Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
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In part 1 of this series, the authors describe the importance of incomplete data in clinical research, and provide a conceptual framework for handling incomplete data by describing typical mechanisms and patterns of censoring, and detailing a variety of relatively simple methods and their limitations. In part 2, the authors will explore multiple imputation (MI), a more sophisticated and valid method for handling incomplete data in clinical research. This article will provide a detailed conceptual framework for MI, comparative examples of MI versus naive methods for handling incomplete data (and how different methods may impact subsequent study results), plus a practical user's guide to implementing MI, including sample statistical software MI code and a deidentified precoded database for use with the sample code.
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Multicenter Study
Lack of agreement in pediatric emergency department discharge diagnoses from clinical and administrative data sources.
Diagnosis information from existing data sources is used commonly for epidemiologic, administrative, and research purposes. The quality of such data for emergency department (ED) visits is unknown. ⋯ ED diagnoses retrieved from electronic administrative sources and manual chart review frequently disagree, even if similar diagnosis codes are grouped. Agreement varies by institution and by diagnosis. Further work is needed to improve the accuracy of diagnosis coding; development of a grouping system specific to pediatric emergency care may be beneficial.
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Randomized Controlled Trial Comparative Study
Can untrained laypersons use a defibrillator with dispatcher assistance?
Automated external defibrillators (AEDs) provide an opportunity to improve survival in out-of-hospital cardiac arrest by enabling laypersons not trained in rhythm recognition to deliver lifesaving therapy. This study was performed to examine whether untrained laypersons could safely and effectively use these AEDs with telephone-guided instructions and if this action would compromise the performance of cardiopulmonary resuscitation (CPR) during a simulated ventricular fibrillation out-of-hospital cardiac arrest. ⋯ The quality of dispatcher-assisted CPR is poor. Dispatcher assistance in defibrillation by a layperson not trained to use an AED seems feasible and does not compromise the performance of CPR.
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Comparative Study
Gender bias in cardiovascular testing persists after adjustment for presenting characteristics and cardiac risk.
Previous studies have found that female patients receive fewer invasive tests for cardiovascular disease than male patients. The authors assessed whether different clinical characteristics at emergency department presentation account for this gender bias. ⋯ Female patients with potential ACS receive fewer cardiac catheterizations than male patients, even when presenting complaint, history, ECG, and diagnosis are taken into account. The gender bias cannot be explained by differences in presentation or clinical course.
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Missing data are commonly encountered in clinical research. Unfortunately, they are often neglected or not properly handled during analytic procedures, and this may substantially bias the results of the study, reduce study power, and lead to invalid conclusions. ⋯ In part 1, the authors will describe relatively simple approaches to handling missing data, including complete-case analysis, available-case analysis, and several forms of single imputation, including mean imputation, regression imputation, hot and cold deck imputation, last observation carried forward, and worst case analysis. In part 2, the authors will describe in detail multiple imputation, a more sophisticated and valid method for handling missing data.