特别版：未来展望——糖尿病患者的新兴技术

欢迎收看糖尿病核心更新特别系列，我们将探讨糖尿病患者的新技术。

Welcome to this special series of Diabetes Core Update, where we will discuss emerging technologies for people with diabetes.

最近，全球最大的糖尿病技术盛会——ATTD 2026（第十九届国际糖尿病先进技术与治疗大会）在巴塞罗那举行，我们将讨论会上的一些令人兴奋的进展。

Recently, the world's largest technology conference for people with diabetes, ATTD twenty twenty six, that stands for the nineteenth International Conference on Advanced Technologies and Treatments for Diabetes, was held in Barcelona, and we're gonna discuss some of the exciting things that were going on there.

我是您的主持人，医生。

I'm your host, Doctor.

尼尔·斯科尼克，托马斯·杰斐逊大学西德尼·金梅尔医学院家庭与社区医学教授。

Neil Skolnik, Professor of Family and Community Medicine at the Sidney Kimmel Medical College of Thomas Jefferson University.

本系列糖尿病核心更新特别节目由西格罗夫合伙公司赞助。

This special series of Diabetes Core Update is sponsored by Seagrove Partners.

今天与我们一同讨论这一主题的是埃里克·韦尔霍夫。

And joining us to discuss this topic is Erik Veerhoef.

先生。

Mr.

韦尔霍夫先生是西格罗夫合伙公司的创始人、总裁兼首席执行官。

Veerhoef is the founder, president, and CEO of Seagrove Partners.

Seagrove Partners是一家利用数据发掘客户和行业洞察的研究与咨询公司。

Seagrove Partners is a research and consulting firm that uses data to discover customer and industry insights.

Erik于2016年创立了Seagrove Partners，此前他在Tandem Diabetes Care工作了九年，负责战略、业务发展、市场营销和市场研究，主导了获奖的胰岛素泵t:slim的设计与商业化推出。

Erik founded Seagrove Partners in 2016 after spending nine years at Tandem Diabetes Care, where he headed up strategy, business development, marketing, and market research, leading to the design and commercial launch of t:slim, the award winning insulin pump.

他还曾在BioCyte、百时美施贵宝和葛兰素史克担任商业分析和市场营销方面的职务。

He also held roles in commercial analytics and marketing at BioCyte Bristol Myers Squibb and GlaxoSmithKline.

Erik，欢迎来到ADA糖尿病核心更新播客。

Erik, welcome to the ADA's Diabetes Core Update podcast.

谢谢邀请我。

Thank you for having me.

Erik，我知道你最近参加了ATTD会议。

Erik, I know you were recently at ATTD.

今年你认为最突出的主题或变化是什么？

Your sense of what the biggest themes were or shifts that stood out to you this year?

当然。

Sure.

是的

Yeah.

这是我最喜欢参加的会议之一。

It's one of my favorite con conferences to go to.

我从2013年左右就开始参加这个会议了，那时Libre刚刚被首次公布。

I've I've been going to this since about 2013, which is when the Libre was first kind of announced.

当时我根本不知道雅培在那个产品上做什么，但他们早就清楚了。

And I back then, I had no idea what Abbott was doing with that, you know, that product, but they knew.

而我们现在都看到了它的成功。

And, you know, we all now have seen kind of the success of that.

所以这是一个很多糖尿病设备发布的重要会议。

So it's one of these conferences where a lot of diabetes devices kind of get launched.

而这次会议，我认为最大的收获是，胰岛素泵和闭环系统在自动化方面投入了大量工作。

And in this one, I think the big takeaway was, just the amount of work that's being done on the insulin pump side and AID systems to automate things more and more.

具体来说，我认为距离市场上推出能自动计算餐时胰岛素剂量的商业产品，还差一年左右。

So specifically, we're, I'd say we're a year away from a commercial product on the market that automates meal boluses.

所以人们不需要再手动宣布用餐。

So people don't have to announce meals.

他们不需要计算碳水化合物，而且即使不与泵有任何互动，您的目标范围内时间也能超过70%，甚至高于ADA指南。

They don't have to count carbs and essentially, you know, your time and range is gonna be above the ADA guidelines above 70%, even without any interaction with the pump.

而如今的系统已经接近能够实现这一点。

And with today's systems, they're kind of close to being able to do that.

我认为有些人已经在超适应症使用，但我们在巴塞罗那看到的算法改进，正是为了训练泵，使其能大致判断您何时进食，并做出相应调整。

And I think some people kind of do that off label, but the algorithm improvements from what we saw in Barcelona are specifically designed to train the pump so that it knows when you're eating basically and makes the appropriate adjustment.

因此，MiniMed在这方面的进展可能是最领先的，他们展示了一些初步数据，预计今年将向FDA提交该新产品的申请。

So MiniMed was probably the farthest along with that and they presented some kind of initial data, but they probably will be filing that with the FDA this year for that new product.

但其他公司如SelectTandem和MyLife（原Ipsomed）也在各自开发这一技术，采用不同的算法参数。

But the other companies in SelectTandem, MyLife, which used to be Ipsomed, they're all working on this with different forms and factors on the algorithm.

但我认为，这对那些目前注射胰岛素、却觉得胰岛素泵操作繁琐、需要大量数据输入的人来说，真的令人振奋。

But I think that it's really exciting for people that are either currently taking injections and maybe feel like pumps are kind of require a lot of work and a lot of data entry and things like that.

而现在，如果所有功能都能自动化，那么真正的问题就变成了：您是愿意佩戴设备，还是继续选择注射。

And now, you know, if everything's kind of automated, then it's really a discussion about, you know, whether you wanna wear a device versus take an injection.

这确实是个进步。

And that's something.

对于像我们这些医生听众来说，作为非技术背景的人，您有什么见解吗？

And do you have any insight in a manner that lay techno people like all of us doctors listening?

是什么让我们能够做到这一点？

What led to us being able to do that?

是否有什么新的因素促使这些公司能够开发出这些算法？

Is there something new that led led the companies to be able to create these algorithms?

是的。

Yeah.

有几个方面。

There's a there's a couple things.

