Background Patients taking medication with high anticholinergic and sedative properties are at increased risk of experiencing poor cognitive and physical outcomes. Therefore, precise quantification of the cumulative burden of their drug regimen is advisable. There is no agreement regarding which scale to use to simultaneously quantify the burden associated with medications.Objectives The objective of this review was to assess the strengths and limitations of available tools to quantify medicationrelated anticholinergic burden and sedative load in older adults. We discuss specific limitations and agreements between currently available scales and models and propose a comprehensive table combining drugs categorized as high, moderate, low, or no anticholinergic or sedative activity as excerpted from the selected studies. Methods A targeted search was carried out using the National Library of Medicine through PubMed using medical subject heading terms and text words around the following search terms: (anticholinergic OR sedative) AND (load OR burden OR scale) for studies published between 1 January 1945 and 5 June 2021. In addition, the following databases were searched using the same terms: MEDLINE-EBSCO, APA PsycInfo, CINAHL Plus, Cochrane Library, Scopus, OAIster, OVID-MEDLINE, Web of Science, and Google Scholar. Screening by titles was followed by an abstract and full-text review. After blind evaluation, agreement between reviewers was reached to establish drug characteristics and categories. Results After 3163 articles were identified, 13 were included: 11 assigned risk scores to anticholinergic drugs and two to sedative drugs. Considerable variability between anticholinergic scales was observed; scales included between 27 and 548 drugs. We generated a comprehensive table combining the anticholinergic and sedative activities of drugs evaluated and proposed a categorization of these drugs based on available scientific and clinical evidence. Our table combines information about 642 drugs and categorizes 44, 25, 99, and 474 drugs as high, moderate, low, or no anticholinergic and sedative activity, respectively. Conclusions Variability and inconsistency exists among scales used to categorize drugs with anticholinergic or sedative burden. In this review, we provide a comprehensive table that proposes a new categorization of these drugs. A longitudinal study will be required to validate the new proposed anticholinergic and sedative burden catalog in an evidence-based manner.
Determination of the risk–benefit ratio associated with the use of novel coronavirus disease 2019 (COVID-19) repurposed drugs in older adults with polypharmacy is mandatory. Our objective was to develop and validate a strategy to assess risk for adverse drug events (ADE) associated with COVID-19 repurposed drugs using hydroxychloroquine (HCQ) and chloroquine (CQ), alone or in combination with azithromycin (AZ), and the combination lopinavir/ritonavir (LPV/r). These medications were virtually added, one at a time, to drug regimens of 12,383 participants of the Program of All-Inclusive Care for the Elderly. The MedWise Risk Score (MRSTM) was determined from 198,323 drug claims. Results demonstrated that the addition of each repurposed drug caused a rightward shift in the frequency distribution of MRSTM values (p < 0.05); the increase was due to an increase in the drug-induced Long QT Syndrome (LQTS) or CYP450 drug interaction burden risk scores. Increases in LQTS risk observed with HCQ + AZ and CQ + AZ were of the same magnitude as those estimated when terfenadine or terfenadine + AZ, used as positive controls for drug-induced LQTS, were added to drug regimens. The simulation-based strategy performed offers a way to assess risk of ADE for drugs to be used in people with underlying medical comorbidities and polypharmacy at risk of COVID-19 infection without exposing them to these drugs.
Superoscillations, oscillations of a bandlimited signal at frequencies greater than its band limit, have been verified both theoretically and experimentally. The design of such superoscillatory waves, however, has typically relied on complicated mathematics. We introduce a simple Fourier method to construct superoscillations in the transverse plane of an optical field in the form of optical vortices.
Sensor data validity is extremely important in a number of applications, particularly building technologies. An example of this is Oak Ridge National Laboratory's ZEBRAlliance research project, which consists of four singlefamily homes located in Oak Ridge, TN. The homes are outfitted with a total of 1,218 sensors to determine the performance of a variety of different technologies integrated within each home. Issues arise with such a large amount of sensors, such as missing or corrupt data. This paper aims to eliminate these problems using: (1) Kalman filtering and (2) linear predictive coding (LPC) techniques. Simulations show the Kalman filtering method performed best in predicting temperature, humidity, pressure, and airflow data, while the LPC method performed best with energy consumption data.
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