The immense body of knowledge that emergency medicine (EM) encompasses is constantly growing and ever changing. Textbooks build a strong foundation for the EM resident, but journal articles critical for modifying and improving EM practices are equally important for a well-rounded education. Determining which journal articles are vital to an EM residency education is a challenge. Lacking a formalized list of key articles available to EM residents and realizing that a list of articles without a guide may be difficult and confusing for novice readers, we created the “Colorado Compendium”: a recommended reading list, limited to 100 articles with accompanying summaries, tailored to emergency medicine residents.
Prediction models using multiple logistic regression are appearing with increasing frequency in the medical literature. Problems associated with these models include the complexity of computations when applied in their pure form, and lack of availability at the bedside. Personal digital assistant (PDA) hand-held devices equipped with spreadsheet software offer the clinician a readily available and easily applied means of applying predictive models at the bedside. The purposes of this article are to briefly review regression as a means of creating predictive models and to describe a method of choosing and adapting logistic regression models to emergency department (ED) clinical practice.
