Benefits and Risks of Insulin Pumps and Closed-Loop Delivery Systems
A case study in reverse causality and moral hazards
If you’re a T1D, I’m sure you’ve heard about—or even use—either a fully automated closed-loop insulin pump, or a semi-automated (hybrid) pump, where algorithms read glucose levels from a CGM and administer insulin depending on glucose levels. When your levels rise too high, more insulin is administered; when levels are too low, insulin infusion stops.
The premise behind Automated Insulin Delivery (AID) systems is great—who wouldn’t want to relieve the burden of the daily management of T1D if an automated system can take care of it for you? This feels like a big win for T1Ds, right?
Yeah, perhaps. But in the parlance of today’s teenagers, the chatter surrounding AID systems is a bit glazed.
Or, in my parlance, “it’s not that simple.”
To start, AID technologies are in very early in development. The FDA has approved of only a couple systems, one of which being The MiniMed™ 770G, a hybrid closed loop system, discussed in detail later in this article. It, along with the DIY (home-brew) software programs that run older pumps. Many users are claiming great success, some claiming they don’t need to do anything at all—let the system run automatically and they’re magically achieving time-in-range percentages up to 70%.
Most early adopters of any new technology are usually the most successful users, and it’s their effort, work and advocacy that brings more attention to the domain. The next stage is the “valley of death,” which describes the phase of products that reach beyond the early adopters into the general consumer space. The name (“valley of death”) is termed as such because this is when most technologies face a more diverse and less technically adept world of users, many of whom present conditions that the technology is less able to achieve. The graveyard of Silicon Valley startups are full of companies whose technologies initially looked great, but failed to overcome challenges that would enable them to succeed in the long term. The article, “The 84 biggest flops, fails, and dead dreams of the decade in tech,” takes you down memory lane of things you probably have long forgotten now, but at the time, these were as promising as automated insulin pumps are today.
Of course, not all tech fails, and there’s certainly reason to believe that insulin pumps are here for the long term. But “failure” is pretty absolute. What is not yet known is how well AID systems actually work in a wider world, and perhaps more importantly, which users actually benefit the most, which users don’t benefit any differently, and which users may actually do worse.
Researchers who watch these trends are conducting more tightly-controlled (randomized) clinical trials that include a broader spectrum of people that aren’t the strong advocates that tend to be early adopters.
As the data from those trials are becoming available, the pros and cons of AID systems are becoming evident, shaving some of the glaze from the narrative. What these researchers are looking for are two key end-points: Glycemic targets (“healthy” vs. “neutral” vs. “harmful”), and user profiles (good vs. bad candidates).
Before anyone should consider an AID system, they should understand where they lie along those considerations.
Glycemic Targets
The first consideration—and arguably the most important one—is whether an AID system can help you achieve glucose targets.
Again, the headlines and anecdotal data show some users are able to achieve A1c levels of 7%, but it that really your target? Hold onto that thought for a moment.
Let’s instead understand what a healthy outcome is, versus a specific target. Yes, the American Diabetes Association’s recommendation is to aim for an A1c level <7% and a time-in-range target of >70%, but the ADA did not intend to imply that those levels are “healthy” ranges—rather, they are what medical care teams discerned to be achievable targets. Big difference.
For the past few decades, medical literature finds that only 20-30% of T1Ds achieve A1c levels of 7% (with socioeconomic factors being determining factors of success). Care teams like to use A1c of 7% and 70% time-in-range because patients can see those levels as something they could achieve without totally giving up, and without experiencing severe hypoglycemia, which can be as harmful as hyperglycemia, but in different ways, and in different time scales.
Physiologically speaking, however, A1c levels of 7% are still quite unhealthy—long-term complications happen at those levels, too, just more slowly than, say, 8% and higher. As years and decades go by, the risk of cardiovascular disease from elevated glucose levels rises precipitously, including for A1c levels of 7%.
The correlation between health outcomes and A1c levels is discussed in the paper, “The association of chronic complications with time in tight range and time in range in people with type 1 diabetes: a retrospective cross-sectional real-world study.” Here, the authors found that the more time spent in “tight” range (70-140 mg/dL), the rate of long-term complications dropped significantly. The following graphic from that paper shows that a 10% increase for time in tight range resulted in a decrease of 23.8% of cardiovascular disease, and 34.9% of strokes.
The UK Prospective Diabetes Study found A1c levels between 6% and 8% were linearly paired to all cause mortality. The longer one’s glucose levels were higher, the worse the risk became.
