Fifth Thursday Update

October 29, 2015

 


Is "burst exercise" better?

Canadian researchers conducted an interesting study comparing the health benefits of "burst exercise" versus sustained exercise for Type 2 diabetes patients.

Sustained exercise, for the purposes of the Canadian study, means the conventionally recommended daily workout: one that lasts 30 minutes and is only of moderate intensity (with heart rate at 60% of the age-determined maximum heart rate). Burst exercise, on the other hand, means three separate workouts which only last 10 minutes each, but are at a high level of intensity (85% of the age-determined maximum heart rate).

Before I say anything else, I should point out that there is a great deal of uncertainty surrounding this concept of age-determined maximum heart rate. The most commonly quoted formula for this is 220 minus your age. I'm 58, so my maximum rate should be 220 - 58 = 162 beats per minute, according to that formula. But that formula was literally worked out on the back of an envelope, by two cardiologists while flying to a conference. They have since expressed regret that their casual estimate is so routinely quoted as if it were a law of physics. Other cardiologists have concluded that the formula gives too low a rate for older exercisers. In 2001 an updated formula was published: 208 - (age times .7). For me, that increases the rate to 167. I'm not sure which formula the Canadian exercise researchers were using, however.

Anyway, the results of the study showed that burst exercise had a number of important health advantages. The diabetes patients doing burst exercise had significantly greater reduction in their hemoglobin A1c results ("as good as adding a drug", said one of the researchers). Burst exercisers also experienced significantly greater improvement in their lipid profiles (triglycerides reduced more, "bad" cholesterol reduced more, "good" cholesterol boosted more). As if that were not enough, the burst exercisers also showed greater improvement in Body Mass Index and cardiopulmonary fitness.

The improvement in hemoglobin A1c was a little surprising: the body often raises blood sugar in response to an intense burst of exercise (because the liver releases stored sugar for the overtaxed muscles to use), and this gives many diabetes patients the false impression that hard exercise does them more harm than good. Apparently, testing your glucose right after a burst of exercise is misleading: any glucose spike caused by the workout is brief, and is more than compensated for by a reduction in blood sugar during a longer period after the workout is over.

So, am I sold on this? Am I going to be dropping the five-mile runs in favor of a trio of ten-minute hard workouts?

Probably not, at least for now. I need to know more about this.

The study had some serious limitations. It involved a fairly small sample size: 76 patients. And the patients were all newly-diagnosed -- very much by intention. The researchers were nervous about the possibility that the high-intensity workouts might cause their test subjects to have heart attacks, and they knew the risk of that was low with newly-diagnosed patients (long-term diabetes patients face a heightened risk of cardiovascular trouble). So, this study looked at a small number of patients of a particular type; the results might not apply so well to diabetes patients in general.

But my biggest concern is that I'm not sure how practical it would be to incorporate burst exercise into my life. The Medscape summary of the research left it quite unclear how much time elapsed between the three daily "bursts", and the abstract I was able to see online didn't say a word about this, either. So I have no idea how long the waiting period between bursts was supposed to be. Were people asked to do one burst in the morning, one at noon, and one in the evening? Or were they supposed to do them all at once, with a few minutes of rest in between? The latter seems improbable, but if that isn't how the workouts are done, I don't see a good way to fit them into my daily schedule.

My workplace has locker rooms and showers, and an exercise-friendly culture: lots of people work out at lunchtime, or get their exercise in by bicycle-commuting to work. Certainly nobody has ever hinted to me that there's anything wrong with my running at lunch.

But how would I do a trio of ten-minute workouts? Even a ten-minute workout would seemingly have me sweating enough to need a change of clothes, if it pushed me to a heart rate of 142 (85% of maximum heart rate). Whatever else my future holds, I'm pretty sure it isn't going to involve me bringing three sets of workout clothes to the office -- or changing into already-damp workout clothes for the second and third bursts.

Changing my clothes is not something I like to devote a lot of time to, so one workout per day seems like plenty of locker-room time to me.

Maybe the idea is to do the ten-minute burst in your regular clothes, and then head straight back to whatever you were doing. Well, it seems to me that I look bad enough coming back to the office after a run as it is. On a warm day (and, despite the date, today was pretty warm here in California), my office clothes look conspicuously damp even after a cool shower. Running uphill for ten minutes (which is what it would take to get me to 142 beats per minute) is just not something I'm going to do in office clothes, and changing my clothes before and after three workouts a day is another thing I'm just not going to do.

I'm not denying that the Canadian researchers have found something intriguing and potentially valuable. But they seem to be looking at it in an utterly impractical way. If they want diabetes patients in the real world to give burst exercise a try, they're going to have to provide some specifics about what is involved and how it can be done in a practical way.

