BACKGROUND: This study was undertaken to identify the prevalence of pulmonary embolism (PE) in the emergency department (ED) of an urban teaching hospital and also to test a Bayesian model in estimating the number of CT pulmonary angiography (CTA) expected to be performed in an emergency department. METHODS: The data for this study was obtained through a retrospective review of electronic medical records for all ED patients suspected of PE who underwent chest CTA or ventilation perfusion scanning (V/Q) between 2009 and 2010. The data is presented as means and standard deviation for continuous variables and percentages with 95% confidence intervals (95%CI) for proportions. The prevalence of PE was used as pre-test probability in the Bayesian model. Post-test probability was obtained using a Fagan nomogram and likelihood ratios for CTA. RESULTS: A total of 778 patients (560 females) with mean age of 50 years (range 18-98 years) were enrolled (98.3% underwent chest CTA and 1.7% underwent V/Q scan). A total of 69 patients had PE, rendering an overall prevalence of 8.9% (95%CI, 7.1% to 11.1%) for PE. We calculated that 132 CTA's per year could be avoided in our institution, without compromising safe exclusions of PE (keeping post-test probability of PE below 2%). CONCLUSIONS: Despite differences in our patient populations and /or study designs, the prevalence of PE in our institution is about average compared to other institutions. Our proposed model for calculating redundant chest CTA is simple and can be used by institutions to identify overuse of CTA.
BACKGROUND: This study was undertaken to identify the prevalence of pulmonary embolism (PE) in the emergency department (ED) of an urban teaching hospital and also to test a Bayesian model in estimating the number of CT pulmonary angiography (CTA) expected to be performed in an emergency department. METHODS: The data for this study was obtained through a retrospective review of electronic medical records for all ED patients suspected of PE who underwent chest CTA or ventilation perfusion scanning (V/Q) between 2009 and 2010. The data is presented as means and standard deviation for continuous variables and percentages with 95% confidence intervals (95%CI) for proportions. The prevalence of PE was used as pre-test probability in the Bayesian model. Post-test probability was obtained using a Fagan nomogram and likelihood ratios for CTA. RESULTS: A total of 778 patients (560 females) with mean age of 50 years (range 18-98 years) were enrolled (98.3% underwent chest CTA and 1.7% underwent V/Q scan). A total of 69 patients had PE, rendering an overall prevalence of 8.9% (95%CI, 7.1% to 11.1%) for PE. We calculated that 132 CTA's per year could be avoided in our institution, without compromising safe exclusions of PE (keeping post-test probability of PE below 2%). CONCLUSIONS: Despite differences in our patient populations and /or study designs, the prevalence of PE in our institution is about average compared to other institutions. Our proposed model for calculating redundant chest CTA is simple and can be used by institutions to identify overuse of CTA.
Authors: Peter B Richman; D Mark Courtney; Jeremy Friese; Jessica Matthews; Adam Field; Roland Petri; Jeffrey A Kline Journal: Acad Emerg Med Date: 2004-06 Impact factor: 3.451
Authors: Ian D Weir; Frank Drescher; Daniel Cousin; Ezra T Fraser; Ronald Lee; Lewis Berman; Edward Strauss; Yun Wang; Jonathan M Fine Journal: Conn Med Date: 2010-01
Authors: Arne van Belle; Harry R Büller; Menno V Huisman; Peter M Huisman; Karin Kaasjager; Pieter W Kamphuisen; Mark H H Kramer; Marieke J H A Kruip; Johanna M Kwakkel-van Erp; Frank W G Leebeek; Mathilde Nijkeuter; Martin H Prins; Maaike Sohne; Lidwine W Tick Journal: JAMA Date: 2006-01-11 Impact factor: 56.272
Authors: D Mark Courtney; Jeffrey A Kline; Christopher Kabrhel; Christopher L Moore; Howard A Smithline; Kristen E Nordenholz; Peter B Richman; Michael C Plewa Journal: Ann Emerg Med Date: 2010-01-01 Impact factor: 5.721