Sometimes my mind is boggled by the idiotic logic used by people who are telling patients how to live their lives. For example, a physician writing about low-carb diets recently wrote:
"People do lose weight, but not for the reasons put forth by those who champion such plans. The weight loss comes partly from eating fewer calories and partly because in this day and age, eliminating carbohydrates means eliminating calorie dense, highly processed foods (most of which contain high fructose corn syrup (HFCS)."
Huh? You mean eating fewer calories and eliminating highly processed foods full of HFCS is a bad thing? Maybe I don't understand this because I never went to medical school, but I thought when you wanted to lose weight, eating fewer calories was your goal, and everyone is saying today that we should eliminate highly processed foods.
Then this sage goes on to say, "I can't imagine why anyone would follow a diet -- any diet -- that takes entire food groups away from you. There's no reason to give up great foods like pasta, potatoes, beans and corn to lose weight or to be healthier. Giving up these foods is one of the main reasons that the Atkins diet is not a diet that can be sustained for the long term."
One could also say, "There's no reason to give up great foods like whole-fat milk and yogurt, steaks, and heavy cream to lose weight or to be healthier. Giving up these foods is one of the main reasons that low-saturated-fat diets cannot be sustained for the long term."
Because people like this author think that low-carb diets consist of nothing but rib roasts and cream cheese with no vegetables, they're prejudiced about them, label them "fad diets," and then use ridiculous logic to support their preconceptions.
Another stupid argument warns people with diabetes not to go on low-carb diets because their blood sugar might go down, as if that were a terrible thing. Of course people should be warned to keep track of their blood sugar and if it goes down too much to consult their doctors about reducing their medications. But for someone with a disease that causes high blood sugar to avoid a diet because it would make blood sugar go down is ridiculous.
One can only hope that physicians like this use better logic with the non-nutritional aspects of their practices. Would they say, "I don't want you to use chemotherapy because it might make your cancer cells shrink too much"? Or would they tell people who were gluten-intolerant, "There's no reason to give up great foods like bread and cereal to be healthier. Giving up these foods is one of the main reasons that gluten-free diets are not diets that can be sustained for the long term."
No one really wants to give up "great foods" like potatoes, bread, corn, and peas. But sometimes when you have a chronic disease like diabetes, you have to make difficult choices. Would you rather eat "great foods" or would you rather have your eyesight?
Tuesday, April 26, 2011
Friday, April 15, 2011
Caffeine and Diabetes
Does caffeine make our blood glucose (BG) levels go up?
The popular news stories about caffeine and BGs can be confusing. Some say that caffeine is bad for BG control. Others say it's good. For example, heavy coffee drinkers are at lower risk of developing diabetes than light users or coffee abstainers.
What's going on here?
James D. Lane's recent review in a new science journal, the Journal of Caffeine Research, attempted to bring some order to these conflicting views by doing a meta-analysis of the various studies of caffeine and insulin resistance and BG control.
There does seem to be good evidence that high caffeine doses cause an increase in insulin resistance (IR) in healthy, nondiabetic adults. In a healthy, nondiabetic person, however, an increase in insulin resistance wouldn't necessarily mean higher BG levels. They'd just secrete more insulin to cover the increased IR.
When you have diabetes, however, and you can't just secrete more insulin, then an increase in IR usually results in an increase in BG levels. And, indeed, research has shown higher BG levels in people with type 2 diabetes after drinking coffee.
According to Lane, more than 17 studies in nondiabetic adults from 1968 through 2010 have demonstrated transient increases in IR with moderate caffeine doses (equivalent to 2 or 3 cups of brewed coffee) in both habitual caffeine consumers and abstainers. Different studies used different methods, but the results were consistent. Thirteen of 14 studies measuring the glucose response after a carbohydrate challenge found an increase in insulin resistance with caffeine. (Those who want more details can consult the references in the Lane paper, which is free full text online.)
Many studies used pure caffeine in amounts designed to replicate the amounts in coffee, and some of the caffeine doses were infused intravenously, hardly a physiological situation, although I've sometimes thought mainlining my coffee would get me going faster in the morning.
So Terry Graham and colleagues at the University of Guelph, Ontario, studied the effects of drinking coffee, to try to mimic the real-world effect of caffeine. They also studied the effect of fat. As reported here, they found that both fat and caffeine independently increased insulin resistance and glucose levels in the 10 young healthy men in the study. The caffeinated coffee had the greatest effect alone. Both together had an even greater effect than either one alone.
Both caffeinated and decaffeinated coffee increased levels of glucagon-like peptide-1 (GLP-1).
Graham explained that coffee alone won't raise BG levels. It only increases BG levels when you eat carbs. And even drinking the coffee at the same time you eat the carbs won't have much effect. But when you drink coffee, wait a bit, and then eat carbs, your BGs will go higher. The researchers had previously shown that this effect persists through a second meal and occurs with low-glycemic-index as well as high-glycemic-index carbohydrates.
Lane concluded from the meta-analysis that "Caffeine in coffee, tea, or soft drinks causes transient insulin resistance that can produce exaggerated glucose and insulin responses when carbohydrate is consumed" [italics mine].
This qualifier made me wonder what the effect would be in people on low-carb diets. The Graham group used 75 grams of carbohydrate in their test meals. Many people on low-carb diets eat only 30 to 50 carbohydrate grams a day. Would the caffeine be important in them?
To test this question in myself I adopted the following procedure.
1. Drink my usual 2 cups of strong espresso (or decaf another day) on arising.
2. Measure BG every hour until 2 hours after lunch.
3. Wait an hour after the coffee. Then eat 26 home roasted almonds.
4. Eat a poached egg with butter an hour after the almonds (so I'd have some protein to keep me until lunch) and take oral meds, including extended-release metformin.
5. Have lunch. I had 3 oz beef, 6 spears of asparagus with 1 tsp olive oil and a few slivers of red pepper, cracker-sized wedge of LC wrap with butter, half cup of plain kefir with a few nuts.
An hour after eating lunch and measuring, I took my standard walk, about 1.4 miles.
Here are the results:
Time__CAF__DECAF
0_____87____ 89
1_____85_____81___almonds
2_____104____86___ egg and ER metformin
3_____105___104
4_____*_____101
5_____88____108___lunch
6_____133____130___walk
7_____104____119
*I was absorbed in something else and forgot to test here.
At hour 2 (1 hour after eating nuts), I thought maybe the coffee was having an effect, but at hour 3 the readings were almost identical. Graham said that research has shown that caffeine doesn't affect gastric emptying, so this could be random variation.
Because my BG was higher before lunch on the decaf day than it was on the caffeine day, although the 1-hour postlunch BGs were similar, the rise was almost twice as much on the caffeine day.
Finally, perhaps the real peak might have occurred at 1.5 hours after eating the almonds and might have been higher with the caffeine (I'd planned to measure every 30 minutes, but then I got lazy).