In any case, I suspect that what I'm doing already combines the virtues of burst exercise and sustained exercise. My run today was over five miles long -- it was sustained, in the sense that it took a long time to do it. But it also intense in places. It involved some pretty ferocious climbs. This hill, in particular, goes on climbing like this for over a mile:

Maybe I'm already getting more benefit than either the sustained exercisers in the study (with their half-hour moderate workouts) or the burst exercisers (with their ten-minute intense workouts, which probably weren't any harder than the steep parts of my run today).

Anyway, I will watch with interest to see what comes of this research, but I'm not yet at the point where I see a need to change my approach to working out.

 


4th Thursday Update

October 22, 2015

 


Is sitting down okay after all?

Once a particular food, drink, or environmental factor has fallen under suspicion of causing a health problem, the suspicion usually continues forever, whether it is warranted or not. It's been said that science can issue an indictment in such matters, but it cannot dismisses the charges.

The reason for this asymmetry is that it takes only a small amount of data (and not necessarily the most reliable data) to raise suspicion that there is a problem. It takes a much larger amount of data (and top-quality data) to build a convincing case that there isn't a problem. Raising suspicion is quick, easy, and cheap -- so it's done all the time. Debunking false suspicion is time-consuming, difficult, and expensive -- so it's done rather rarely (and when it does happen, it is usually decades overdue).

Most health problems turn up randomly in the human population; when we find them turning up in what seems like a non-random way (for example, when a disease is more common in the people who work in, or live near, an oil refinery) we naturally become suspicious that this pattern of association indicates a cause-and-effect relationship. Which it might -- and also might not. It's hard to avoid over-reacting to such claims, but we need to make the effort. A single, small study claiming that people who eat tangerines have more glaucoma than people who don't is not enough to prove that tangerines cause glaucoma. (But if the study is widely believed, the tangerine growers then have a problem on their hands, because it's going to take a lot of time and money to gather enough data to show tangerines don't cause glaucoma.)

The trouble with a random distribution of disease cases is that truly random data is not as evenly distributed as most people imagine. Random data tends to clump. Flip a coin fifty times, and you're pretty sure to get a much longer streak of consecutive heads or consecutive tails than you imagine a random sequence would include. A truly random series of coin-flips will have long streaks, not matter how much we may feel that, after five heads in a row, the next flip is somehow "due" to be tails. This tendency of random data to be more lumpy than people expect tends to make us quick to imagine we have spotted a non-random pattern in random data.

Suppose you draw up a map of cancer cases within a city, showing a little red dot at every address where a cancer patient is living. What will you find? "Cancer clusters", of course (which are bound to occur in any random distribution of cancer cases). Look -- there are more red dots on Hopper Avenue than on Pine Meadow Drive! What's over there on Hopper Avenue that's giving people cancer? Once you start looking for a difference between conditions on Hopper Avenue and Pine Meadow Drive, you're sure to find some difference or other which you can cite as a possible cause of the cancer cluster on Hopper Avenue. Hey, wait a minute! There are high-voltage power-lines running along Hopper Avenue. That's got to be it -- power lines cause cancer! (This is not remotely plausible, by the way, but some people believe it, because it's so hard to disprove it beyond doubt.)

To be sure, sometimes a disease cluster occurs because there really is some local variable which is causing disease risk to be higher in one place than another. But that variable could be anything. (Is the population older in the place where disease prevalence is high? Or are there a lot of poor people living there? Age and poverty are risk factors for many diseases.) Similarly, a heightened (or reduced) prevalence of illness in people who eat a particular food certainly suggests that that food could be causing (or preventing) that illness -- but there could also be many other differences between people who developed the illness and people who didn't. That food is not the only factor in play here!

If you find shorter lifespans in people who never eat sushi, you haven't necessarily shown that they are being deprived of the health-preserving qualities of raw yellowfin tuna. More likely you have shown that they are being deprived of the health-preserving qualities of having money. People who can afford sushi tend to have a lot of advantages besides that one.

The tricky thing about research into the question of what is healthy or unhealthy is that you have to find a way to account for all these variables, so that you're not focusing on the wrong thing, and blaming an illness on some factor that is only coincidentally associated with it. Small, short-term studies are especially vulnerable to being led astray by some side-issue that looks important and isn't, such as the presence of power-lines or the absence of sushi.

