Purpose To examine the range of prevalence of pediatric polypharmacy in literature through a scoping review, focusing on factors that contribute to its heterogeneity in order to improve the design and reporting of quality improvement, pharmacovigilance, and research studies. Methods We searched Ovid Medline, PubMed, EMBASE, CINAHL, Ovid PsycINFO, Cochrane CENTRAL, and Web of Science Core Collection databases for studies with concepts of children and polypharmacy, along with a hand search of the bibliographies of six reviews and 30 included studies. We extracted information regarding study design, disease conditions, and prevalence of polypharmacy. Results Two hundred eighty‐four studies reported prevalence of polypharmacy. They were more likely to be conducted in North America (37.7%), published after 2010 (44.4%), cross‐sectional (67.3%), in outpatient settings (59.5%). Prevalence ranged from 0.9% to 98.4%, median 39.7% (interquartile range [IQR] 22.0%‐54.0%). Studies from Asia reported the highest median prevalence of 45.4% (IQR 27.3%‐61.0%) while studies from North America reported the lowest median prevalence of 30.4% (IQR 14.7%‐50.2%). Prevalence decreased over time: median 45.6% before 2001, 38.1% during 2001 to 2010, and 34% during 2011 to 2017. Studies involving children under 12 years had a higher median prevalence (46.9%) than adolescent studies (33.7%). Inpatient setting studies had a higher median prevalence (50.3%) than studies in outpatient settings (38.8%). Community level samples, higher number and duration of medications defining polypharmacy, and psychotropic medications were associated with lower prevalence. Conclusions The prevalence of pediatric polypharmacy is high and variable. Studies reporting pediatric polypharmacy should account for context, design, polypharmacy definition, and medications evaluated.

In research on photovoltaic (PV) device degradation, current-voltage (I-V ) datasets carry a large amount of information in addition to the maximum power point. Performance parameters such as short-circuit current, open-circuit voltage, shunt resistance, series resistance, and fill factor are essential for diagnosing the performance and degradation of solar cells and modules. To enable the scaling of I-V studies to millions of I-V curves, we have developed a data-driven method to extract I-V curve parameters and distributed this method as an open-source package in R. In contrast with the traditional practice of fitting the diode equation to I-V curves individually, which requires solving a transcendental equation, this data-driven method can be applied to large volumes of I-V data in a short time. Our data-driven feature extraction technique is tested on I-V curves generated with the single-diode model and applied to I-V curves with different data point densities collected from three different sources. This method has a high repeatability for extracting I-V features, without requiring knowledge of the device or expected parameters to be input by the researcher. We also demonstrate how this method can be applied to large datasets and accommodates nonstandard I-V curves including those showing artifacts of connection problems or shading where bypass diode activation produces multiple "steps." These features together make the data-driven I-V feature extraction method ideal for evaluating time-series I-V data and analyzing power degradation mechanisms in PV modules through cross comparisons of the extracted parameters.

Purpose:The purpose of this study is to describe medications most commonly studied in pediatric polypharmacy research by pharmacologic classes and disease using a scoping review methodology.Methods: A search of electronic databases was conducted in July 2019 that included Ovid Medline, PubMed, Elsevier Embase, and EBSCO CINAHL. Primary observational studies were selected if they evaluated polypharmacy as an aim, outcome, predictor, or covariate in children 0-21 years of age. Studies not differentiating between adults and children or those not written in English were excluded. Study characteristics, pharmacologic categories, medication classes, and medications were extracted from the included studies. Results:The search identified 8,790 titles and after de-duplicating and full text screening, 414 studies were extracted for the primary data. Regarding global pharmacologic categories, central nervous system (CNS) agents were most studied (n=185, 44.9%). The most reported *

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