- Researches have proposed that 5% of the over 55 population have CAD. You areworking with a colleague who believes that you should screen at your health center allpatients over 65 with the lipid sniff test.. This test has reported a sensitivity of 33 -78% anda specificity of 70 – 93%. Construct two 2×2 tables and calculate the PPV, NPV, for theworse (sensitivity 33%/ specificity 70%) and best case-sensitivity and specificity of thistest (sensitivity 78%/ specificity 93%). Please show the equations, your calculations, andplace your answers in the tables below. What would you recommend to your colleagueabout screening for dementia using this test and explain your answer?
N=1,000
NPV = d
c+d
= 630
67 + 630
= 630/ 697
= 0.90
PPV = a
a + b
= 33
33+270
= 33/ 303
= 0.119
NPV = d
c+d
= 837
22 + 837
= 837/ 859
= 0.97
PPV = a
a + b
= 78
78 + 63
= 78/ 141
= 0.553
Both NPV and PPV are seen to provide clinical relevance to a test. They are crucial because they use the prevalence of a condition to determine the possibility of a test that diagnoses that particular disease. Sensitivity and specificity are important measures in the diagnostic accuracy of a test, but they do not estimate the probability of a disease in an individual patient. PPV and NPV, on the other hand, are estimates of the probability of a disease, but they both vary according to the prevalence of a disease.
- “(Routine CT scans for smokers) yielded an estimated 10-year survival rate of more than90%, researchers said.Currently, about 5% of the 174,000 lung cancer patients diagnosed each year survive for ten years…_.” Efficiently use concept(s) from Welch’s lectures to explain this finding.
This statement shows the possibility of curing patients early of lung cancer and using CT scans to find the disease. The results are astonishing! That a CT scan for smokers can increase the survival rates of lung cancer patients from 5 to 90% is unbelievable, and the question to ask is, does this prove that the scans work?
This can be determined by understanding the survival rate:
In this case, the survival rate is 10-years, which is the proportion of people diagnosed with lung cancer that is still alive after 10 years. Take, for instance, 10,000 people were diagnosed with lung cancer 10 years ago. If 500 of them are still alive today, then the survival rate is 500/10000, which is also 5%, and if 2,000 of them are alive today, the survival rate will be 5,000/ 10,000, giving us 50%. Yet, even if the survival rate increased to 50%, none of the diagnosed patients may live an extra day. The understanding is, some patients are diagnosed early enough, and they may survive more than ten years after the diagnosis. Still, patients who are diagnosed late have zero chances of survival.
- See the above forest plot:
Demonstrate your mastery of reading forest plots by explaining each line in detail. What dothese results indicate?
The data provided in the above forest plot on the effects of antiplatelet therapy on women with gestational hypertension events were available from five trials and included 1643 participants and 193 events. The overall, compared with the usual care control or placebo groups, the antiplatelet therapy produced a 40% reduction on the odds of the gestational hypertension events, or 0.60; 95% CI, 0.45 – 0.78; P = 0.0033, without evidence of heterogeneity in the results of the individual trials since I2 = 74%, and heterogeneity is = 15.63. According to Clasp (1994), 46 events were recorded of 667 participants in which the risk of gestational hypertension was not altered by antiplatelet agents (0.92; 95% CI, 0.63 – 1.36). For India (1994), however, antiplatelet agents helped reduce the odds of gestational hypertension by 79% (0.21; 95% CI; 0.09 – 0.19). The same case applies to India (1999), where antiplatelet agents reduced the occurrence of gestational hypertension. In Israel (1990), the risk of gestational hypertension was not altered at all by antiplatelet agents, although there was a clear effect in the UK (1992).
- E-cigarettes vs. nicotine replacement therapy (NRT) for smoking cessation
The rate of sustained one-year abstinence in the e-cigarette group was 18% while that for the nicotine-replacement group was 10% (RBI 0.83; 95% CI 0.3 to 1.58). The absolute difference existing between the e-cigarette and the nicotine-replacement group is eight percentage points. This results in a number that is needed to treat for an additional person. The results do not change significantly for the four risks. However, abstinence rates are higher in the e-cigarette group than the nicotine-replacement group at all the different time points.
