High sensitivity in a study means

ANS. B* Sensitivity: A/(A+C) x 100Sensitivity is the probability that a test will indicate 'disease' among those with the disease.* Specificity: D/(D+B) x 100Specificity is the fraction of those without disease who will have a negative test result.* Positive Predictive Value: A/(A+B) x 100Positive predictive value--diagnostic power of a screening test to correctly identify the disease.* Negative Predictive Value: D/(D+C) x 100Negative predictive value--diagnostic power of a screening test to exclude the disease.# Important formulas in SPM1. Extra edge in sensitivity, specificityIn sequential testing (one diagnostic test is done, if that test is positive, same test is repeated again):- False positivity decreases- Specificity increases- Sensitivity decreasesIn parallel testing (two different diagnostic tests are done together):- False negativity decreases- Sensitivity increases- Specificity decreases(This question was asked in May and November session JIPMER 2017)2. Normal distribution curve3. Positive and negative skew* In positive skew: Mean > Median > Mode* In negative skew: Mean < Median < Mode4. Odds ratio = P/(l-P) {where, P is the probablity}.5. Sample size of a study = 4PQ/D2 {where, P = prevalence, Q = (1-P), D is error6. Standard error of a population[?] (PQ/sample size)7. Crude birth rate = (8 x total fertility rate) + 1.