Background and hypothesis
Advancing age and chronic kidney disease (CKD) are risk factors for polypharmacy. Polypharmacy is associated with negative healthcare outcomes. Deprescribing, the systematic rationalisation of potentially inappropriate medications, is a proposed way of addressing polypharmacy. The aim of this study was to describe longitudinal prescribing patterns of oral medications in a cohort of older people with advanced CKD in their last years of life.
Methods
The EQUAL study is a European, prospective cohort study of people ≥65 years with an incident estimated glomerular filtration rate (eGFR) of ≤20ml/min/1.73m2. We analysed a decedent sub-cohort, using generalized additive models to explore trends in the number and types of prescribed oral medications over the years preceding death.
Results
Data from 563 participants were analysed (comprising 2,793 study visits) with a median follow-up time 2.2 years (interquartile range 1.1-3.8) pre-death. Participants’ numbers of prescribed oral medications increased steadily over the years approaching death – 7.3 (95% confidence interval 6.9-7.7) 5 years pre-death, and 8.7 (95% confidence interval 8.4-9.0) at death. Over the years pre-death, the proportion of people prescribed i) proton-pump inhibitors and opiates increased; ii) statins, calcium-channel blockers and renin-angiotensin-aldosterone system inhibitors decreased; whilst iii) beta-blockers, diuretics and gabapentinoids remained stable. At their final visits pre-death 14.6% and 5.1% were prescribed opiates and gabapentinoids respectively.
Conclusion
Elderly people with advanced CKD experienced persistent and increasing levels of polypharmacy as they approached the end of life. There was evidence of cessation of certain classes of medications, but at a population level this was outweighed by new prescriptions. This work highlights the potential for improved medication review in this setting to reduce the risks associated with polypharmacy. Future work should focus at the individual patient-clinician level to better understand the decision making process underlying the observed prescribing patterns.