我认为其中一个重大变化是FDA允许研究人员使用这些计算机模拟模型，也就是说，他们不再需要进行大规模的、有对照组和活性对照组的人体关键性试验，现在可以通过计算机分析以往的患者数据，来预测算法的表现并进行训练。

I think one of the big changes was the FDA allowing researchers to use these in silico models where essentially they're they don't have to do these giant pivotal trials with humans, you know, with a comparator and an active comparator, and now they can use computers to look at previous patient data and figure out how the algorithm would work and then train it that way.

MiniMed在巴塞罗那的演示中，恰恰向人们展示了这一过程。

And the really interesting thing about, MiniMed's presentation in Barcelona was they kinda walked people through that.

他们提到，对于他们的现有产品780g，全球有数十万患者在使用这一产品。

And they said, with the seven eighty g, which is their current product, you know, we have hundreds of thousands of patients on this on this product worldwide.

因此，我们可以利用这些数据进行挖掘和训练，针对不同患者群体优化算法。

So that allowed us to take that data and mine it and train the algorithm in different patient sets.

比如儿童1型糖尿病、2型糖尿病以及老年患者，他们基本上都能实现这一点。

So pediatrics type one, type two, older patients, and they're able essentially to do that.

我认为，这意味着未来，你的胰岛素泵在连接Wi-Fi系统、实时下载数据的情况下，可以在北里奇德或公司所在地拥有一个数字孪生体，根据你的生活方式实时调整算法，无论是每月还是每年一次，同时与医生共同确认调整方案。

And I think, you know, what that says to me is going forward, you can imagine that your pump, you know, when when kind of tied to a Wi Fi system and it's downloading data and things like that real time, it could have a digital twin back in Northridge or wherever the company is that's making these real time adjustments for how you're living your life and how the algorithm should be responding, whether that's once a month or once a year, in conjunction with the physician to kind of sign off on it.

但用通俗的话说，我们现在拥有了针对每位患者的实时数据，用以训练这些算法。

But that's really in lay terms is that we now have that real time patient data and it's specific to individual patients to train those algorithms.

听你这么说，我觉得很有趣，你提到FDA现在允许他们这样操作。

You know, it's fascinating as I listen, you know, you said the FDA allows them to do it this way now.

要实现这些了不起的成就，监管环境、底层计算机技术与医学科学三者协同一致至关重要。

And how important is to have everything aligned, the regulatory environment, the underlying computer technology along with the medical science in order to have these really incredible achievements.

现在，当你从这些发布内容中抽身回望，你觉得今年的ATTD向我们揭示了技术未来的发展方向是什么？

Now, when you step back from some of the announcements, how do you think that ATTD this year informs us about where technology is heading?

是的

Yeah.

我认为过去更注重外形设计。

I think it's it used to be more form factor focused.

你知道，我们怎么才能让传感器更小更薄？

You know, it's how do we get the sensors small and thin?

我们怎么才能让贴片式胰岛素泵更小巧，并使用尽可能好的粘合剂？

How do we get the patch pumps out and make them have really good adhesives small as possible?

哪个控制器看起来最像手机？

Which controller looks the best and looks like a phone?

所以我们在2007年创立Tandem时，恰逢iPhone发布之前。

So when we started Tandem in 2007, it was fortuitously at the time right before the iPhone launched.

因此，当我们进行市场调研时，通过焦点小组与患者、护士和医生交流，大家纷纷表示，希望自己的医疗设备看起来像消费电子产品。

So when we were doing our market research, all of a sudden, with the focus groups and everything with patients, nurses and doctors, people were saying, want my medical device to look like a consumer device.

你们能把它设计得像iPhone一样吗？

Can you make it look like an iPhone?

而我们恰好处于开发过程中，可以顺利地在泵上加装触摸屏。

And we happened to be in the development process where we could go ahead and put a touchscreen on the pump.

所以当时一切都围绕着外形设计，而不是数学算法，我们只是默认所有胰岛素泵的输送方式都一样。

And so back then it was all about this form factor and not so much about the math and the we just kind of assume that all pumps deliver insulin the same way.

而且当时也不需要进行关键性临床试验。

And back then there wasn't a need to do pivotal trials either.

你知道，当时他们只是做一种所谓的‘510(k)’流程，向FDA表明你的产品与前代产品功能相同。

You know, you would just kind of what they do, what they call a five ten with the FDA, which basically says that your product works the same as your predecessors.

所以一切都以外形设计为导向，非常注重消费体验。

So it was all form factor driven, very consumer driven.

对于像我这样来自制药营销领域的人来说，这与我擅长的工作完美契合。

And for somebody like me who came from pharmaceutical marketing, perfect alignment with kind of what I knew how to do.

现在，我认为外形设计已经做得非常好，而且目前还有多种贴片式泵正在研发中。

Now, I'd say that the form factors have gotten so good and there's different patch pumps that are in development now.

每个人都拥有一个类似iPhone的控制器。

Everybody's got an iPhone controller.

现在每个人都理解了人因工程的重要性，以及如何让产品对用户更简单。但现在，我认为我们又回到了数学层面。

Everybody understands the role of human factors and making things simple for the user to Now, I think we're switching back to math.

我们重新关注如何让泵背后的‘大脑’，或者同样使用算法的CGM传感器，更好地发挥其功能。

We're switching back to how do I make the, you know, the brains behind the pump, or the CGM sensor, which uses algorithms as well-to-do what they do.

我们如何提高准确性，最小化低血糖、高血糖等可能在患者日常生活中出现的异常情况。

How do we, improve accuracy, minimize things like hypoglycemia, hyperglycemia, kind of these outliers that may happen in a person's daily life.

在巴塞罗那的会议上，还专门讨论了如何应对运动、怀孕等即使在自动化系统下也会影响血糖水平的因素。

And then there was a whole section in Barcelona on how to deal with things like exercise and pregnancy and these things that affect somebody's blood sugar even when they're on an automated system.

这太有趣了。

That is fascinating.

这些非常重要，因为虽然从总体上看这些情况并不常见，但对于任何个体而言，安全运动和怀孕的能力都至关重要。

Such important things because even though in aggregate they're not common for any given individual, that's pretty important, the ability to exercise safely, pregnancy.

你是否觉得，正如你所说，我们正进入糖尿病技术的新阶段？

And is your sense that we're entering a new phase of diabetes tech as you're saying that?