Larger, long-terms studies are more likely to give us a reliable answer. Sometimes they even exonerate a factor which was formerly assumed to cause health problems. The idea that saturated fat in the diet causes heart disease came out of a study which compared disease rates in seven countries -- but that study ignored data from fourteen other countries where the pattern didn't hold true. More recent, larger studies (which didn't play games with the inclusion of data) have found no evidence that saturated fat promotes heart disease.

It's difficult to know what to do when a health bogeyman is suddenly exonerated in this way. Often people deal with it by ignoring it. Public-health organizations tend to continue saying whatever they were saying before, rather than admit they were wrong. The same authorities who were telling us not to eat saturated before have, for the most part, decided that that's their story and they're sticking to it; dietary recommendations are not changing to reflect the state of research.

Of course, another possible reason people tend to ignore the exoneration of a health bogeyman is that they're afraid it's too good to be true. What if they start eating butter again, and then it turns out there's a reason to think it's actually bad for us after all?

I guess that's why I'm having mixed feelings about a new, large, long-term study which contradicts earlier studies claiming that extended sitting is bad for you even if you exercise regularly. For years, I had assumed that my sedentary job (I spend a great deal of my life seated at a computer) wasn't doing me any harm because I go out for a run almost every day. Then I started to hear about studies saying that sitting several hours a day sets you up for chronic disease and early death even if you work out! This upset me, but I was holding out hope that, once researchers took a more careful look at the issue, they would find that it wasn't true.

The new study tracked over 5000 people, over a 16-year period, and analyzed their various kinds of activities (and sitting behaviors) closely. Their conclusion? "No associations were observed between any of the five sitting indicators and mortality risk". The study authors do acknowledge a possible source of bias in the study: it's possible the 5000 people in this study are more active (when not seated) than the average person, because the study participants were living in London, and Londoners might be more active than other UK citizens (walking more often, for example). Still, even if Londoners are more active on average, wouldn't some of them be more active than others, and wouldn't there still be at least some association between sitting and health problems among Londoners, if sitting mattered? And, anyway, the whole issue the study was supposed to be looking at was whether long periods of sitting are harmful regardless of how active you are when not sitting. How active Londoners are when they're not sitting shouldn't be relevant here, seemingly.

At this point I'm taking a great deal of comfort in this study. (And also worried that somebody's going to be able to discredit it.) The nature of my job and pastimes is not going to change, so I'm glad the science seems to be changing in my favor!

 


3rd Thursday Update

October 15, 2015

 


My little experiment

Figuring out how your endocrine system deals with blood glucose, by taking one or two glucose tests a day, is like trying to follow a fistfight that is illuminated only by flashes of lightning: you may get an idea of how things end up, but you're not going understand the progression of events that led to that outcome.

Is that too negative a metaphor? Well, if so, think of it as trying to learn a dance by watching it performed by flashes of lightning. The point I'm trying to make is that a snapshot of an subject in motion doesn't tell you a lot about how it moved and when.

Blood sugar is a fluctuating quantity (even in people who don't have diabetes), and you really have no way to know what your blood sugar is doing when you're not checking it. That is why the fasting glucose test (first thing in the morning, before breakfast) is such a misleading indicator of how well-controlled your blood glucose is. Most doctors use an annual fasting glucose check as a screening test for diabetes, but this isn't a very good early-warning indicator. People who are becoming diabetic (but don't know it) often continue to get normal fasting tests for years. If they don't get tested at any other time, neither they nor their doctors are going to know that they're spiking like crazy after meals.

Tests after meals are a more useful measure of glycemic control. But how soon after the meal should you test? If you're going to collect only one data point, you seemingly should collect it at the point when your post-meal glucose spike is likely to be as high as it's going to get. For most non-diabetic people, glucose spikes 50 to 60 minutes after a meal, and it goes up (on average) to about 125 mg/dl. When I was diagnosed (in 2001), I was told to take my post-prandial tests an hour after a meal, which certainly makes sense if you want to compare yourself to a normal glucose profile, to see how closely you match it. I've tested at the one-hour mark ever since, if at all possible.

Apparently most diabetes patients these days are told to test at the two-hour mark. I have no idea why, and it makes no sense to me. The normal glucose profile is supposed to settle back to the pre-meal level well before the 2-hour mark, and I take it that the whole point of diabetes management is to get as close to a normal glucose profile as we can.

Unfortunately, the only way we can find out what our glucose profile looks like is to use up a bunch of test strips and test at short intervals right after taking a meal. The health insurance companies, with their increasing reluctance to cover glucose test strips as a legitimate medical cost, have discouraged diabetes patients from doing the necessary experiment, to see what really goes on in their bloodstream during the hour or so following a meal. However, I've lately been hoarding test strips, saving them up for a proper experiment, to find out what my glucose profile looks like these days. (I've done this in the past, but it was years ago and things could easily have changed since then.)

