CNUR600 TEST#3 PRACTICE STUDY GUIDE WITH VERIFIED SOLUTIONS 2023-2024 GRADED A, Exams of Nursing

Download CNUR600 TEST#3 PRACTICE STUDY GUIDE WITH VERIFIED SOLUTIONS 2023-2024 GRADED A and more Exams Nursing in PDF only on Docsity! 1 CNUR600 TEST#3 PRACTICE STUDY GUIDE WITH VERIFIED SOLUTIONS 2023-2024 GRADED A WEEK 9: 1. A diagnostic test sounds like a laboratory test, but refers to clinical information collected by which of the following methods? a. comprehensive client history b.physical examination c. imaging procedures d.all of the above 2.Blood pressure is used in a diagnostic procedure to determine whether or not a client has hypertension and is measured on an interval scale to the nearest 1 mmHg. Which of the following blood pressure readings might indicate "stage 1 hypertension"? a. 120/80 mmHg b.134/86 mmHg c. 163/101 mmHg d.100/70 mmHg 3.True or false: Diagnosis results in a probability rather than a certainty of being right. a. True b.False 4.Simplifying Data Clinical measurements, including data from diagnostic tests, are expressed on , , scales nominal, ordinal, or interval ○i.e. A simple ordinal scale -grades I to VI for heart murmurs, instead of expressing subtle gradations in the intensity of murmurs 5.The Accuracy of a Test Result - Establishing diagnoses is an imperfect process, resulting a probability rather than a certainty - In the past, doctor's diagnostic certain or uncertainty was expressed by using terms such as rule out or possible before a clinical diagnosis 6.The Gold Standard - used to identify an accurate test that can be considered the proxy diagnostic test to best indicate the presence or absence of disease. 2 7. For diseases that are long-term and chronic in nature...... - a variety of tests considered as "whole" can serve as a gold standard. For example, for most types of cancers, there is no one definitive test to prove that a client has cancer 8.When There Is No Gold Standard... - Sometimes there is no perfect test to accurately diagnose a disease. Angina pectoris is an example of this. Even though angina was first identified over 100 years ago, it is still accepted practice to identify this condition after conducting a careful history and at least one or more tests 9.True Positive (TP) - the patient has the disease and the test is positive. 10.False positive - the patient does not have the disease but the test is positive. 11.True Negative (TN) - the patient does not have the disease and the test is negative 12.False negative - the patient has the disease but the test is negative 13.Diana has hypoglycemia but her blood tests came back normal. What type of result is this an example of? a. true positive b. false positive c. false negative d. true negative 14.The nurse practitioner reviews a client's recent pregnancy test. The urinary test from over the counter shows that the client is pregnant; yet the serum hCG levels are 3.2 mIU/ml. What is this an indication of? a. true positive b. false positive c. false negative d. true negative 5 WEEK 10: 1.Sensitivity Overview Does the test detect true disease (TP) High sensitivity = High TP Low sensitivity = High FN With a high number of FN you have LOW negative predictive value (NPV) 2.Specificity Overview Does the test detect those who do not have the disease (TN) High specificity = High TN Low specificity = High FP With a high number of FP you have LOW positive predictive value (PPV) 3.A test with a high sensitivity will yield - a high true positive rate. 4.A test with a low sensitivity will yield . - a high false negative rate 5.When we have a test that produced a high false negative rate (which is the people who are really positive, but score negative) - you end up with a low negative predictive value. 6.A test with a high specificity then it will produce. - A high true negative rate 7. If we have a test with low specificity - Then it will produce a high false positive rate (the people who are really negative for the disease but score positive) 6 8.When we have a high false positive rate for a test then that means that - the test has a low positive predictive value. - As a result, the test is not that great at identifying patients who truly have the disease. 9.When we administer a screening test to many people in the population, what do you think will happen to the incidence? - Well, the incidence rate will go up, or increase, because you are identifying more people who were living with the disease but they didn't actually know they had the disease until they took the screening test 10.When we have a disease with a low prevalence like Xeroderma pigmentosum - then our positive predictive value (the ability to predict positives) will also be low. But if your test has poor specificity, you won't be detecting more true positives - you will end up identifying more false positives, so these are the people who do not have the disease but score positive. Hence, your specificity value is important to think about. 11.Screening programs - Screening programs have a long history in helping to identify and control epidemics and target treatment for chronic disease (Institute of Medicine, 1999). 