是的。

I do.

我想回到我之前关于每日多次注射的评论，决定是否佩戴设备不仅意味着你需要佩戴输注部位或像Omnipod这样的贴片泵，你还得佩戴CGM。

I think that back to my previous comment about multiple daily injectors, making that decision about wanting to wear a device and you not only have to wear an infusion site or a patch pump in the case of the Omnipod, but you're gonna have to wear a CGM.

所以你实际上是在身体上使用两个不同的部位。

So you're talking about two different sites on your body.

因此，随着时间推移，长期应对糖尿病时，人们确实会担心疤痕组织等问题。

And so there's real concerns about scar tissue and things like that kind of over time as you deal with having diabetes.

所以，当初我们在Seagrove刚开始构建预测模型时，我总是提醒人们，即使你拥有最好的AID系统，仍然会有大约60%的人不愿意佩戴它。

So I, back in the, when we first started putting forecast models together at Seagrove, I always caution people to say that even if you have the best AID system, there's always going to be sixty percent of the people out there that don't want to wear it.

他们对自己的每日多次注射管理方式很有信心。

You know, that, that they're confident with how they manage diabetes with multiple daily injections.

他们觉得没必要改变，也不愿意让输注部位钩到门把手，或者整天贴着贴片之类的东西。

They feel like they don't need to change and they don't want to, you know, catch an infusion site on a doorknob or wear a patch or something like that.

我现在正在修正这个观点，我觉得大约40%的人会继续选择注射，而其余的人则会转向新技术，因为如今的治疗效果好得多，而且这些成果已经发表在权威期刊上。

I think now I'm revising that, you know, and saying, you know, about forty percent are gonna wanna stay with injections and the rest of them, because the outcomes are so much better now, and they're published in real journals out there.

现在我们甚至有了不需要计算碳水化合物摄入量的产品。

And now we've got things where you don't have to count carbs.

这是一个艰难的论点，尤其是如果我女儿明天被诊断出患有1型糖尿病，我会说，当我们已经有了如此高水平的自动化、安全检查以及我之前提到的设备形态时，很难劝她继续使用注射治疗。

It's a hard argument, especially like if my daughter got diagnosed tomorrow with type one diabetes, I'd say it would be a hard argument to tell her to stay with injections when we have this level of automation, level of safety checks that are out there and the form factors that I mentioned before.

这很有趣，埃里克。

You know, it's fascinating, Erik.

我听着你的说法，觉得这与另一个完全不同的领域中的自我驱动和创新有相似之处。

I'm listening and I'm hearing a parallel with self thriving and innovation in a completely different area, obviously.

但其中一部分是信任。

But, you know, part of it is trust.

如果你曾经坐过自动驾驶汽车，刚上车时，那真是一次让你手心冒汗的经历。

If you've ever been in a car that has self driving, when you first get in, it is one of those, you know, white knuckle experiences.

但过一段时间后，你会开始意识到，哇。

But then after a while, you begin to realize, wow.

当你开始关注这个领域的数据时，会发现它的安全性优于所有人类驾驶者的总和。

And when you start listening to the data on that area, it's the safety is better than the aggregate of of humans.

我认为，如果我理解得没错的话，我们正在这两个领域看到类似的情况：要选择接受，就需要——你用了‘信心’和‘信任’这个词。

And I think that if I'm hearing you correctly, we're seeing a parallel thing happen in those two areas where in order to opt in, it requires, and you use the word confidence and trust.

我认为这一点变得非常重要。

And I I I think that becomes very important.

人们不会因为别人告诉你某物有效就立即产生信心或信任，而是随着时间的推移，这些设备及其制造公司用实际表现赢得了你的信心和信任。

And one doesn't have confidence or trust immediately because someone tells you something works, but you get confidence and trust because over time that those devices and the companies that make them prove themselves.

没错。

That's correct.

对。

Yeah.

有趣的是，许多开发这些算法、测试并确保其安全的软件工程师，正在汽车公司和医疗设备公司之间来回流动。

And what's interesting is that a lot of the software engineers that kind of put these algorithms together and test them and make sure they're safe, They are going back and forth between the auto companies and the med device companies.

我一位朋友之前在胰岛素泵公司工作，现在去了Rivian公司。

So one of my friends that was that one of the pump companies now works for Rivian.

他正在从事自动驾驶汽车的工作，而很多人都是从早期的定速巡航等技术开始，逐步进入医疗设备领域，但你说得完全正确。

He's working on, you know, self driving vehicles And a lot of them have gone into, you know, med devices from, you know, kind of the the early days of cruise control and those kind of technologies, but you're act you're absolutely right.

这正是它的起源。

That's that's where it came from.

这太有趣了。

That is fascinating.

那我们来详细聊聊，先从CGM开始。

So let's go over some details, and let's start with CGM.

你认为下一代CGM会有哪些进步？

What do you see as the advance in the next generation of CGM?

是的。

Yeah.

我觉得，CGM其实一直走在前列，记得2013年我去巴黎参加第一次ATTD会议时，那时还只有所谓的瞬感血糖监测。

I I think, you know, CGM really led the way, you know, from that first ATTD meeting that I went to in Paris in 2013, where you had this thing called flash glucose monitoring.

后来我们逐步发展到不再需要单独的发射器，所有功能都集成在传感器上，传感器也变得更小了。

And then we evolved to not having to have the transmitter and everything being on the sensor itself and the sensors got smaller.

然后，使用时长从五天或三天延长到五天、七天、十四天，现在已达到十五天，而准确性几乎没有下降。

Then they became, you know, went from five day or three days to five days to seven days to fourteen, and now we're at fifteen day, you know, duration without really any decrease in accuracy.

说到底，问题还是在于粘合剂——你真的愿意连续佩戴十五天吗？

It kind of comes down to like the adhesive, do you really wanna wear that for fifteen days?

而且它们的粘合剂也改进了。

And they've they've gotten better on the adhesives.

所以现在，我认为它们已经解决了外形设计的问题，就像它们对胰岛素泵所做的那样。

So now we're at the point where I think they figured out the form factor stuff, just like they did with with pumps.