But if so, it came down fast enough, so I concluded that for me and my diet, the effect of the caffeine was not large enough to persuade me to give up the pleasure I get from drinking black coffee.
Because we're all slightly different physiologically, with different sensitivities to chemicals and different diets, anyone who is concerned about the effects of caffeine should try a similar test themselves. If you want, you could let us know what you found.
The effect in someone on a low-fat high-carb diet might be quite different. And the effect on most Americans, who eat a lot of carbohydrate and fat as well as a lot of caffeine, especially in today's world where coffee houses are so popular, might be more significant.
The mechanism of the increased IR from caffeine is not known. There are two major hypotheses. The first is that it's because of interference with adenosine receptors on cells. Adenosine is involved in insulin-mediated glucose transport as well as playing a role in sleepiness.
One reason coffee keeps us awake is that blocking the adenosine receptors means adenosine can't bind to the receptors and make us sleepy. Blocking the receptors also seems to reduce inflammation and affect IR. Some research has shown that blocking the receptors decreases IR. Other research shows the opposite. And a study cited by Lane suggested that adenosine receptors had no effect.
The picture is further complicated by the fact that there are different subtypes of adenosine receptors on different cells, and the caffeine may have different effects in different tissues.
The other hypothesis is that caffeine increases the release of stress hormones like cortisol and epinephrine (adrenaline), counterregulatory hormones known to increase BG levels. There is some evidence for this effect, but more research needs to be done.
Finally, there's the paradoxical evidence that heavy coffee users are at much lower risk of getting type 2 diabetes. Those who drink 7 cups a day have half the risk of those who drink 2 or less.
Perhaps there's something in coffee other than caffeine that is causing this protection. In some studies, decaffeinated coffee reduced risk as much as caffeinated.
Common sense suggests that people who drink a lot of coffee probably drink fewer sodas.
But now a study at the University of California at Los Angeles, reported in January, suggests that a hormone-binding protein called SHBG (sex-hormone binding globulin) may be involved. The levels of SHBG in postmenopausal women were increased by caffeine; decaffeinated coffee and tea had no effect.
So far, this is just a hypothesis, but it's one more clue in this complex picture. When it comes to diet and type 2 diabetes control, nothing seems to be simple.
The popular news stories about caffeine and BGs can be confusing. Some say that caffeine is bad for BG control. Others say it's good. For example, heavy coffee drinkers are at lower risk of developing diabetes than light users or coffee abstainers.
What's going on here?
James D. Lane's recent review in a new science journal, the Journal of Caffeine Research, attempted to bring some order to these conflicting views by doing a meta-analysis of the various studies of caffeine and insulin resistance and BG control.
There does seem to be good evidence that high caffeine doses cause an increase in insulin resistance (IR) in healthy, nondiabetic adults. In a healthy, nondiabetic person, however, an increase in insulin resistance wouldn't necessarily mean higher BG levels. They'd just secrete more insulin to cover the increased IR.
When you have diabetes, however, and you can't just secrete more insulin, then an increase in IR usually results in an increase in BG levels. And, indeed, research has shown higher BG levels in people with type 2 diabetes after drinking coffee.
According to Lane, more than 17 studies in nondiabetic adults from 1968 through 2010 have demonstrated transient increases in IR with moderate caffeine doses (equivalent to 2 or 3 cups of brewed coffee) in both habitual caffeine consumers and abstainers. Different studies used different methods, but the results were consistent. Thirteen of 14 studies measuring the glucose response after a carbohydrate challenge found an increase in insulin resistance with caffeine. (Those who want more details can consult the references in the Lane paper, which is free full text online.)
Many studies used pure caffeine in amounts designed to replicate the amounts in coffee, and some of the caffeine doses were infused intravenously, hardly a physiological situation, although I've sometimes thought mainlining my coffee would get me going faster in the morning.
So Terry Graham and colleagues at the University of Guelph, Ontario, studied the effects of drinking coffee, to try to mimic the real-world effect of caffeine. They also studied the effect of fat. As reported here, they found that both fat and caffeine independently increased insulin resistance and glucose levels in the 10 young healthy men in the study. The caffeinated coffee had the greatest effect alone. Both together had an even greater effect than either one alone.
Both caffeinated and decaffeinated coffee increased levels of glucagon-like peptide-1 (GLP-1).
Graham explained that coffee alone won't raise BG levels. It only increases BG levels when you eat carbs. And even drinking the coffee at the same time you eat the carbs won't have much effect. But when you drink coffee, wait a bit, and then eat carbs, your BGs will go higher. The researchers had previously shown that this effect persists through a second meal and occurs with low-glycemic-index as well as high-glycemic-index carbohydrates.
Lane concluded from the meta-analysis that "Caffeine in coffee, tea, or soft drinks causes transient insulin resistance that can produce exaggerated glucose and insulin responses when carbohydrate is consumed" [italics mine].
This qualifier made me wonder what the effect would be in people on low-carb diets. The Graham group used 75 grams of carbohydrate in their test meals. Many people on low-carb diets eat only 30 to 50 carbohydrate grams a day. Would the caffeine be important in them?
To test this question in myself I adopted the following procedure.
1. Drink my usual 2 cups of strong espresso (or decaf another day) on arising.
2. Measure BG every hour until 2 hours after lunch.
3. Wait an hour after the coffee. Then eat 26 home roasted almonds.
4. Eat a poached egg with butter an hour after the almonds (so I'd have some protein to keep me until lunch) and take oral meds, including extended-release metformin.
5. Have lunch. I had 3 oz beef, 6 spears of asparagus with 1 tsp olive oil and a few slivers of red pepper, cracker-sized wedge of LC wrap with butter, half cup of plain kefir with a few nuts.
An hour after eating lunch and measuring, I took my standard walk, about 1.4 miles.
Here are the results:
Time__CAF__DECAF
0_____87____ 89
1_____85_____81___almonds
2_____104____86___ egg and ER metformin
3_____105___104
4_____*_____101
5_____88____108___lunch
6_____133____130___walk
7_____104____119
*I was absorbed in something else and forgot to test here.
At hour 2 (1 hour after eating nuts), I thought maybe the coffee was having an effect, but at hour 3 the readings were almost identical. Graham said that research has shown that caffeine doesn't affect gastric emptying, so this could be random variation.
Because my BG was higher before lunch on the decaf day than it was on the caffeine day, although the 1-hour postlunch BGs were similar, the rise was almost twice as much on the caffeine day.
Finally, perhaps the real peak might have occurred at 1.5 hours after eating the almonds and might have been higher with the caffeine (I'd planned to measure every 30 minutes, but then I got lazy).
But if so, it came down fast enough, so I concluded that for me and my diet, the effect of the caffeine was not large enough to persuade me to give up the pleasure I get from drinking black coffee.
Because we're all slightly different physiologically, with different sensitivities to chemicals and different diets, anyone who is concerned about the effects of caffeine should try a similar test themselves. If you want, you could let us know what you found.