Having an A1c of 7% for forty years is going to impose a great deal of irreversible harm on your cardiovascular system. You can’t decide later in life to get glucose under control and undo past cardiovascular damage.
If you really want to be healthy, a lifetime of A1c of 6% had the lowest risk profile for all-cause mortality, provided that you also minimize hypoglycemia (time-below-range (70 mg/dL) should be <3%).
And therein lies the challenge for T1Ds.
This is what brings us to the slipperiness of “health” and glycemic control using automated closed-loop insulin pumps: These systems are inherently capped in how well they can keep glucose levels in control, because they can only react to glucose movements after they have moved higher or lower. Again, that’s nice when it keeps you from wandering off the farm, but studies show that the best these systems can do is an A1c of 7%, unless the user intervenes more to tighten up control. When they do that, then the system is no longer automated.
While 7% may well look good to most T1Ds, those are statistical rarities within the closed-loop community.
Most closed-loop users are achieving A1c levels of >8%. To do better, these systems would have to anticipate future events, such as administering insulin before eating, but that’s not possible without user intervention. Therefore, there is going to be an upper limit as to how well automated systems can possibly work.
This then leads to the trade-off: You can do better on your own if you manually bolus for meals and take other preemptive actions before glucose levels move, but it comes at a cost of convenience. Having to pay attention to do these things is, to some, “hard.”
So, there’s your choice: Convenience vs. less-healthy glucose levels. Pick One.
Fine, but not everyone is going to be very good at self-management, in which case, an AID system may well be better, which leads to the question: Who among us would benefit most from closed-loop systems, and who are not good candidates?
Ideal candidates for AID systems
Perhaps you’re one of those who would say of yourself, or perhaps your child, “I do great with these automated systems!”
Hey, I believe you. I’ve even met many of you. But anecdotal data is not a scientific study, and what the literature tells us that those who do the best with these systems are not necessarily the general T1D population. I don’t mean to be using Orwellian double-speak, so I’ll quote what researchers call it: healthy user bias.
Those who do well with automated systems continue to use them. Those who do not do well, give them up (especially because they’re quite expensive). This imbalance of users contributes to the illusion that those who use closed-loop systems all achieve ADA recommendations. That’s not only an erroneous conclusion, but it’s also correlation, not causality.
What the medical literature tells us is that the best candidates for automated systems are those who are either unable or unwilling to manage their disease on their own—that is, individuals with A1c levels >8%. These include young children and teens (up to the mid-20s), the elderly, those in denial of their disease, those who become overwhelmed with the daily management, and those with certain mental health concerns. This may well be a broad swath of T1Ds, for sure.
And that leads us to the contrarian question: Who should not attempt to use such systems? That’s the question that few people really ask, but to put it bluntly, people who should NOT use automated systems are those who wish to achieve “healthy” A1c levels, and who are willing and capable of engaging more closely with their disease. In fact, using automated systems may impair one’s ability to achieve healthier outcomes, not due to technical reasons, but psychological ones.
This is what’s called a moral hazard: The more you rely on the automation, the less incentive—or even opportunity—you have to learn on your own, which is what would eventually be required to achieve “healthy” glycemic control.
Again, we can see this phenomenon playing out in the real world: According to this T1D Exchange report, the authors state that, although the use of pumps increased from 57% in 2010–2012 to 63% in 2016–2018, “the average A1C overall has risen from 7.8% to 8.4%.” The authors conclude that A1c levels are directly correlated to user engagement. For those who relied on the pump to manage their disease for them, they fell further behind than those who bothered to learn on their own.
(Parents: Do you have a transition plan for your kids to one day learn about T1D? I know—tough question. Oops… Too soon?)
If not pumps, then what—insulin pens? Well, yes, as that’s the only other option (besides the very old disposable syringe). But, it’s not that simple either. Pen users are subject to the same errors and challenges of engagement and self-discipline, but at pen users are not under the illusion that the device will do their work for them, or that it will relieve them of work. Pen users know that they have to be the ones in control of their T1D management. Over the course of time, these users learn better than pump users do.
An article published in the June, 2024, issue of Diabetes Care magazine titled, “Association Between Treatment Adherence and Continuous Glucose Monitoring Outcomes in People With Diabetes Using Smart Insulin Pens in a Real-World Setting,” the authors analyzed data from 3,945 T1Ds that use smart insulin pens (NovoPen 6 or NovoPen Echo Plus) and CGMs. They found that those who pay close attention to their daily management (as measured by reliably administering meal-time bolus injections) were able to achieve better A1c levels that are comparable to—or better than—AID systems. The key, of course, is that this group remembered to do meal-time boluses.