12.In Ontario, Cancer Care Ontario - is an organization funded by the government to carry out cancer screening initiatives for breast, cervical, and colorectal cancer. The screening process begins with a letter inviting eligible Ontarians to get screened for breast, cervical or colorectal cancer 13.Purpose of Screening Programs - Screening is often implemented to identify cases of disease (usually before the client is symptomatic), to conduct surveillance (monitoring the incidence and prevalence of a disease), and to provide appropriate interventions for those identified as needing treatment (IOM, 1999). - Screening programs are also completed for controlling disease (prospective disease), research purposes (evaluating the effectiveness of screening) and for educational purposes (increasing public awareness about a health condition) 14.The classic screening criteria proposed by Wilson and Jungner in 1968 as cited in Andermann et al., 2008 were: 1.The condition sought should be an important health problem. 2.There should be an accepted treatment for patients with recognized disease. 7 3. Facilities for diagnosis and treatment should be available. 4.There should be a recognizable latent or early symptomatic stage. 10 - Involves assessing groups of people because they are known to have a specific risk factor for a disease 27.Targeted screening Example - To implement part of this screening at airports for all incoming flights - especially for foreigners who were entering the country 28.Systematic screening An example of this is if you received a letter from the Ministry of Health and Long-Term care inviting you for a Pap test (if you're a women) or a colonoscopy. 29.Case finding, which is also known as opportunistic screening - When the health care provider carries out the screening when the opportunity presents itself. 30.Opportunistic screening Example - Suppose you visit your family physician or your nurse practitioner and your chief complaint is say, feeling short of breath and light headed. Your practitioner might take your blood pressure and identify that you have a blood pressure of 130/95 mm/Hg and then you get weighed on the scale and you've found you've 30 lbs in the last year. 31.Critique of Screening Programs (Disadvantages) - Recent evidence suggests that mass screening programs, especially multiphasic screening at the population level, are expensive and not necessarily good in terms of maximizing health care resources. - The problem is exacerbated by using screening tests with low sensitivity and/or low specificity 32.Critique of Screening Programs (Advantages) - Recent evidence-based guidelines suggest that annual health exams or "opportunistic" screening may be most beneficial because health care providers can monitor clients, provide follow up treatment, and assess ongoing adherence to treatment regimens (Canadian Foundation for Healthcare Improvement, 2017). WEEK 11: 11 1.Principles of Causality - causation requires the factor to be present for the outcome (e.g., disease) to occur; - an adverse outcome might be related to a multitude of factors; and that when we identify - an association between two factors, it does not mean causation. 2.What is an example for "Causation requires the factor to be present for the outcome"? - If the outcome is a car accident, I have to be driving or in the car before it happens. 3.What is an example for "an adverse outcome might be related to a multitude of factors"? - If the outcome is a car accident, then the factors occurring might be a) texting, b) driving too fast, c) not alert to the driver stopping suddenly in front, and/or d) swerving unexpectedly because a tire fell off a nearby truck. 4.What is an example for "when we identify an association between two factors, it does not mean causation"? - If the outcome is a car accident, then it is possible that texting while driving and driving too fast are associated with one another, but it does not mean that they caused the accident. Likewise, texting while driving and driving too fast are associated with the accident occurring, but may not have caused the accident. 5.History of Causation (Christian) - At one point many scientists believed that disease and other events were caused by a higher power. 6.History of Causation (John Snow) - John Snow and the Cholera outbreak, in the Victorian period the prevailing thoughts on causation related to "miasmas," which were toxic vapours from filthy cesspools of water. 7.History of Causation (Hippocrates) Time of Hippocrates where disease was caused by the humours - bile, phlegm, and blood. 8.History of Causation (Holmes) 12 - In 1843, Oliver Holmes, a professor at Harvard Medical School, identified that if obstetricians washed their hands, they could reduce the spread of puerperal fever - a fatal post-childbirth disease. 9. "Henle-Koch Postulates". These postulates, grounded in germ theory, were: - Bacteria must be present in every case of the disease - Bacteria must be isolated from the host with the disease or be grown in pure culture - Specific disease must be reproduced when a pure culture of the bacteria is inoculated into a healthy susceptible host; and - Bacteria must be recoverable from the experimentally infected host. 10."Henle-Koch Postulates" Limitation - But by the mid-20th century, non-infectious disease was receiving more attention, and these criteria were limited in their application to all disease. - Multi-variant causality such as Chronic Disease 11.Multiple Causes - The iceberg theory, not everyone who is exposed to the disease becomes infected with tuberculosis. - But it is too simplistic to believe that every disease has just one cause. - Heart disease, which we learned about in earlier modules, has multiple causes, from cigarette