Anyway, I chose tonight for the big experiment. I went running after work, came home, and got ready for the test. I tested my glucose (91 mg/dl), and then ate a dinner consisting of stir-fried meat and vegetables (with no rice, but one slice of bread and hummus).

Then I started testing at ten-minute intervals. I should mention that I count test times from the end of the meal. (Some people think "an hour after a meal" means "an hour after you started the meal", but their dictionaries probably have a different definition of the word "after" than mine does.)

The first result, ten minutes after I finished eating, was 88 mg/dl -- essentially the same as the pre-meal result. It was too early for any of the carbohydrate in the meal to have reached the bloodstream as glucose. But at the twenty-minute mark, carbohydrate digestion was making a measurable impact; I was up to 119 mg/dl.

To make a long story short, here's the rest of the glucose profile, over a 90-minute test interval:

It's pretty much a textbook non-diabetic glucose profile, with a peak in the 120-130 range between 50 and 60 minutes, and a decline to 95 at the eighty-minute mark. Strictly speaking, a truly non-diabetic person would probably drop lower than I did, and a little faster than I did, but if this isn't normal, it's pretty close.

However, I shouldn't get too complacent about this. The meal began only an hour after I finished exercising. My profile at lunchtime probably would have gone higher, and stayed high longer, simply because I hadn't had my exercise for the day yet. And more starch in the meal certainly would have given me a higher spike. (If I'd eaten this stir-fry in a restaurant, it would have been served on a mound of rice the size of a throw-pillow, and even if I left most of the rice uneaten on the plate, I think the I would have seen higher numbers.)

If you're testing only once or twice a day, because that's what your insurance covers, and you don't think the results are telling you what you want to know, skip some of those uninformative tests, and hoard enough strips to do a proper experiment and find out what's really going on with your blood sugar when you're not looking. If you're one of those people who tests at the two-hour mark, and you assume everything's okay because you're down to 110 by then, better make sure that you're not going over 200 at an earlier point in the process. If that's happening, you can't find it out by not checking.

 


Celebrate!

You can't say I never bring you any good news.

A new study of the effects of alcohol consumption on people with diabetes concludes that moderate consumption of red wine yields a "modest" but significant health benefit, mainly by reducing cardiovascular risk. "Red wine was found to be superior in improving overall metabolic profiles, mainly by modestly improving the lipid profile, by increasing good (HDL) cholesterol and apolipoprotein A1 (one of the major constituents of HDL cholesterol), while decreasing the ratio between total cholesterol and HDL cholesterol."

That's my early Christmas present to you. But keep in mind that they did say moderate consumption. Apparently drinking yourself unconscious doesn't provide the benefits outlined here.

 


But it's harder for me!

I probably shouldn't be sharing this information with you, because it may provide diabetes patients who hate exercise with an excuse for not doing it, but honesty is probably the best policy when you're writing about medical issues....

Anyway, a study comparing women with and without diabetes found that, for women who were matched for age and weight, those with diabetes found the same level of exercise intensity more exhausting and painful than did non-diabetic women. Exercise was simply harder on women with diabetes. This conclusion was not based merely on the women's verbal reports on how they had felt during exercise -- the researchers also tested their blood, to look for chemical markers of exercise stress (such as lactic acid buildup) and found that, indeed, the women with diabetes really were more physically stressed by exercise than non-diabetic women.

Why would this be? Apparently people with diabetes process chemical energy differently, and use it less efficiently -- with the result that a given level of exercise intensity becomes more tiring, and causes the muscles to "burn" more from lactic acid buildup, than would be the case for someone whose body does a better job of processing energy. Therefore, people with diabetes, who need exercise more than other people do, have a harder time performing it than other people do.

The lesson here may be that people with diabetes need to find ways to exercise that don't over-stress them. If you find that running is too tough for you, don't just give up and become entirely sedentary; try going for a long walk instead.

I've never found exercise easy, and a lot of it is punishing for me. (My run after work today involved a steep hill-climb that goes on for about a mile, and every time I do that route it gives me the uncomfortable feeling that this time I won't make it to the top alive.) I've learned to live with that kind of I-can't-do-this anxiety. But if the exercise you're trying to do makes you feel so awful that dying before your time seems like a better plan, try easing off a bit. You may find that a walk after dinner gives you real and measurable benefit. It's bound to be better than giving up and doing nothing, which seems to be Plan B for a lot of people.

 


2nd Thursday Update

October 8, 2015

 


October in California

It sounds like such a good idea, in principle, to have this kind of sunny warm weather well into October. But there are practical reasons why a little rain now and then is also kind of nice...

