Clinical Epidemiology Flashcards
Normal as common
Classifies values that occur frequently as normal, and those that occur infrequently as abnormal.
Operational definition of abnormality
Assume that an arbitrary cut-off point on the frequency distribution is the limit of normality and consider all values beyond this point as abnormal.
Usually two standard deviations above or below the mean
Gaussian distribution
Normal in statistical sense
Cut-off would identify 2.5% of the population as abnormal using this cut off
Percentile approach
Does not assume a statistically normal distribution, no biological basis
We can consider that the 95th percentile point is the dividing line between normal and abnormally high values, thus classifying 5% of the population as abnormal
Abnormality associated with disease
Distinction between normal and abnormal can be based on the distribution of the measurements for both healthy and diseased people, we attempt to define the cut-off point that separates the two groups. Classification error can arise, comparison of two frequency distributions often shows considerable overlap.
Abnormal as treatable
These difficulties in distinguishing accurately between normal and abnormal have led to the use of criteria determined by evidence from randomized controlled trials, which can be designed to detect the point at which treatment does more good than harm. Such trials are not always designed to account for other risk factors or the cost of treatment.
Diagnostic tests
Diagnose treatable disease and to help confirm possible diagnoses suggested by the patient’s signs and symptoms. Usually involve laboratory investigations (genetic, microbiological, biochemical or physiological), the principles that help determine the value of these tests.
Value of a test
Disease present or absent and a test result either positive or negative.
Four combinations of disease status and test result
True positive, true negative, false negative, and false positive.
Only use these categories when there is an absolutely accurate method of determining the accuracy of other tests.
Practical utility of a given test
A test’s positive and negative predictive value.
Depends on the sensitivity and specificity of the test, and the prevalence of the disease in the population being tested.
Depend critically on the prevalence of the abnormality in the patients being tested
Positive predictive value
The probability of disease in a patient with an abnormal test result
Negative predictive value
probability of a patient not having a disease when the test result is negative
Natural history refers to
- Pathological onset
- The pre-symptomatic stage, from onset of pathological changes in the first appearance of symptoms or signs
- The stage when the disease is clinically obvious and may be subject to remissions and relapses, regress spontaneously or progress to death
Prognosis
Prediction of the course of a disease and is expressed as the probability that a particular event will occur in the future.
Epidemiological information from many patients is necessary to provide sound predictions on prognosis and outcome. Clinical experience alone is inadequate for this purpose, since it is often based on a limited set of patients and inadequate follow-up.
Quality of life
assessment of prognosis should include measurement of all clinically relevant outcomes and not just death, since patients are usually interested in the quality of life as they are in its duration. Randomly selected groups.
Quantity of life
Prognosis in terms of mortality is measured as case-fatality rate or probability of survival. Both the date of onset and the duration of follow-up must be clearly specified. Survival analysis is a simple method of measuring prognosis.
Clearly advantageous treatments
antibiotics for pneumonia and surgery for trauma. Rarely is there such clarity in clinical medicine. Usually effects are less obvious, and most interventions require research to establish their value. Specific treatments need to be shown to do more good than harm among patients who actually use them: efficacy.
Compliance
The extent to which patients follow medical advice.
Practical effectiveness
Determined by studying outcomes in a group of people offered treatment, only some of whom will be compliant.
Best method of measuring efficacy and effectiveness of treatments
By randomized controlled trial, however, some times trials like this cannot be done, and only a small proportion of current medical interventions have been assessed with such trials.
Use of evidence based guidelines
Assist practitioners and patients in making decisions about appropriate health care for specific clinical circumstances. Putting evidence into practice requires evidence-based guidelines.
Prevention in clinical practice
Clinical practice prevention is often secondary or tertiary. But primary prevention can be implemented on a routine basis.
Reducing risks
opportunities for health professionals to offer practical advice and support to patients with the hope of preventing new diseases or exacerbation of existing illnesses. Clinical epidemiologists are often involved in figuring out how effective these interventions are.
Reducing risks in patients with established diseases
evidence based approaches to reducing the risk of adverse outcomes in those with the disease are very similar to the approaches used to reduce disease onset. Behavioural interventions, pharmacological interventions, other interventions.
