The Heart Attack Study Data And R Studio Software Essay

You need to explain to him the s/s of blood clotting (since he may have too low an INR d/t treatment and he needs to know this). Explain that his a-fib puts him at risk for blood clots.

This study used a descriptive, correlational, comparative and quantitative design to determine the probable causes of heart failure readmissions (Anderson, 2014). Independent t tests were used to the characteristics between those individuals that were readmitted and those that were not. Correlation coefficients were examined using the Pearson product-moment and the Spearman ρ test to determine the indications for readmission. (Anderson, 2014). Once these were established the Hosmer and Lemeshow tests were used in binary logistical regression analysis to determine how well each predictor variable determined the probability of readmission. Using these tests, the results showed that P=0.599, indicating that the model adequately fits the data (Anderson, 2014). To add to this, further proving the study’s validity, a hierarchical approach was preferred because “entry of variables is based upon an evaluation of theoretic, clinical, and statistical considerations” (Anderson, 2014, p. 234). This allowed for the assessment of predictive ability. This study through multiple statistical tests proved strong validity in its data collection, research design, and measurement

The right ventricle fills up  tricuspid valve closes  right ventricle contracts  pulmonary valve opens  the blood flows into the pulmonary artery  pulmonary valve closes  pulmonary artery splits into two vessels each going to the lungs.

physical release of all the energy built up in the body does not actually take

Accurate data mining works wonders for medical billing agencies to improve their level of service and collection. With new and improved innovations being incorporated in medical billing software, unique reports can be executed that help in providing specific information which then assists in decision making and implementing improvements.

Coronary Heart Disease Coronary heart disease remains the most common cause of death in the United Kingdom. A statistic from the American Heart Association is that heart disease claims a life every 24 seconds. [www.americanheart.org] Another is that it is the largest single cause of premature death in the United Kingdom, responsible for 180 000 deaths annually. [www.americanheart.org]

These measurements include the assessment of risk factors[61], quality of care[62], diagnostic criteria[63], etc. Most of these studies used rule-based method[62, 63] to detect clearly defined and less complex (fewer expression variations) measurements, such as glucose level and body mass index. For some ambiguous and complex measurements, such as coronary artery disease and obesity status, machine learning plus external terminologies[61] are often

The third article I found talks about the prediction of Perioperative Cardiac Complications and Mortality using the Revised Cardiac Risk Index (RCRI). The RCRI discriminated well between patients at low versus high risk for cardiac events after mixed non cardiac surgery, but did not do well at predicting deathly outcomes derived from cardiac arrest. I need something that helps to predict deathly outcomes, because I stated at the beginning of the paper my problem in reality is not the incidence of cardiac arrests, the main problem is the mortality. Therefore, I need to find something better, and fortunately I found it in

The National Heart Foundation of Australia (2014) estimated that more than 350,000 Australians had experienced heart attack at some point in their lives, and about 54,000 cases are reported annually. In a statistical report circulated by Wong et al., (2013), more men than women who ages 30 to 65 years old, account of encountering this life-threatening disease in the last five years. This had claimed the lives of 8,611 Australian nationals in 2013, or in a mean of 24 people die every day (Wong et al., 2013).

Hospital Readmissions are costly to the government, hospitals, and patients. Some of these pricey readmissions can be avoided by providing the appropriate care for the patients that are at a higher risk of readmission. Many studies have used predictive analytical approaches to discover which patients are more likely to be readmitted. Most of said studies use some form of regression to analyze all patients. We took a different route and used an advanced decision tree (Gradient Boosted Tree) as we found it to be more fitting for the data we collected. With COPD as a constant factor in our patients, we were able to develop a specific model for a subsection of all hospital readmissions. With COPD being a fix variable, our model was able to dig deeper into other

Project: “Pulmonary Function Testing and Prognosis in Heart Failure Patients Listed for Heart Transplantation”. The study examined the prediction power of spirometric variables on the prognosis among HF patients listed for heart transplantation. During this experience, I was actively involved in data collection, data entry and result analysis. I also had hands-on experience in the conduct and administration of the clinical research study protocol. The data were published in Cardiac Failure Journal August 2014 and had presented at the 18th Annual Scientific meeting of the Heart Failure Society of America, November 2014.

Heart disease and stroke statistics—2017 update: a report from the American Heart Association, January 25, 2017].Circulation. doi: 10.1161/CIR.0000000000000485.

During inspection of the heart assessment observe abnormal finding. Inspect the jugular vein and the carotid artery. Note pallor or cyanotic skin color, temperature, turgor, texture, and clubbing of finger. Observe for swelling, edema and ulceration. Clubbing is a sign of chronic hypoxia caused by a lengthy cardiovascular or respiratory. Poor cardiac output and tissue perfusion is noted by cyanosis and pallor. For dark-skinned, inspect his mucous membranes for pallor. Decreases or absent of pulse with cool, pale, and shiny skin, and hair loss to the area, and the patient may have pain in the legs and feet may indicate arterial insufficiency. Ulcerations typically occur in the area around the toes, and the foot usually turns deep red when dependent

It is the time of progress. The time of supercomputers, space shuttles, and many other wonders of technology. We have walked on the moon. We do our shopping at home via Internet navigation.

As the population ages heart failure is expected to increase exceptionally. About twenty-two percent of men and forty-four percent of women will develop heart failure within six years of having a heart attack. “Thirty years ago patients would have died from their heart attacks!” (Couzens)