Observational Study related to CHD in India

Phillip McKegg

Dr. Z

Biostatistics Blog 2

September 22nd, 2016

 

Blog Assignment: Example of a peer reviewed journal article with experimental or observation study method. A reflection piece on the observational study explained in the paper/experimental design that is used (between 300-500 words)

Due 1:00pm on September 23, 2016 (Please post it before our lab, so we can discuss the design examples in your sample articles)

 

In this study, the researchers were focusing on the prevalence of congenital heart disease (CHD) in newborn babies, particularly in Northern India. In first world countries, congenital heart disease is the main cause of death within the first year of life, however, in third world and developing countries, there is little data that relates to CHD and newborns.1 The objective of this study was to observe the number of babies born with a CHD in a hospital located in Northern India. Specifically, this was a cross sectional study that was conducted in a pediatric hospital over a three-year period, and only babies born during a specific eight-hour time frame were used.1 After birth, normal tests were conducted and an echocardiogram was administered to determine if the newborns were suffering from a CHD.1

In this study, a total of 20,307 newborns were screened for congenital heart diseases. Of these, “874 had abnormal echocardiograms, 687 had insignificant echocardiograms, 164 had significant congenital heart diseases, and 24 had abnormal cardiac findings.”1 Those born with a significant congenital heart disease had a birth prevalence rate of 8.07 per 1000 live births. In the study, 131 babies had acyanotic CHD, 93 had a minor CHD and 38 had a major acyanotic CHD. These yield birth prevalence rates of 4.58 per 1000 live births and 1.87 per 1000 live births.1 Prior to this particular study, there had been inconsistent data relating to CHD in newborns. The range found in literature was 1.3-13.28 per 1000 live births.1 This study allowed researchers to give a relatively accurate number that described the prevalence of CHD in babies born in Northern India. In this study, the birth prevalence of CHD in newborns delivered in Northern India was 8.07 per 1000 live births.1 Before the data was deduced, the researchers initially predicted that the prevalence would be similar to the rest of the world. Interestingly enough, the prevalence of CHD in newborns delivered in India was very close to the prevalence in the rest of the world.1 This research has many important implications because it highlights some of the problems faced by newborns in developing countries. Many of these countries lack significant medical/research funding, and the results may help certain hospitals/medical centers secure the critical funding they need to help future newborns that may suffer from a CHD.

 

Works Cited:

(1)      Saxena, A.; Mehta, A.; Sharma, M.; Salhan, S.; Kalaivani, M.; Ramakrishnan, S. 2016, 9 (3), 205–209.

 

Example of An Experimental Study

Effect of Wearable Technology Combined With a Lifestyle Intervention on Long-term Weight Loss: The IDEA Randomized Clinical Trial is an example of an experimental study. It is not single-blind or double-blind as both the participants and the researchers were aware of who received what treatment. The research question the researchers were trying to answer is whether, compared to standard behavioral weight loss intervention (standard intervention), technology-enhanced weight loss intervention (enhanced intervention), such as wearable technologies specific to physical activity and diet, are effective at improving weight loss and would result in greater weight loss. A sample of 471 adults at or around the University of Pittsburgh were representative of a population of people with a BMI between 25 and less than 40 and an age range of 18 to 35 years old. The participants were separated into two randomized groups and both would receive treatment. The first group received the standard intervention and the second group received the enhanced intervention. After concluding the study, the researchers concluded that as a result of the treatment, both groups had significant improvements in body composition, fitness, physical activity, and diet, but that there was no significant difference between the two groups. Although there were no significant differences between the two groups at the end of the study, I would argue that it was due to the nature of the study itself and that in an uncontrolled setting, the wearable devices would provide an improvement. In the study, both groups were provided with the support and incentive to stick with their diet and exercise, the wearable technology was designed to bring support and reminders to people without access to a traditional support group. Although the study didn’t show any distinct benefit of one approach to weight loss over another, it did further validate the need for a support group when attempting this sort of lifestyle change.

