BackgroundPolypharmacy is common in older people and associated with potential harms. The aim of this study was to analyse the characteristics of an older multimorbid population with polypharmacy and to identify factors contributing to excessive polypharmacy in these patients.MethodsThis cross-sectional analysis is based on the PRIMA-eDS trial, a large randomised controlled multicentre study of polypharmacy in primary care. Patients’ baseline data were used for analysis. A number of socioeconomic and medical data as well as SF-12-scores were entered into a generalized linear mixed model to identify variables associated with excessive polypharmacy (taking ≥10 substances daily).ResultsThree thousand nine hundred four participants were recruited. Risk factors significantly associated with excessive polypharmacy were frailty (OR 1.45; 95% CI 1.22–1.71), > 8 diagnoses (OR 2.64; 95% CI 2.24–3.11), BMI ≥30 (OR 1.18; 95% CI 1.02–1.38), a lower SF-12 physical health composite score (OR 1.47; 95% CI 1.26–1.72), and a lower SF-12 mental health composite score (OR 1.33; 95% CI 1.17–1.59) than the median of the study population (≤36.6 and ≤ 48.7, respectively). Age ≥ 85 years (OR 0.83; 95% CI 0.70–0.99) led to a significantly lower risk for excessive polypharmacy. No association with excessive polypharmacy could be found for female sex, low educational level, and smoking. Regarding the study centres, being recruited in the UK led to a significantly higher risk for excessive polypharmacy compared to being recruited in Germany 1/Rostock (OR 1.71; 95% CI 1.27–2.30). Being recruited in Germany 2/Witten led to a slightly significant lower risk for excessive polypharmacy compared to Germany 1/Rostock (OR 0.74; 95% CI 0.56–0.97).ConclusionsFrailty, multimorbidity, obesity, and decreased physical as well as mental health status are risk factors for excessive polypharmacy. Sex, educational level, and smoking apparently do not seem to be related to excessive polypharmacy. Physicians should especially pay attention to their frail, obese patients who have multiple diagnoses and a decreased health-related quality of life, to check carefully whether all the drugs prescribed are evidence-based, safe, and do not interact in an unfavourable way.Trial registrationThis trial has been registered with Current Controlled Trials Ltd. on 31 July 2014 (ISRCTN10137559).Electronic supplementary materialThe online version of this article (10.1186/s12875-018-0795-5) contains supplementary material, which is available to authorized users.

Abstract Objective To evaluate the effects of a computerised decision support tool for comprehensive drug review in elderly people with polypharmacy. Design Pragmatic, multicentre, cluster randomised controlled trial. Setting 359 general practices in Austria, Germany, Italy, and the United Kingdom. Participants 3904 adults aged 75 years and older using eight or more drugs on a regular basis, recruited by their general practitioner. Intervention A newly developed electronic decision support tool comprising a comprehensive drug review to support general practitioners in deprescribing potentially inappropriate and non-evidence based drugs. Doctors were randomly allocated to either the electronic decision support tool or to provide treatment as usual. Main outcome measures The primary outcome was the composite of unplanned hospital admission or death by 24 months. The key secondary outcome was reduction in the number of drugs. Results 3904 adults were enrolled between January and October 2015. 181 practices and 1953 participants were assigned to electronic decision support (intervention group) and 178 practices and 1951 participants to treatment as usual (control group). The primary outcome (composite of unplanned hospital admission or death by 24 months) occurred in 871 (44.6%) participants in the intervention group and 944 (48.4%) in the control group. In an intention-to-treat analysis the odds ratio of the composite outcome was 0.88 (95% confidence interval 0.73 to 1.07; P=0.19, 997 of 1953 v 1055 of 1951). In an analysis restricted to participants attending practice according to protocol, a difference was found favouring the intervention (odds ratio 0.82, 95% confidence interval 0.68 to 0.98; 774 of 1682 v 873 of 1712, P=0.03). By 24 months the number of prescribed drugs had decreased in the intervention group compared with control group (uncontrolled mean change −0.42 v 0.06: adjusted mean difference −0.45, 95% confidence interval −0.63 to −0.26; P<0.001). Conclusions In intention-to-treat analysis, a computerised decision support tool for comprehensive drug review of elderly people with polypharmacy showed no conclusive effects on the composite of unplanned hospital admission or death by 24 months. Nonetheless, a reduction in drugs was achieved without detriment to patient outcomes. Trial registration Current Controlled Trials ISRCTN10137559 .