 


Cheap generic end-of-the-world scenarios!
(And costly drugs!)

How's this for an understatement?
"Since it is now October 8th it is now obvious that we were incorrect regarding the world's ending on the 7th."

That was today's message from E Bible Fellowship, doing their best to explain how it comes about that we're still here, despite their predictions to the contrary.

I'm pretty annoyed about this. I thought I wasn't going to have to bother creating a blog post for today, seeing as the world was going to end yesterday. And yet here we are.

Perhaps you weren't even aware that yesterday was supposed to be the apocalypse; press coverage of the subject was not as intense as it might have been, what with the big event coming only ten days after the hysteria (in some circles) about the possibility that the latest lunar eclipse would somehow trigger the end of all things. (Note to doomsday prophets: try to pick a date that's at least a few months after the last failed prediction, so people have a chance to forget.)

Because doomsday predictions have become so frequent, news editors are finally starting to experience doomsday fatigue. For years they dutifully reported on (and therefore participated in) the latest round of end-times panic every time some loon with a big enough mailing list predicted that the Day of Wrath was going to be next Wednesday. The press coverage of the "issue" would seem to legitimize the possibility that the prediction was valid, and easily-influenced people would put their affairs in order, waiting for the end, and often giving away their money (preferably to the doomsday prophet). In other words, predicting the end of the world was something a guy could make a decent living at.

But now it's not so easy! There's too much competition. Too many people want a piece of the action. And, let's face it, anybody who wants to go into the doomsday-prophet business can do so fairly easily. You don't even have to be religious: some doomsday predictions are based on misinterpretations of astronomy texts (ancient and modern) rather than misinterpretations of religious texts. As doomsday predictions become more commonplace, journalists are becoming reluctant to play their part in the scheme, so it's getting to be harder and harder for a doomsday prophet to obtain free publicity. When you have to pay for your own publicity, costs go up and profits go down. Billboards aren't free!

To put this in business terms, the end of the world has been "commoditized". Commoditization is a much-dreaded free-market phenomenon in which a product which once had high profit margins (because only a few producers made it) becomes increasingly devalued because too many producers are able to make it, and because customers don't perceive a difference in value between one brand and another. The result: price-competition increases, and drives profit margins down.

A classic example of commoditization is the dynamic-RAM memory chip, which was highly profitable when it was cutting-edge technology, but became far less profitable when too many companies started making them, and the market saw little difference between one and another, so that purchasing decisions were based only on price. The tech industry is particularly at risk for this kind of thing, because this year's unique must-have product can so quickly find itself competing with multiple copycat products which cost less. However, it's not just the tech industry that has to worry about commoditization; every industry deals with it. You can try to fight this, by using expensive advertising campaigns to create a popular impression that your product is superior to its imitators -- but when this approach fails, it fails big. Once your customers decide that an aspirin is an aspirin, they don't want to pay extra for Bayer.

Of course, another way a producer can defend itself from commoditization is to keep potential competitors out of the market, by claiming exclusive intellectual-property rights to the product. This doesn't always work (patent law is a messy business), but when you're the only producer of something, you can get away with just about anything -- as in the case of Martin Shkreli, the boyish Wall Street gargoyle turned pharmaceutical CEO.

He acquired the rights to produce a drug that treats parasitic infections in cancer and AIDS patients. The drug costs $1 per pill to make, and was selling for $13 per pill; he raised the price to $750 per pill. Why not? If it was a commoditized drug, with a dozen other producers making the drug as a "generic" and competing on price, such a move would not be possible. But nobody else was making the drug, so it was pay or die. After the firestorm of bad publicity which followed this decision, Shkreli announced he would lower the price of the drug -- then didn't do it. You'd smirk too, if you could behave that way and get away with it.

Anyway, commoditization benefits only consumers, not producers. Producers hate it. Avoiding commoditization is a big concern in any business.

If you're in the business of creating end-of-the-world panics, you'd prefer to be the only one in the business. That way you can do it in style, and you can even do it repeatedly. (Harold Camping did it twice, and refused to give back the donations he collected either time.) If you're selling a more tangible product, you'd prefer not to have to compete with a bunch of other producers selling something similar.

