF-HEART) Pilot Study

Mitrani, Lindsey; Goldenthal, Isaac; Leskowitz, Jamie; Wan, Elaine; Dizon, José; Saluja, Deepak; Creber, Ruth Masterson; Turchioe, Megan Reading; Sciacca, Robert R.; Garan, Hasan; Hickey, Kathleen T.; Körner, Judith; Biviano, Angelo

doi:10.1016/j.cvdhj.2021.11.003

Cited by 2 publications

(3 citation statements)

References 59 publications

(107 reference statements)

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“…In the Atrial Fibrillation Helping Address Care with Remote Technology (AF-HEART) prospective cohort study, 20 patients with AF undergoing antiarrhythmic therapy, cardioversion, and/or catheter ablation underwent an intervention including heart rhythm tracking (AliveCor, Kardia), risk factor reduction by weight reduction, blood pressure monitoring, alcohol reduction, and sleep apnea reduction through referrals. 66 During the 6-month follow up period, the quality of life improved and symptom severity decreased.…”

Section: Integrated Digital Atrial Fibrillation Management: a Systema...mentioning

confidence: 95%

“…A total of 33 publications were considered relevant. Of those, 14 publications reported on integrated e-health enhanced management of AF, 47 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 5 on remote AF management platforms, 65 , 66 , 67 , 68 , 69 3 publications on mHealth-based heart rate/rhythm monitoring, 70 , 71 , 72 6 publications on mHealth supported patient self-care and medication adherence tools 73 , 74 , 75 , 76 , 77 , 78 and 5 publications reported on clinical decision making support tools. 79 , 80 , 81 , 82 , 83 …”

Section: Integrated Digital Atrial Fibrillation Management: a Systema...mentioning

confidence: 99%

“… 65 United Kingdom PC Ortus-iHealth Virtual arrhythmia clinic appointment via video call 46 62 (23–86) 36% 3 months Patient activation: high satisfaction with installation and registration process (in 62% patients), sense of reminders (100%) and clinical letters (83%) usefulness, sense of cost- and time-effectiveness (80%) Small sample size Short FU Lack of control group Mitrani et al. 66 PC AF-HEART Heart rhythm, weight and BP tracking, televisitations (dietician), referrals for sleep apnea and hypertension treatment 20 62 ± 8.0 35% 6 months Weight loss mean 3.5 kg (p = 0.005) or 3.3 ± 4.4% Patient QoL (baseline vs FU): improved based on SF-12 (p = 0.01), AFSS (p = 0.01), EQ-5D (p = 0.006), AFEQT (p = 0.03) Correlation between weight loss and decrease in symptom severity (absolute r = −0.45, p = 0.05 and % r = −0.49, p = 0.03) Small sample size Single-center setting Stegman et al. 67 Germany RCT Daily transmission of body weight, BP, heart rate/rhythm, oxygen saturation, and self-rated health status 282 (IC) 289 (UC) 74 ± 8.0 74 ± 8.1 32% 30% 12 months Days lost due to unplanned CV death or hospitalization (IC vs UC): OR 0.60, 95% CI 0.25–0.95 All-cause mortality: HR 0.60, CI 0.36–1.00 Unpowered results Specific-region setting New-diagnosed AF not considered in the analyses Weng et al.…”

Section: Integrated Digital Atrial Fibrillation Management: a Systema...mentioning

confidence: 99%

See 2 more Smart Citations

Atrial fibrillation: epidemiology, screening and digital health

Linz,

Gawalko,

Betz

et al. 2024

The Lancet Regional Health - Europe

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Section: Integrated Digital Atrial Fibrillation Management: a Systema...mentioning

confidence: 95%

Section: Integrated Digital Atrial Fibrillation Management: a Systema...mentioning

confidence: 99%

Section: Integrated Digital Atrial Fibrillation Management: a Systema...mentioning

confidence: 99%

See 1 more Smart Citation

Atrial fibrillation: epidemiology, screening and digital health

Linz,

Gawalko,

Betz

et al. 2024

The Lancet Regional Health - Europe

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Factors Associated with Quality of Life among People with Atrial Fibrillation: Jordan Atrial Fibrillation Registry Study

Al-Bashaireh,

Alkouri,

Alharbi

et al. 2024

Medicina

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Background and Objectives: Atrial fibrillation (AF) is a common arrhythmia that may adversely affect the quality of life (QoL). Several factors could be associated with the QoL among patients with AF; however, evidence regarding these factors is still limited and controversial. Therefore, this study aimed to identify the level of QoL and its associated factors among Jordanian patients with AF. Subjects and methods: A case study design was implemented. A sample of 620 participants were recruited from 28 outpatient clinics registered in the Jordan atrial fibrillation registry AF (JoFIB). Data on QoL were gathered through the self-reported Atrial Fibrillation Effect on Quality-of-life tool (AFEQT). A QoL questionnaire was validated in this population before starting this study. The cardiac nurse then provided the research assistant with data relating to patients’ characteristics and associated comorbidities. Results: The overall AFEQT scores were positively skewed (median 21.3, IQR: 14.4–31.9). This pattern was reflected for the AFEQT sub-scales ‘Symptoms’ (20.8, 8.3–33.3), ‘Daily activities’ (16.7, 10.4–27.1), and ‘Treatment concerns’ (27.8, 19.4–41.7), whereas ‘Treatment satisfaction’ was negatively skewed (91.7, 83.3–91.7). Patients in the higher quartiles, indicating a better QoL, tended to be younger and were less likely to experience dyslipidemia, stroke, pulmonary hypertension, or other comorbidities. Over 90% of patients were currently experiencing AF, and patients with a better QoL tended to be less likely to be currently experiencing AF and more likely to have had their latest episode of AF more than a month ago (compared to less than a month ago). Age, BMI, dyslipidemia, heart failure, COPD, CAD, history of ablation, and the use of anticoagulants were significantly associated with the overall AFEQT score (R2 = 0.278). Conclusions: This study demonstrates that AF Jordanian patients had low levels of QoL. Patients in higher quartiles for the overall AFEQT score were younger, with fewer disease comorbidities and less experience of current AF episodes. Several modifiable and non-modifiable factors were associated with QoL in AF patients. Age, BMI, dyslipidemia, heart failure, COPD, CAD, history of ablation, and the use of oral anticoagulants were significantly associated with the overall AFEQT score. Healthcare providers should target these factors as indicators or interventions for which QoL is continuously monitored.

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Risk factor management of atrial fibrillation using mHealth: The Atrial Fibrillation – Helping Address Care with Remote Technology (AF-HEART) Pilot Study

Cited by 2 publications

References 59 publications

Atrial fibrillation: epidemiology, screening and digital health

Atrial fibrillation: epidemiology, screening and digital health

Factors Associated with Quality of Life among People with Atrial Fibrillation: Jordan Atrial Fibrillation Registry Study

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