title: Potentially inappropriate medication use in Indian elderly: comparison of Beers' criteria and Screening Tool of Older Persons' potentially inappropriate Prescriptions.
abstract: OBJECTIVE
  To compare Beers' criteria (BC) and Screening Tool of Older Persons' potentially inappropriate Prescriptions (STOPP) for prevalence, specificity, sensitivity and predictors for potentially inappropriate medication (PIM) use.
  
  
  METHODS
  Patients aged ≥ 60 years from medicine wards of a tertiary care hospital were included. Comparisons between BC and STOPP were made using Pearson's χ(2) -test for categorical variables and Mann-Whitney U-test for continuous variables. Specificity and sensitivity were assessed by using 2 × 2 contingency table. Bivariate analysis and subsequent multivariate logistic regression was used to identify the predictors of PIM use.
  
  
  RESULTS
  In the 540 patients included, prevalence of PIM use as per BC and STOPP was 24.6% and 13.3%, respectively. Sensitivity and specificity of BC in detecting PIM was 0.65 and 0.53, respectively. Considering the diagnoses/conditions, sensitivity and specificity of BC was 0.12 and 0.48, respectively, whereas independent of diagnoses/conditions, corresponding values were 0.75 and 0.54. PIM as per BC and STOPP accounted for 11 and 6 adverse drug reactions (ADR), respectively. Medications not listed in BC or STOPP were more likely to be associated with ADR. Multiple diseases (≥ 4) and use of more drugs during hospital stay (10-14) predicted PIM use as per BC, whereas age (60-74 years) predicted PIM use as per STOPP.
  
  
  CONCLUSIONS
  Overall, BC is useful in the detection of PIM use independent of diagnoses/conditions, whereas STOPP is useful in detection of PIM use considering the diagnoses/conditions. There is a need for consensus on using the tool for detection of PIM use in Indian elderly.
authors.affiliation: Department of Pharmacy Practice, JSS College of Pharmacy, Mysore, India.
authors.forename: Hunsur Nagendra
authors.initials: HN
authors.lastname: Vishwas
authors.forename: Anand
authors.initials: A
authors.lastname: Harugeri
authors.forename: Gurumurthy
authors.initials: G
authors.lastname: Parthasarathi
authors.forename: Madhan
authors.initials: M
authors.lastname: Ramesh
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D016009:Chi-Square Distribution; D005260:Female; D015577:Geriatric Assessment / Q000379:methods; D006801:Humans; D057970:Inappropriate Prescribing / Q000706:statistics & numerical data*; D007194:India; D016015:Logistic Models; D008297:Male; D008403:Mass Screening / Q000295:instrumentation*; D008508:Medication Errors / Q000517:prevention & control / Q000706:statistics & numerical data; D008875:Middle Aged; D015995:Prevalence; D011446:Prospective Studies; D018709:Statistics, Nonparametric