Attributes of a healthy T1D
When considering whether you should use an AID system, researchers say that, regardless of their method of administering insulin, these are the attributes of healthy T1Ds: They are more informed about T1D management, they’re more engaged with daily administration, they have more support systems (family and medical resources), and—most importantly—they are more willing invest a great deal amount of their time learning to use and work with their systems. This can and does apply to both pump and pens alike.
Obviously, those personal attributes are not necessarily going to be found in everyone. Indeed, it requires a level of maturity and intelligence, not typically seen until people reach their 20s and 30s. The fortunate thing about today’s technology is that people can live decades without serious complications, even with high glucose levels.
Therefore, it might be worthwhile for kids to use automated systems to minimize damage at an age when healing is easier and more effective. Let’s let kids grow up to be harmed by the usual things, like social media and video games.
But for those who wish to live longer and healthier, learning to manage the disease requires personal engagement in ways that automated systems just can’t do, and may even prevent or delay people from learning that essential lesson of personal engagement. (For a personal story on this, see my article, “The Sound of Diabetes.”)
There’s a lot of detail here and medical journals to cite, so let’s get into the weeds.
Today’s AID technology
One of the leading contributors to the idea that pumps are universally beneficial is pump manufacturers themselves, such as those who presented at the October, 2023 convention of the European Association for the Study of Diabetes. An example is the following figure produced by Medtronic for their MiniMed 780G system, which included data from over 100,000 users, showing reduced incidents of hypoglycemia and hyperglycemia, while also improving time-in-range (TIR) to the sought-after threshold of >70%.
Other manufacturers showed similar results at the conference.
As noted, these are not clinical trials, nor is this data subject to independent scrutiny. But even taken at face value, this is clearly an example of what researchers call selection bias, which is when the users in a dataset is not representative of the target population. In this case, T1Ds as a group.
Most studies conducted by objective researchers not affiliated with, or financed by device manufacturers show that user engagement is the determining factor, not the technology itself.
The other problem is that we don’t know how these same users performed without using the AID system. If, as objective trials have indicated, they didn’t really perform better, the systems net effect was negligible, raising the question of whether the systems are worthwhile. Remember, they’re expensive, and they require considerable administration (dealing with changing parts, managing software, obtaining supplies, etc.)
A valid consideration is whether T1Ds like and want to use a pump more than insulin pens.
Being motivated to use a new/hot technology is hardly anything new these days. Just look at the rate in which people upgrade to the latest smartphones or other devices.
This is a phenomenon known as the Christmas Tree Effect, where users’ attraction to (and satisfaction of) new technology is often driven by the illusion that it is better than the older model/method, and it has lots of “bells and whistles.”
A Christmas tree is more fun if you just add more lights. And make them blink. Even better if they blink to Taylor Swift. Imaging an insulin pump doing that.
The problem is, this effect is short-lived. Being enamored with technology is highly volatile, which explains why many tech gadgets fail—Google Glass, VR headsets, and hundreds of other products. (Fun read!)
This has happened with insulin pumps too. An example that illustrates this is the paper, “Glycemic Outcomes in Adults With T1D Are Impacted More by Continuous Glucose Monitoring Than by Insulin Delivery Method: 3 Years of Follow-Up From the COMISAIR Study.” The authors showed that insulin pumps – both automated and not – initially spurred engagement with users, but tapered off quickly, and ended up having little effect on overall glycemic control versus MDI.
But here’s the catch: The better outcomes were restricted to those who wore CGMs.
Indeed, the rise of CGM use has mirrored the rise of pump use (automated and not), which also leads to the impression that it’s the pump that drives improved outcomes, when in fact, CGM use is the strongest contributor of improved glycemic control over any other technology or method of insulin intake.
A more robust study that teases out these differences CGM use, pumps and MDI can be found in this 2018 study by the T1D Exchange, where researchers engaged over 21,000 subjects who used a combination of these. The results are differentiated, along with separations for age groups, as shown in the following figure:
The researchers wrote that “there isn’t a substantial difference between A1c outcomes for those who manually take insulin injections compared to those who use pumps” when the users are over the age of 26 and use CGMs. In fact, CGM+MDI users slightly outperformed CGM+pump users.
Once again, there’s nuance to appreciate: As with many other studies, the T1D Exchange study showed that CGM+pump use for people under 26 years old benefitted more than MDI. But over the age of 26, the advantage disappeared.