于是我想，我们还能在算法上做些什么，让我的传感器比你的传感器更出色？

And so I was like, what can we do again with the math that makes it my sensor better than your sensor?

从准确性角度来看，它们的表现都相当不错。

And so they've, from an accuracy standpoint, they all seem to do pretty well.

我们的误差平均相对幅度都低于9%，也就是说，91%的时间内，它与工业级监测设备的读数一致。

We're all, you know, we're below MERD of 9%, which is, you know, 91 of the time it's gonna agree with a, you know, industrial grade, you know, monitor.

当精度达到这个水平后，问题就变成了：你希望传感器是植入式的吗？

And so when we're down to that, then it comes down to, okay, do you want the sensor implanted?

你希望它佩戴在身体的不同部位吗？

Do you want it to be worn on different part of the body?

你希望它的形状有所不同吗？

Do you want it to be a different shape?

但他们现在大力追求的一个方向是：你是否希望它测量除了葡萄糖之外的其他指标，从而更好地提升整体健康状况或糖尿病管理？

But the big one they're pursuing now is do you want it to measure something other than glucose that would kind of enhance either your health in general or your management of diabetes?

因此，在最近几届会议上，雅培公司发布的重要公告或演讲都强调了持续监测酮体的重要性。

And so the big announcement or the big presentation I saw at the conference from Abbott, which they've done in the last kind of couple of conferences was talk about the importance of continuous ketone measurements.

我认为，过去人们普遍没有意识到持续监测酮体的必要性。

And so I don't think that there was a general appreciation of the need for continuous ketone measurements.

他们做了所有研究，只是为了证明人们实际上根本不会去监测酮体，至少在大多数情况下是这样。

They did all their research just to show that people really aren't monitoring ketones like in general at all, you know, for the most part.

那么，持续监测酮体能带来什么好处呢？

And what would be the benefit to having that being done continuously?

我的理解是，我本人并不是这方面的临床专家。

And my understanding and not being a clinician on this.

但我的理解是，持续监测酮体比单靠葡萄糖测量能更早地发现糖尿病酮症酸中毒的迹象。

So, but my understanding is that it kind of catches the path to a DKA quicker than if you're just to rely glucose measurements to do that.

因此，它能更早地预警糖尿病酮症酸中毒，让你及时得到提醒，采取相应措施。

So, it's an earlier read for DKA and that can give you kind of a warning to say, hey, you might want to do something about that.

然后你可以开始思考，如果我们同时测量酮体和葡萄糖，这如何帮助人工胰腺自动化系统？

And then you can start to think about, well, if we're getting ketones measured and glucose measured, how could that help an AID automation system?

我们目前还没有达到那个阶段，但你会发现，许多胰岛素泵公司的新闻稿都提到，他们正与雅培合作，将这种连续葡萄糖和酮体测量系统应用于未来版本的人工胰腺系统。

And we're not really there at that point, but you'll notice a lot of the press releases for the pump companies, they are partnering with Abbott on this continuous glucose ketone measurement system for future versions of their AID systems.

所以我敢打赌，在未来的会议上，你会开始看到一些研究结果表明，如果使用双指标检测，血糖达标时间会更长。

So I bet you in future conferences that you're going to start to see outcome studies showing, hey, better time in range if you have the dual analyte.

此外，还有许多其他可以测量的指标，比如血压、心率等，这些更接近住院环境中的监测项目，可能有助于检测败血症等状况。

And then on top of that, there's a whole bunch of other things that they can measure, whether it's blood pressure, heart rate, and things that are more akin to the inpatient setting, you know, that might detect sepsis and things like this.

因此，我们真正的发展方向是让这个小型传感器能够测量比葡萄糖多得多的指标。

So that's really where we're going is getting that little sensor to measure things a lot more than just glucose.

这太惊人了。

That is amazing.

我们稍后会讨论一些可穿戴设备的监测功能。

We'll talk about some measurements wearables in a little while.

我要提到，我们最近有一期播客采访了埃默里大学的医学教授吉列尔莫·翁佩雷斯，话题是关于双指标酮体-葡萄糖监测仪。

I will say we had a recent podcast where we talked with Guillermo Umperez, who is a professor of medicine down at Emory, about the dual ketone glucose monitor.

这非常令人兴奋，因为有一些人反复因糖尿病酮症酸中毒住院，如果能提前检测到这种情况，避免需要住院治疗，可能会挽救生命。

And it is very exciting because there are people who just have repeated admissions for DKA, and the ability to detect that early before it requires a hospital admission can be lifesaving.

我们来谈谈闭环自动胰岛素输注系统。

Let's move on to closed loop automated insulin delivery systems.

你认为这方面有什么进展？

What do you see going on there?

是的。

Yeah.

正如我们之前提到的，下一步——我们距离实现大约只有一年了，那就是自动餐前胰岛素推注功能。

As we mentioned before, the next step, we're only about twelve months away, is to have this automated meal bolus.

目前，有几种系统采用了不同的方式。

Today, there's a couple of systems that do it differently.

比如Tandem Control IQ，你在进食前手动输入碳水化合物含量，这是一种比较传统的方式，即告诉泵：我要吃饭了，这是碳水化合物的量。

You know, the Tandem Control IQ, you enter in carbs when you're about to eat and it's kind of more the traditional way of telling the pump that I'm about to eat, here are the carbs.

而在边缘领域，还有一些应用程序可以让用户拍摄所吃食物的照片，对于不熟悉碳水化合物计算的人来说，这能帮助他们获得更准确的估算，因为我相信你一定看过不少研究，显示即使人们真的去计算碳水化合物，也只有大约20%到30%的时间能准确计算出来。

And then kind of along the edge, there are, different apps that people can use to take a picture of what they're eating and if they're not familiar with carb counting and to get a better estimate, because I'm sure you've seen plenty of studies that it's only like 20 or 30% of the time do people actually accurately, you know, count carbs when they do count carbs.

所以我觉得这类功能很有帮助。

So I think that kind of stuff is helpful.

然后是Beta Bionics的islet系统，你只需要说‘我要吃午餐、晚餐或早餐’，它就会根据你过去一周的平均摄入量，自动给出稍小、稍大或相同的餐时胰岛素量。

Then you have, Beta Bionics, the islet where you essentially just say, I'm eating lunch, dinner, or breakfast, and it's, you know, smaller or larger or the same of what I've currently been doing over the past week.