The effect in someone on a low-fat high-carb diet might be quite different. And the effect on most Americans, who eat a lot of carbohydrate and fat as well as a lot of caffeine, especially in today's world where coffee houses are so popular, might be more significant.
The mechanism of the increased IR from caffeine is not known. There are two major hypotheses. The first is that it's because of interference with adenosine receptors on cells. Adenosine is involved in insulin-mediated glucose transport as well as playing a role in sleepiness.
One reason coffee keeps us awake is that blocking the adenosine receptors means adenosine can't bind to the receptors and make us sleepy. Blocking the receptors also seems to reduce inflammation and affect IR. Some research has shown that blocking the receptors decreases IR. Other research shows the opposite. And a study cited by Lane suggested that adenosine receptors had no effect.
The picture is further complicated by the fact that there are different subtypes of adenosine receptors on different cells, and the caffeine may have different effects in different tissues.
The other hypothesis is that caffeine increases the release of stress hormones like cortisol and epinephrine (adrenaline), counterregulatory hormones known to increase BG levels. There is some evidence for this effect, but more research needs to be done.
Finally, there's the paradoxical evidence that heavy coffee users are at much lower risk of getting type 2 diabetes. Those who drink 7 cups a day have half the risk of those who drink 2 or less.
Perhaps there's something in coffee other than caffeine that is causing this protection. In some studies, decaffeinated coffee reduced risk as much as caffeinated.
Common sense suggests that people who drink a lot of coffee probably drink fewer sodas.
But now a study at the University of California at Los Angeles, reported in January, suggests that a hormone-binding protein called SHBG (sex-hormone binding globulin) may be involved. The levels of SHBG in postmenopausal women were increased by caffeine; decaffeinated coffee and tea had no effect.
So far, this is just a hypothesis, but it's one more clue in this complex picture. When it comes to diet and type 2 diabetes control, nothing seems to be simple.
Thursday, March 17, 2011
Metformin and Thyroid Tests
Every drug we take has many effects. The main effects are usually known by patients as well as physicians. For example, most people know that the drug metformin often causes gastric distress, which can be reduced by starting with a small dose and gradually working up to a therapeutic dose.
But most drugs also have minor effects. Sometimes your doctor is aware of these but doesn't tell you because the incidence of these effects is low and the doctor doesn't want to worry you. This is often true of the muscle weakness and memory problems that statins can cause.
Sometimes even your doctor isn't aware of the minor side effects.
Sometimes no one has yet discovered some side effects. This can be because you have to be on a drug for a certain amount of time before these side effects show up. It can be because no one has noticed the link between a particular drug and some side effect.
Or it can be because drugs can interact with other drugs, and when you're taking a lot of different drugs -- say a diabetes drug, a blood pressure drug, a lipid-lowering drug, an anti-reflux drug, an antidepressant, a beta blocker, an antihistamine, an osteoporosis drug, and an asthma drug -- and you complain of fatigue, it's not immediately clear which one of these drugs or which combination is causing that problem.
One relatively unknown drug-hormone interaction was first reported in 2006.
It seems that metformin suppresses thyroid-stimulating hormone (TSH; also called thyrotropin), the hormone that is generally tested to ascertain your thyroid function.
When your thyroid hormones (called T4 and T3) are too low, your pituitary gland secretes TSH. The TSH then tells the thyroid gland to secrete more T4 and T3.
Thus a high TSH level suggests low thyroid, and a low TSH level suggests high thyroid.
Your doctor often tests the T4 and T3 levels too, but often not. If the TSH is in the normal range, your doctor may assume your thyroid levels are fine and refuse to do more testing.
The normal ranges are controversial. The usual range is said to be about 0.4 to 5 microunits per milliliter. But some people say the cutoff on the high end should be lower, about 2.5. And graphs in endocrinology books show that the average TSH level in people considered to have healthy thyroid control is only 1.1, with very few in the upper ranges.
The new research shows that metformin therapy suppresses TSH levels. Two studies showed that it did this without affecting T4 and T3 levels. A third found that free T4 levels increased as TSH went down.
Most of the T4 and T3 in your blood is bound to proteins. The free (unbound) levels of the hormones are the active hormones, and that's what the free T4 (fT4) and free T3 (fT3) measure.
No one yet understands the mechanism of the TSH reduction by metformin. It's especially puzzling because it doesn't seem to be linked with the thyroid hormone level. And the metformin has no effect on TSH in people who have no thyroid problems.
But what it does mean for you is that if you're on metformin you should be aware of this link. Let's say you're on thyroid medication and then you start taking metformin. Your TSH goes down, and your doctor may worry that your thyroid is now too high and might reduce your dose.
But what if it's just a result of the metformin? Then you'd end up with a thyroid level that was too low.
So if you're on metformin and your TSH test doesn't seem to agree with how you're feeling, discuss this interaction with your doctor and have your T4 and T3 levels tested as well as the TSH. It could be that the lower TSH is caused by the metformin and notw higher thyroid levels.
Does this mean that metformin could interact with other lab tests? It's possible. The metformin-TSH interaction was only noticed in 2006, more than 10 years after the drug first became available.
Does this mean that other drugs could interact with the TSH test? It's possible.
We need to be vigilant about all the drugs we take, and if something seems wrong, we need to try to figure it out. Sometimes the published science reports can't tell us.
Trust your body. You know it better than anyone else. And don't let some doctor tell you that your symptoms are all in your head because there's no evidence for what you're saying. Maybe you're right and the current literature is wrong.
But most drugs also have minor effects. Sometimes your doctor is aware of these but doesn't tell you because the incidence of these effects is low and the doctor doesn't want to worry you. This is often true of the muscle weakness and memory problems that statins can cause.
Sometimes even your doctor isn't aware of the minor side effects.
Sometimes no one has yet discovered some side effects. This can be because you have to be on a drug for a certain amount of time before these side effects show up. It can be because no one has noticed the link between a particular drug and some side effect.
Or it can be because drugs can interact with other drugs, and when you're taking a lot of different drugs -- say a diabetes drug, a blood pressure drug, a lipid-lowering drug, an anti-reflux drug, an antidepressant, a beta blocker, an antihistamine, an osteoporosis drug, and an asthma drug -- and you complain of fatigue, it's not immediately clear which one of these drugs or which combination is causing that problem.
One relatively unknown drug-hormone interaction was first reported in 2006.
It seems that metformin suppresses thyroid-stimulating hormone (TSH; also called thyrotropin), the hormone that is generally tested to ascertain your thyroid function.
When your thyroid hormones (called T4 and T3) are too low, your pituitary gland secretes TSH. The TSH then tells the thyroid gland to secrete more T4 and T3.
Thus a high TSH level suggests low thyroid, and a low TSH level suggests high thyroid.
Your doctor often tests the T4 and T3 levels too, but often not. If the TSH is in the normal range, your doctor may assume your thyroid levels are fine and refuse to do more testing.
