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Objective: We propose 2 Medical Dictionary for Regulatory Activities-enabled pharmacovigilance algorithms, MetaLAB and MetaNurse, powered by a per-year meta-analysis technique and improved subject sampling strategy.Matrials and Methods: This study developed 2 novel algorithms, MetaLAB for laboratory abnormalities and MetaNurse for standard nursing statements, as significantly improved versions of our previous electronic health record (EHR)-based pharmacovigilance method, called CLEAR. Adverse drug reaction (ADR) signals from 117 laboratory abnormalities and 1357 standard nursing statements for all precautionary drugs ( n   = 101) were comprehensively detected and validated against SIDER (Side Effect Resource) by MetaLAB and MetaNurse against 11 817 and 76 457 drug-ADR pairs, respectively.Results: We demonstrate that MetaLAB (area under the curve, AUC = 0.61 ± 0.18) outperformed CLEAR (AUC = 0.55 ± 0.06) when we applied the same 470 drug-event pairs as the gold standard, as in our previous research. Receiver operating characteristic curves for 101 precautionary terms in the Medical Dictionary for Regulatory Activities Preferred Terms were obtained for MetaLAB and MetaNurse (0.69 ± 0.11; 0.62 ± 0.07), which complemented each other in terms of ADR signal coverage. Novel ADR signals discovered by MetaLAB and MetaNurse were successfully validated against spontaneous reports in the US Food and Drug Administration Adverse Event Reporting System database.Discussion: The present study demonstrates the symbiosis of laboratory test results and nursing statements for ADR signal detection in terms of their system organ class coverage and performance profiles.Conclusion: Systematic discovery and evaluation of the wide spectrum of ADR signals using standard-based observational electronic health record data across many institutions will affect drug development and use, as well as postmarketing surveillance and regulation. [ABSTRACT FROM AUTHOR]

Statin therapy is beneficial in reducing cardiovascular events and mortalities in patients with atherosclerotic cardiovascular diseases. Yet, there have been concerns of increased risk of diabetes with statin use. This study was aimed to evaluate the association between statins and new onset diabetes mellitus (NODM) in patients with ischemic heart disease (IHD) utilizing the Korean Health Insurance Review and Assessment Service claims database. Among adult patients with preexisting IHD, new statin users and matched nonstatin users were identi- fied on a 1:1 ratio using proportionate stratified random sampling by sex and age. They were subsequently propensity score matched further with age and comorbidities to reduce the selection bias. Overall incidence rates, cumulative rates and hazard ratios (HRs) between statin use and occurrence of NODM were estimated. The subgroup analyses were performed according to sex, age groups, and the individual agents and intensities of statins. A total of 156,360 patients (94,370 in the statin users and 61,990 in the nonstatin users) were included in the analysis. The incidence rates of NODM were 7.8% and 4.8% in the statin users and nonstatin users, respectively. The risk of NODM was higher among statin users (crude HR 2.01, 95% confidence interval [CI] 1.93-2.10; adjusted HR 1.84, 95% CI 1.63-2.09). Pravastatin had the lowest risk (adjusted HR 1.54, 95% CI 1.32-1.81) while those who were exposed to more than one statin were at the highest risk of NODM (adjusted HR 2.17, 95% CI 1.93-2.37). It has been concluded that all statins are associated with the risk of NODM in patients with IHD, and it is believed that our study would contribute to a better understanding of statin and NODM association by analyzing statin use in the real-world setting. Periodic screening and monitoring for diabetes are warranted during prolonged statin therapy in patients with IHD. [ABSTRACT FROM AUTHOR]

This article addresses how we learn technology across the lifespan. After outlining findings of research into how children, adolescents, teens and adults learn technology, we address theoretical shifts from sociocultural to technocultural theories of cognition and reorientations from mediated to cyborgenic learning. The balance of the article describes effective methods for researching cognition and technology. In the process of outlining key findings from research, we emphasize the links among methods and theories employed, data produced and conclusions drawn. Our goal is to sketch a lifelong learning context for undertaking studies of cognition and technology, and to provide a methodological and theoretical analysis for researchers venturing into this dynamic and volatile field. In summary, we provide a far-ranging agenda for researching cognition and technology. [ABSTRACT FROM AUTHOR]