The study also shows that cough and phlegm were higher in the nicotine-replacement group than the e-cigarette group, which is an indication that replacing nicotine had greater health impacts than resorting to e-cigarette. The relative risk for phlegm, however, was higher than that of cough for both groups. It is also evident that the severity of the urge at one week was higher for the NRT group than for the e-cigarette group, and it remained higher even after four weeks. The relapse rates and time to relapse at 52 weeks for subjects with sustained abstinence at four weeks did not record a significant difference between the two groups
What is evident, however, is that the mean difference between the two groups decreased as time increased, although the time provided is a bit limited in helping come up with a conclusive answer.The table also indicates that the participants reported a reduction by at least five cigarettes from the two weeks following their quit date, and an expired carbon monoxide level (<8ppm). There were also reports of no-smoking from two weeks after the quit date and expired carbon monoxide level <8ppm at four weeks.
- Demonstrate your understanding of the two principal forms of reasoning. What is thedifference between inductive and deductive reasoning? How do you identify which formof reasoning you are implementing? How would this affect patient care?
Two types of reasoning exist, including inductive and deductive reasoning. I understand inductive reasoning as reasoning in which the premises support the conclusion, which is the hypothesis. This means that the conclusion is reasoning that inductive reasoning intends to prove. An example is where Kelvin, a firstborn, believes that all firstborns marry before their siblings. He argues that his cousin, who is a firstborn, married before his siblings, his father married before his younger brothers, and his friend, James, also married before his siblings. This is a generalized conclusion that all older brothers marry before their siblings. Deductive reasoning, on the other, is reasoning where true premises develop a true and valid conclusion. In this case, the conclusion is only true if the premises are true. Deductive reasoning uses general principles to develop a certain conclusion. It is also known as top-down reasoning in that it starts from the general, working its way down to specifics. An example is that “all cars have engines, and I have a car. Therefore, my car has an engine.”
One can differentiate between the two forms of reasoning by understanding that while deductive refers to the outcomes of a set of conditions, inductive is concerned with determining the probability of an outcome. Yet, it is important to understand that only possible conclusions can be drawn since not all conditions that influence or determine the outcome of a certain situation are known.
- In fewer than 100 words, discuss the concepts of Bayesian thinking.
Bayesian thinking takes into consideration not only want the data says but what the expertise says as well. Bayesian thinking is based on the idea that more is known about a physical situation than what is contained in data gathered from a single experiment. It is therefore advisable that decisions are made based on prior information about a certain situation, and new evidence from collected data.
- See the above graphic: 02 therapy
“In acutely ill hospitalized patients, an international panel strongly recommends thatSpO2 be maintained at no higher than 96% in patients with stroke or M.I., they suggestnot starting oxygen therapy for Spo2>90%.”
You are preparing an information session for your staff about this issue. Please use theabove graphic to develop a brief bulleted handout in simple language summarizing thisinformation.
- The hospital provides supplemental oxygen to patients admitted regardless of oxygen saturation in their blood.
- This table shows that too much supplemental oxygen can increase the mortality for patients admitted in hospital,
- The patients receiving oxygen therapy should receive peripheral capillary oxygen saturation (SpO2) of less than or equal to 97%.
- The target range of peripheral capillary oxygen saturation range of 92% seems to be okay for most patients and 90% for patients who are at risk of respiratory failure. It is always better to use the minimum amount of oxygen possible.
- Finally, acutely ill patients and those suffering from myocardial infarction and stroke, oxygen therapy should not go above 90%.
- See the graphic below (Poorly diagnostic findings). This is poorly diagnostic findings incommunity-acquired pneumonia, explain why the same physical exam findings of crackles anddecreased breath sounds have poor sensitivity and specificity. Yet, they are considered to have a good likelihood ratio. Please explain each line.
The above diagnosis shows that the Crackles have a sensitivity of 50%, specificity of 81%, LR+ of 2.6, and an LR- of 0.6. The decreased O2 saturation has a sensitivity of 52%, specificity of 80%, LR+ of 2.6, and LR- of 0.6. It also showed that decreased breath sounds had 48% sensitivity, 81% specificity, 2.5 LR+, and 0.6 LR-. The explanation behind the findings of crackles and breathing sounds having poor sensitivity and specificity, and a good likelihood ratio may be first, pneumonia patients with crackles may be sicker than those without, and are therefore likely to be admitted and frequently. Atypical pneumonia, on the other hand, means low sensitivity to crackles as opposed to patients with pneumococcal pneumonia. The second explanation may mean that a pneumonia diagnosis can be missed when crackles are not present, which means a lower rate of admission.