Commoditization as a business concern has an especially complex and subtle impact on the way drugs are used to treat Type 2 diabetes. There are many different "families" of diabetes drugs which work in different ways. Some of them have been around long enough to be "generic" and therefore commoditized. Those are the cheaper diabetes drugs. Newer ones are still under patent control and are more expensive (usually by a wide margin). Naturally, the pharmaceutical industry would prefer to have doctors prescribe only the newer and more profitable drugs (such as empagliflozin), not the commoditized ones (such as metformin). The trick is to convince doctors that the more profitable drugs are worth the extra money. Currently, doctors are being given clinical guidelines which recommend cheaper commoditized drugs. The pharmaceutical manufacturers have a desperate need to turn that situation around, by generating data to show that the more expensive drugs do a better job than the cheap ones. (Comparing either the expensive ones or the cheap ones to exercise is not thought to be necessary.)

The reason I mention this is that I think there are powerful economic pressures being brought to bear on medical researchers to come up with data showing the expensive drugs are superior. When the financial stakes are that high, standards are compromised. A pharmaceutical company might sponsor multiple studies, most of which show the expensive drug isn't better than the cheap one, and publish only the one anomalous study which gives the expensive drug an edge. When we hear exciting reports such as the one from Stockholm which I wrote about on September 24th, which reported that doctors at a medical conference were "gasping" at how good the data was on empagliflozin, we should probably wait to see how well these promising findings can be confirmed by researchers with no financial stake in the outcome (if such researchers are ever allowed to get involved!).

It's hard to assess the behavior of pharmaceutical companies realistically if you don't bear in mind how much they hate having to deal with competition. Things go so much better when you're the only game in town!

 


My petty thought-process

Paul Prudhomme, enthusiastic creator (and consumer) of high-calorie southern recipes, died today. All things considered, I guess it was quite an achievement for him to have made it to age 75. Still, all I could think was: I was counting on him to outlive Paula Deen!

Maybe I just have the wrong attitude about celebrity chefs.

 


1st Thursday Update

October 1, 2015


I tried to get a decent picture of the lunar eclipse on Sunday, but the eclipse was ending by the time the moon rose in California, and the sky wasn't yet dark enough for the moon to show up very well. This was the best I could do!

At least it required a long hilly walk to get to where I took the picture, so there was some exercise involved.

 


Flu shot thoughts

I found out too late that I had missed the annual flu-shot clinic at work this year (it happened while I was taking some time off). I have been getting annual flu shots for several years now, and although I've heard people complain that it seems to do them more harm than good, it works for me. Since I started getting the shots, I haven't had the flu once. I've had colds (usually one per year), but not the real thing -- not a terrible, incapacitating viral fever of the kind that the vaccine is designed to prevent.

I know what the real thing is like; I remember having had the true-blue flu more than once, several years ago, before I started getting immunized, and it was pretty awful. I didn't want to take a chance on not getting the shot this year.

I think it's especially important to get immunized against the flu if you have diabetes, because an illness as severe as that plays havoc with glycemic control. Even if it had no other effects, a bout of the flu is certainly going to interfere with your exercise program -- perhaps for rather a long time. So, I found a pharmacy that does flu shots, and went there today.

After I filled out the paperwork and waited around for what seemed like a mysteriously long time, the pharmacist in rubber gloves came out to give me the shot. "Left arm or right?" he asked. "Left," I said. "I always get a muscle-ache afterwards and I'd rather have it on that side". I like to volunteer information indicating I'm experienced, in the hope of heading off any special lecture they give to first-timers.

He swabbed a patch of skin on my left arm -- a patch large enough to make room for a tattoo rather than a needle-prick, but the syringe when he brought it out was the normal size.

"It's the quad", he said.

It's the quad? No doubt people in his business think the public knows what that means (just as people in my business think cell phone users know what "4G" means), but I was drawing a blank. I gave him an inquiring look (raising an eyebrow while slightly dropping the head is my method, but there are probably other ways to do it).

"It's the quadrivalent", he said, eliminating all confusion.

"Oh", I said.

I wondered what the quadrivalent was. I asked him if there was trivalent, for people who were looking to save a little money on the deal. I was kidding around -- I thought I had just invented the term trivalent -- but it turns out that there is a trivalent version of the vaccine.

"We give the quad first", he said.

First? Was he planning to give me more than one shot? I gave him a little more of the raised eyebrow.

"We start out giving the quadrivalent version, because it covers four strains of the virus. When we sell out of that, we fall back on the supply of the trivalent. That covers only three strains."

I said I was glad I wasn't getting the trivalent version, because if it left out one strain, that would surely be the one I'd get exposed to.

After we were done miscommunicating, he jabbed the needle into my arm, and as always it hurt less than I would have expected it to. In fact, the needle itself hurt less than the influx of fluid into the muscle as he pressed the plunger down.

"It always hurts less than I would expect it to", I observed sagely.

"You'd be surprised," he said. "For some people it hurts a lot more than they expect it to."

