Literature DB >> 16679076

Influence of cardiac risk factors and medication on length of hospitalization in patients undergoing major vascular surgery.

Marleen A van de Pol1, Mark van Houdenhoven, Erwin W Hans, Eric Boersma, Jeroen J Bax, Harm H H Feringa, Olaf Schouten, Marc R H M van Sambeek, Don Poldermans.   

Abstract

Major vascular surgery is associated with a long in-hospital length of stay (LOS). Cardiac risk factors identify patients with an increased risk. Recent studies have associated statin, aspirin, and beta-blocker therapies with improved postoperative outcome. However, the effect of all these factors on LOS has not been defined. Our aims were to determine the effect of cardiac risk factors and (preventive) statin, aspirin, and beta-blocker therapy on LOS and to deduce from these factors a model that predicts LOS. In total, 2,374 patients from 1990 to 2004 were enrolled. Mean LOS was 18 +/- 9 days. Cardiac risk factors that were significantly associated with LOS in the multivariable analysis were age, previous heart failure, hypertension, diabetes mellitus, renal failure, and chronic obstructive pulmonary disease. Statin and aspirin use was associated with a shorter LOS. Beta blockers shortened LOS only in patients with underlying coronary artery disease. Together, these factors explained 14.1% of the variance in LOS. In conclusion, in-hospital LOS in patients who undergo major vascular surgery can be predicted more accurately by clinical cardiac risk factors. A significant decrease in in-hospital LOS was achieved with statin, aspirin, and beta-blocker therapies.

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Year:  2006        PMID: 16679076     DOI: 10.1016/j.amjcard.2005.12.032

Source DB:  PubMed          Journal:  Am J Cardiol        ISSN: 0002-9149            Impact factor:   2.778


  2 in total

Review 1.  Current and future status of beta-blockers in the treatment of hypertension.

Authors:  Steven G Chrysant; George S Chrysant; Billy Dimas
Journal:  Clin Cardiol       Date:  2008-06       Impact factor: 2.882

2.  Optimizing intensive care capacity using individual length-of-stay prediction models.

Authors:  Mark Van Houdenhoven; Duy-Tien Nguyen; Marinus J Eijkemans; Ewout W Steyerberg; Hugo W Tilanus; Diederik Gommers; Gerhard Wullink; Jan Bakker; Geert Kazemier
Journal:  Crit Care       Date:  2007       Impact factor: 9.097

  2 in total

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