Differentiating patterns of prescription stimulant medical and nonmedical use among youth 10–18 years of age

The research question that was proposed in the experiment I studied was “Differentiating patterns of prescription stimulant medical and nonmedical use among youth 10–18 years of age.” The objective of this experiment was to asses the past 30-day prevalence of prescription stimulant use, report different forms of nonmedical use, and investigate different characteristics associated with Medical Users Only, Nonmedical Users Only, and youth who reported both medical and nonmedical use. The control group, thus in this experiment would be medical users, as one would assume that a medical user would be taking their prescription stimulants everyday. While, the youth who reported Nonmedical and both nonmedical and medial use served as the experimental groups. The experimental design of this experiment was set up to test 11,048 youth aged 10-18 years who were recruited from entertainment venues in 10 US cities. The recruited 10-18 year olds were recruited by the The National Monitoring of Adolescent Prescription Stimulants Study.

 

It was found from this study overall that 6.8% of the youth surveyed reported that they had used prescription stimulants in the past 30 days, ultimately with 3% reporting that they had used it for medical use only. While, the other 1.1% reporting both medical and nonmedical use and 2.5% reporting nonmedical use only. It can also be noted that 88.4% said they had tried other stimulants other than prescription stimulants. It was concluded in this experiment that youth that used prescription drugs for medical use and nonmedical use tended to have more conduct problem behaviors compared to medical users only and nonmedical users only. Although, from the experiment it was also concluded that the nonmedical users were more likely to have close friends who tried Adderall (prescription stimulant), endorsing illicit drug use.

 

From this experiment it can be known that there is some bias within the experiment, as this experiment does not necessarily speak for the general population of 10-18 year olds patterns with prescription stimulant use. For future trials, the researchers should survey people outside of entertainment venues such as schools in general opening a larger variability in the data within the sample population. Also, the researchers of this experiment should survey different cities across the world, because prescription stimulant use most likely varies all across the world, as in some parts of the world prescription stimulants aren’t even accessible.

 

http://www.drugandalcoholdependence.com/article/S0376-8716(15)01688-9/abstract

 

Experimental vs. Observational

The study titled, Metabolic effects of Carvedilol vs. Metoprolol in Patients with Type 2 Diabetes Mellitus and Hypertension, is a randomized control trial.   β-Blockers have been proven to decrease various cardiovascular risks such as hypertension and Type II diabetes in patients, so researchers wanted to investigate this further in this study. The investigators posed a research question to compare the effects of two different β-Blockers (Carvedilol and Metoprolol) in metabolic and glycemic control in diabetic patients with hypertension.  They gave diabetic patients with hypertension a RAS blockade (renin-angiotensin system blockade) to determine how it would effect metabolic and glycemic control in a context of cardiovascular risk factors.

The researchers used a double-blind design for this experiment.   This study targeted patients with hypertension and Type 2 DM with ages ranging from 36 to 85.  There was a sample of 1235 participants in the study, and the patients were monitored over the course of 35 weeks.  In the experiment, there were 2 groups formed.  One group received a Carvedilol dosage of 6.25 to 25 mg twice daily, and the other group received a Metoprolol dosage of 50 to 200 mg twice daily.  These ranges were dependent on the patients’ individual baselines.  Blood pressure and hemoglobin were monitored throughout the experimentation.

The researchers concluded that both of the β-Blockers were tolerated by the patients.  Carvedilol was more successful than the Metoprolol in regards to improving metabolic syndrome and not affecting glycemic control.  Researchers used the mean change in HbA1c and blood pressure measurements over the course of the 35-week study.  HbA1c was utilized as a marker, since it is linked linearly to the risk of cardiovascular complications in diabetic patients. To track the changes in the HbA 1c , Biostatisticians relied on confidence intervals and p-values  from the  mean HbA 1c , which they were then able to compare to a baseline measurement for each patient.  Researchers concluded that the use of β-Blockers in the presence of RAS blockers reduces insulin resistance, which leads to greater glycemic control.  Researchers were able to prove that levels of glycemic control do indeed predict cardiovascular events in patients with Type 2 DM and hypertension.

 

 

Reference:

Bakris GL, Fonseca V, Katholi RE, et al. Metabolic Effects of Carvedilol vs Metoprolol in Patients With Type 2 Diabetes Mellitus and Hypertension: A Randomized Controlled Trial. JAMA. 2004;292(18):2227-2236. doi:10.1001/jama.292.18.2227.