The normal ranges are controversial. The usual range is said to be about 0.4 to 5 microunits per milliliter. But some people say the cutoff on the high end should be lower, about 2.5. And graphs in endocrinology books show that the average TSH level in people considered to have healthy thyroid control is only 1.1, with very few in the upper ranges.
The new research shows that metformin therapy suppresses TSH levels. Two studies showed that it did this without affecting T4 and T3 levels. A third found that free T4 levels increased as TSH went down.
Most of the T4 and T3 in your blood is bound to proteins. The free (unbound) levels of the hormones are the active hormones, and that's what the free T4 (fT4) and free T3 (fT3) measure.
No one yet understands the mechanism of the TSH reduction by metformin. It's especially puzzling because it doesn't seem to be linked with the thyroid hormone level. And the metformin has no effect on TSH in people who have no thyroid problems.
But what it does mean for you is that if you're on metformin you should be aware of this link. Let's say you're on thyroid medication and then you start taking metformin. Your TSH goes down, and your doctor may worry that your thyroid is now too high and might reduce your dose.
But what if it's just a result of the metformin? Then you'd end up with a thyroid level that was too low.
So if you're on metformin and your TSH test doesn't seem to agree with how you're feeling, discuss this interaction with your doctor and have your T4 and T3 levels tested as well as the TSH. It could be that the lower TSH is caused by the metformin and notw higher thyroid levels.
Does this mean that metformin could interact with other lab tests? It's possible. The metformin-TSH interaction was only noticed in 2006, more than 10 years after the drug first became available.
Does this mean that other drugs could interact with the TSH test? It's possible.
We need to be vigilant about all the drugs we take, and if something seems wrong, we need to try to figure it out. Sometimes the published science reports can't tell us.
Trust your body. You know it better than anyone else. And don't let some doctor tell you that your symptoms are all in your head because there's no evidence for what you're saying. Maybe you're right and the current literature is wrong.
Saturday, February 26, 2011
A1c and Iron
Sigh. It's happened again. I set up an experiment and then something beyond my control made the results meaningless.
That often seems to happen. I'm doing a test that requires measuring blood glucose (BG) at a specific time, and just as I'm about to do so, the phone rings, and it's an important call I can't ignore. Or I want to compare BG control on two consecutive days, do a whole slew of tests on day 1 and then on day 2 come down with the flu, which makes any BG measurements useless.
I've always had A1c levels that seem to be higher than what I'd expect on the basis of my BG readings. Because of this, I even spent more than $500 on continuous glucose monitor sensors (a kind friend gave me the meter) to make sure I wasn't going high at some unexpected time when I wasn't measuring.
I wasn't. The results were what I'd expect. Fastings were 70 to 90, and going over 130 was rare. But my A1c was always around 6, which calculates to an average BG of 130, which means I'd be going way over 130 a lot of the time to balance the lower fastings.
I tested my two different meters (Ultra and Freestyle), and they agreed quite well with each other and with my hospital lab.
I know there's some individual variation in red blood cell (RBC) lifetimes, and an increased lifetime could raise A1c, because the longer a RBC has been in your body, the more likely it is to be glycated.
So when I read, as reported here, that low iron can make your A1c higher than it should be, I decided to try taking iron-containing multivitamins a couple of weeks before my next A1c. I usually use iron-free vitamins, because iron can contribute to cardiac problems, and people with diabetes are at increased risk of that.
The theory is that if you're iron-deficient, you won't produce reticulocytes, or new RBCs, as fast as you should, so your body will let the older, more-glycated RBCs live longer. If you take iron, you'll produce more new, glycation-free RBCs, so your A1c will be lower.
I did the test, and the results seemed to confirm the theory. My A1c dropped to 5.3, which is about what I'd expect.
But then I read the fine print. Apparently the A1c machine at the local hospital had broken, so they sent all the samples to the Mayo Clinic. So was the lower A1c because of the iron? Or was it because Mayo was using a different type of test that gave different results. I didn't know.
So I did the test again. Two weeks before I gave blood, I switched to the iron-containing vitamins. This time the A1c, done at my local hospital, was 5.4.
I called the hospital lab to make sure they were still using the high-performance liquid chromatography method they'd used before. This is supposed to be the best method because it's the one used in the famous DCCT trials.
They weren't. They'd changed methods to an immunoassay. So was the result this time because of the iron? Or was it because of a different method?
I don't know. I'll have to do it all over again. I don't get labwork every three months, more like six, because it's a pain and the results are usually pretty much the same. So maybe by the time I get this resolved I'll be living in a nursing home. Who knows.
It's just one of the many frustrations of having diabetes.
On the other hand, being able to test things is one of the fun things about having diabetes. With so many other diseases, we have to let the medical people do all kinds of arcane tests and procedures. I don't know of a home MRI machine, or a home "put in your own coronary stent" kit, for example.
If I ever resolve this issue, I'll post here about it.
That often seems to happen. I'm doing a test that requires measuring blood glucose (BG) at a specific time, and just as I'm about to do so, the phone rings, and it's an important call I can't ignore. Or I want to compare BG control on two consecutive days, do a whole slew of tests on day 1 and then on day 2 come down with the flu, which makes any BG measurements useless.
I've always had A1c levels that seem to be higher than what I'd expect on the basis of my BG readings. Because of this, I even spent more than $500 on continuous glucose monitor sensors (a kind friend gave me the meter) to make sure I wasn't going high at some unexpected time when I wasn't measuring.
I wasn't. The results were what I'd expect. Fastings were 70 to 90, and going over 130 was rare. But my A1c was always around 6, which calculates to an average BG of 130, which means I'd be going way over 130 a lot of the time to balance the lower fastings.
I tested my two different meters (Ultra and Freestyle), and they agreed quite well with each other and with my hospital lab.
I know there's some individual variation in red blood cell (RBC) lifetimes, and an increased lifetime could raise A1c, because the longer a RBC has been in your body, the more likely it is to be glycated.
So when I read, as reported here, that low iron can make your A1c higher than it should be, I decided to try taking iron-containing multivitamins a couple of weeks before my next A1c. I usually use iron-free vitamins, because iron can contribute to cardiac problems, and people with diabetes are at increased risk of that.
The theory is that if you're iron-deficient, you won't produce reticulocytes, or new RBCs, as fast as you should, so your body will let the older, more-glycated RBCs live longer. If you take iron, you'll produce more new, glycation-free RBCs, so your A1c will be lower.
I did the test, and the results seemed to confirm the theory. My A1c dropped to 5.3, which is about what I'd expect.
But then I read the fine print. Apparently the A1c machine at the local hospital had broken, so they sent all the samples to the Mayo Clinic. So was the lower A1c because of the iron? Or was it because Mayo was using a different type of test that gave different results. I didn't know.
So I did the test again. Two weeks before I gave blood, I switched to the iron-containing vitamins. This time the A1c, done at my local hospital, was 5.4.
I called the hospital lab to make sure they were still using the high-performance liquid chromatography method they'd used before. This is supposed to be the best method because it's the one used in the famous DCCT trials.
