Table 5.
Analysis of factors related to PIMs
| Univariate analysis | Multivariate analysis | ||||
|---|---|---|---|---|---|
| PIMs = No n = 5923 |
PIMs = Yes n = 2157 |
Pa | Adjusted ORb (95% CI) | Pc | |
| Sex, female, n (%) | 3192 (53.9) | 1220 (56.6) | 0.033 | 1.10 (0.99–1.23) | 0.084 |
| Age, ≥ 85, n (%) | 1485 (25.1) | 586 (27.2) | 0.056 | 0.96 (0.85–1.08) | 0.486 |
| No. of prescribing physicians per patient, ≥ 2, n (%) | 989 (16.7) | 840 (38.9) | < 0.001 | 1.51 (1.34–1.71) | < 0.001 |
| Polypharmacy | 1800 (30.4) | 1681 (77.9) | < 0.001 | 7.11 (6.29–8.03) | < 0.001 |
| No. of drugs, median (IQR) | |||||
| Overall | 3 (2–5) | 7 (5–10) | < 0.001d | ||
| Chronic-phase systemic drugs | 2 (1–4) | 6 (4–9) | < 0.001d | ||
Adjusted confounding variables in the multivariate logistic regression analysis; sex, age, the number of physicians per patient and polypharmacy
PIM potentially inappropriate medication, OR odds ratio, CI confidence interval, IQR interquartile range
aP value according to Chi square test
bOdds ratio adjusted for sex, age, number of prescribing physicians per patient, and polypharmacy
cP value according to logistic regression analysis
dP value according to Mann–Whitney U test