In the final result of this double blind study, 25% or one in four of patients who received the treatment responded positively. Though the difference is significant at P<0.05, it is better to present this as a significant difference at 0.4%. The number needed to treat (NNT) is defined as the inverse of the absolute risk reduction. Taking this as 0.25 (25%), the NNT is 1/0.25 = 4. However given the 95% confidence interval is between 10-50% for absolute risk reduction, the NNT with 95% CI is between 2 and 10. Therefore we cannot say with certainty that the NNT is at least 4.

In case control studies, observational studies are made to compare two groups, individuals with a certain condition, to those without the condition, with all other factors being equal. In the situation presented by the question, the study was to determine whether a prior risk factor, a low birth weight, was associated with later developing adolescent hypertension, using a paired t-test to statistically determine whether there was indeed a significant association between the two conditions. Case control studies only help to draw associations between two groups and therefore cannot indicate causation. In this scenario we are also not given the p value to determine whether the association is statistically significant. Therefore there is not enough evidence to conclude whether or not birthweight affects the development of adolescent hypertension.

Case control studies are observational studies which retrospectively determine whether a patient might have been exposed to a risk factor for a certain disease, as compared to a control group from the general population. They can be used for a range of outcomes as well as rare diseases. One of the biggest problems with this type of study is recall bias. Research subjects may selectively remember factors that are more predictive of the disease outcome when compared to the control group. All studies should have prior power calculations before the study commences.

A case–control study (also known as case–referent study) is a type of observational study in which two existing groups differing in outcome are identified and compared on the basis of some supposed causal attribute. Case–control studies are often used to identify factors that may contribute to a medical condition by comparing subjects who have that condition/disease (the cases) with patients who do not have the condition/disease but are otherwise similar (the controls).
An odds ratio (OR) is a statistic that quantifies the strength of the association between two events, A and B. The odds ratio is defined as the ratio of the odds of A in the presence of B and the odds of A in the absence of B or vice versa.

Before the test, the patient was likely to have the disease being tested for. Their pre test odds were 2, making them twice as likely to have the disease. After testing positive, their pretest odds of 2 and the likelihood ratio of 3 are multiplied to produce 6 as the post test odds. The patient is now 6 times as likely to have the disease after the test. Likelihood ratios above 10 or below 0.1 are strong evidence to rule in and rule out a diagnosis. The negative likelihood ratio is not known here, but does not subtract from the interpretation of the outcomes in this patient.

Standard deviation is defined as the measure of dispersion of a set of data from its mean. It measures the absolute variability of a distribution| the higher the dispersion or variability, the greater is the standard deviation and greater will be the magnitude of the deviation of the value from their mean.

Crossover trials are characterized by the switching of study participants throughout the treatment groups, keeping a random order of switching. This randomization is important to determine any carry-over effect of different treatment modalities. The benefit of this study is the evaluation of the efficacy of various short-term treatment options for the relief of chronic conditions. The washout period is small in this type of study. Crossover studies are more efficient than the parallel studies, but they should be used according to the treatment options and outcomes.

Case control studies are used to determine the relationship between exposure to a risk factor and the resultant outcomes. It finds patients in the general population who have a certain condition and retrospectively searches for past exposure to possible risk factors for the disease. Controls are people who do not have the disease found in the general population. This type of study is useful for rare diseases, and is less time consuming to conduct. While cohort studies can be used to study rare diseases they measure the relative risk of developing the disease over time based on exposure. Ecological or cross-sectional studies attempt take a snapshot of a whole population, and thus are inappropriate for rare diseases as larger sample numbers are needed. A randomised control trial is better suited to determine the effect of an intervention.

A cohort study is a particular form of longitudinal study that samples a cohort (a group of people who share a defining characteristic, typically those who experienced a common event in a selected period, such as birth or graduation), performing a cross-section at intervals through time.
The relative risk (RR) or risk ratio is the ratio of the probability of an outcome in an exposed group to the probability of an outcome in an unexposed group. Relative risk is used in the statistical analysis of the data of experimental, cohort and cross-sectional studies, to estimate the strength of the association between treatments or risk factors, and outcomes.

The sensitivity of a screening test can be described in a variety of ways, typically such as sensitivity being the ability of a screening test to detect a true positive, being based on the true positive rate, reflecting a test’s ability to correctly identify all people who have a condition, or, if 100%, identifying all people with a condition of interest by those people testing positive on the test.The specificity of a test is defined in a variety of ways, typically such as specificity is the ability of a screening test to detect a true negative, being based on the true negative rate, correctly identifying people who do not have a condition, or, if 100%, identifying all patients who do not have the condition of interest by those people testing negative on the test.