Can bariatric surgery prevent diabetes?

I’ve previously written here about the 2 major New England Journal trials looking at treating type 2 diabetes with bariatric surgery.  Those studies showed a very robust ability of bariatric surgery to treat type 2 diabetes.  If you can use bariatric surgery to treat type 2 diabetes, what about prevention?  This question was examined in a more recent NEJM publication of selected results from the Swedish Obese Subjects (SoS) study from Carlsson et al.

Guest Post by Dr. Jonathan Carter

I’m pleased to say that my friend and colleague, Dr. Jonathan Carter, has agreed to follow this post with a guest blog post of his own, giving his analysis of the study.  Dr. Carter is an Assistant Professor of Surgery at UCSF, frequently performing bariatric surgery.

For those who skim blogs…

I’ll start with my take-away points, and then go backwards to analyze the study in more depth.  So, without further ado, the major takeaways from this study are:

1) Bariatric surgery impressively reduced the risk of type 2 diabetes in a middle-aged, obese population by 80% compared to the control group.  The number needed to treat (NNT) was 1.3!

2) This study did not address the most important comparison, i.e. between bariatric surgery and an intensive lifestyle modification program.  Unfortunately, the control group in this study received minimal attempt at lifestyle modification.  Prior studies like the Diabetes Prevention Program, the Finnish Diabetes Prevention Study, and the Chinese Diabetes Prevention Study showed between a 30-50% reduction in type 2 diabetes incidence with lifestyle modification.  However, one cannot directly compare the rates in these studies to each other.

3) Due to #s 1 and 2 above, the next study should directly compare bariatric surgery and intensive lifestyle modification with regard to diabetes prevention.

4) Weight loss prevents the onset of type 2 diabetes in obese patients.  Bariatric surgery causes weight loss.

With these results, we have to start discussing whether it is ethical, reasonable, and cost-effective to use bariatric surgery to prevent type 2 diabetes.

Now, for those of you interested in some more information about the study and results, keep reading…


This study was a prospective, non-randomized trial which enrolled 4,047 obese patients from 1987-2001 in Sweden.  The researchers note that they did not randomize the participants due to “ethical reasons related to the high postoperative mortality associated with bariatric surgery in the 1980s.”  In other words, enough people died from bariatric surgery at the time the study began that it would have been unethical for them to randomly assign people to have it done.

The control group was selected by a matching algorithm that concurrently tried to keep the current mean values of the matching variables between the two groups as similar as possible.  Included patients were aged 37-60 years old and had BMI over 34 for men and over 38 for women.  And, of course, they did not have diabetes at baseline.  Ultimately, those included in this analysis were 1,658 patients who had surgery and 1,771 who were in the control group.

Baseline characteristics: Surgery group had more severe risk factors

Due to the matching process, those in the surgery group were older, heavier (120 kg vs 114 kg), had higher insulin levels, higher blood pressures, worse cholesterol, higher smoking rates, lower physical activity rates, and higher caloric intakes compared to those in the control group.  Because the groups were non-randomized, it was likely that these “sicker” and “riskier” patients were more likely to be recommended surgery by their physicians.  However, in the end, this makes the results even more impressive because the surgical group had 80% lower rates of diabetes despite being a sicker group to begin with.  The surgical group had the decks stacked against them, and still came out ahead.  It is as if the surgical group started a 100 meter race with a 1-2 second handicap, but was still able to win.

No attempt at standardizing lifestyle therapy in control group

As I discussed above, a weakness of this study is that there was no attempt to standardize treatments in the control group.  Some might say that this is a positive because it reflects “real-world” treatments.  And indeed, the authors note that “patients in the control group received the customary treatment for obesity at their primary health care centers.”  However, according to questionnaires, this meant that only 54% of these patients received even some professional guidance.  So, nearly half of the control group received no help at all from their healthcare providers with weight loss.

The Results: Surgery caused weight loss and prevented diabetes

These two figures say it all… compared to “customary treatment” in this cohort of obese patients, the patients who got bariatric surgery lost significantly more weight (Figure S3) and had significantly less progression to type 2 diabetes (Figure 1A).

Do insulin pumps and continuous glucose monitors actually improve outcomes?