所以这是一种避免计算碳水化合物的方法。

So that's one way to avoid counting carbs.

而美敦力的做法是采用一种称为‘餐食检测技术’的功能，它通过分析CGM数据中血糖上升的速度，判断你可能正在进食，从而主动启动餐时胰岛素输送，而无需等待你手动输入进食信息。

And then with what Medtronic is doing, they have this thing called meal detection technology, which is essentially just tuning the algorithm to look at the CGM data and how quickly it's spiking to say, hey, you're probably eating a meal and we're gonna interview you right now and not wait for you to go ahead and tell us that you're eating.

在这些数据中，你知道，在欧洲，其标签使用方式与美国略有不同。

And in that data, you know, in Europe, I think it's a little bit different than it is in The US in terms of how the label works.

但在欧洲，他们明确表示：如果你希望按照设备的预期方式使用胰岛素泵——即计算碳水化合物并手动输入——你的血糖目标范围达标率将达到80%或更高，这已经非常接近非糖尿病人群的水平。

But in Europe, they essentially say, hey, if you wanna use the pump the way it's intended, which is to count carbs and enter it into the pump, your time and range is going to be 80% or better, which is pretty close to somebody without diabetes.

如果你不想这样做，不想手动输入碳水化合物，而让泵自行运行，你的血糖目标范围达标率仍能达到71%，这依然很不错。

If you don't want to do that, if you don't want to enter carbs and just have the pump run by itself, your timing range is gonna be 71%, which is still pretty good.

因此，这实际上是用户与医生在沟通后，共同决定选择哪种方式。

And so I that they're the choices really with the user maybe in conversation with their physician about what they wanna do.

但相比过去，情况已经好太多了，那时候用胰岛素笔治疗，时间在范围内可能只有45%，孩子的情况可能更差。

But it's a lot better than in the past where, you know, you're starting out with time and range of like 45% on MDI, probably worse with kids.

然后，使用胰岛素泵后，我们把时间在范围内提升到了六十几百分比。

And then, you know, with a pump, we got it up into the sixties.

现在，即使完全不干预，我们也能达到七十几百分比。

Now we're getting into the seventies without any interaction at all.

所以我认为未来两年的重点将是这些算法自我优化，以进一步完善时间在范围内的表现。

So I'd say the next two years is all about, you know, these algorithms fine tuning themselves to kind of perfect that time and range.

接下来，在巴塞罗那听到的另一个讨论是关于新的指标，比如精准时间在范围内，以及多大比例的时间能避免DKA和低血糖，目前这些方面他们做得都还不错。

Now, next discussion after that, that I heard in Barcelona was these new metrics like tight time and range and what percent of the time are you eliminating things like DKA and hypoglycemia, which they all do pretty well right now.

但如果要有临床数据证明，真正带来微血管和大血管并发症益处的，不仅仅是保持在70到180之间（这是时间在范围内的定义），而是要持续保持在80到100之间。

But if there's outcomes data and clinical data showing that it's not just staying between seventy and one hundred eighty, which is defining time and range, it's really about staying between eighty and one hundred that gives you those micro and macrovascular complication benefits.

听到这些真是令人惊叹。

This is just amazing to hear.

你作为临床医生，已经多次提到，现在有太多事情在发生了。

Now, you've mentioned a couple of times, as the clinician will, Now, there's a lot going on.

作为临床医生，我们该如何跟上这些变化？

Any thoughts about how we as clinicians can keep up with these changes?

如何为合适的患者匹配合适的技术？

And how does one begin to match the right technology for the right patient?

是的，我认为这在初级保健环境中尤其具有挑战性。

Yeah, that's really, I think, especially in the primary care setting is the big challenge.

你知道，我在这里加州有一位很棒的全科医生，但他必须应对各种不同的疾病和类型的患者。

You know, I have a great primary care doc here in California and, but he has to see so many different disease states, so many different types of patients.

他在糖尿病药物治疗方面非常专业，但在设备方面，他会问我一些关于当前进展的问题。

He's really up to speed on the drug part of things within diabetes, but on the device stuff, he asked me questions, you know, about kind of what's going on.

我知道他们每月都会举行会议，让医生们互相交流学习。

And I know that they have, you know, monthly meetings where they kind of get to listen to their peers and things like that.

但随着CGM公司和胰岛素泵公司希望拓展到2型糖尿病领域——而大多数患者都是由全科医生接诊的——设备公司必须让远程指导变得简单易行，比如通过在线教育课程、播客等形式，持续提供技术更新，因为这些初级保健医生几乎不可能飞去巴塞罗那听这些报告，甚至今年去新奥尔良参加ADA会议我也知道他们很难抽身。

But as the CGM companies and the pump companies want to expand into type two, where most of the patients are being seen by primary care physicians, it's really going to be up to the device companies to make it easy for somebody to dial in remotely when they have time to get education sessions, podcasts like this to provide kind of updates on what's going on from a technology standpoint, because very few of these physicians on the primary care side are gonna fly to Barcelona to to listen to these presentations or even to ADA and, you know, in New Orleans this year where I where I go.

所以这必须是线上的，而且必须简单易懂。

And so it's gotta be it's gotta be online and it's gotta be easy to to kinda listen to for sure.

确实如此。

It really is.

我想我们很多人都想飞去巴塞罗那，参加多尔伦特会议。

I I I think a lot of us would like to fly to Barcelona and go to Dorlent.

我只是不确定。

I'm just not sure.

你说得对。

You're right.

这正在发生。

It's happening.

说到2型糖尿病，你认为技术将如何扩展到这个领域？

So speaking of type two diabetes, how do you see technology expanding to that area?

没错。

Right.

我认为，随着GLP-1药物和每周一次的GLP-1药物的出现，它们不仅在减重方面效果显著，而且当你看到HbA1c降低时，比如使用门冬胰岛素的患者佩戴CGM，血糖曲线会变得非常平稳。

I see, you know, with the advent of the GLP-1s and the once weekly GLP-1s that have been fantastic in terms of not only weight loss, but when you look at, a one c reduction, you'll you'll have people on a CGM that are on Montero, for instance, and it's it's a flat line.