smoking, hypertension, hypercholesterolemia, diabetes, inflammation, and heredity Web of Causation When many factors come together to create disease - which is clear for degenerative disease or chronic disease like cancer, but is also possible for infectious disease such as HIV and AIDS 12.A "web of causation" is - a graphic, pictorial, or paradigm representation of complex sets of events or conditions caused by an array of activities connected to a common source or event 13.David Hume - In the 18th century, David Hume argued that causation was a concept that required logical induction. This means that we can never know for sure if exposure or risk factor X causes disease Y. Causation can be inferred by observing the variables over time 14.Karl Popper 15 Diabetes occurs after the client has the following risk factors: obesity, elevated HbA1c, weight loss and unusual fatigue, and hypertension Temporality 29.Causal inference is - a conclusion about the presence of a health-related state or event and what factors influence its presence, such as environmental, physical, psychosocial, or even social factors. 30.Causal inferences are based - on the scientific examination of a health issue, which includes developing a hypothesis or prediction that is based on data and can be demonstrated through formal methods for analysis 31.Direct causal association - the source has a direct effect on the outcome. For example, if you cut your finger while chopping vegetables, you can bleed. If you eliminate the exposure (chopping with a sharp knife), you eliminate the adverse health outcome (the need for a band-aid). 32.Indirect causal association - involves one or more intervening factors and is often more complicated to identify just one causal factor. For example, having a high-risk pregnancy and an arrest of dilation may lead to a prolonged labor and fetal distress, which in turn could result in a cesarean section. Indirectly, the high-risk pregnancy and the inability to dilate could result in a cesarean section when the labor does not progress and fetal distress develops 33.For causation to occur - it is necessary to eliminate the possibility that the result occurred due to bias or chance (spurious association, error in judgement)- As a result, choosing a study design with high methodological quality and strong internal validity will help to reduce the possibility that the results are due to chance or bias. 34.Rothman's Sufficient-Component Cause Model 16 - Consider that the cause of disease is an event, condition or characteristic that preceded the disease and without it (the cause), the disease would either not occur or occur later in time - Each disease needs to have a "sufficient" cause to occur, meaning a set of conditions that come together to create the optimal conditions for disease to occur. 35.According to Rothman's model, there are four possibilities that could occur: 1.Necessary and sufficient - where the risk factor is both necessary and sufficient to cause the disease; 2.Necessary, but not sufficient - where the risk factor is necessary for disease to occur but not sufficient alone to create disease. Often more than one risk factor needs to be present and sometimes in a temporal sequence. 3.Sufficient, but not necessary - where the risk factor should be sufficient to cause disease, but so can other factors acting alone. The factor when considered alone is not the only one to cause disease. 4.Neither sufficient nor necessary - where the factor is not sufficient enough to cause disease and therefore not necessary to be present for the disease to occur (Gordis, 2014). 36.A group of individuals eat salsa that has been infected with clostridium botulinum at a local restaurant. Within the normal incubation period, those that ate the salsa develop botulism. Eating the infected salsa was an example of? a.Necessary and sufficient cause for disease b.Necessary but not sufficient cause for disease c.Sufficient but not necessary cause for disease d. Neither sufficient nor necessary cause for disease 37.All women who have had a hysterectomy cannot become pregnant. Hysterectomy is sufficient to prevent pregnancy, but not everyone obtains a hysterectomy when they do not want to become pregnant. a. Necessary and sufficient cause for disease b.Necessary but not sufficient cause for disease c. Sufficient but not necessary cause for disease d.Neither sufficient nor necessary cause for disease 17 38.An individual comes to the nurse practitioner clinic for an annual check up. She is obese but has an H1Ac that is within normal range. The nurse practitioner believes the client to be at risk for diabetes. a.Necessary and sufficient cause for disease b.Necessary but not sufficient cause for disease c.Sufficient but not necessary cause for disease d.Neither sufficient nor necessary cause for disease 39.All individuals with three copies of the 21st chromosome will develop Trisomy 21. a.Necessary and sufficient cause for disease b.Necessary but not sufficient cause for disease c.Sufficient but not necessary cause for disease d.Neither sufficient nor necessary cause for disease 40.Not all individuals who smoke will develop lung cancer. Not all lung cancer cases are smokers. Therefore, smoking alone does not cause cancer. a.Necessary and sufficient cause for disease b.Necessary but not sufficient cause for disease c.Sufficient but not necessary cause for disease d.Neither sufficient nor necessary cause for disease