Young people lack years of experience living with T1D, their bodies are undergoing rapid changes, and they lack the maturity to understand a difficult disease or to develop the wherewithal to remain engaged. Yes, automated systems did better for them than they could do on their own, but their A1c levels were still dangerously high. Teaching them how to manage themselves is the real goal. When and how will that be managed isn’t being discussed right now, because the perception is that AID systems will be the be-all-end-all solution. Only when the nuances emerge will this problem be addressed.
User demographics and insulin pump outcomes
Perhaps the most important detail to consider about pump users is demographics. Given the high expense of pumps and CGMs (and the education and medical infrastructure to deliver them), pump users tend to be one or more of the following: They’re well-insured, come from higher socioeconomic households, have greater access to medical care, have higher income levels, and/or are typically more educated. Perhaps most importantly, they come from families that promote healthy lifestyles. The more any of those conditions apply, the more likely that person is to be engaged and informed about managing T1D, which is in keeping with the theme of this article.
The following paper, “Racial, ethnic, socioeconomic disparities in insulin pump use have persisted over 20 years,” breaks down this data accordingly:
“insulin pump use was 67% among non-Hispanic whites, 41% among Hispanics, 29% among Blacks, and 46% among other racial and ethnic groups. In addition, 70% of people with bachelor’s degrees or higher used the pumps, compared with 56% among those with some college, 40% among holders of high school degrees, and 18% among those with no high school education. By income level, 74% of those with household incomes of $75,000 or more, 66% with $50,000 to 74,999, 51% with $25,000 to $49,999, and 41% with less than $25,000, used the pumps.
Many attribute this as being the inequality of our healthcare system. That is, people who are white, rich, and educated have better access to technologies like automated insulin pumps.
True, but again, it’s not the pump doing the real work; it’s all the other factors.
To test whether this is the case is to review trials where subjects’ A1c levels are measured before and after introducing them to pumps and then evaluating their outcomes according to the various socioeconomic groups.
The paper, “Time in Range for Closed-Loop Systems versus Standard of Care during Physical Exercise in People with Type 1 Diabetes: A Systematic Review and Meta-Analysis,” analyzed dozens of random controlled trials (RTCs) among a wide range of socioeconomic groups, and also factored studies involving T1Ds who exercise. The authors concluded that pump users were only able to achieve a 1.07% improvement over control groups who didn’t use an an insulin pumps (and did use CGMs), irrespective of their background.
One can get even more granular still: In a 2021 study titled, “Predictors of the effectiveness of insulin pumps in patients with type 1 diabetes mellitus,” the authors conclude that the subjects whose A1c levels were >8% going into the study saw an improvement of 0.9 ± 1.2% when started on insulin pumps, whereas those whose A1c levels were <8% saw no benefit to pumps at all, irrespective of age, race, and income levels.
This is another example of statistical significance, but clinically irrelevant.
What about “lifestyle” factors?
Lastly, there are those who claim that, even if pumps offer no clinical benefit, the lifestyle benefits make them worthwhile.
Don’t take this the wrong way, but are they really having a better lifestyle with pumps? Fortunately, there are RCTs that study that too.
An interesting paper is “The DIAMOND Randomized Trial,” which initially aimed to assess the relative difference in costs associated with pumps versus MDI therapy. The authors found that pump users’ lifetime costs are $112,045 greater than those on MDI.
But researchers unexpectedly found that pump users’ quality-of-life factors decreased by 0.71 compared to MDI, and (even more unexpectedly) life expectancy dropped by 0.48 years (based on higher risk of DKA, among other risk factors that rose). Minimal differences from MDI to be sure, but these numbers certainly didn’t improve, as pump advocates would like to believe.
The reduction of efficacy AND the higher costs of insulin pumps (compared to pens) are two primary reasons why insurance companies are reluctant to cover insulin pumps.
Similar conclusions are found in multiple studies compiled in the paper, “Systematic literature review: quality of life associated with insulin pump use in type 1 diabetes.” By assessing a much larger set of trials, the authors concluded that there was little change in quality-of-life outcomes for most users due to a subtle psychological bias: Pump users really wanted them to work better, and in so doing, they believed they were. This makes “actual” satisfaction hard to assess, which brings us to the realm of psychology, especially around technology.