BackgroundMultimorbidity is increasing in aging populations with a corresponding increase in polypharmacy as well as inappropriate prescribing. Depending on definitions, 25-50 % of patients aged 75 years or older are exposed to at least five drugs. Evidence is increasing that polypharmacy, even when guidelines advise the prescribing of each drug individually, can potentially cause more harm than benefit to older patients, due to factors such as drug-drug and drug-disease interactions. Several approaches reducing polypharmacy and inappropriate prescribing have been proposed, but evidence showing a benefit of these measures regarding clinically relevant endpoints is scarce. There is an urgent need to implement more effective strategies. We therefore set out to develop an evidence-based electronic decision support (eDS) tool to aid physicians in reducing inappropriate prescribing and test its effectiveness in a large-scale cluster-randomized controlled trial.MethodsThe “Polypharmacy in chronic diseases–Reduction of Inappropriate Medication and Adverse drug events in older populations” (PRIMA)-eDS tool is a tool comprising an indication check and recommendations for the reduction of polypharmacy and inappropriate prescribing based on systematic reviews and guidelines, the European list of inappropriate medications for older people, the SFINX-database of interactions, the PHARAO-database on adverse effects, and the RENBASE-database on renal dosing. The tool will be evaluated in a cluster-randomized controlled trial involving 325 general practitioners (GPs) and around 3500 patients across five study centres in the United Kingdom, Germany, Austria and Italy. GP practices will be asked to recruit 11 patients aged 75 years or older who are taking at least eight medications and will be cluster-randomized after completion of patient recruitment. Intervention GPs will have access to the PRIMA-eDS tool, while control GPs will treat their patients according to current guidelines (usual care) without access to the PRIMA-eDS tool. After an observation time of 2 years, intervention and control groups will be compared regarding the primary composite endpoint of first non-elective hospitalization or death.DiscussionThe principal hypothesis is that reduction of polypharmacy and inappropriate prescribing can improve the clinical composite outcome of hospitalization or death. A positive result of the trial will contribute substantially to the improvement of care in multimorbidity. The trial is necessary to investigate not only whether the reduction of polypharmacy improves outcome, but also whether GPs and patients are willing to follow the recommendations of the PRIMA-eDS tool.Trial registrationThis trial has been registered with Current Controlled Trials Ltd. on 31 July 2014 (ISRCTN10137559).Electronic supplementary materialThe online version of this article (doi:10.1186/s13063-016-1177-8) contains supplementary material, which is available to authorized users.

A number of previous works have shown that information about a subject is encoded in sparse kinematic information, such as the one revealed by so-called point light walkers. With the work at hand, we extend these results to classifications of soft biometrics from inertial sensor recordings at a single body location from a single step. We recorded accelerations and angular velocities of 26 subjects using integrated measurement units (IMUs) attached at four locations (chest, lower back, right wrist and left ankle) when performing standardized gait tasks. The collected data were segmented into individual walking steps. We trained random forest classifiers in order to estimate soft biometrics (gender, age and height). We applied two different validation methods to the process, 10-fold cross-validation and subject-wise cross-validation. For all three classification tasks, we achieve high accuracy values for all four sensor locations. From these results, we can conclude that the data of a single walking step (6D: accelerations and angular velocities) allow for a robust estimation of the gender, height and age of a person.