I thought about that. It seemed to mean that optimists were at a disadvantage. I expect a shot to hurt like hell, and when it doesn't I'm greatly relieved. Apparently people with sunnier dispositions expect a shot to feel great, and when it doesn't they're shocked and disappointed. Maybe being a worrier isn't such a bad thing.

 


It's alive!

It seems especially important to do what we can to prevent viral infections, now that we know viruses are alive. Perhaps you didn't know there was any doubt about viruses being living things, but for many years there has been.

After all, what do we mean by "alive"? What distinguishes living things from nonliving things? It's not a question most of us ask. We think life is like pornography, in the sense that "we know it when we see it". (I'm not claiming that life is like pornography in any other regard, so don't send me letters correcting me on that point.) We don't usually think in terms of defining life, so as to distinguish living things from nonliving things.

However, science needs to define its terms pretty carefully, and it turns out to be surprisingly difficult to define "life" in such a way that your definition includes everything we think of a living thing, and excludes everything we don't think of as a living thing. If you're not careful, you might end up with a definition of life under which your car qualifies as living because it moves and uses energy, or your phone qualifies as living because it exchanges signals with its environment. (I am tempted to think of the flu virus as being alive simply because of its resourcefulness in adding misery to my life, but by that definition some the computer apps I use are alive, too.)

For a while it was possible to exclude human technological products from the definition of life simply by requiring that a living thing be able to reproduce. But we're probably pretty close to having robots that can build more robots, and we definitely have computer viruses that can make copies of themselves. Therefore, self-replication is becoming an unreliable way to distinguish living things from non-living things.

I mention computer viruses because they are called viruses for a reason. They operate in very much the same way natural viruses operate. A computer virus is a piece of code which, when it is introduced to a computer, starts making copies of itself and sends those copies to other computers. A natural virus is a piece of genetic code on a strand of nucleic acid which, when it is introduced into a cell, starts making copies of itself and sends those copies to other cells. (Unfortunately, the way a natural virus does that is to fill up the cell with copies until it bursts, releasing the copies to infect new cells. Hijacking and killing cells turns out to be bad for the health of the host organism.)

The most interesting similarity between a computer virus and a natural virus is that neither one of them can operate independently. A computer virus can only make copies of itself when it's in a computer. A real virus can only make copies of itself when it's in a cell. Neither kind of virus can do anything all on its own. It needs to hijack the functional apparatus of a computer or a cell if it's going to function at all. If it's not in a computer or in a cell, it's inert. When deprived of a host, a natural virus doesn't interact with its environment. It has no metabolism: it doesn't take in energy or use energy, it doesn't grow, and it doesn't change. Should we call it a living thing just because it becomes functional when it's placed inside something else? (By that definition, your car keys are alive!)

This lack of independence has always made some biologists argue that viruses are nonliving. They're just troublesome molecules that happen to trigger a copying mechanism within cells. And anyway, it's the host cell that's doing the reproducing, not the virus; to claim that a virus reproduces itself is like claiming that a muffin recipe reproduces itself every time someone bakes another batch. A recipe only looks like it's reproducing itself if you forget that cooks exist; a virus only looks like it's reproducing itself if you forget that cells exist. Without cells, viruses are nothing, therefore viruses aren't alive. Right?

Not necessarily. There are serious counterarguments to be made against the view that viruses can't be alive because they can't function independently. Are parasites non-living, if they spend their lives inside some other living thing? Are honeybees non-living, if they can't live independently of the hive? Are plant seeds and mushroom spores non-living, because of their lack of metabolic activity over long periods, when they're lying on the forest floor waiting for the right conditions to start growing? It is hard to argue that viruses aren't life forms if those other things are life forms.

Increasing knowledge of the way genes work has led to more sophisticated arguments against viruses being alive. It was thought that viruses were just "dumb" copying mechanisms (with no capability of altering genes), and probably originated as nothing more than bits of DNA from a cell that broke free from their natural moorings. In other words, viruses don't have an independent evolutionary lineage, nor do they have much of a history. At least, it used to seem as if they didn't have those things. A virus doesn't leave a fossil behind, so there's no way to work out viral evolutionary history by comparing different variants of virus-bones. Comparing genes in viruses didn't seem to reveal much of a viral evolutionary history, either. Nothing did, at least until now.

Now biologists have developed another method of reconstructing evolutionary history -- not by studying genes, but by studying patterns in protein-folding. Proteins have fantastically elaborate shapes, and the patterns of folding which produce these shapes are as important to the protein's biological function as the sequence of amino acids (building-blocks of a protein) which a gene codes for. Comparing protein folds (treating them as a kind of fingerprint) is potentially more revealing of the way organisms relate to one another evolutionarily than comparing genes.

