ACC: ICD shocks management

An implantable cardiac defibrillator (ICD), is a relative new cardiac rhythmic management device. Other similar cardiac rhythmic management devices include the well-known pace-maker. Different from the pace-maker, the ICD has a special wire, called a lead, which is implanted inside the heart, and can deliver an electrical shock to the heart muscle to adjust the heart beat. In the past decade, ICD market sharply increased 10 times, from 25,000 to 250,000.


Repetitive shocks are a medical emergency, which are associated with significant morbidity. An ICD is associated with a 2- or 5- fold increase in mortality, with the most common cause being progressive Heart Failure.

“Among patients with heart failure in whom an ICD is implanted for primary prevention, those who receive shocks for any arrhythmia have a substantially higher risk of death than similar patients who do not receive such shocks”--according to content showed by the speaker in ACC. About 65% of deaths were from progressive heart failure versus 35% arrhythmic deaths.

Only 20-35% of ICD shocks are appropriate. 33% are inappropriate shocks, while the last is “Phantom” shocks which only can be sensed by patients, but no record in ICD memory data.

Cardiologists are looking for effective ways to reduce inappropriate ICD shocks to insure the patient security.

Antiarrhythmic drugs are a controversial topic among experts about how to reduce the ICD shocks. Some scholars argue that these drugs can both decrease appropriate and inappropriate ICD shocks, but a few of them hold a counterview.

Catheter ablation may favorably affect mortality. Because it is effective in the short-term treatment of ventricular tachyarrhythmia storm by preventing it recurrence, it may play protective role over the long-term together with pharmacological therapy.
Other approaches to manage ICD inappropriate shocks are staying away from electromagnetic interference resource, and fixing a malfunctioning device if it is not working properly.

ACC--Biomarkers, future clinical endpoint in heart failure trials

A biomarker is in general a substance used as an indicator of a biological state. In clinical trials, the candidate markers include dyspnea, weight change, blood pressure, natriuretic peptides, markers for left ventricular (LV) and gene expression and so on. For example, COMPANION biomarker is a well established endpoint for morbidity in clinical trials, while SCD-HeFT is used for mortality.

In recent heart failure clinical trials, the biomarkers are also being widely used as primary and secondary indications. The primary biomarkers are dyspnea, weight loss, LV size and composite. The secondary biomarkers are LV size and function-ACE-I, BB trials, BNP-Val-HeFT, NYHA class-ACTION-HF.

However, these common biomarkers are not relevant endpoints in heart failure trials as a result of lacking better fidelity, cleaner signal to noise ratio, convincing evidence of meaningful clinical benefit and ideal surrogacy. Cardiologists keep looking for the ideal biomarkers which can better address these questions and become the clinical endpoints in heart failure trials in future.

They have even already written down the scenarios for the future of biomarkers not so far away.
Scenario I: clinical trial XXX tests the ability of treatment YYY to reduce the likelihood of developing heart failure; a biomarker assay is used as the endpoint that biomarker ZZZ is used as a surrogate for heart failure.

Scenario II: clinical trial XX hypothesizes that intervention YYY will improve outcomes in patients with established heart failure; rather than follow longitudinal events, a biomarker assay is used as a surrogate for prognosis.

Scenario III: because an elevated biomarker corresponds with a poor prognosis company AAA develops a “biomarker blocker”; clinical XXX is then done with drug YYY, endpoint combined morbidity/mortality.

Scenario IV: a new antihypertensive purportedly works in part via unregulation of natriuretic peptide production.

Beverage vending environment

Last Tuesday (March 16th2010), the world’s second-biggest soft-drink maker, PepsiCo Inc., announced its plan for removing full-calories sweetened drinks from schools in more than 200 countries by 2012. This happened at the same day first lady Michelle Obama urged major companies to put less fat, salt and sugar in foods and reduce marketing of unhealthy products to children.

Rather than only persuading people to resist outside temptation, building a healthy environment is a way to improve people’s health as well. Especially, when we are living in a world which has vending machines everywhere, even in the healthcare facilities.

In a study about vending machines in California (published at in Pediatrics, Jun 2009), hospitals hospitals averaged 9.3 vending machines per facility compared with 3 vending machines per health department and 1.4 per small clinic. Across all health care facilities, 75% of beverages sold in vending machines did not adhere to the California school nutrition standards. Sodas comprised the greatest percentage of all beverages offered in vending machines, more than 30%.


Not just sweetened beverages like soda, foods are an even bigger problem. 81% of foods sold in vending machines did not adhere to the nutrition standards.

If you logged into the homepage of Georgia Vending Service, whose FREE snack & soda machine service covers a large area including Athens-Clarke County, you will find out that having a free vending service is just one “click” away. You can get all kinds of vending machines, from snack & soda machines to medical machine, even cigarette machines.


I don’t know how many vending machines there are in Athens-Clarke County, but I found out that at UGA, with vending services provided by Coca-Cola Enterprises Inc., there are more than 500 vending machines located in over 150 buildings on campus. Fortunately, not all of them are for snacks and soda, some of them provide newspapers and magazines. But compared to the fact that we only have one Health Center on campus, the average number of vending machines that sell unhealthy food and beverages is still large. The same day when I am writing this post, I checked the Tate Center where hold many activities for students, staff, faculty and visitors. There are 10 vending machines, but there are also some ones in the Bulldog Café.