They weren't. They'd changed methods to an immunoassay. So was the result this time because of the iron? Or was it because of a different method?
I don't know. I'll have to do it all over again. I don't get labwork every three months, more like six, because it's a pain and the results are usually pretty much the same. So maybe by the time I get this resolved I'll be living in a nursing home. Who knows.
It's just one of the many frustrations of having diabetes.
On the other hand, being able to test things is one of the fun things about having diabetes. With so many other diseases, we have to let the medical people do all kinds of arcane tests and procedures. I don't know of a home MRI machine, or a home "put in your own coronary stent" kit, for example.
If I ever resolve this issue, I'll post here about it.
Wednesday, February 16, 2011
Escaping Old Ideas
I wonder if we could supply these to all (well most) nutritionists.
The article cites the economist John Maynard Keynes, who said, "“The difficulty lies, not in the new ideas, but in escaping from the old ones, which ramify . . . into every corner of our mind.”
And this is just what is true today. Many nutritionists just can't escape the idea that dietary fat is the cause of all our problems.
The article cites the economist John Maynard Keynes, who said, "“The difficulty lies, not in the new ideas, but in escaping from the old ones, which ramify . . . into every corner of our mind.”
And this is just what is true today. Many nutritionists just can't escape the idea that dietary fat is the cause of all our problems.
Wednesday, February 2, 2011
Diagnosing Diabetes
Diagnosing diabetes is a lot like trying to sculpt warm Jell-O.
At the extremes, it's pretty easy to decide if someone has diabetes or not. For example, when I was diagnosed, I was having symptoms (constant thirst and urinating a lot), my random blood glucose (BG) level was over 300 mg/dL (to convert to mmol/L divide by 18) hours after my last meal, and my next-day fasting was 269. The glucose level in my urine was so high that the hospital recalibrated its machine to make sure the result was correct.
Clearly, I was diabetic.
At the other extreme, someone with a fasting BG level of 65 who goes up to 80 after drinking a huge glucose drink and has a hemoglobin A1c level of 4.2 obviously doesn't have diabetes.
In between the extremes, there are a lot of patterns that could or could not be considered to be diabetes.
The official guidelines for diagnosing diabetes are that you should be considered diabetic if
Your fasting BG level is 126 or greater on at least two occasions (less than 100 is considered normal) or
Your BG level is 200 or greater 2 hours after starting an oral glucose tolerance test (OGTT) with 75 grams of glucose (less than 140 is considered normal) or
A random BG level is greater than 200 and you're having symptoms.
Recently, some official diabetes groups are suggesting using the hemoglobin A1c test for diagnosis, with any result of 6.5 or greater confirmed by a second test considered diagnostic.
Some years ago, the diagnostic fasting levels were even higher, as some diabetes experts felt that a diagnosis of diabetes would cause harm because of the stigma against "diabetics" and because insurance companies would refuse to insure them. More recently, people have realized that diabetic complications occur even at BG levels below these diagnostic values, and the earlier people are diagnosed, the greater their chance of preventing complications.
However, regardless of where the cutoff points are set, none of these criteria are perfect. Anyone with diabetes knows that fasting BG levels can vary from day to day, and even testing fasting levels on two different days doesn't ensure that they represent a true value.
The same may be true of the OGTT. We all know that we can eat exactly the same thing on two different days at exactly the same time and get exactly the same amount of exercise, yet one day our postprandial BG levels will be higher than the other. Furthermore, because this test is time consuming, very few physicians use it for diagnosis.
And the A1c test is affected by a lot of things, including red blood cell lifetime, which can be genetic and is also affected by various hemolytic anemias, spleen damage, or major blood loss; and abnormal hemoglobin types. Furthermore, although most labs now claim to have standardized their A1c tests, in practice there's still variation from one lab to the other.
Hence one person might have normal BG levels all day long but have an abnormal A1c result, and another person might have elevated BG levels yet have a low A1c. I know someone who had fasting BG levels above 130 but an A1c in the 4s so her doctor refused to diagnose her until things got much worse.
To further complicate things, there are various different patterns of BG abnormalities. Some people may have normal fasting BG levels but go high after meals (this was formerly called impaired glucose tolerance). Others may have high fasting levels but not go very high after meals (this was formerly called impaired fasting glucose).
Some years ago official diabetes groups decided to merge both groups into a new category called prediabetes even though some people think their risks and outcomes differ.
These aren't the only patterns one can get. Some people may have a little impaired glucose tolerance and a little impaired fasting glucose.
Some may have normal fasting BG levels, go very high after meals, but come down again quickly, so they wouldn't satisfy the official requirement for high BG levels at 2 hours after an OGTT. This and this show the variation in BG levels after a high-carb breakfast in people considered nondiabetic.
But no one knows if such wide variations in BG levels might cause complications. Some people think wide variation is worse than sustained high BG levels. Yet the people shown in the cited graphs are considered nondiabetic. Their A1c levels are in normal ranges.
Other people may have temporary increases in BG levels because of some stress, such as surgery or emotional stress, and then revert to normal BG levels.
Diet can also affect your BG levels. Someone following a low-carb diet for weight loss might have normal fasting and postprandial BG levels and normal A1c levels as long as he or she followed the LC diet. An OGTT would show the underlying diabetic defect, but most doctors don't use that test these days, especially in someone with normal fasting BG levels. And these people would be grouped with the nondiabetics if they were included in any clinical trials.
Just fasting can affect your BG levels. Fasting is the ultimate low-carb diet, and after a long fast you'll test diabetic even if you're not on a standard carbohydrate-containing diet because when you don't need them, your body stops producing carbohydrate-processing enzymes. This is called starvation diabetes.
If you've been on a very low carb diet and you're given an OGTT, you'll probably test diabetic even if you're not, for the same reason.
Some people may have abnormal BG levels because of very high insulin resistance, which can sometimes be reversed with weight loss and exercise. They also have defective beta cells that aren't able to cope with the excess demand. But if they can reduce the insulin resistance, their beta cells can cope. Many overweight couch potatoes don't have diabetes because their beta cell mass simply expands to cover the increased need.
The same situation occurs during pregnancy. In most people, the beta cell mass expands during pregnancy to cover the increased need in late pregnancy. Some people have beta cells that are unable to do this, so they are diagnosed with gestational diabetes. After the baby is born and the demand is lowered, their BG levels revert to normal.
Others may have abnormal BG levels with a lot less insulin resistance and but even wimpier beta cells. And of course there can be all kinds of combinations of these two factors.
If diagnosing diabetes is difficult, diagnosing prediabetes is even more difficult because someone with full-blown diabetes like I had when I was diagnosed is unlikely to revert to normal no matter what they do. At that point we've lost so many beta cells that unless we figure out how to get them to regenerate, we're always going to have to be careful about our diet.