看起来血糖并没有太多波动。

It's like there's not a lot of spikes going on.

所以问题来了，好吧。

And so the question's like, okay.

如果真是这样，那我作为二型糖尿病患者，如果血糖没有这种大幅波动，还需要佩戴持续葡萄糖监测仪吗？

Well, if that's the case, then do I need to wear a CGM as a type two if I'm not having that those kind of swings in my blood sugar?

如果需要，那么我该如何利用这些信息采取实际行动？

And if I do, kind of what's the actionable, item that I need to do with that information?

所以我认为，下一阶段是持续葡萄糖监测设备公司和制药公司需要共同探讨：是否可以形成某种自然的组合方案或报告，无论是通过人工智能、健康指导，还是每季度与医生的会诊，来结合药物与技术，比如将持续葡萄糖监测仪的数据与治疗结合使用，因为随着即将推出的三重激动剂，持续葡萄糖监测仪会变得越来越强大和精准。

So I see that's really the next phase is for this, like the CGM companies and the pharma companies to figure out if, is there a natural kind of combination argument or report or something that whether it's with AI or coaching or just the quarterly visit with the physician to use the combination of med tech like CGM with the CGM data, because the CGMs are just going to get more powerful and even better as we go to triple agonist coming up.

因此，会有一部分人只想每周打一针，不想再额外处理这些设备。

And so, you'll have one camp of people that just want to take a weekly injection and not have to deal with the additional device part of it.

但当人们在使用药物后体重下降进入平台期，体重又开始回升，尤其是当他们停药后，我认为持续葡萄糖监测仪其实有一个绝佳的机会——不是在患者已经出现反弹时才去推动行为改变，而是在他们刚开始注射时就介入，帮助他们在早期就建立健康习惯，避免在使用GLP-1药物的两年里因不良选择而让病情恶化。

But as people plateau on the CGMs and the weight loss is starting to creep up again, and especially if they drop off the drug, then I see like there's a real opportunity for devices like CGMs to not at the end of that when somebody is already starting to regress to make behavioral change, but to see those behavioral changes at the very beginning of when they go on the injection so that they don't kind of, you know, they don't go two years on a GLP-one by making bad choices and, you know, not changing their behavior.

这正是我所看到的设备与制药结合的巨大优势。

That's really, I see, you know, the benefit of the combination of devices and pharma.

这很有趣。

That's interesting.

而且这正是我经常跟我的病人讨论的问题：你可能正在使用GLP-1受体激动剂。

And it's something that, you know, I've discussed all the time with my patients that you can be on a GLP-one.

它能帮助你减重。

It will help you achieve weight loss.

但如果你想获得最佳健康状态，正如埃里克所说，关键还在于做出正确的选择。

But if you wanna have optimal health, it's exactly Erik, as you said, it's about also making the right choices.

没有什么比CGM能更快地给你反馈，告诉你什么才是真正重要的。

And boy, there's nothing like CGM to give one feedback quickly on what matters.

我目前有一个病人的情况简直令人惊叹。

I actually have a patient that I'm seeing now that has just been amazing.

这位患者多年来一直饱受困扰，开始使用CGM后，她的糖化血红蛋白从8.7%降到了7.2%，期间没有任何药物调整。

That person has struggled for years, started using a CGM, and dropped her A1c from about eight seven to 7.2 without any changes in medicines.

我们之前当然也讨论过饮食选择，但当你能几乎立即获得反馈时，这种即时反馈会形成一个闭环。

And it's not that we haven't talked about food choices before, but when you get that feedback so quickly, almost immediately, when you make those choices, it creates a feedback loop.

很高兴听到你也认为GLP-1的重要性得到了认可。

I'm happy to hear you saying that that's acknowledged as important on GLP-1s as well.

你觉得除了你刚才提到的，技术在肥胖治疗中还有其他作用吗？

Do you see technology having any place other than what you've already said with regard to obesity care?

是的，我认为关于GLP-1的讨论现在正逐渐扩展到减重和糖化血红蛋白降低之外，开始涉及心血管方面。

Yeah, I think that part of the argument for GLP-1s is now starting to expand outside of weight loss and A1C reduction, and it's on the cardiovascular side.

我家里有一半的亲属，我妈妈的十个兄弟姐妹都早早死于心血管疾病。

And I've got a family, one half of my family side where my mom's 10 brothers and sisters all died fairly early of cardiovascular disease.

所以，谈到心血管疾病的家族风险，对吧？

So talk about family risk of CVD, right?

因此，问题是，我们在Mounjaro和Ozempic的临床试验中确实看到了全因死亡率、主要不良心血管事件、中风和心肌梗死风险的降低，但哪些行为改变能与此配合，以最大化这种效果呢？

And so the question then is, yes, we see in the clinical trials of Mounjaro and Ozempic, these risk reductions in all cause mortality in MACE, in stroke and myocardial infarction, but what kind of behavioral changes can go with that to maximize that?

因为我们知道，在临床试验环境中，往往无法完全反映真实生活的情况。

Because we know that in a clinical trial setting, like it's not gonna mirror real life, you know, in many cases.

那么在真实生活中，面对现实的压力，比如你住在加州，而我在费城，堵车等等，我们到底该比较哪些因素呢？

So in real life, with real life stresses and living in California and you're in Philadelphia and you're in traffic and all that kind of stuff, what are the things really that we compare?

是否需要额外的药物或行为干预，以充分发挥GLP-1类药物的全部效益。

Whether there are additional drugs to go with it or behavioral interventions to really get the full benefit of the GLP-1s.

非常有趣。

Very interesting.

现在我们转向数据分析。

Let's shift now to data analytics.

我知道这一直是你长期关注的领域。

And I know that's been an area of yours for a long time.

我们一直在收集越来越多的数据，无论是血糖、家庭血压，还是现在通过可穿戴设备监测的心率，这些数据都可能带来挑战。

We collect more and more data all the time, whether it is blood sugars, home blood pressures, heart rate now with wearable heart rate monitors, and it can become a challenge.

我们如何利用数据分析来改善医疗，而不是让海量数据仅仅压在我们头上？

How do we use analytics to improve care rather than just have lots and lots of data hovering over us?

