The value of wearable cardioverter defibrillator in adult patients with recent myocardial infarction: Economic and clinical implications from a health technology assessment perspective.

AIMS: Sudden cardiac death (SCD) causes high mortality and substantial societal burdens for healthcare systems (HSs). The risk of SCD is significantly increased in patients with reduced left ventricular ejection fraction after myocardial infarction (MI). Current guidelines recommend re-evaluation of cardioverter-defibrillator implantation 40 days post-MI, earliest. Medical therapy alone does not provide sufficient protection against SCD, especially in the first month post-MI, and needs time. Consequently, there is a gap in care of high-risk patients upon hospital discharge. The wearable cardioverter defibrillator (WCD) is a proven safe, effective therapy, which temporarily protects from SCD. Little information on WCD cost-effectiveness exists. We conducted this research to demonstrate the medical need of the device in the post-MI setting defining WCD cost-effectiveness. METHODS & RESULTS: Based on a randomized clinical trials (RCTs) and Italian and international data, we developed a Markov-model comparing costs, patient survival, and quality-of-life, and calculated the Incremental Cost-Effectiveness Ratio (ICER) of a WCD vs. current standard of care in post-MI patients. The rather conservative base case analysis - based on the RCT intention-to-treat results - produced an ICER of €47,709 per Quality Adjusted Life Year (QALY) gained, which is far lower than the accepted threshold of €60,000 in the Italian National HS. The ICER per Life Year (LY) gained was €38,276. CONCLUSION: WCD utilization in post-MI patients is clinically beneficial and cost-effective. While improving guideline directed patient care, the WCD can also contribute to a more efficient use of resources in the Italian HS, and potentially other HSs as well.

Rationale and design of a large population study to validate software for the assessment of atrial fibrillation from data acquired by a consumer tracker or smartwatch: The Fitbit heart study.

BACKGROUND: Early detection of atrial fibrillation or flutter (AF) may enable prevention of downstream morbidity. Consumer wrist-worn wearable technology is capable of detecting AF by identifying irregular pulse waveforms using photoplethysmography (PPG). The validity of PPG-based software algorithms for AF detection requires prospective assessment. METHODS: The Fitbit Heart Study (NCT04380415) is a single-arm remote clinical trial examining the validity of a novel PPG-based software algorithm for detecting AF. The proprietary Fitbit algorithm examines pulse waveform intervals during analyzable periods in which participants are sufficiently stationary. Fitbit consumers with compatible wrist-worn trackers or smartwatches were invited to participate. Enrollment began May 6, 2020 and as of October 1, 2020, 455,699 participants enrolled. Participants in whom an irregular heart rhythm was detected were invited to attend a telehealth visit and eligible participants were then mailed a one-week single lead electrocardiographic (ECG) patch monitor. The primary study objective is to assess the positive predictive value of an irregular heart rhythm detection for AF during the ECG patch monitor period. Additional objectives will examine the validity of irregular pulse tachograms during subsequent heart rhythm detections, self-reported AF diagnoses and treatments, and relations between irregular heart rhythm detections and AF episode duration and time spent in AF. CONCLUSIONS: The Fitbit Heart Study is a large-scale remote clinical trial comprising a unique software algorithm for detection of AF. The study results will provide critical insights into the use of consumer wearable technology for AF detection, and for characterizing the nature of AF episodes detected using consumer-based PPG technology.

Clustering Insomnia Patterns by Data From Wearable Devices: Algorithm Development and Validation Study.

BACKGROUND: As societies become more complex, larger populations suffer from insomnia. In 2014, the US Centers for Disease Control and Prevention declared that sleep disorders should be dealt with as a public health epidemic. However, it is hard to provide adequate treatment for each insomnia sufferer, since various behavioral characteristics influence symptoms of insomnia collectively. OBJECTIVE: We aim to develop a neural-net based unsupervised user clustering method towards insomnia sufferers in order to clarify the unique traits for each derived groups. Unlike the current diagnosis of insomnia that requires qualitative analysis from interview results, the classification of individuals with insomnia by using various information modalities from smart bands and neural-nets can provide better insight into insomnia treatments. METHODS: This study, as part of the precision psychiatry initiative, is based on a smart band experiment conducted over 6 weeks on individuals with insomnia. During the experiment period, a total of 42 participants (19 male; average age 22.00 [SD 2.79]) from a large university wore smart bands 24/7, and 3 modalities were collected and examined: sleep patterns, daily activities, and personal demographics. We considered the consecutive daily information as a form of images, learned the latent variables of the images via a convolutional autoencoder (CAE), and clustered and labeled the input images based on the derived features. We then converted consecutive daily information into a sequence of the labels for each subject and finally clustered the people with insomnia based on their predominant labels. RESULTS: Our method identified 5 new insomnia-activity clusters of participants that conventional methods have not recognized, and significant differences in sleep and behavioral characteristics were shown among groups (analysis of variance on rank: F4,37=2.36, P=.07 for the sleep_min feature; F4,37=9.05, P<.001 for sleep_efficiency; F4,37=8.16, P<.001 for active_calorie; F4,37=6.53, P<.001 for walks; and F4,37=3.51, P=.02 for stairs). Analyzing the consecutive data through a CAE and clustering could reveal intricate connections between insomnia and various everyday activity markers. CONCLUSIONS: Our research suggests that unsupervised learning allows health practitioners to devise precise and tailored interventions at the level of data-guided user clusters (ie, precision psychiatry), which could be a novel solution to treating insomnia and other mental disorders.

Benefit of the Wearable Cardioverter-Defibrillator in Protecting Patients After Implantable-Cardioverter Defibrillator Explant: Results From the National Registry.

OBJECTIVES: This study reports on the time course of reimplantation and benefits of the wearable cardioverter-defibrillator (WCD) in patients post implantable cardioverter-defibrillator (ICD) explantation. BACKGROUND: The WCD is used to treat patients at high risk for ventricular tachycardia (VT) and ventricular fibrillation (VF), including patients with ICD-related infections who undergo device removal and cannot be immediately reimplanted. METHODS: This retrospective study included consecutive patients from 2002 to 2014 who underwent ICD removal because of device-related infection and were prescribed a WCD. WCD-stored electrocardiograms were reviewed. Event outcome was assessed through either the manufacturer WCD registry or the Social Security death index search. RESULTS: A total of 8,058 patients (mean age 62 ± 14 years, 75% male) were included in the analysis. Median time to reimplantation of an ICD was 50 days (interquartile range: 24 to 83 days). While wearing the WCD, 334 patients (4%) experienced 406 VT/VF events, of which 348 events were treated. Shocks were averted in 54 events by conscious patients. The overall 24-h survival, both treated and nontreated, was 93% (312 of 334). VT/VF occurrence was the highest in the initial weeks after ICD removal (0.9%, 0.7%, and 0.7% per week for weeks 1, 2, and 3, respectively). The 12-month cumulative event rate was 10%. For all patients, the 30-day post-event survival was 81%. An ICD was reimplanted in 80% of patients. CONCLUSIONS: The risk of VT/VF reaches 4% during the first 2 months and 10% at 1 year after ICD removal. WCD demonstrated a high efficacy for protecting patients from VT/VF. Clinicians may use the WCD as an ICD alternative when reimplantation is medically delayed.