But in the prediabetes range, the probability of reverting to normal BG control is greater, especially if you're very overweight and hence are still producing a lot of insulin when you're diagnosed. Thus a diagnosis may be more vague. One month you'd qualify as prediabetic and then you'd lose some weight and you wouldn't. Then you'd regain the weight and you would.
Because of all this diagnostic vagueness, arbitrary cutoff points, and changing standards, any studies that purport to show that "diabetics" are at increased risk or decreased risk or should be taking X drug or avoiding Y practice are somewhat questionable. The older the study, the less relevant it's likely to be. In the old days they didn't even differentiate between type 1 (autoimmune; insulin requiring) and type 2.
I personally don't put a lot of trust into studies that rely on complex statistics to show some effect. You can study 10,000 patients with type 2 and show that there's a slightly better, statistically significant benefit from some treatment (usually a drug). If you're a physician interested in prescribing that drug, that suggests that the odds of success are greater if you prescribe it. (Not taking into account the biases caused by the fact that most drug studies are sponsored by drug companies that know how to manipulate data.)
But it says nothing about whether the drug will help or harm any individual patient. And as patients, that's what we want to know.
Does that mean we should simply ignore all these massive trials? I don't think so. They do tell us something; they suggest that some treatment could help or harm.
But if your doctor tells you that all "diabetics" should be taking some drug or avoiding some drug or following some other regimen and you don't think it sounds "right for you" as the TV ads are so enamored of saying, then research it carefully.
Find out if the patients in the study sound similar to you. If they were mostly elderly white men on low-fat diets and you're a young Asian woman on a low-carb diet, you might respond differently than those patients.
Diabetes comes in many flavors. Diagnosis can be arbitrary. Statements like "All diabetics should be on aspirin" are unlikely to be true, even if supported by references to some big clinical trial.
At the extremes, it's pretty easy to decide if someone has diabetes or not. For example, when I was diagnosed, I was having symptoms (constant thirst and urinating a lot), my random blood glucose (BG) level was over 300 mg/dL (to convert to mmol/L divide by 18) hours after my last meal, and my next-day fasting was 269. The glucose level in my urine was so high that the hospital recalibrated its machine to make sure the result was correct.
Clearly, I was diabetic.
At the other extreme, someone with a fasting BG level of 65 who goes up to 80 after drinking a huge glucose drink and has a hemoglobin A1c level of 4.2 obviously doesn't have diabetes.
In between the extremes, there are a lot of patterns that could or could not be considered to be diabetes.
The official guidelines for diagnosing diabetes are that you should be considered diabetic if
Your fasting BG level is 126 or greater on at least two occasions (less than 100 is considered normal) or
Your BG level is 200 or greater 2 hours after starting an oral glucose tolerance test (OGTT) with 75 grams of glucose (less than 140 is considered normal) or
A random BG level is greater than 200 and you're having symptoms.
Recently, some official diabetes groups are suggesting using the hemoglobin A1c test for diagnosis, with any result of 6.5 or greater confirmed by a second test considered diagnostic.
Some years ago, the diagnostic fasting levels were even higher, as some diabetes experts felt that a diagnosis of diabetes would cause harm because of the stigma against "diabetics" and because insurance companies would refuse to insure them. More recently, people have realized that diabetic complications occur even at BG levels below these diagnostic values, and the earlier people are diagnosed, the greater their chance of preventing complications.
However, regardless of where the cutoff points are set, none of these criteria are perfect. Anyone with diabetes knows that fasting BG levels can vary from day to day, and even testing fasting levels on two different days doesn't ensure that they represent a true value.
The same may be true of the OGTT. We all know that we can eat exactly the same thing on two different days at exactly the same time and get exactly the same amount of exercise, yet one day our postprandial BG levels will be higher than the other. Furthermore, because this test is time consuming, very few physicians use it for diagnosis.
And the A1c test is affected by a lot of things, including red blood cell lifetime, which can be genetic and is also affected by various hemolytic anemias, spleen damage, or major blood loss; and abnormal hemoglobin types. Furthermore, although most labs now claim to have standardized their A1c tests, in practice there's still variation from one lab to the other.
Hence one person might have normal BG levels all day long but have an abnormal A1c result, and another person might have elevated BG levels yet have a low A1c. I know someone who had fasting BG levels above 130 but an A1c in the 4s so her doctor refused to diagnose her until things got much worse.
To further complicate things, there are various different patterns of BG abnormalities. Some people may have normal fasting BG levels but go high after meals (this was formerly called impaired glucose tolerance). Others may have high fasting levels but not go very high after meals (this was formerly called impaired fasting glucose).
Some years ago official diabetes groups decided to merge both groups into a new category called prediabetes even though some people think their risks and outcomes differ.
These aren't the only patterns one can get. Some people may have a little impaired glucose tolerance and a little impaired fasting glucose.
Some may have normal fasting BG levels, go very high after meals, but come down again quickly, so they wouldn't satisfy the official requirement for high BG levels at 2 hours after an OGTT. This and this show the variation in BG levels after a high-carb breakfast in people considered nondiabetic.
But no one knows if such wide variations in BG levels might cause complications. Some people think wide variation is worse than sustained high BG levels. Yet the people shown in the cited graphs are considered nondiabetic. Their A1c levels are in normal ranges.
Other people may have temporary increases in BG levels because of some stress, such as surgery or emotional stress, and then revert to normal BG levels.
Diet can also affect your BG levels. Someone following a low-carb diet for weight loss might have normal fasting and postprandial BG levels and normal A1c levels as long as he or she followed the LC diet. An OGTT would show the underlying diabetic defect, but most doctors don't use that test these days, especially in someone with normal fasting BG levels. And these people would be grouped with the nondiabetics if they were included in any clinical trials.
Just fasting can affect your BG levels. Fasting is the ultimate low-carb diet, and after a long fast you'll test diabetic even if you're not on a standard carbohydrate-containing diet because when you don't need them, your body stops producing carbohydrate-processing enzymes. This is called starvation diabetes.
If you've been on a very low carb diet and you're given an OGTT, you'll probably test diabetic even if you're not, for the same reason.
Some people may have abnormal BG levels because of very high insulin resistance, which can sometimes be reversed with weight loss and exercise. They also have defective beta cells that aren't able to cope with the excess demand. But if they can reduce the insulin resistance, their beta cells can cope. Many overweight couch potatoes don't have diabetes because their beta cell mass simply expands to cover the increased need.
The same situation occurs during pregnancy. In most people, the beta cell mass expands during pregnancy to cover the increased need in late pregnancy. Some people have beta cells that are unable to do this, so they are diagnosed with gestational diabetes. After the baby is born and the demand is lowered, their BG levels revert to normal.
Others may have abnormal BG levels with a lot less insulin resistance and but even wimpier beta cells. And of course there can be all kinds of combinations of these two factors.
If diagnosing diabetes is difficult, diagnosing prediabetes is even more difficult because someone with full-blown diabetes like I had when I was diagnosed is unlikely to revert to normal no matter what they do. At that point we've lost so many beta cells that unless we figure out how to get them to regenerate, we're always going to have to be careful about our diet.
