With a global pandemic still ongoing and vaccines still scarce, early detection of COVID-19 is key to treating the disease. Unfortunately, COVID-1
The study comes from researchers at Mount Sinai, where hundreds of health workers wore an Apple Watch for eight hours a day. Each participant also answered daily surveys about their current symptoms through a custom app designed for the study. The large number of employees and the long periods of time should help to achieve good consistent results across a wide spectrum, but the results must be confirmed as with all studies.
But the study uncovered several intriguing findings. The researchers kept a close eye on heart rate variability (HRV), which measures changes in your heart rate that could indicate imbalances in the autonomic nervous system. According to the researchers, subtle changes in HRV helped predict COVID-19 infections up to a week before a nasal swab was tested.
That puts the timing right at a time when a person may not realize they are infected and could spread COVID-19 to others. Researchers also found that HRV returned to normal 7-14 days after diagnosis. Statistically, the HRV of an infected patient looks the same as that of an uninfected person. That would indicate that early monitoring is even more important.
Early detection can help slow the spread of COVID-19 and lead to life-saving treatments earlier in the process. And by using an Apple Watch (or other heart rate tracking devices), doctors can even remotely detect and diagnose the disease, without having to go to the hospital or doctor’s office. All of this is a huge victory in the fight against the pandemic.
Other similar investigations are underway, such as the NBA’s use of Oura Rings in a similar fashion, and that’s a good thing. One study is not enough to trust results; it is always best if the results are confirmed in independent follow-up studies. But it’s a good sign of new ways to detect and prevent the spread of the disease using everyday equipment that people may already own.
Source: Journal of Medical Internet Research