BackgroundThe cumulative effect of taking multiple medicines with anticholinergic properties termed as anticholinergic burden can adversely impact cognition, physical function and increase the risk of mortality. Expert opinion derived risk scales are routinely used in research and clinical practice to quantify anticholinergic burden. These scales rank the anticholinergic activity of medicines into four categories, ranging from no anticholinergic activity (= 0) to definite/high anticholinergic activity (= 3). The aim of this systematic review was to compare anticholinergic burden quantified by the anticholinergic risk scales and evaluate associations with adverse outcomes in older people.MethodsWe conducted a literature search in Ovid MEDLINE, EMBASE and PsycINFO from 1984-2014 to identify expert opinion derived anticholinergic risk scales. In addition to this, a citation analysis was performed in Web of Science and Google Scholar to track prospective citing of references of selected articles for assessment of individual scales for adverse anticholinergic outcomes. The primary outcomes of interest were functional and cognitive outcomes associated with anticholinergic burden in older people. The critical appraisals of the included studies were performed by two independent reviewers and the data were extracted onto standardised forms.ResultsThe primary electronic literature search identified a total of 1250 records in the 3 different databases. On the basis of full-text analysis, we identified 7 expert-based anticholinergic rating scales that met the inclusion criteria. The rating of anticholinergic activity for medicines among these rating scales was inconsistent. For example, quetiapine was rated as having high anticholinergic activity in one scale (n = 1), moderate in another scale (n = 1) and low in two other scales (n = 2). Citation analysis of the individual scales showed that the Anticholinergic Cognitive Burden (ACB) scale was the most frequently validated expert based anticholinergic scale for adverse outcomes (N = 13).ConclusionsIn conclusion, there is not one standardised tool for measuring anticholinergic burden. Cohort studies have shown that higher anticholinergic burden is associated with negative brain effects, poorer cognitive and functional outcomes.Electronic supplementary materialThe online version of this article (doi:10.1186/s12877-015-0029-9) contains supplementary material, which is available to authorized users.

There are substantial differences in the estimation of anticholinergic burden exposure between the nine scales. Anticholinergic burden scores obtained from each of the scales were associated with adverse clinical outcomes of interest.

Many medicines that are commonly prescribed to older people have a degree of anticholinergic activity that can contribute to anticholinergic burden. Anticholinergic burden, measured in several ways that consider number, dose and/or degree of anticholinergic activity of medicines, has shown to be a predictor of adverse health and functional outcomes. The anticholinergic burden on older people should be minimised by avoiding, reducing dose and deprescribing medicines with anticholinergic activity where clinically possible.

The study of the magnitude and variation of drug response is defined as pharmacodynamics (PDs). PD models examine plasma concentration and effect relationship. It can predict the archetypal effect ([Formula: see text]) of a drug as a function of the drug concentration ([Formula: see text]) and estimate an unknown PD parameter ([Formula: see text]). The PD models have been described as fixed, linear, log-linear, [Formula: see text], sigmoid [Formula: see text], and indirect PD response. Ligand binding model is an example of a PD model that works on the underpinning PD principle of a drug, eliciting its pharmacological effect at the receptor site. The pharmacological effect is produced by the drug binding to the receptor to either activate or antagonise the receptor. Ligand binding models describe a system of interacting components, i.e. the interaction of one or more ligands with one or more binding sites. The [Formula: see text] model is the central method that provides an empirical justification for the concentration/dose-effect relationship. However, for ligand binding models justification is provided by theory of receptor occupancy. In essence, for ligand binding models, the term [Formula: see text] is best used to describe the fraction of receptors occupied at a particular ligand concentration. It is stated that the [Formula: see text], which means the effect of a drug should depend on the fraction of receptors that are occupied. In the future, network-based systems pharmacology models using ligand binding principles could be an effective way of understanding drug-related adverse effects. This will facilitate and strengthen the development of rational drug therapy in clinical practice.

Background: Polypharmacy and hyperpolypharmacy are proxy indicators for inappropriate medicine use. Inappropriate medicine use in older people leads to adverse clinical outcomes. Objective: The objectives of this study were to investigate the prevalence and trends of polypharmacy and hyperpolypharmacy in older people in New Zealand from 2005 to 2013, analyzing the pharmaceutical collections maintained by the Ministry of Health. Methods: A repeated cross-sectional analysis of population-level dispensing data was conducted from January 1, 2005 to December 31, 2013. Polypharmacy and hyperpolypharmacy in individuals were defined as the use of 5-9 medicines and ≥10 medicines, respectively, dispensed concurrently for a period of ≥90 days. Differences in polypharmacy and hyperpolypharmacy between 2005 and 2013 were examined. A multinomial regression model was used to predict sociodemographic characteristics associated with polypharmacy and hyperpolypharmacy. Results: Polypharmacy and hyperpolypharmacy were found to be higher in 2013 compared to 2005 (polypharmacy: 29.5 vs. 23.4%, p < 0.001; hyperpolypharmacy: 2.1 vs. 1.3%, p < 0.001). The risk of polypharmacy and hyperpolypharmacy was higher in females, in those aged 80-84 years, in the Māori population (for polypharmacy) and the Middle Eastern, Latin American, or African population (for hyperpolypharmacy), in people living in the Southern-district health board, and in individuals with increasing deprivation. Conclusion: The population of New Zealand is aging and the number of older people with multiple chronic conditions is increasing. The proportion of older people exposed to polypharmacy and hyperpolypharmacy has increased in 2013 compared to 2005. Our study provides important information to alert health policy makers, researchers, and clinicians about the dire need to reduce the medication burden in older New Zealanders.