Long Covid sufferers don’t have it easy; they have to work harder than everyone else to get the care they need. They have to do research and advocate for themselves in ways people with better-understood diseases don’t. Our work is making sure they have the tools they need to make that work worthwhile and to maximize the outcomes they get from their effort.
We recently posted an article discussing the concept of titration: in plain language, titration is using your impression of how you feel as feedback to guide changes you make to the dose of a medication. If you’ve found your way to this article you are probably most familiar with titration as it relates to ramping up low-dose naltrexone (LDN) dose amounts. LDN is one of the most promising treatments for Long Covid symptoms, but it comes with a few common side effects like nausea, poor sleep quality, headaches, and fatigue that are best avoided by starting your dose low and increasing it over time.
This kind of fine-tuning is tricky at the best of times, but it moves up a difficulty tier for someone who is weighed down by Long Covid brain fog or fatigue. We’d like to go more in-depth on how Eureka’s app can help with that by making the data-collection pieces of the process easier, showing you your outcomes in a clearer way, and uncovering important aspects of your journey you might otherwise miss.
The first step to monitoring the process of titration is deciding what data you want to gather. The first and most obvious factor to track is your LDN dose. The app does the heavy lifting here - when you go to set up your new experiment, it will ask all the relevant questions: The name of the experiment, the kind of data being tracked, and how often you want the app to gather data. You will end up with something like this, which tracks your dose on a daily basis:
The app will now alert you when it’s time to complete your daily surveys, which then take only a few seconds to fill out. It would be really easy to skate right past this point, but it’s worth stopping and noting how useful this already is; the reminder notifications alone are a big deal. Habits are hard to establish and even harder to keep; the app makes this much easier by reminding you to take the surveys at the appropriate time and keeping things simple and easy when you do.
Since the app automatically slices and dices the raw data into various kinds of visualizations, it’s much easier to look at your data in meaningful ways compared to trying to mine meaning from written notes or a spreadsheet. In this case, the app would automatically deliver a chart tracking your dose that might look something like this:
You might object that this chart isn’t all that useful by itself; since you are probably only adjusting your dose every week or two, you could have tracked that yourself. But now imagine that you also told the app that it should ask about the severity of both brain fog and fatigue symptoms in your daily survey. Now you have something to compare the dose with:
And suddenly you’ve learned an incredibly useful thing: your brain fog symptoms are improving more the higher your dose goes, and you have a no-guesswork way to see exactly how big that improvement is.
Tracking more symptoms is as easy as adding them to the surveys; the app will then ask you about them and automatically generate similar reports. We keep setup easy and fast because it’s important; the idea is to make sure everything is low-effort in a way that accommodates detailed tracking of the aspects of your health that matter to you.
We’ve been talking about tracking the upsides of the treatment, but you also care about the downside in the form of side effects. Since you also want to see enough side effects data to know what to do to avoid them, you might set up an experiment that tracks the downsides of the treatment as well:
You can also add in harder, less subjective forms of data. The app talks to wearables like sleep and fitness trackers, so it’s easy to set up a hands-off experiment that records specifics that would otherwise be tedious to track:
You sometimes might learn that a particular health metric is unaffected by a particular input, as is the case with resting heart rate and LDN treatments not interacting in any obvious way in the example above. That’s a feature, not a bug; ruling out possible effects by gathering evidence that indicates they aren’t significant is just as important as finding the effects that do make a difference.
You are now pretty firmly in the realm of more-than-you-could-do-yourself; the app is now potentially tracking dozens of health metrics and can automatically take some or all of them to make visualizations for any part of it you want to examine. Since a dozen streams of data might be too much to look at at one time, the results are adjustable with just the push of a button:
Most people get hangovers when they drink too much. It’s really easy to tell this is true because the relationship between the two things is very direct - if you have a lot of drinks on Friday, you are going to feel bad on Saturday. It’s not a pattern that’s hard to detect. But now imagine that hangovers were delayed by 20-30 days from the night at the bar; it would be much, much harder to uncover that relationship.
People would have probably figured out the hangover/alcohol connection eventually, but it would have taken longer. The same principle is true with LDN treatments and your health in general - less obvious correlations are much harder to notice, even if they are just as important to find.
The more aspects of your health and habits that you track, the greater chance you have to uncover unexpected but significant effects. Even if you don’t expect caffeine to be a specific part of your Long Covid picture, you can still track how many cups you drink. If you think exercise might play a role, you can track that as well. Because setting up an experiment is easy and the surveys are so quick to fill out, it’s a low-cost proposition to track more data than you are sure you need and see what you uncover.
As an example, imagine that in addition to tracking how much LDN you took a day you also decided to track the time of day you took the dose. Some people report poor sleep quality or insomnia from the treatment; imagine you noticed that same effect in yourself some nights. Comparing the time-of-dose and poor sleep quality data might uncover something like this:
There’s a good chance you’d miss this kind of association keeping track of things mentally, but this experiment makes the relationship much more obvious. You’d now have an indication you wouldn’t have otherwise had that taking your doses earlier might just solve some of the problems with your sleep. Not every type of data you track will end up driving amazing discoveries, but the more you track the better chance you have of learning useful things about your health you wouldn’t have otherwise known.
The potential for individuals to learn more about their health with the app is obvious, but the potential of what we can do goes up exponentially as more and more of us work together. If one person’s health data is a powerful thing, the combination of different data from dozens, hundreds or thousands of people is much more so.
With permission, we can take anonymized data from many people and use it to learn more about the best treatments for little-known diseases. This lets us uncover useful information one person’s data might not show by itself. The potential here is huge; as we get more and more data to work with, we will be able to design better experiments, find insights that were unfindable on the individual level, and help demystify new and poorly understood diseases faster.
Covid is here to stay, which means that Long Covid isn’t going anywhere either. People like you are doing the hard work to pioneer the treatments and knowledge that we hope will pave the way for future Long Covid sufferers to get better faster. The more we learn together, the better we will be able to help, and the better outcomes will get for everyone both now and in the future.
If you are down, we can do some cool things. Let’s get to it.
Feel free to contact me at email@example.com if you need advice, help, or insight—I am happy to help!