The guilty conscience and health promotion

When we want to persuade somebody to do something, we always would like to tell him or her how much he or she will benefit from the new thing. For example, in most commercials the audience hears, “If you eat this new one but not that old one, you will lose weight,” or “if you buy this equipment, you will save heat/gas/time/money.” That is the same way healthcare promoters work in most cases. They give people new medicine, show them how to exercise and teach them to try new things.

But the first time I heard someone using a guilty conscience in health promotion was when I was talking with Katie Porter, a Ph.D student in UGA. She is working on the senior obesity issue in Northeast Georgia. Her job is teaching them how to cook healthy food and do exercise, like yoga. She mentioned guilty conscience because she just realized that she met a great challenge that when people take their poor health condition as a normal and common situation that also happens in others around them, they won’t change their lifestyle simply to gain some “benefit.”
The increasing body weight and waist circumference always are considered as the natural result of aging. Most senior people are satisfied with their bodies, because their parents, friends and neighbors all seem to be living the same way.

Exercise and healthy diets, all the ways for losing some weights, seem more attractive to young adults. Part of the reason may be that they want to become attractive in the society and gain more benefit by their health condition. But as a person ages, this motivation is also missing.
When this happens, the guilty conscience seems to become more effective in persuading older adults to lose weight.

So Katie Porter always tried to drive home the question about how much impact they are going to have on other people if her target population doesn’t change its behavior. For a senior, the main thing for him or her is to live independently as long as he or she can. If seniors’ health conditions become worse, they can’t take care of themselves, and may need somebody else to take care of them, even end up in a nursing home. And more money will go from the healthcare system to taking care of them. By getting that point across to those seniors, Katie Porter hopes she might be able to change their behavior. But so far, this is just a goal for her program and a hypothesis for her thesis. She and her colleagues may need more time before providing more convincing evidence in the future.

"Why us?" II: possible answer

Since I can’t get the authoritative answer for “why us” in most cases, I didn’t use the “probable answers” from experts in my stories. But I am still a little bit interested in confirming their guesses. So I did some study by myself to look into it.

Take the example of the obesity issue. I tried to find some papers to answer my question: whether population status, such as low-income, high-minority will affect a population’s weight.
In a paper published in the Journal of Public Health, January 2010, researchers conducted surveys in three low-income, high-minority California communities. The results suggest that: (1) the average intake of salty snacks, candy, cookies and sweet beverages was 532 kcal, 88% higher than the US Dep. Agriculture and Dep. Health and Human Services recommend; (2) energy from these sources was more strongly related to Body Mass Index (BMI) than reported physical activity, fruit or vegetable consumption. (3)Policies to promote healthy eating and physical activity were limited in worksites; (4)Fruit and vegetables were less salient than junk food in community food outlets.

Another paper I looked at regarding childhood obesity and socioeconomic condition was published at Health Aff. in March 2010. They conducted this study among US children and adolescents using the 2007 National Survey of Children’s Health (So they have very complete data, as I said before). Their findings demonstrate that the odds of a child’s being obese or overweight were 20-60% percent higher among children in neighborhoods with the most unfavorable social conditions such as unsafe surroundings; poor housing; and no access to sidewalks, parks, and recreation centers than among children not facing such conditions. Among the young girls ages 10-11, the obesity and overweight were two or four times more likely than among their counterparts from more favorable neighborhoods.

These two studies draw a similar conclusion: there is a health inequalitiy between the low-income, high minority communities and their counterparts from more favorable circumstances.

In the meantime, if you have checked the social demography information about Clarke County, which I also posted on my blog, you will find out that we do have a large minority population and a high rate of poverty, compared to other states.

Although I was working on the senior obesity and overweight issue story, I think the “possible answer” from experts is probably right for their cases. But if you want more convincing conclusion, I guess you need to contact the demography experts to answer this big question.

"Why us?" I: no answer?

When I am working on the local health issues stories for Athens-Clarke County, I ask the experts one question—“Why us?”

“Why we do have higher health risks than other states?” or “Why do we have higher health risks than other counties?”

Regarding the food safe issue, our county has a higher rate of “high risk” restaurants than other counties in Northeast Georgia.

Regarding the teenage pregnancy issue, Clarke County had the highest rate in Georgia twenty years ago. Georgia had the highest rate in the United State in the 90s.

Regarding the senior obesity, the rate in Clarke and Greene Counties is 55%, much higher than the average Georgia, 37%.

So what is the relation between these facts?

Most experts would give two possible answers: a higher poverty rate and a larger minority population. But, they are not sure about it.

Most researchers don’t study the relationship between the demographic characteristics and their research findings.

In my opinion, this limitation is a natural result produced during the scientific research process.
First, researchers want to control the variance of samples and get significant different results between their target group and their control group (baseline). So they always choose the samples sharing similar characteristics, for example, those living in the same area, having a similar life style, or getting exposed to the same hazard. In that case, they don’t need to answer the question “why us” by comparing their subjects to others who already have been excepted from their research at the very beginning.

Second, the funding is a real problem for researchers. Under most situations, a single institute can’t afford to do everything all by itself. Data collecting and data analysis will be a big challenge if a single institute wants to cover a big area. A better choice is just for a big organization to collect information separately from each area then analyze it together. CDC and WHO gave great examples of how they work on nationwide, even worldwide.