Nadim Yared: Bill, the study and by the way. Thank you for this question. It’s an excellent question. Yes, direct-to-consumer awareness campaigns that medical device companies did 20-years ago are very different from what we are doing today. Think about it, what they did back then, putting TV ads was an open loop system. What we’re doing is a closed loop system. We favor channels where we have traceability of every single click and every single patients. I mean, everything was saw the ads and convert it, so we know all of those metrics at every single stage of the game. And the visible tip of the iceberg is the marketing campaign itself. 90% of the work is what happened behind the scene. Those consumers who saw the ad all the way to becoming candidate or not becoming to identify if they are candidates to basically offer them possibilities and contact our sites that are doing the procedure.
So cost for every single one of those campaigns is very closely tracked and monitored almost on a daily basis and we wanted to optimize. We’re not in the business right now of throwing money and creating awareness. This is not what we’re doing. We’re paying money where we believe that those money would lead to X number of patients. And that equation should be profitable for us from their , that’s what we’re trying to explore. As an example, we added a new channel two days ago. And we’ll be testing it for a few weeks, iteration and see if it’s as profitable, more profitable or less profitable than other channels we’re using. And that’s mainly what we’re trying to do here, trying to figure out different geographies, different type of sites different type of advertisement, different channels between some of the , social media out there.
And you do not advertise Facebook the same way you do it on Instagram or TikTok or Twitter and so forth. So it’s a big
William Plovanic: Okay, good. And then quick Jared, the 1.136 gain in the other, that’s a little it’s kind of a big number, just curious what would that was. And then just you’ve kind of went through it with Margaret, but in like as simply as possible, what would you define as positive, what would you define as neutral and what would you define as negative for the B2HF outcomes. And I know that’s hard to do, but I think for investors, if you could sum it up like where are those kind of break points and how should we think about it? Thanks.
Jared Oasheim: Hey, Bill. I’ll just — on the first piece of it, I mean, the biggest chunk that’s fallen into that other expense net bucket is the interest income that we’re seeing from the cash balance that we have at this point in time. So that’s kind of the biggest number there. Nadeem, I’ll let you cover the second piece.
Nadim Yared: Yes. Regarding the and statistics though, there is a p-value that you’ve widened five to ensure that the type one error less than a certain percentage, right? So what FDA wants to know is whether you achieve those results as a fluke by chance or whether the observation is preparation . What I consider to be positive is if the primary endpoint met the statistical relevance that FDA is looking for. I would then say it will be in between Margaret, if either the is trending close to that point, but not reaching it or what if other pre-specified, prioritized endpoints that we have previously agreed with FDA to analyze with clinical relevance. Why do I say so? Usually, when you’re designing a for approval, you select the endpoint, FDA approved the endpoint and if you need the endpoint, you win, if you don’t beat the endpoints, you lose and that’s the end of the game.