是的，回到心脏病学的例子，我每年只去看一次心脏病专家来检查情况。

Yeah, I think going back to the cardiology example, and I see a cardiologist once a year just to look at things.

这个领域在为心脏病专家以及全科医生提供支持方面做得非常好，我认为克利夫兰诊所是这方面的倡导者。

That industry has done a really good job of providing not only cardiologists, but primary care physicians with a, I think it's the Cleveland Clinic is the one that kind of champions this.

这是一份基于患者各项血液检测和其他检查结果的综合建议摘要，仅一页纸。

It's a one page snapshot of all the recommendations based on the blood tests and everything that are being done on that patient.

而且非常清晰，我能轻松理解。

And it's very clear, it's something that I can understand.

所以我认为，在糖尿病领域，目前你有来自Clarity的数据、胰岛素泵数据、血糖信息、血液检测结果等各种数据。

And so I think that's something that within diabetes right now, you have your data from the com Clarity, for instance, you have the pump data, you have blood glucose information, you have blood tests that you're doing, all this kind of stuff.

如果你运气好的话，可能会有一个Epic系统之类的工具把这些信息集中到一个地方。

If you're lucky, you've got an epic system or something that's kind of putting that all in one spot.

但从分析的角度来看，我认为还没有人真正成功地像克利夫兰诊所那样在心脏病领域那样，做出一份这样的一页纸摘要。

But from a, like an analytic standpoint, I don't know that anybody's really crushed it in terms of creating that one pager the way Cleveland Clinic did on the cardiology side.

所以，这正是我所期待的。

So that's really what I'd like to see.

我知道有人正在学术界或制造商端努力开发这类一页纸报告。

And I think that I know people are working on that at and, you know, either in the the academic setting or in the the manufacturer setting to to come up with these, you know, kind of one page reports.

但你说得对。

But you're right.

数据只会变得越来越密集。

The the data is just going to get more and more intense.

然后，另一个问题是，患者愿意分享多少这些数据呢？

And and then the the, you know, the question too is, you know, how much of that data does the patient wanna share?

很多时候，他们希望隐瞒自己曾休假两周，没有像应该做的那样管理健康状况。

A lot of times, they they wanna hide the fact that they were on vacation for for two weeks and not, you know, managing things the way they should be.

这确实是个很好的观点，我们会失去在我们希望留下好印象的人面前展现自我的机会。

Well, that's that that that's a really good point that we will lose the opportunity to make ourself look wonderful in front of the people we want to look wonderful in front of.

托德，我们来谈谈可穿戴设备。

Todd let's touch on wearables.

你认为这方面有什么进展？

What do you see going on there?

有各种各样的设备，比如苹果手表或戒指，仅举几个流行的例子。

There's all sorts of things, Apple Watch or Ring, just to name a couple of popular devices.

你认为可穿戴设备将如何发挥作用？

Where do you see wearables fitting in?

我认为，目前只有少数人真正需要这些设备，他们想通过阶段性的数据来改善生活，但过一段时间后就会停止佩戴。

I think, for me, it's a it's a, right now, a niche group of people that really want either episodic data to make an improvement to their life and then they'll stop, you know, kind of wearing the thing, after a while.

或者是一些健康状况不佳的人，他们需要持续监测卡路里消耗或血糖水平的数据。

Or it's people that are just really under their health that want that continuous data of how they're doing from either a calorie burn or blood glucose levels.

在这里圣地亚哥，有很多非糖尿病患者佩戴传感器，监测血糖，尽管他们可能并不知道该如何利用这些数据，但这些信息对他们来说仍是一种补充。

And here in San Diego, there's plenty of those people who are non diabetic that are wearing sensors and they're looking at blood sugar and probably not knowing what to do with it, but it's kind of like additional information for them.

所以目前来看，我认为是这一小群人——这些特例——在持续使用这些设备。

And so right now, I think it's that group of people, they're kind of outliers kind of over here that are using these things on a continuous basis.

我认为，要让大众广泛使用可穿戴设备，它们必须做出不同的改变。

I think to get the broad populace to use wearables, they have to do different things.

我研究过很多声称能无创测量血糖的智能手表。

And I think having like, I've looked at a whole bunch of different watches that are supposed to measure blood glucose in a non invasive standpoint.

它们还能监测血压，做各种其他功能，去参加展会时你会觉得，哇，这太棒了，还能试戴，看起来也很漂亮，但之所以看起来好看，是因为我没有糖尿病。

And they also do blood pressure and they do all these kinds of things and you go to the conference and you're like, wow, that's And they let you wear it and it looks good, but it looks good on my arm because I don't have diabetes.

而当这些设备用在1型或2型糖尿病患者身上时，它们就完全失灵了，数据根本不准。

And so these, you have these normal kind of flat lines where they don't work at all is when you put that on somebody with type one or type two diabetes, they're not accurate.

我认为这属于空谈，但一旦我们在这方面取得改进，他们终将找到更好的算法，找到使用红外线、激光等技术的更优传感器。

And, I think it's vaporware, but once we improve on that and they will, they'll find the, you know, a better algorithm, they'll find better sensors that use infrared and lasers and things like this.

如果他们能同时实现多种功能，并搭配一个提供可操作信息的应用程序，比如明确告诉你：‘如果你每天不走四千步或 whatever 的步数，这周你就会胖一磅。’

If they do multiple things and then have the app next to it that that has actionable information that's as specific as, hey, if you don't go and walk, you know, four hundreds or, you know, 4,000 steps or whatever it is, you know, per day, you are going to gain a pound this week, you know.

哇，真的吗。

Oh, wow.

一种如此直接的反馈。

Something that direct.

是的。

Yeah.

因为否则的话，我认为如果不将它与明确的行动指导相结合，它就只是更多无用的信息。

Because otherwise, I think if you don't pair it with a directionable, you know, action that the patient's taking, it's just more information.

人们会因此感到压力。

They get stressed out by it.

你可能在疫情期间听说过，当人们只是把手机放下时，感觉好多了。

And you probably heard during like the pandemic and stuff that when people just, you know, were able to put their phones away, how much better they felt.

还有类似这样的东西。

And, you know, things like that.

