Background Several anticholinergic scales and equations to evaluate the anticholinergic burden have been previously created. Association of these instruments with the anticholinergic outcomes are usually estimated by means of hypothesis contrast tests, which ignore the size of the association effect. Objective To evaluate the effect size of the associations between the scores on cumulative anticholinergic burden instruments with peripheral or central anticholinergic adverse outcomes in older patients. Setting Internal medicine ward of a Tertiary University Hospital. Methods A case-control study was conducted in patients over 65 years who were admitted to two internal medicine wards of a Portuguese university hospital. The Anticholinergic Drug Scale, Anticholinergic Risk Scale, Anticholinergic Cognitive Burden scale and Drug Burden Index were used to calculate the patients' anticholinergic burden. Peripheral (dry mouth-swab technique; dry eye-Schirmer test) and central (falls and cognitive impairment-Mini-Mental State Examination) anticholinergic adverse outcomes were investigated. The Barthel Index was used to assess overall physical functionality. The Mann-Whitney test was used to evaluate probabilistic differences in the anticholinergic scores between case and control individuals. To establish the effect size of the associations, the area under the curve of the receiver operating characteristics curve was calculated. Main outcome measure Anticholinergic adverse effects. Results A total of 250 patients (mean age 81.67 years, standard deviation 7.768; 50% females) were included. In total, 148 patients (59.2%) presented with dry mouth, 85 (34%) with dry eye, 141 (56.4%) with impaired functionality, 44 (17.6%) with a history of falls and 219 (87.6%) with cognitive impairment. Significant differences (p < 0.05) were obtained for the majority of the associations between Anticholinergic Drug Scale, Anticholinergic Risk Scale, Anticholinergic Cognitive Burden and Drug Burden Index and adverse effects. Conversely, the effect sizes of these associations ranged from "fail" (area under the curve 0.5 to 0.6) to "fair" (area under the curve 0.7 to 0.8). Conclusion Although significant differences in the scores of anticholinergic burden instruments and adverse outcomes may exist, the effect sizes of these associations ranged from 'fail' to 'fair', which limits their utility in preventing anticholinergic adverse outcomes with medication review interventions. Keywords Aged • Cholinergic antagonists • Reproducibility of results • Risk assessment • ROC curve

The Maastricht Utrecht Adherence in Hypertension (MUAH) questionnaire provides clinicians with information about the causes of a patient's poor adherence to antihypertensive drugs. In this study, the authors aimed to develop and validate a short version of the MUAH questionnaire. After an exploratory factor analysis, the number of | INTRODUCTION

Background The STOPP/START criteria are an explicit tool to detect potentially inappropriate medications (PIMs). Patient clinical information may not be available in all settings. Objective To identify patient clinical information needed to apply the STOPP/START criteria. Setting: Four nursing homes in Portugal. Methods First, a theoretical analysis was performed to identify the patient information required to apply the STOPP/START criteria (v2), according to the following categories: patients' current medication, medication history (previous medication and duration), medical records (current and past medical conditions), and laboratory test results. A verification of the information requirements was conducted through a crosssectional study on a nursing home population with patients over 65 years old. Patients' medical records were appraised to extract only demographic data and current medication profiles. Main outcome measure Information requirements of STOPP/ START. Results For only 29 of the 81 STOPP criteria and 1 of the 34 START criteria, a judgement could be made with only the information in the patient's medication profile. 52 STOPP and 33 START criteria require additional information, (i.e. duration of therapy, previous medication, current and past medical conditions, and laboratory data). The 208 evaluated persons (87 years; 68.75% female) used 1770 medications, with 989 (55.9%) potentially involved in 1629 STOPP criteria. Sufficient information to judge STOPP criteria was available for only 529 (32.5%) potential STOPP criteria situations, with a positive identification of a STOPP PIM in 397 instances (75.0%). Conclusions Although STOPP/START criteria can be considered a high-level tool to identify PIMs, their use may be compromised in scenarios where access to patients' clinical information is limited. Impact on practice• The correct use of the STOPP/START criteria requires access to patients' current and past medication profiles and medical records. • Limited access to patients' clinical information invalidates any comparative analysis of inappropriate prescribing using the STOPP/START criteria.

Introduction: Obtaining the best possible medication history is the crucial step in medication reconciliation. Our aim was to evaluate the potential contributions of the main data sources available – patient/caregiver, hospital medical records, and shared electronic health records – to obtain an accurate ‘best possible medication history’.Material and Methods: An observational cross-sectional study was conducted. Adult patients taking at least one medicine were included. Patient interview was performed upon admission and this information was reconciled with hospital medical records and shared electronic health records, assessed retrospectively. Concordance between sources was assessed. In the shared electronic health records, information was collected for four time-periods: the preceding three, six, nine and 12-months. The proportion of omitted data between time-periods was analysed.Results: A total of 148 patients were admitted, with a mean age of 54.6 ± 16.3 years. A total of 1639 medicines were retrieved. Only 29% were collected simultaneously in the three sources of information, 40% were only obtained in shared electronic health records and only 5% were obtained exclusively from patients. The total number of medicines gathered in shared electronic health records considering the different time frames were 778 (three-months), 1397 (six-months), 1748 (nine-months), and 1933 (12-months).Discussion: The use of shared electronic health records provides data that were omitted in the other data sources available and retrieving the information at six months is the most efficient procedure to establish the basis of the best possible medication history.Conclusion: Shared electronic health records should be the preferred source of information to supplement the patient or caregiver interview in order to increase the accuracy of best possible medication history of the patient, particularly if collected within the prior six months.

Anticholinergic burden tools have relevant pharmacological gaps that may explain their limited predictive ability for clinical outcomes. The aim of this study was to provide a universal pharmacological-based list of drugs with their documented affinity for muscarinic receptors. A comprehensive literature review was performed to identify the anticholinergic burden tools. Drugs included in these instruments were searched in four pharmacological databases, and the investigation was supplemented with PubMed. The evidence regarding the potential antagonism of the five muscarinic receptors of each drug was assessed. The proportion of drugs included in the tools with an affinity for muscarinic receptors was evaluated. A universal list of drugs with anticholinergic activity was developed based on their documented affinity for the different subtypes of muscarinic receptors and their ability to cross the blood-brain barrier. A total of 23 tools were identified, including 304 different drugs. Only 48.68%, 47.70%, 48.03%, 43.75%, and 42.76% of the drugs had an affinity to the M1, M2, M3, M4, and M5 receptor, respectively, reported in any pharmacological database. The proportion of drugs with confirmed antagonism varied among the tools (36.8% to 100%). A universal pharmacological-based list of 133 drugs is presented. It should be further validated in different clinical settings.