 

 

 

 

 

 

 

Example of Peer Reviewed Journal

The peer reviewed journal, “Consumption of a dark roast coffee decreases the level of spontaneous DNA strand breaks: a randomized controlled trial,” questioned whether or not the antioxidant constituents in dark roast coffees reduce the amount of DNA damage by preventing oxidation reactions in white blood cells (WBC). This was an experimental study that used a block-randomized design. To divide the individuals into the control and treatment group, they were first divided into two cohorts based on BMI (BMI <24.9 and BMI >24.9). Then, participants from each cohort were randomly assigned to either the control or coffee group. This ensured that each group would have around the same mean BMIs.

The population consisted of 84 individuals and each sample was n=42 in the control group and the treatment group. This was a parallel study, thus the control group and treatment group were studied at the same time. Prior to the intervention phase was a 4-week washout (WO) period where both the control and treatment groups received 750ml of water per day. Blood samples were taken after the washout phase to get a baseline reading of DNA damage in the participant’s white blood cells.  During the 4-week intervention phase, the control group received 750ml of water per day as a placebo because there were no sufficient substitutions for coffee, and the treatment group received 750ml of coffee per day. Blood samples were taken after the intervention phase to measure the amount of DNA damage in white blood cells.

The study found that consumption of dark roast coffee for 4 weeks was associated with a significant difference (p=0.0002) and reduction of DNA damage in white blood cells. The control group had an increase in DNA damage, concluding that it is the coffee constituents influencing the amount of antioxidant protection against free radicals.

Experimental vs. Observational Journal Article

Title of study: Nitrogen Loads to Estuaries: Using Loading Models to Assess the Effectiveness of Management Options to Restore Estuarine Water Quality

I chose an experimental study over how effective specific methods improve water quality in an estuarine system – specifically, Waquoit Bay, Massachusetts. The methods tested were diverting nitrogenous runoff from impervious surfaces, changing zoning ordinances, preserving forested tracts of land and wetlands, harvesting macroalgae, dredging estuary channels, and eradicating waterfowl.

This article is an example of using an experimental method because it is a case study using a control, dependent and independent variables. The researchers manipulated the subjects in order to find the effects and get results. Most of the results were shown as numeric values represented in graphs and tables.

Land cover data was obtained to show the amount of nitrogen released as well as amount of nitrogen that remains in the Walquoit Bay. The results for the effectiveness of each method were gathered differently because they were not related. For instance, the method that reduces fertilizer inputs is to add different dosages of fertilizer to farms, lawns and golf courses, whereas the method for preserving vegetated tracts is to use NLM to calculate nitrogen amounts from a hypothetical forested plot and comparing it to other areas (ie a golf course, residential area, etc.).

The researchers concluded that the methods holding the most potential in lessening the nitrogen loads in Walquoit Bay – as well as other estuaries – include improvement of the septic system, having zoning regulations, preserving forested tracts and freshwater bodies, and conserving salt marshes. The methods that are somewhat less promising in reducing nitrogen loads are through installing wastewater treatment plants, regulating the use of fertilizer, and harvesting macroalgae. Those that would be the least successful are diverting runoff from impervious surfaces, dredging, and eradicating waterfowl. It is mentioned that these methods are focused on this particular region and that similar studies should be done on other estuaries. Each estuary is different, therefore may react differently to each method.

(Bowen, J. L., & Valiela, I. (2004). Nitrogen loads to estuaries: Using loading models to assess the effectiveness of management options to restore estuarine water quality. Estuaries, 27(3), 482-500. doi:http://dx.doi.org/10.1007/BF02803540)

Fatty Acids vs Skin Triglycerides

The research question being tested in this experiment was “How do dietary factors such as glycemic load and fatty acid consumption impact the presence of acne?” This experimental design was subject to be tested on thirty one male acne patients between the ages of 15 to 25. This was an experimental control, as both parties were aware of the treatment being imposed. They were then separated respectively into control and experimental groups. The experimental treatment was a low glycemic load diet consisting of energy from protein and carbohydrates of a low glycemic index, with portion sizes being monitored. The control group on the other hand was treated with carbohydrate-dense foods that didn’t take into account their glycemic index or the amount being eaten. This experiment was conducted over a 12-week period, with acne lesion counts assessed monthly, as well as before beginning.