我觉得我也是这样，我有个AuraRing，还有一块Apple Watch，但很多时候我就把它摘下来了。

And I think the same is with me where I have an AuraRing and I have, you know, an Apple Watch and a lot of times I just take it off.

就是太多了。

I just it's just too much.

是的。

Yeah.

我也担心这个设备太多了。

I worry about that too much piece.

顺便说一下，我很喜欢你提出的将信息与可操作的结论相结合的想法，这些结论能促使行为改变。

And and I love your idea, by the way, about pairing information with actionable conclusions that that that lead to a change in behavior.

因为如果没有这一点，正如你所说，很容易引发焦虑。

Because without that, you there's so much room for, as you said, anxiety.

实际上，我有个朋友因为手表告诉她心率过快，就停止锻炼了。

Actually, a friend of mine stopped exercising because her watch told her heart rate was too fast.

这是一个二十多岁、身体健康、没有任何理由担心的年轻人。

This is a young healthy person who has no reason to worry in her twenties.

你知道，她运动时心率上升了。

You know, her heart rate went up when she exercised.

在大多数情况下，这是好事。

That is, for the most part, a good thing.

所以，一种方式是通过某种叠加层来判断——无论是由人工智能来完成，还是由能够结合个人健康背景解读信息的人工智能来实现。

And and so a way to have that kind of overlay of whether it'll be AI that does it, artificial intelligence that's able to interpret the information in the context of that person's health.

你觉得这种事将来会实现吗？

Do you see that sort of thing happening at some point?

是的。

Yeah.

我非常支持在正确使用的情况下，让人工智能填补我所看到的未被满足的需求。

I I I'm a big kind of proponent of of AI when it's used correctly to to fill in the gaps of where I see the unmet need.

所以，如果你看一下过去五年里针对糖尿病或心血管事件的辅导项目，大多数都是由蓝十字或其他类似机构的项目资助的。

So if you looked at coaching programs for diabetes or for cardiovascular events or something in the last five years, most of them were being funded by a program at Blue Cross of whatever.

这一直是保险公司推动的，搭配一名保险公司的病例管理员或护士管理员，但使用的应用程序非常糟糕，根本不知道怎么登录，沟通机制也很差，而且你不确定他们能不能发短信给你，通常只能打电话。

And it's been an insurance driven thing paired with a case manager, a nurse manager who works for the insurance company with a really bad app that you can't figure out how to log into, really bad communication structures and, you know, whether or not they could text you or not, or usually it's gonna be a phone call.

你真的会接那个电话吗？

And are you actually going to answer that phone?

不会。

No.

所以这仅仅是执行得很差。

So it's just been bad implementation.

因此，对我来说，必须是一个用户感兴趣的可穿戴设备，结合人工智能，而这个人工智能是由像你这样的临床医生开发的，他们真正懂得该怎么做，同时又能将临床信息提供给开发算法的人。

So for me, it's got to be a wearable that the person's interested in tied with AI, where that AI is being developed by clinicians like yourself that actually know what they're doing, but, you know, can can feed that clinical information into somebody who's developing the algorithm.

这太有道理了。

That makes so much sense.

嗯，我们的时间差不多到了。

Well, we're we're almost out of time.

真希望我们能再聊一个小时。

I wish we had another hour to talk.

事情太多了。

There's so much going on.

如果你要给我们的听众一些来自ATTD和当前创新周期的实用建议，你会怎么看？

What do you see if you were to give our listeners some practical takeaways from ATTD and this current cycle of innovation?

最后一个问题给你。

Final question to you.

那些实用建议会是什么？

What would that what what would those takeaways be?

我觉得这些会议的特点是，对于药物和设备的热情会有所起伏。

I I think the what happens with these conferences is there's an ebb and flow in terms of the excitement around a drug and the excitement around the device.

这次会议明显是以设备为主，药物方面没什么动静，因为我觉得人们通常会把药物方面的内容留到12月的ADA会议。

And so this definitely was a device focused conference and not a lot going on the drug side, just because I think a lot of times people save that for ADA later in December.

对我来说，最大的收获是我们今天为客户发布了关于巴塞罗那会议的摘要报告，我们的最佳展示是MiniMed关于其自动化免疫检测技术的演示，以及背后的数据。

So the biggest takeaway for me was, we're publishing today for our clients a conference primer on what happened in Barcelona And our best in show was the MiniMed presentation for their automated immune detection technology in the data that was behind it.

而且他们相当坦诚地分享了算法的实现方式。

And the fact that they kind of shared how they did the algorithm, I think it was like very forthcoming.

对我来说，这种清晰度非常重要，很多人会欣赏，尤其是因为这是一场临床会议。

So to me, I think that that kind of that kind of clarity, I think a lot of people appreciate, especially since this is a clinical conference.

当涉及到他们的临床实践时，能够清楚地了解他们所开的药物，会让事情变得容易得多。

And it just makes things a lot easier when it when it comes into their practice to understand what it is they're prescribing.

这是一个令人兴奋的领域，充满了诸多变化、创新和进步。

It is just such an exciting area filled with so many changes, innovations, and advances.

埃里克·韦尔霍夫，非常感谢你加入我们。

Erik Veerhoef, thank you so much for joining us.

尼尔，这场讨论我真的很享受。

Really enjoyed the the discussion, Neil.

最重要的是，一如既往，感谢我们的听众。

And most of all, as always, thanks to our listeners.

感谢您收听本次《糖尿病核心更新》特别节目，探讨糖尿病护理中的新兴技术。

Thank you for joining us on this special edition of Diabetes Core Update, discussing emerging technology and diabetes care.

有很多事情正在发生。

There is a lot going on.

我想我们已经学到了一些内容，也了解了这些细节。

It's I think what we've learned, and we've learned some of those details.

本期《Diabetes Corps Update》特别节目由Seagrove Partners赞助。

This special edition of Diabetes Corps Update is sponsored by Seagrove Partners.

感谢您的收听。

We thank you for listening.

代表美国糖尿病协会，我是尼尔·斯科尼克医生。

For the American Diabetes Association, I'm doctor Neil Skolnik.

下次再见，保持安全，持续学习。

Till next time, stay safe and keep learning.