Mobile Apps Improve Atrial Fibrillation Detection

A new study has shown that mobile health (mHealth) devices are able to screen for the common cardiac disorder called atrial fibrillation (AF). This condition which affects about a million people in the UK denotes an irregular heartbeat (called arrhythmia) originating in the abnormal fluttering contraction of the heart’s upper chambers, or atria. In contrast, the normal heart has a regular “sinus rhythm”; triggered by the regular electrical impulses from the sino-atrial (SA) node in the right atrium.

Many causes can cause atrial fibrillation; but the outcome is an abnormally random and sometimes extremely rapid heart rate which prevents the heart from fulfilling its pumping action. Since each beat occurs at no fixed interval from the last; also often at a very short interval, the heart cannot get time to relax and receive the infilling blood. This reduces the volume of blood pump out of the heart and therefore the supply of oxygen to the whole body.

These clots or clot fragments are then carried down to the ventricles and out through the large arteries, to lodge in the body veins or in the lungs, depending on which ventricle they are pumped from. Thus AF is associated with a high risk of stroke due to a clot fragment in a brain vessel, lung embolism (blockage of a lung vessel by a clot), of death, of heart failure and dementia. However, the lack of early symptoms and failure to take medication as required contribute to the difficulty of managing this condition properly.

Cause of atrial fibrillation

Several screening techniques have test but do not show much benefit in terms of preventing complications of AF. Single-lead ECG approaches have been able to increase the detection rates of new-onset AF in high-risk groups; but without obvious impact on adverse sequelae like stroke or embolism. As a result, community level screening is not recommended by public health organizations.

The use of a smartwatch strap with a sensor for ECG recording is a better method for continuous monitoring; but only 66% of the signals picked up can be interpret by the app algorithm in isolation; also requiring modifications to enhance signal quality and eliminate motion artifacts. The new study looked at the current use of fitness trackers; so smart watches and mobile phones to help people remain healthy. It concludes that using a technique called photoplethysmography (PPG); it is possible to make a diagnosis of AF in a non-invasive and inexpensive manner.

The current study explore the success of the mAF App; which is an AF mobile platform; so that brings together tools to support clinical decision making; treatment base on medical guidelines; educational materials and self-monitoring and self-care strategies, with follow up. The app can be download; also use with any compatible mobile device. The aim was to screen a low-risk population for AF and analyze the incidence of AF as well as the percentage of patients who successfully treat with anticoagulation.

Feasibility of using smart devices

The researchers look at the feasibility of using smart devices equip with PPG technology for this screening; follow by adoption of a standard course of clinical management if atrial fibrillation was detected. The study include almost 190 000 participants with smart Health devices which measure the pulse rate and rhythm for 14 days or longer. All participants were 18 years or above.

Almost 92% of the signals confirm to be AF, showing the high sensitivity of this method. The number of patients who were suspect to have AF following this initial screening was about 420 (0.23%). However, above 55 years the detection rate was much higher, at 2.62%; showing the validity of this tool in an older population with assume higher risk as well.

Researcher Yutao Guo says, “Base on our present study; continuous home-monitoring with smart device base PPG technology could be a feasible; cost-effective approach for AF screening. This would help efforts at screening and detection of AF; as well as early interventions to reduce stroke and other AF-related complications.” This approach combines comfort, quality and continuity of signal monitoring without motion artifacts; allowing high predictive value for AF using smart devices.