Chapter 7 summarized

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The text describes the period of luxury and indulgence in America after World War II and how heart disease emerged as an epidemic despite the increased affluence . The Framingham Heart Study, initiated in 1948, aimed to observe a large population of healthy adults over time to understand the factors contributing to heart disease. The study collected data on over 80 variables about 5,209 people before the age of computers, and the data has been used in more than 2,400 studies. The Framingham Heart Study is considered one of the top 10 cardiology advances of the twentieth century. 7.1 Early Misconceptions The text explains the misconceptions about high blood pressure in 1948 when physicians believed that high blood pressure was a natural part of aging. The Framingham Heart Study aimed to understand the factors contributing to heart disease. The text also explains the case of President Roosevelt, who died from heart disease in 1945. His personal physician hid Roosevelt's deteriorating health from his family and the public, and it's unclear whether this deception was due to medical ignorance or a deliberate cover-up. Roosevelt's death served as a wake-up call, leading to a massive research effort to understand the causes of heart disease . Today, high blood pressure is treated with medication to reduce the stress on artery walls. 7.2 The Beginning of the Study The text describes the beginning of the Framingham Heart Study in 1948. The study aimed to track a large cohort of initially healthy patients over time to understand the factors contributing to heart disease. The town of Framingham, Massachusetts was selected due to several reasons, including its population stability and willingness to participate, and its proximity to Boston, a city with several prestigious medical schools and research institutions. The study recruited 5,209 men and women between the ages of 30 and 59, which was surprising for the time as medical science believed women were immune to heart disease. Researchers later discovered that women were not immune, but acquired it at a lower rate than men . The study aimed to discover the role of family history, smoking, drinking, obesity, inadequate sleep, high blood pressure, or high cholesterol in the development of heart disease. The Data The Framingham Heart Study began in 1948 and involved collecting data on 80 different variables from 5,209 volunteers every 2 years. The collected data included personal and family history of disease, physical measurements, and samples of urine and blood. The study expanded over time to include additional risk factors such as physical activity and genomic information. The Framingham Heart Study is now in its seventh decade of collecting and analyzing data, and it has since started the Framingham Offspring Study in 1971, which follows the children of the original volunteers, and the Third Generation Study in 2002, which follows the grandchildren of the original volunteers. First Findings The first paper from the Framingham Heart Study was published in 1957 after ten years of study, reporting surprising results such as the rate of heart disease in women and high blood

pressure and high cholesterol as risk factors for heart disease. In 1961, another paper from the study showed that heart disease could be prevented by detecting and treating certain risk factors. 7.3 The Framingham Risk Score The Framingham Heart Study involved collecting data on over 80 different variables every two years from a cohort of healthy volunteers between the ages of 30 and 59, beginning in 1948. The study produced groundbreaking research, including the discovery that high blood pressure and high cholesterol are risk factors for heart disease. The statisticians working on the project developed multivariate analysis, which is now a core method used in virtually every epidemiology study. In 1998 , the Framingham Risk Score was developed, which allows physicians to predict an individual's 10-year risk of developing coronary heart disease using a simple prediction algorithm. This score is based on a multiple logistic regression model, and a points system has been developed to make the model more useful to practitioners. The data used to build the models described in this chapter can be downloaded from the online companion for the book. The Data, Variables, and Model This text describes the development and evaluation of a logistic regression model called the Framingham Risk Score, which predicts an individual's 10-year risk of developing coronary heart disease (CHD) based on age, gender, systolic blood pressure, diabetes, and smoking status. The model was developed using data from the Framingham Heart Study and was trained and tested on separate subsets of the data. The model's performance was evaluated using a Receiver Operator Characteristic (ROC) curve, which shows the trade-off between false positives and false negatives. The model achieved an area under the curve (AUC) of 0.72, indicating promising results for clinical prediction models. The text also discusses the trade-off between false positives and false negatives and presents a classification matrix showing the model's performance on the training set. Overall, the model can help physicians prioritize which patients to treat, and it can be further improved with more detailed data and advanced methods. A Points System The text describes the development of a points system for predicting the risk of developing coronary heart disease (CHD) based on risk factors such as age, blood pressure, sex, diabetes, and smoking status. The risk factors are organized into meaningful categories with assigned reference values, and a base computation is made by adding up reference values that represent low risk. A "Logit Units" column is then produced by multiplying the difference in reference value from the base value by the corresponding logistic regression coefficient for each variable. The Logit Units column is scaled and rounded to produce integer points values using a five-year increase in age as the scaling factor. The Logit equation is used to compute an estimate of the Logit for a given points value, and the probability of developing CHD can be computed using this estimate. Variable Category Reference Base Diff Logit Units

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