Results from the experiment proved that there was in fact a relationship between the fatty acid and glycemic load intake on sebum production and acne. After only 12 weeks, the men subjected to high fatty acid diets experienced increased levels of follicular sebum outflow, as well as increased proportion of fatty acids in sebum, when compared to the experimental group. They also experienced a higher ratio of saturated to monosaturated fats of their skin surface triglycerides, which has a direct correlation to the formation of acne.

These results do not speak for the entire acne ridden population, mostly because of sampling error. Though it does not mention how the sample was taken, using 31 male acne patients would most likely not be representative of the overall population. This can be due to a number of factors ranging from differing diets in males and females to how different foods impact each sex. The information however is still beneficial to us as it does give some insight on the impact our diets may be having on our skin. With further work, this can be a very valuable study!

 

https://www.ncbi.nlm.nih.gov/pubmed/18178063

Observational Study

The study I examined is Sex Differences in Reported Pain Across 11,000 Patients Captured in Electronic Medical Records. This study seeks to answer the research question, “Do women feel more, less, or equal pain than men.” The study was a retrospective study analyzing 11,000 patients charts from Stanford area hospitals and clinics divided into groups by gender (56.2% female, 43.8% males). The study excluded children. The cases were stratified by disease and the patient reported pain scores were compared for those diseases with at least 41 patients of each gender.
The researchers collected data from a variety of medical practices in the Stanford area. They then took only the pain scores, disease, and gender from the case. The data was then analyzed using several method including a t-test. Through maintaining a large n, the study was able have a study on a larger scope than any other previous to it. Such a study wouldn’t have been possible to complete experimentally without great cost so a retrospective study was highly useful.
The pain score of the female group was higher for musculoskeletal diseases and respiratory diseases. This supported other gender based pain study’s findings. Several potential problems with this study were that it doesn’t apply to pediatric patients. Additionally, some pain scores started as a 0-5 scale and others as a 0-10 scale in mixing these scores could have caused complications. This study suggests that more research should go into such studies on the experience of pain including tests that are more experimental rather than observational as this one was in order to determine which gender experiences more pain given the same amount of stimulus. Still this study was highly effective due to the very large sample size.

References:
Ruau, David et al. “Sex Differences in Reported Pain across 11,000 Patients Captured in Electronic Medical Records.” The journal of pain : official journal of the American Pain Society 13.3 (2012): 228–34. Web. 22 Sept. 2016.

Blog Post 2: Biostatistics for Obesity and Social Media

The article “You Are What You Tweet: Connecting the Geographic Variation in America’s Obesity Rate to Twitter Content” was published by the Virginia Modeling, Analysis and Simulation Center, the study was performed by Ross Joseph Gore, Saikou Diallo and Jose Padilla. The main purpose of their study was to understand the relationship of the obesity rate of a certain area and the expressions shown in social media in the areas of happiness, diet and physical activity. They developed an observational study, which is one that looks into a sample of population but does not hold control of the variables. This observational study had a retrospective approached which looks at occurrences of the past. The focused on the Twitter social media from 2012 to 2013 and created a geo-tagged data to be able to compare it with the obesity levels.  The date they collected was a 10% random sample of all the tweets in 2012-2013 and 1.5% of the tweets were geo-tagged resulting in 25 million geo-tagged tweets.

They used language assessments methods to conclude the measurement of happiness, of diet and of physical exercise in a Tweet, these tools were also helpful to target the specific 189 regions of the United States that they were including in there study. With the tools they were able to confirm that the areas in the United States that have lower obesity rates have happier tweets and are more likely to discuss topic in food that involve fruits and vegetables. The tweets from lower obesity rates areas show that they talk about various types of physical activity that include various levels of intensity. They also concluded that from the data recovered from this observational study they believe that social media can be used potentially to estimate real-time populations measurements that create a scale of factors that are related to higher obesity rates in those areas.

 

References:

Gore, Ross Joseph, Saikou Diallo, and Jose Padilla. “You Are What You Tweet: Connecting The Geographic Variation In America’S Obesity Rate To Twitter Content.” Plos ONE 10.9 (2015): 1-16. Academic Search Premier. Web. 22 Sept. 2016.