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. 2010 May;54(5):589-95.
doi: 10.1111/j.1399-6576.2009.02205.x. Epub 2010 Jan 18.

Mixed venous oxygen saturation is a prognostic marker after surgery for aortic stenosis

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Mixed venous oxygen saturation is a prognostic marker after surgery for aortic stenosis

J Holm et al. Acta Anaesthesiol Scand. 2010 May.

Abstract

Background: Adequate monitoring of the hemodynamic state is essential after cardiac surgery and is vital for medical decision making, particularly concerning hemodynamic management. Unfortunately, commonly used methods to assess the hemodynamic state are not well documented with regard to outcome. Mixed venous oxygen saturation (SvO(2)) was therefore investigated after cardiac surgery.

Methods: Detailed data regarding mortality were available on all patients undergoing aortic valve replacement for isolated aortic stenosis during a 5-year period in the southeast region of Sweden (n=396). SvO(2) was routinely measured on admission to the intensive care unit (ICU) and registered in a database. A receiver operating characteristics (ROC) analysis of SvO(2) in relation to post-operative mortality related to cardiac failure and all-cause mortality within 30 days was performed.

Results: The area under the curve (AUC) was 0.97 (95% CI 0.96-1.00) for mortality related to cardiac failure (P=0.001) and 0.76 (95% CI 0.53-0.99) for all-cause mortality (P=0.011). The best cutoff for mortality related to cardiac failure was SvO(2) 53.7%, with a sensitivity of 1.00 and a specificity of 0.94. The negative predictive value was 100%. The best cutoff for all-cause mortality was SvO(2) 58.1%, with a sensitivity of 0.75 and a specificity of 0.84. The negative predictive value was 99.4%. Post-operative morbidity was also markedly increased in patients with a low SvO(2).

Conclusion: SvO(2), on admission to the ICU after surgery for aortic stenosis, demonstrated excellent sensitivity and specificity for post-operative mortality related to cardiac failure and a fairly good AUC for all-cause mortality, with an excellent negative predictive value.

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