Background: Although Idiopathic Parkinson’s disease (IPD) develops in considerable patients with drug-induced Parkinsonism (DIP), the association hasn’t been well defined. We aimed to evaluate the underlying association and risk factors of DIP and IPD. Methods: A retrospective cohort study using National Health Insurance Claims data in 2011–2016 was conducted. New-onset DIP patients in 2012 were selected and matched with active controls having diabetes mellitus at a 1:4 ratio by age, sex, and Charlson’s Comorbidity Index score. Comorbidity, causative drugs, and prescription days were evaluated as covariates. Results: A total of 441 DIP were selected. During the 4-year follow up, 14 IPD events in the DM group but 62 events in the DIP group were observed (adjusted hazard ratio, HR: 18.88, 95% CI, 9.09–39.22, adjusting for comorbidities and causative drugs). IPD diagnosis in DIP was observed high in males compared to females (15.58/13.24%). The event was the most within the 1^st year follow-up, mean days 453 (SD 413.36). Subgroup analysis in DIP showed calcium channel blocker (verapamil, diltiazem, and flunarizine) was significantly associated with increased IPD risk (HR: 2.24, 95% CI, 1.27–3.93). Conclusion: Increased IPD in DIP patients might not be from the causal toxicity of antidopaminergic effects but from a trigger by the causative drugs on the DIP patients who already had subclinical IPD pathology. DIP can serve as a strong proxy for IPD incidence. Subjects who develop DIP should be monitored carefully for potential IPD incidence.

Background: The relationship of claims-based frailty index (CFI), a validated measure to identify frail individuals using Medicare data, and frailty measures used in clinical practice has not yet been fully explored. Methods: We identified community-dwelling participants of the 2015 National Health and Aging Trends Study (NHATS) whose CFI scores could be calculated using linked Medicare claims. We calculated 9 commonly used clinical frailty measures from their NHATS in-person examination: Study of Osteoporotic Fracture Index (SOF), FRAIL Scale, Frailty Phenotype, Clinical Frailty Scale (CFS), Vulnerable Elder Survey-13 (VES-13), Tilburg Frailty Indicator (TFI), Groningen Frailty Indicator (GFI), Edmonton Frail Scale (EFS), and 40-item Frailty Index (FI). Using equipercentile method, CFI scores were linked to clinical frailty measures. C-statistics and test characteristics of CFI to identify frailty as defined by each clinical frailty measure were calculated. Results: Of the 3 963 older adults, 44.5% were ≥75 years, 59.4% were female, and 82.3% were non-Hispanic White. A CFI of 0.25 was equipercentile to the following clinical frailty measure scores: SOF 1.4, FRAIL 1.8, Phenotype 1.8, CFS 5.4, VES-13 5.7, TFI 4.6, GFI 5.0, EFS 6.0, and FI 0.26. The C-statistics of using CFI to identify frailty as defined by each clinical measure were ≥0.70, except for CFS and VES-13. The optimal CFI cutpoints to identify frailty per clinical frailty measure ranged from 0.212 to 0.242, with sensitivity and specificity of 0.37–0.83 and 0.66–0.84, respectively. Conclusions: Understanding the relationship of CFI and commonly used clinical frailty measures can enhance the interpretability and potential utility of CFI.

We aimed to evaluate the prevalence of potentially inappropriate medication (PIM) use and drug–drug interactions (DDIs) in older adults and their associated factors. This cross-sectional study used National Health Insurance data of older adults in South Korea. The 2015 AGS Beers Criteria were used to classify PIM use and DDIs. The associations of PIM use and DDIs with patient- and prescriber-related factors were evaluated using multiple logistic regression. Of the older adults who received at least one outpatient prescription (N = 1,277,289), 73.0% and 13.3% received one or more prescriptions associated with PIM use or DDIs, respectively. Chlorphenamine was most commonly associated with PIM, followed by diazepam. Co-prescriptions of corticosteroids and NSAIDs accounted for 82.8% of DDIs. Polypharmacy and mainly visiting surgeons or neurologists/psychiatrists were associated with a higher likelihood of prescriptions associated with PIM use or DDIs. Older age, high continuity of care (COC), and mainly visiting a hospital were associated with a lower likelihood of PIM use or DDIs. Prescriptions associated with PIM use and DDIS were more frequent for low COC patients or those who mainly visited clinics; therefore, patients with these characteristics are preferred intervention targets for reducing prescriptions associated with PIM use and DDIs.

Jeong S, et al. J Korean Med Sci. 2021 Aug;36(39):e242. https://doi.org/10.3346/jkms.2021.36.e242