Nearly every day in my practice, a patient with diabetes asks me whether he or she should switch from multiple daily insulin injections to an insulin pump.  I often have a discussion with patients about whether or not they should be using a CGM (continuous glucose monitor) to help monitor blood glucose instead of just using SMBG (self-monitoring of blood glucose).  As an endocrinologist, it is very important to be able to advise patients about specifically what these new technologies have to offer them.  Do they decrease mortality?  Do they decrease long-term diabetes complications?  Do they improve glycemic control?  Do they improve quality of life for patients?  Do they lower costs?  All new medical technologies need to undergo a rigorous evaluation and testing with these types of questions in mind.  This is critical not just so that I can be honest and helpful to my patients, but also from the overall perspective of the healthcare system.

In that vein, Yeh et al recently published a meta-analysis in the Annals of Internal Medicine called “Comparative Effectiveness and Safety of Methods of Insulin Delivery and Glucose Monitoring for Diabetes Mellitus: A Systematic Review and Meta-analysis.”

This meta-analysis, funded by AHRQ, looked at the differences between:

  1. MDI vs CSII (multiple daily injections vs continuous subcutaneous insulin infusion)
  2. Type 1 vs type 2 diabetes
  3. SMBG (self-monitoring of blood glucose) vs rt-CGM (real-time continuous glucose monitoring)

What types of studies did they include in their meta-analysis?

  • Studies of adults, adolescents, or children with type 1 or type 2 diabetes mellitus
  • Studies from 1966-2012
  • 19 studies comparing CSII with MDI (>3 injections per day of either basal/bolus insulin or NPH/regular)
  • 10 studies comparing CGM with SMBG (>3 fingersticks per day)
  • 4 studies comparing SAP (Sensor-augmented pump) use with MDI + SMBG

* Studies were excluded if regular insulin was used in the CSII (pump) group (they felt this to be a weakness of prior analyses)

Here is the key data table:

A few things pop out from this table:

  1. Overall, they assessed the strength of evidence as relatively weak.
  2. In children and adolescents, CSII showed no difference in clinical outcomes from MDI.  CSII was better in terms of quality-of-life.
  3. In adults with type 1 diabetes, CSII led to more symptomatic hypoglycemia, but better hemoglobin A1c and quality-of-life.
  4. There were no differences between CSII and MDI in adults with type 2 diabetes.
  5. CGM, whether with an insulin pump or not, led to a benefit in glycemic control without any difference in hypoglycemia.

Some concerns and words of caution when interpreting these results:

  • Meta analyses can always suffer from publication bias.  That is, studies are much more likely to be published if they show positive results.  So it is possible that studies have been done that generated results that would have shown no difference between the two methods being studied, but these may never have been published and thus cannot be included in the meta-analysis.
  • These studies all had durations of 12-52 weeks.  There were no studies reporting on long-term outcomes like micro or macrovascular disease.
  • 24 of the articles (approximately 2/3) were supported by pharmaceutical companies

What does this mean?

According to this meta-analysis, CGMs did improve glycemic control.  Insulin pumps did not appear to have a significant effect on clinical outcomes, but did positively effect quality of life.  Remember that the studies included were all between 12 and 52 weeks, so one major limitation is that any longer-term effects would not be teased out.

While some may discount the quality of life improvements seen with the pump as being less important than clinical outcomes, I caution people from doing so.  In a condition as omnipresent as diabetes, maintaining good quality of life for the patient is critical and a very important goal.

In the end, the decision about whether or not to use one of these devices comes down to a conversation with the patient and their family, based on their personal preferences and what each device might offer them in terms of benefits and harms.  This meta-analysis adds some more information to that conversation.

Finally, this meta-analysis shows that we simply need more data to study so that more concrete conclusions can be drawn.

MedX 2012 Conference at Stanford

I spent a few hours this morning watching the livestream of the MedX conference at Stanford organized by Dr. Larry Chu.  From the portions I have been able to watch, this looks so far to be a really great conference.  The speakers this morning included a panel of self-trackers, Dr Paul Abramson (a physician who uses self-tracking in his office), Anne Wright of BodyTrack, and Sean Ahrens of Crohnology.  As I’ve always found with the mhealth and quantself communities, even from my office on the other end of the peninsula watching the video via livestream, the energy, excitement, and passion are phenomenal.  A few themes and ideas stand out from MedX itself and from the Twitter feed #medx, meriting some discussion.

