Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
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Patients presenting with chest pain or related symptoms suggestive of myocardial ischemia, without ST-segment elevation (NSTE) on their presenting electrocardiograms, often present a diagnostic challenge in the emergency department (ED). Prompt and accurate risk stratification to identify those patients with NSTE chest pain who are at highest risk for adverse events is essential, however, to optimal management. Although validated and used frequently in patients already enrolled in acute coronary syndrome trials, the Thrombolysis in Myocardial Infarction (TIMI) risk score never has been examined for its value in risk stratification in an all-comers, non-trial-based ED chest pain population. ⋯ The TIMI risk score may be a useful tool for risk stratification of ED patients with chest pain syndrome.
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To determine whether the Mac-technique test can detect kinking of the chest tube upon thoracostomy tube placement. ⋯ On the basis of this study, a positive Mac-technique test is useful to detect chest tubes that are likely to be kinked after insertion and before securing.
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To determine the publication status and time to publication of randomized controlled trials (RCTs) that were presented at the Society for Academic Emergency Medicine (SAEM) meetings from 1995 to 2003. The impact of positive-outcome bias, time-lag bias, and gray literature bias also was assessed. ⋯ The proportion of emergency medicine RCT abstracts published is slightly lower than that for other biomedical specialties; however, biases reported by investigators in other biomedical areas do not appear to be as problematic in emergency medicine research. Differences between conclusions from abstracts and manuscripts must be considered when employing meeting abstracts as a source of evidence for future research or for systematic reviews in emergency medicine.
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Comparative Study
Using queueing theory to increase the effectiveness of emergency department provider staffing.
Significant variation in emergency department (ED) patient arrival rates necessitates the adjustment of staffing patterns to optimize the timely care of patients. This study evaluated the effectiveness of a queueing model in identifying provider staffing patterns to reduce the fraction of patients who leave without being seen. ⋯ Timely access to a provider is a critical dimension of ED quality performance. In an environment in which EDs are often understaffed, analyses of arrival patterns and the use of queueing models can be extremely useful in identifying the most effective allocation of staff.