But in the prediabetes range, the probability of reverting to normal BG control is greater, especially if you're very overweight and hence are still producing a lot of insulin when you're diagnosed. Thus a diagnosis may be more vague. One month you'd qualify as prediabetic and then you'd lose some weight and you wouldn't. Then you'd regain the weight and you would.
Because of all this diagnostic vagueness, arbitrary cutoff points, and changing standards, any studies that purport to show that "diabetics" are at increased risk or decreased risk or should be taking X drug or avoiding Y practice are somewhat questionable. The older the study, the less relevant it's likely to be. In the old days they didn't even differentiate between type 1 (autoimmune; insulin requiring) and type 2.
I personally don't put a lot of trust into studies that rely on complex statistics to show some effect. You can study 10,000 patients with type 2 and show that there's a slightly better, statistically significant benefit from some treatment (usually a drug). If you're a physician interested in prescribing that drug, that suggests that the odds of success are greater if you prescribe it. (Not taking into account the biases caused by the fact that most drug studies are sponsored by drug companies that know how to manipulate data.)
But it says nothing about whether the drug will help or harm any individual patient. And as patients, that's what we want to know.
Does that mean we should simply ignore all these massive trials? I don't think so. They do tell us something; they suggest that some treatment could help or harm.
But if your doctor tells you that all "diabetics" should be taking some drug or avoiding some drug or following some other regimen and you don't think it sounds "right for you" as the TV ads are so enamored of saying, then research it carefully.
Find out if the patients in the study sound similar to you. If they were mostly elderly white men on low-fat diets and you're a young Asian woman on a low-carb diet, you might respond differently than those patients.
Diabetes comes in many flavors. Diagnosis can be arbitrary. Statements like "All diabetics should be on aspirin" are unlikely to be true, even if supported by references to some big clinical trial.
Sunday, January 23, 2011
Cholesterol, CVD Risk, and Type 2
Deciding whether or not to use a statin to reduce cholesterol levels can be confusing.
On one hand is the medical profession, which in general thinks statins are good things and that LDL cholesterol levels above normal ranges should be treated with statins. Recently, some have been recommending statins even for people with normal cholesterol levels but elevated levels of C-reactive protein (CRP), an indication of inflammation.
In some populations, lowering cholesterol with statins has been shown to result in lower rates of cardiovascular "events" and deaths. But some people think this isn't because of lower cholesterol levels. They suggest that the statins have some other effect as well and the lower cholesterol levels are simply a "side effect" of the drug.
At the other extreme are people who think statins are poisons. Some think no one should take a statin. Others agree they're warranted in specific populations, for example middle-aged men with previous heart attacks, but they say there's no evidence that statins help women or elderly men.
A recent Cochrane Systematic Review concluded that risks of statins are greater than benefits for those at low risk of heart disease. However, when you have diabetes, you're not considered to be at low risk.
An earlier study concluded that statins don't benefit women who have not had a heart attack and in fact may increase cardiovascular risk in this population. They say CRP levels are better predictors of heart attacks in women.
Most people agree that statins do have side effects, most commonly muscle weakness or pain, which can cause permanent damage if it's serious (rhabdomyolysis). In mild cases, taking coenzyme Q10 can sometimes help with the muscle weakness. Tendons can also be weakened by statin treatment (and treatment with other drugs like niacin that reduce cholesterol).
Beatrice Golomb of the University of California at San Diego has been studying side effects of statins and has published a comprehensive review on the topic. She says the two most common side effects are muscle weakness or pain and memory impairment.
She agrees that statin benefits outweigh risks in middle-aged men with high cholesterol and existing heart disease who tolerate the drugs, and that statins probably benefit middle-aged men with high cholesterol and "significant other risk factors for heart disease."
But she says that although those without significant risk factors for heart disease do have fewer cardiovascular deaths, there is not even a trend for lower overall death rates. In other words, fewer heart attacks and strokes but more deaths from other diseases.
Golomb says that statin benefits are not clear in middle-aged men who have heart disease or significant risks but who get side effects from statins. There is some evidence that the benefits of statins don't occur in people who get side effects.
Golomb says there is currently no evidence that statins benefit women or men over 70. They do reduce heart attacks, she says, but not overall mortality.
One problem when reading about all these studies is that different studies use different patient populations and different end points, but the news media tend to report the results without emphasizing that point.
So a drug-company-sponsored trial might be headlined as "Drug X Reduces Heart Attacks by 40%" when in fact the study showed that the drug reduced heart attacks in middle-aged men who had already had several heart attacks, had high blood pressure and high blood sugar, and smoked, and the deaths from some other disease increased with the drug. But what the public, and some physicians, will remember is "Drug X prevents heart disease."
And the confusing thing for those of us with diabetes is knowing whether or not simply having diabetes constitutes a "significant other risk factor."
Most people consider simply having diabetes to give you the same risk of cardiovascular events as people who have already had a heart attack. Is that true?
A recent Spanish research group says no, at least in the Spanish patient population they studied: 4410 patients aged 30 to 74 years, 2260 with type 2 diabetes and 2150 who had already had an acute myocardial infarction but no diabetes.
They found that the 10-year hazard ratios for the type 2 patients were significantly lower than those of the MI patients.
That's encouraging. So should we stop worrying about heart disease?
Definitely NO!
For one thing, other studies have had conflicting results. Some show that people with diabetes have heart disease death risks similar to those of nondiabetics who have had heart attacks; others show the opposite. Another study showed that prior heart attacks resulted in higher risks than diabetes among men 45 to 54 years old, but in older men, the risk was reversed.
As noted by the Spanish researchers, "Part of the discrepancy may stem from differences in the duration of diabetes, type of treatment, and baseline glucose control of diabetic patients included in the studies."
The cited studies also noted differences according to the age and sex of the patients. Furthermore, the results may depend on how you define diabetes.
Someone with type 2 diabetes who was diagnosed 5 years ago, controls blood glucose levels well, eats healthy foods, gets a lot of exercise, doesn't smoke, and makes sure to keep blood pressure and lipid levels in good ranges would be different from someone who is unfortunately probably more typical: a patient who just takes a pill or two, doesn't measure blood glucose levels, continues to smoke and spend most of the evening watching TV, eats mostly fast food or convenience foods, and has high blood pressure.
And the recent Spanish study was comparing diabetic patients with patients who had already had an acute MI, not with healthy people.
When we have type 2 diabetes, we're still at increased risk of heart disease, and we should do whatever we can to reduce that risk: Keep blood glucose levels down, monitor lipid levels and treat if necessary, monitor blood pressure and treat that if necessary, get regular exercise, and eat a healthy diet, although definitions of "healthy diet" of course depend on who you're talking to.
But all these studies illustrate the need to be vigilant when reading a popular press article stating that some study has shown something or other. First, see if you can read the journal article that the popular press story refers to. Even if you can't see the full text, you can usually see the abstract for free.
