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|Title:||A pragmatic approach for mortality prediction after surgery in infective endocarditis: optimizing and refining EuroSCORE.|
Marsal, J R
Aznar, M L
de Alarcón, A
Reguera-Iglesias, J M
De La Torre-Lima, J
Lomas, J M
Castro, M A
|metadata.dc.subject.mesh:||Cardiac Surgical Procedures|
|Abstract:||To simplify and optimize the ability of EuroSCORE I and II to predict early mortality after surgery for infective endocarditis (IE). Multicentre retrospective study (n = 775). Simplified scores, eliminating irrelevant variables, and new specific scores, adding specific IE variables, were created. The performance of the original, recalibrated and specific EuroSCOREs was assessed by Brier score, C-statistic and calibration plot in bootstrap samples. The Net Reclassification Index was quantified. Recalibrated scores including age, previous cardiac surgery, critical preoperative state, New York Heart Association >I, and emergent surgery (EuroSCORE I and II); renal failure and pulmonary hypertension (EuroSCORE I); and urgent surgery (EuroSCORE II) performed better than the original EuroSCOREs (Brier original and recalibrated: EuroSCORE I: 0.1770 and 0.1667; EuroSCORE II: 0.2307 and 0.1680). Performance improved with the addition of fistula, staphylococci and mitral location (EuroSCORE I and II) (Brier specific: EuroSCORE I 0.1587, EuroSCORE II 0.1592). Discrimination improved in specific models (C-statistic original, recalibrated and specific: EuroSCORE I: 0.7340, 0.7471 and 0.7728; EuroSCORE II: 0.7442, 0.7423 and 0.7700). Calibration improved in both EuroSCORE I models (intercept 0.295, slope 0.829 (original); intercept -0.094, slope 0.888 (recalibrated); intercept -0.059, slope 0.925 (specific)) but only in specific EuroSCORE II model (intercept 2.554, slope 1.114 (original); intercept -0.260, slope 0.703 (recalibrated); intercept -0.053, slope 0.930 (specific)). Net Reclassification Index was 5.1% and 20.3% for the specific EuroSCORE I and II. The use of simplified EuroSCORE I and EuroSCORE II models in IE with the addition of specific variables may lead to simpler and more accurate models.|
|Appears in Collections:||Producción 2020|
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