The Christmas Tree effect leads to a moral hazard: People overlook the drawbacks when technology fails, which can be rather serious for T1Ds. For example, diabetic ketoacidosis (DKA), a condition that occurs when the body doesn’t receive enough insulin, sometimes causing death, is more strongly associated with insulin pumps than those on MDI.
In the BMJ paper, “Incidence and prevalence of diabetic ketoacidosis (DKA) among adults with type 1 diabetes mellitus (T1D): a systematic literature review,” the authors aimed to summarize incidence and prevalence of T1Ds who were admitted to hospitals for DKA, and sort them into different subgroups (age, sex, geographical region, ethnicity and type of insulin administration). The paper is excessively long, as the reviewers started with 1082 separate articles in order to characterize each of the criteria. Among the many citations, a clinic in Colorado stood out, where all the patients admitted with DKA used pumps—none were on MDI. Other citations are listed below:
In the paper, “Insulin pump therapy is associated with higher rates of mild diabetic ketoacidosis compared to injection therapy: A 2-year Swedish national survey of children and adolescents with type 1 diabetes,” the authors found that 85% of admissions were pump users vs. MDI.
In the paper, “Severe Hypoglycemia and Diabetic Ketoacidosis in Adults With Type 1 Diabetes: Results From the T1D Exchange Clinic Registry,” researchers performed a cross-sectional analysis from the T1D Exchange clinic registry at 70 U.S. endocrinology centers, and found that 2972 incidents of DKA were associated with pump use, versus 2034 for those on MDI (roughly 47% greater risk for pump users).
In the paper, “Causes of diabetic ketoacidosis among adults with type 1 diabetes mellitus: insulin pump users and non-users,” researchers conducted a prospective observational study between January and June 2019 at the Cleveland Clinic Fairview Hospital, and found that, among patients admitted with DKA, 55% of the cases were pump users.
The list of similar findings is extensive.
Many people assume that DKA from insulin pumps is largely due to device malfunction, but this isn’t always the case. A more prevalent reason for DKA is user error. In the paper, “Risk and Relevance of Insulin Pump Therapy in the Aetiology of Ketoacidosis in People with Type 1 Diabetes,” the authors found that “an overwhelming majority were those on insulin pump treatment (93%)”, and added, “Overall, patient errors caused more DKA cases than device malfunctions.”
Imagine that: user error on a device that should be either automated or semi-automated, and where people are enamored with the technology, and who prefer to use them over much simpler insulin pens. The authors of this paper, “DKA Prevention and Insulin Pumps: Lessons Learned From a Large Pediatric Pump Practice,” were more blunt: “Most events could have been avoided if users followed standard troubleshooting guidelines.”
And yet, T1Ds are willing to overlook this due to the Christmas Tree Effect. And that brings us to the ultimate moral hazard: automation.
The perils of automation
Look, T1D is complex, and it needs your attention. If you’re distracted by something else, you won’t give it that attention. Automation is great, so long as it works, but if it’s semi-automated, now there’s the trade-off between the benefit of it working, versus the risk of your not giving it the attention it needs.
When the stakes are high, such as automated cars or insulin pumps, the consequences of taking your eyes off the road can be catastrophic. Automation robs people of the experience and expertise necessary to manage the same task, which are essential when the consequences are high.
This sentiment is similarly expressed by the authors in a 2022 review of closed-loop systems in the Diabetes Journal article, “Diabetes Technology: Standards of Medical Care in Diabetes—2022,” where the authors wrote:
“The most important component in all of these systems is the patient. [...] Simply having a device or application does not change outcomes unless the human being engages with it to create positive health benefits. [...] Expectations must be tempered by reality—we do not yet have technology that completely eliminates the self-care tasks necessary for treating diabetes.”
When it comes to engagement, this is one of the primary advantages of MDI. The physical act of injecting insulin makes one keenly aware of what the patient is doing. This is an example of The Hawthorne Effect, a phenomenon where people modify their behavior (usually positively) when they know they’re being observed. Observing yourself is the base case of the Hawthorne Effect.
In a study titled, “The Importance of the Hawthorne Effect on Psychological Outcomes Unveiled in a Randomized Controlled Trial of Diabetes Technology,” study subjects were exposed to a series of tasks associated with T1D management. The authors found that T1Ds who exhibited fear of hypoglycemia (FOH) saw a significant reduction in FOH, simply because they were being closely watched, even though there was no intervention whatsoever in how they managed their disease. They simply did what they knew they should do on their own. (All the other studies cited in this article do not have subjects “closely watched.”)