1) Self-tracking is about the process, not the data.

This is absolutely true.  Using diabetes as a reference point, just looking at data for the sake of data is a waste of time.  People with diabetes make decisions all day, every day, most of which are minor and subtle decisions driven by habit.  Looking at data might help them make changes, but it’s not very likely.  More important is that they actively engage with the data and learn from it.  This process leads to crucial education about the self and personal habits that might help lead to different behavior the next time they are faced with a decision.  The act of gathering the data itself also enables personal exploration and revelations that would not be otherwise possible.  Self-care behaviors and self-awareness have no choice but to improve if someone is actively engaged in self-tracking.  Data should include not just numbers but life stories and context for what was going on at the time the numbers were collected.

2) Patients want doctors who believe them.

We heard this from many of the self-trackers and e-patients at MedX.  There are many patients who have found our current healthcare system too impersonal and uncaring.  I’ve heard this over and over, seen it happen in places where I work, and experienced it with family members.  There are a million reasons why this has happened and changes have to be made to medical education and healthcare economics in order to start making patients feel cared for again.  Regardless, we have no excuse.  No matter what pressures exist on doctors, we must retain compassion for the person sitting in front of us.  Everything else follows from this simple rule.

Sometimes, the problem can be that our current body of medical knowledge and experience is inadequate and only scratches the surface of the true pathophysiology of human disease and suffering.  All physicians have had experiences with patients where we listen to the patient describe their symptoms and we know something is wrong, but we have no diagnosis, no terminology with which to describe their particular situation.  This is always an incredibly frustrating experience for patient and physician alike.  As physicians, we are left not quite sure what to do, which frustrates us, because we are trained to do (though we should more often be like jazz musicians and place more focus on the empty space, ie what not to do).  Despite our frustration, physicians still have a choice in these situations.  The patient’s symptoms can be believed and empathy given, or the patient can be told, “I don’t know what you have, but at least you don’t have ______.”  I’d imagine patients prefer seeing physicians who do the former.

3) Patients want doctors who are willing to engage with their self-tracking data.

Even as a self-tracker and innovator in diabetes data and tracking, I find this leads me to some internal philosophical conflict.  Do I believe that self-tracking will help many patients improve their health?  Yes.  Do I believe that gathering self-tracked data will play a major role in the future of healthcare?  Yes.  Do I want my patients to self-track and to share their data and their experiences with me?  Absolutely!  Does the healthcare system have the resources and ability to handle this?  No.  Not right now.

First: We’re not ready yet for self-tracking data from a technical standpoint.

The simple fact is that most healthcare organizations are still trying to get an electronic health record implemented.  Getting self-tracked data into EHRs may be on the radar, but it is not imminent.  Once we have self-tracked data in the EHR, then what?  At least the patient’s medical record then becomes more whole, but EHRs have already left physicians in the position of having information overload, and this is in a situation where physicians already lack sufficient time to spend with each patient.  New piles of data will only exacerbate the situation.  Smarter ways of organizing and filtering the information are going to be absolutely necessary to make this manageable and to allow physicians to use the data with patients in the way it should be used.  (As a slight aside, having a single, unified patient-centered record is also a precondition for a functional system.  None of this works if each patient has their data fractured over ten different healthcare organizations, PHRs, and websites.)

Second: We need to find the proper place for self-tracking tools and data within healthcare, which requires a better understanding of their effect on healthcare quality and costs. 

There was a Twitter comment in the #medx stream expressing outrage, saying, “Cannot believe that some diabetes tracking tools are not covered by some insurers. Absolutely nonsense!! give them the tools!!!”

