Journal of evaluation in clinical practice
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I critically examine Jan Deckers' position in Animal (De)liberation, where he defends two main views. The first is "qualified moral veganism": Most humans have a duty to abstain from consuming animal products, even if there are circumstances in which doing so is justified. The author argues, on the one hand, from a pan-sentientist view that attributes sentience to all elementary entities and their compounds. ⋯ Deckers' second proposal is that a qualified ban on the consumption of animal products should be enacted. After discarding other alternative strategies, Deckers defends its feasibility relying on data obtained via a series of surveys. Though the argument partly succeeds in developing a coherent account accommodating the author's intuitions, I conclude that his ontological and normative frameworks remain too underdeveloped, his appeal to biological relatedness has implausible implications, and the methodology he uses in defence of his political position is problematic.
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Clinical Trial
Remote control improves quality of life in elderly pacemaker patients versus standard ambulatory-based follow-up.
Health-related quality of life (HRQoL) improves shortly after pacemaker (PM) implantation. No studies have investigated the HRQoL trend for elderly patients with a remote device monitoring follow-up system. ⋯ Remote device monitoring has a significant impact on HRQoL in pacemaker patients, increasing its levels up to 6 months after implant.
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Observational Study
Evaluation of drug-related problems in older polypharmacy primary care patients.
Targeting older patients with predictive factors for drug-related problems (DRPs) could make clinical medication reviews more cost-effective. The aim of this study was to identify the number, type, and potential predictive factors for DRPs in older polypharmacy patients. ⋯ Patients with asthma, hypertension, and diabetes and lack of statin, antithrombotic agent, and/or proton pump inhibitor use were associated with higher risks for DRPs.
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Reducing preventable harm from repeat medication prescriptions is a patient safety priority worldwide. In the United Kingdom, repeat prescriptions items issued has doubled in the last 20 years from 5.8 to 13.3 items per patient per annum. This has significant resource implications and consequences for avoidable patient harms. Consequently, we aimed to test a risk management model to identify, measure, and reduce repeat prescribing system risks in primary care. ⋯ The risk management model tested uncovered important safety concerns and facilitated the development and communication of related improvement recommendations. System-wide information on hazardous repeat prescribing and how this could be mitigated is very limited. The approach reported may have potential to close this gap and improve the reliability of general practice systems and patient safety, which should be of high interest to primary care organisations internationally.
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In evaluating non-randomized interventions, propensity scores (PS) estimate the probability of assignment to the treatment group given observed characteristics. Machine learning algorithms have been proposed as an alternative to conventional logistic regression for modelling PS in order to avoid limitations of linear methods. We introduce classification tree analysis (CTA) to generate PS which is a "decision-tree"-like classification model that provides accurate, parsimonious decision rules that are easy to display and interpret, reports P values derived via permutation tests, and evaluates cross-generalizability. ⋯ Assessing standardized differences in means as a test of covariate balance is inappropriate for machine learning algorithms that segment the sample into two or more strata. Because the CTA algorithm identifies all statistically valid PS models for a sample, it is most likely to identify a correctly specified PS model, and should be considered as an alternative approach to modeling the PS.