New research on protein-folding in viruses and cells shows that viruses are not newcomers. They have a long evolutionary history alongside cell-based organisms, and not only do viruses evolve themselves, they also seem to have driven evolution of their cellular hosts. It turns out that viruses are not just "dumb" copying mechanisms -- they alter genes in addition to copying them. It used to be thought that viruses got all of their genes from us (by "us" I mean their hosts generally), but it seems that we got some of our genes from them. Viruses can actually originate new genes (there are genes found in viruses that don't exist in cellular organisms).

Anyway, it now appears that viruses are living things, and they are very much integrated into the world of cellular organisms. They have been evolving alongside our ancestor species for a very long time. They have been adapting themselves to us -- and they have also been adapting us to themselves. No wonder it's so hard for us to develop anti-viral drugs that will kill a virus without harming the patient: viruses are too much at home inside us. They blend in. They fit.

I suppose we should be grateful that humans and the flu virus have an especially cozy history: this particular virus is well enough adapted to us that it usually doesn't kill us. Even though the virus evolves so rapidly that we need a new flu shot each year (to capture strains of the virus which weren't around last year), each new strain usually just makes us sick enough to be infectious, and pass the virus on to the next host. A virus that actually kills the host is making a beginner's mistake; that is one indication that the frequently-fatal Ebola virus has had less time than the flu virus to adapt itself to the human species.

So, in a sense the flu virus is our old friend, our dear companion. It's been with us through thick and thin, in good times and bad, for richer and for poorer, in sickness and in poor health. And through it all, it usually doesn't kill us. Let's hope it is true that what does not kill us makes us stronger.

If the vaccine I took today doesn't kill me (which seems a reasonably safe assumption), it may well make me stronger. Which I probably need to be, because two people I know have the flu already. The heat-waves are barely over, and the flu season is already starting up!

 


70,000 ways to get sick or hurt

Okay, this time we mean it! You have to comply with this regulation, as of October 1st, whether you like it or not!

That's the message doctors are getting today. It might be a bad week to see your doctor.

The ICD-10 is an insanely complicated system of codes which, as of today, American doctors must use to identify the conditions they are treating, if they want to be paid. Other countries adopted it years ago, because in other countries doctors are provided with government clerks who understand the coding scheme and fill out the paperwork. American doctors, who won't be given such help, have been fighting hard to keep the ICD-10 from being implemented here, and have succeeded in postponing the deadline from year to year, but apparently they have lost the battle and must now do their best to use the codes -- all 70,000 of them.

Actually, the phrase "insanely complicated" really doesn't begin to do justice to the breathtaking thoroughness with which the World Health Organization attempted to anticipate all possible diseases and injuries when it was creating the ICD-10.

Injuries caused by animals have separate codes depending on what sort of animal was involved, and how it caused the injuries. Not only is there a special code for duck-related injuries, there are also separate codes which specify whether the patient was bitten by a duck, struck by it, or harmed by it in some other manner. Other animals are also covered with the same thoroughness, including cows, dolphins, and turtles. I'm not sure how often anyone is "struck" by a turtle, but if it happens, there's a code for it.

If a patient is being treated for injuries that resulted from walking into something, there are separate codes depending on what the patient walked into. If the patient was asphyxiated by a plastic bag, there are separate codes depending on whether this was attempted murder, attempted suicide, an accident, or none of the above.

Burns are differentiated with extraordinary precision. You might think, for example, that the system wouldn't need more than one code for a patient who was burned by plastic jewelry, but in fact there are separate codes depending on whether the jewelry was merely melting or actually aflame. And there is a code for being burned because your water-skis caught fire, a contingency which I admit might easily arise.

You might think that these things wouldn't really matter, because most medical treatments are not for strange accidents but rather for common chronic diseases such as diabetes. That turns out not to simplify the practical application of the coding scheme nearly as much as you would think. If burns are broken down so thoroughly that there are separate codes for the various ways you might bet burned by plastic jewelry, imagine how thoroughly diabetes and its possible health consequences are differentiated! Any doctor treating a diabetes patient must slog through page after page of subtly varied diabetes-related codes.

The result I predict is that every American doctor will learn a short set of codes which he or she finds understandable, and then force-fit every treatment into something on that abbreviated list. Or, if the doctor is feeling particularly frustrated or rushed, a code will be plugged in at random.

And that is why I will not be too surprised if my next office visit ends up being charged under the code "V9114XA", which pertains to injuries sustained when the patient was crushed between a sailboat and a water-craft that wasn't a sailboat.

 



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