This was in reference to a panelist with type 2 diabetes who used a Dexcom CGM and had to pay for it out of pocket.  This Twitter comment shocked me.  It is not news to anyone that the resources of our healthcare system and entire economy are strained by rising costs.  There is just no way it is sustainable, acceptable, fair, ethical, or you-choose-the-word-to-put-here for everyone to expect that their healthcare insurance should cover every device they want.  Our country has to stop expecting this.  While there have been many new devices in healthcare that have achieved better health at a reasonable cost, history is littered with examples of new devices that have either been overwhelmingly expensive for minimal health benefit or have flat-out had negative impacts on health.  So, there simply HAS to be research done (hopefully efficiently and effectively) showing that a new device has health benefit, and at some reasonable cost, before we expect insurers to cover the device.  Using the specific example of a CGM for a type 2 diabetes patients, there are too many people in the country who don’t even get basic, proven care for type 2 diabetes, like eye and foot exams, blood pressure control, or metformin, for us to be claiming that all insurers should be covering this device for all type 2 patients.  If a patient wants to pay for an unproven device or treatment out of pocket, I have no qualms, but we cannot expect society to pay.

This serves as a clear reminder to those of us innovating in healthcare that successful innovation will be mindful of the value equation, ie either better healthcare quality or lower cost, or ideally both.  I’m incredibly optimistic and excited about what lies ahead in healthcare innovation, because I think we will create things that improve healthcare value.  I believe that self-tracking will be a major component of this, and will be especially important in empowering patients, bringing new and critical data into the doctor’s office, and creating a new paradigm for the doctor-patient relationship.

What a great conference!  Thank you to Dr. Chu and all of the speakers, panelists, attendees, and other remote attendees!

Physician empathy associated with lower rates of diabetes complications


I’ll admit that I’ve not yet read this journal article to form my own conclusions, but I found the headline interesting nonetheless.  Here is a link to the NY Times article and a link to the original journal article in the Journal of Academic Medicine.  It makes intuitive sense… if your physician has a higher level of empathy, you are more likely to form a positive treatment relationship, and the patient is thus more likely to find meaningful and useful treatment recommendations from that relationship, and will end up with fewer acute metabolic complications.  Definitely adding this paper to my journal article reading list.


3 Thoughts About The V-Go Insulin Delivery Device

I had a chance this week to spend some hands-on time learning about the new V-Go insulin delivery device from Valeritas.  Valeritas’ website states that “The V-Go is engineered to simplify basalbolus insulin therapy for the millions of people suffering from Type 2 diabetes.”


The facts:

– This is the first disposable insulin-delivery device that will give basal-bolus insulin.

– It is mechanical, containing no electronics.

– It is designed to be worn for 24 hours before it needs to be refilled with insulin.

– The needle is a 30 gauge needle that stays in the user while the V-Go is in use.

– The V-Go comes in 3 “sizes”: one that delivers 20 units of basal insulin over 24 hours, one that delivers 30 units, and one that delivers 40 units.  Each device is also capable of giving bolus insulin in 2 unit increments up to 36 total units of bolus insulin per 24 hour period.

Three thoughts about the V-Go:

1) Convenient: This device appears well-built and relatively easy to use.  It is about the size of an Omnipod, and because it is placed on the user for 24 hours straight, allows her to leave insulin at home when going out for the day.  The device needs to be refilled every 24 hours with rapid-acting insulin.  So, the user need only take fingerstick/testing supplies out with her when going to work, running errands, or going out to meals.  It is also somewhat elegant that there are no electronics in the device.

2) Not enough insulin for some patients: Though this device promises convenience, the amount of insulin that can be delivered is too little for some people with type 2 diabetes.  The most that can be delivered is 40 units of basal insulin and 12 units of bolus insulin per meal (totaling 36 units of bolus insulin a day).

3) Inability to titrate: The device comes in 3 sizes, each delivering a set basal amount of insulin over 24 hours.  These are either 20, 30, or 40 units.  While this may be useful for a patient who has already been on a steady dose of basal insulin, it does not give much flexibility to titrate doses.  Once a patient has paid her co-pay at the pharmacy and picked up a month’s supply, she would have to pay again to switch to a different basal rate.

I think this device represents an interesting start towards a market that will likely increase rapidly in the next few years of devices intended to deliver insulin to people with type 2 diabetes.  Given the above limitations, I think it’s overall usefulness will prove limited, but I look forward to seeing what future iterations and generations of devices will look like.

What do you think?  Would you want to try this (either patients with type 2 diabetes or providers caring for patients with type 2 diabetes)?