Similar outcomes have been shown for T1Ds who are told to log carbohydrates, exercise, and yes, manually take insulin. When you have to stop and think about calculating insulin and carbs, the act of what you’re about to do becomes more present. You proactively think to yourself, “Do I log 40g or 60g for this glazed donut that I know I shouldn’t be eating?” Believe it or not, the physical act of logging those carbs and taking that insulin causes many to be more engaged and deliberative in their T1D choices. Many people–including me–often choose not to eat that glazed donut. Sigh.
Summary and Commentary
I have lived with T1D for over fifty years, so I can attest to the fact that the disease is grippingly difficult to live with, let alone self-manage. Any technology that can ease the burden–even in the slightest–is a blessing. And this is why I struggle with the concept of automated insulin pumps: They are essential for those who are either unable or unwilling to manage their own care beyond a certain threshold, especially the young or those with cognitive impairment. But for those who are able to take care of themselves, one must remain as engaged as possible with the nuances of daily T1D management. One of the risks of automation is disengagement–failing to learn self-management.
The state of closed-loop technology today is, sadly, as good as it can possibly get, unless and until there are better methods of sensing glucose and delivering insulin in real time (not through interstitial tissue), while also delivering other essential regulatory hormones that are also part of the process. (I cover this in my article, “Challenges Facing Automated Insulin Delivery Systems.”)
Without solving the technical barriers that pumps face, today’s closed-loop systems are like a self-driving car equipped with only a hazy rear-view camera (the CGM), a gas pedal (insulin) and a faulty fuel line that may or may not deliver the gas to the engine in a timely manner. No forward view, no side view, no brakes and no reliable navigation system. In automatic mode, there’s not even a driver. The most powerful AI-driven algorithms that try to calculate proper insulin dosing cannot possibly compensate for these mechanical dysfunctions. At best, the car will go on a very straight road at 5mph, and get pretty banged up along the way. You know, like having an A1c of 8%.
I certainly don’t have any problem with people using these systems, so long as they are acutely aware of what they are doing, and are not under the illusion that it’s the pump making things better. It’s you.
Once again, you've written an extremely thought-provoking article. Thank you for putting this together!
I've had T1D for 45 years. I use Control IQ and I (1) love it and (2) don't disagree with your conclusions in the least. I'm meticulous about bolusing for food and high blood sugars. Without that effort, the pump wouldn't be effective at all.
Why do I love it? For me, it's COMPLETELY eliminated overnight lows since the day I switched to CIQ. I used to run high at night out of fear of those overnight lows. No longer! I wake up every morning at 110 mg/dl. This is the one area where closed loop tech is (understandably) excellent. When a diabetic is asleep, the pump can simply release basal insulin, adding more or giving less as needed. Without meals or exercise or stress to worry about when the patient is asleep, it's pretty hard for CIQ to mess up. That alone is worth it for me. But nothing I'm saying contradicts your conclusions.
Thanks again. I look forward to reading each of your posts.
Proofreading Police! 😉
“Technically, such a system a highly“
You’re missing a verb, perhaps “is”?
“Another way to test that is by measuring A1c levels before and after introducing people to pumps and measuring their outcomes afterwards (while including subjects from diverse social, racial and economic subpopulations). This metaanalysis (literature review) of dozens of RTCs had these aims in mind, and also included”
Please, sir, what are RTCs?
Policing over. Again, thank you for an interesting article. I always learn something from your posts. I'm a Metronic user and I got a new pump over a year ago. They gave me a box of sensors and a chance to try out this new 780G system. Well, I have a problem with rising blood sugar after I get out of bed. I like to eat right away, so first thing I do is check my numbers and enter carbs for breakfast. However, auto mode thought that my rising blood sugars were from eating, but I knew they weren't. So I had to exit auto mode, bolus in manual mode, and then go back to auto mode a few hours later for the rest of the day. I learned from a forum that I could "phantom bolus" to correct, but it just seemed a hassle. It was way easier to set my Basals where they needed to be. Plus, I would have to pay out of pocket for the sensors, when the Libre 2 was covered by the government.
I missed my old pump, because the new one was specifically designed to be used in auto mode and manual mode requires seemingly endless button pressing. Unfortunately, I forgot to take that old pump off when I went swimming in the sea. "Critical Error!" ;-) So, back to my "back up", newer pump.
My 2 months on the Medtronic "closed loop" system was very frustrating and my time in range numbers were worse. I can see where it would be advantageous for someone who was hypo unaware, especially at night, but it just wasn't working for me.
I look forward to your next article.