Find out what populations were studied, how various parameters were measured, and how the researchers define diabetes.
This takes a lot of time, and a firm grasp of statistics helps. So it can be frustrating when you're trying to earn a living or spend time on other projects and don't have time to pour through confusing research reports all day.
Sometimes the authors of drug-company-sponsored studies have used statistics to spin the results to make their drugs look more favorable. You sometimes need to comb through the methods and the statistics to see how the results have been biased. This takes a lot of time.
When you can't track all this down, don't ignore the health news, but take the health news you hear on TV or read in your local paper with a grain of salt. If your LDL cholesterol level is high, you might want to try a statin. Some people can take them without getting side effects. But be vigilant. If you get muscle weakness, try some coenzyme Q10, which Golomb says helps about 70% who have that problem. Some people recommend taking the coenzyme Q10 even if you don't have muscle problems.
But if the muscle pain or weakness persists, talk with y0ur doctor about other alternatives, like niacin. Muscle pain that progresses to rhabdomyolysis is serious.
On one hand is the medical profession, which in general thinks statins are good things and that LDL cholesterol levels above normal ranges should be treated with statins. Recently, some have been recommending statins even for people with normal cholesterol levels but elevated levels of C-reactive protein (CRP), an indication of inflammation.
In some populations, lowering cholesterol with statins has been shown to result in lower rates of cardiovascular "events" and deaths. But some people think this isn't because of lower cholesterol levels. They suggest that the statins have some other effect as well and the lower cholesterol levels are simply a "side effect" of the drug.
At the other extreme are people who think statins are poisons. Some think no one should take a statin. Others agree they're warranted in specific populations, for example middle-aged men with previous heart attacks, but they say there's no evidence that statins help women or elderly men.
A recent Cochrane Systematic Review concluded that risks of statins are greater than benefits for those at low risk of heart disease. However, when you have diabetes, you're not considered to be at low risk.
An earlier study concluded that statins don't benefit women who have not had a heart attack and in fact may increase cardiovascular risk in this population. They say CRP levels are better predictors of heart attacks in women.
Most people agree that statins do have side effects, most commonly muscle weakness or pain, which can cause permanent damage if it's serious (rhabdomyolysis). In mild cases, taking coenzyme Q10 can sometimes help with the muscle weakness. Tendons can also be weakened by statin treatment (and treatment with other drugs like niacin that reduce cholesterol).
Beatrice Golomb of the University of California at San Diego has been studying side effects of statins and has published a comprehensive review on the topic. She says the two most common side effects are muscle weakness or pain and memory impairment.
She agrees that statin benefits outweigh risks in middle-aged men with high cholesterol and existing heart disease who tolerate the drugs, and that statins probably benefit middle-aged men with high cholesterol and "significant other risk factors for heart disease."
But she says that although those without significant risk factors for heart disease do have fewer cardiovascular deaths, there is not even a trend for lower overall death rates. In other words, fewer heart attacks and strokes but more deaths from other diseases.
Golomb says that statin benefits are not clear in middle-aged men who have heart disease or significant risks but who get side effects from statins. There is some evidence that the benefits of statins don't occur in people who get side effects.
Golomb says there is currently no evidence that statins benefit women or men over 70. They do reduce heart attacks, she says, but not overall mortality.
One problem when reading about all these studies is that different studies use different patient populations and different end points, but the news media tend to report the results without emphasizing that point.
So a drug-company-sponsored trial might be headlined as "Drug X Reduces Heart Attacks by 40%" when in fact the study showed that the drug reduced heart attacks in middle-aged men who had already had several heart attacks, had high blood pressure and high blood sugar, and smoked, and the deaths from some other disease increased with the drug. But what the public, and some physicians, will remember is "Drug X prevents heart disease."
And the confusing thing for those of us with diabetes is knowing whether or not simply having diabetes constitutes a "significant other risk factor."
Most people consider simply having diabetes to give you the same risk of cardiovascular events as people who have already had a heart attack. Is that true?
A recent Spanish research group says no, at least in the Spanish patient population they studied: 4410 patients aged 30 to 74 years, 2260 with type 2 diabetes and 2150 who had already had an acute myocardial infarction but no diabetes.
They found that the 10-year hazard ratios for the type 2 patients were significantly lower than those of the MI patients.
That's encouraging. So should we stop worrying about heart disease?
Definitely NO!
For one thing, other studies have had conflicting results. Some show that people with diabetes have heart disease death risks similar to those of nondiabetics who have had heart attacks; others show the opposite. Another study showed that prior heart attacks resulted in higher risks than diabetes among men 45 to 54 years old, but in older men, the risk was reversed.
As noted by the Spanish researchers, "Part of the discrepancy may stem from differences in the duration of diabetes, type of treatment, and baseline glucose control of diabetic patients included in the studies."
The cited studies also noted differences according to the age and sex of the patients. Furthermore, the results may depend on how you define diabetes.
Someone with type 2 diabetes who was diagnosed 5 years ago, controls blood glucose levels well, eats healthy foods, gets a lot of exercise, doesn't smoke, and makes sure to keep blood pressure and lipid levels in good ranges would be different from someone who is unfortunately probably more typical: a patient who just takes a pill or two, doesn't measure blood glucose levels, continues to smoke and spend most of the evening watching TV, eats mostly fast food or convenience foods, and has high blood pressure.
And the recent Spanish study was comparing diabetic patients with patients who had already had an acute MI, not with healthy people.
When we have type 2 diabetes, we're still at increased risk of heart disease, and we should do whatever we can to reduce that risk: Keep blood glucose levels down, monitor lipid levels and treat if necessary, monitor blood pressure and treat that if necessary, get regular exercise, and eat a healthy diet, although definitions of "healthy diet" of course depend on who you're talking to.
But all these studies illustrate the need to be vigilant when reading a popular press article stating that some study has shown something or other. First, see if you can read the journal article that the popular press story refers to. Even if you can't see the full text, you can usually see the abstract for free.
Find out what populations were studied, how various parameters were measured, and how the researchers define diabetes.
This takes a lot of time, and a firm grasp of statistics helps. So it can be frustrating when you're trying to earn a living or spend time on other projects and don't have time to pour through confusing research reports all day.
Sometimes the authors of drug-company-sponsored studies have used statistics to spin the results to make their drugs look more favorable. You sometimes need to comb through the methods and the statistics to see how the results have been biased. This takes a lot of time.
When you can't track all this down, don't ignore the health news, but take the health news you hear on TV or read in your local paper with a grain of salt. If your LDL cholesterol level is high, you might want to try a statin. Some people can take them without getting side effects. But be vigilant. If you get muscle weakness, try some coenzyme Q10, which Golomb says helps about 70% who have that problem. Some people recommend taking the coenzyme Q10 even if you don't have muscle problems.
But if the muscle pain or weakness persists, talk with y0ur doctor about other alternatives, like niacin. Muscle pain that progresses to rhabdomyolysis is serious.
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