I came across a news item stating that Apple and Alivecor had worked out that they could reliably judge a potassium level based on the ECG. While this is clever it isn’t that much of a surprise given when learning how to interpret ECGs you learn what low potassium and high potassium look like. I guess matching it closely to an exact figure is just a question of being able to measure accurately.
Don’t get me wrong I’m impressed and indeed I wrote an article a while ago on digitalhealth.net about possible uses of this tech.
I’d just like to remind everyone about QTc intervals which I think could be equally huge but no one seems to be talking about. Without getting too technical the distance from one part of an ECG waveform to another (from the Q to the T!) adjusted for the rate is a significant measurement that you can make on an ECG.
The longer it gets the more likely someone is to have a serious arrhythmia. Now it can be affected by a load of things but the most common is drugs. Quite a lot of drugs cause a lengthening of the QTc and sometimes combinations of drugs make it worse. Dietary substances can interact as can states of hydration.
Often when we prescribe a drug, we get all sorts of warnings about the QTc. Of course, without bringing someone in to do an ECG you don’t know what their QTc is at any point.
It would seem sensible to me to give patients at risk of a long QTc a smartwatch to monitor it on a regular basis. It could send alerts to medical staff if abnormal. Of course, quite a few of the drugs that cause the problem are mental health drugs and you wonder if this isn’t a sexy or lucrative market to be researching in as opposed to the worried well with a disposable income. But surely if it avoided some hospital admissions or even deaths it could pay for itself.