Cognitive burden and polypharmacy in elderly Japanese patients treated with anticholinergics for an overactive bladder.
Takako ShiotaKazumasa TorimotoMasahiro OkudaRyo IwataHiromi KumamotoMakito MiyakeAkihide HirayamaNobumichi TanakaKiyohide FujimotoPublished in: Lower urinary tract symptoms (2019)
This study aimed to investigate the cognitive burden and polypharmacy in elderly patients treated with anticholinergics for an overactive bladder. We conducted a retrospective study of patients with an overactive bladder receiving treatment at two hospitals in Japan (Nara Medical University Hospital and Saiseikai Nara Hospital). Prescription data were collected from the medical records of the patients registered between January 2013 and April 2014. The Anticholinergic Cognitive Burden Scale was used to estimate the severity of the anticholinergic effects on the cognition of each patient. We collected the prescription data of 584 and 246 patients from the Nara Medical University Hospital and Saiseikai Nara Hospital, respectively. The mean daily total Anticholinergic Cognitive Burden score ranged between 3 and 4 (3.59 ± 1.16 at Nara Medical University Hospital vs 3.32 ± 0.78 at Saiseikai Nara Hospital, P < 0.01). At both hospitals, the mean number of prescriptions was >5 in patients ≥75 years (5.95 ± 4.43 and 5.64 ± 3.90 at Nara Medical University Hospital and Saiseikai Nara Hospitals, respectively). Our findings suggest that 10%-20% of elderly patients (≥65 years) receiving treatment with anticholinergics for an overactive bladder are in a state of polypharmacy. The total anticholinergic cognitive burden of each patient mainly depends on the anticholinergics being used for treating the overactive bladder. Especially for elderly patients with a high risk of adverse effects, including cognitive impairment, careful attention needs to be paid during selection of drugs for treating patients with an overactive bladder.
Keyphrases
- healthcare
- end stage renal disease
- ejection fraction
- newly diagnosed
- prognostic factors
- risk factors
- cognitive impairment
- peritoneal dialysis
- adverse drug
- patient reported outcomes
- machine learning
- case report
- multiple sclerosis
- physical activity
- electronic health record
- mild cognitive impairment
- artificial intelligence
- big data
- white matter