In:
Journal of the American Heart Association, Ovid Technologies (Wolters Kluwer Health), Vol. 5, No. 4 ( 2016-04-03)
Abstract:
Host factors and complications have been associated with higher mortality in infective endocarditis ( IE ). We sought to develop and validate a model of clinical characteristics to predict 6‐month mortality in IE . Methods and Results Using a large multinational prospective registry of definite IE (International Collaboration on Endocarditis [ ICE ]–Prospective Cohort Study [ PCS ], 2000–2006, n=4049), a model to predict 6‐month survival was developed by Cox proportional hazards modeling with inverse probability weighting for surgery treatment and was internally validated by the bootstrapping method. This model was externally validated in an independent prospective registry ( ICE ‐ PLUS , 2008–2012, n=1197). The 6‐month mortality was 971 of 4049 (24.0%) in the ICE ‐ PCS cohort and 342 of 1197 (28.6%) in the ICE ‐ PLUS cohort. Surgery during the index hospitalization was performed in 48.1% and 54.0% of the cohorts, respectively. In the derivation model, variables related to host factors (age, dialysis), IE characteristics (prosthetic or nosocomial IE , causative organism, left‐sided valve vegetation), and IE complications (severe heart failure, stroke, paravalvular complication, and persistent bacteremia) were independently associated with 6‐month mortality, and surgery was associated with a lower risk of mortality (Harrell's C statistic 0.715). In the validation model, these variables had similar hazard ratios (Harrell's C statistic 0.682), with a similar, independent benefit of surgery (hazard ratio 0.74, 95% CI 0.62–0.89). A simplified risk model was developed by weight adjustment of these variables. Conclusions Six‐month mortality after IE is ≈25% and is predicted by host factors, IE characteristics, and IE complications. Surgery during the index hospitalization is associated with lower mortality but is performed less frequently in the highest risk patients. A simplified risk model may be used to identify specific risk subgroups in IE .
Type of Medium:
Online Resource
ISSN:
2047-9980
DOI:
10.1161/JAHA.115.003016
Language:
English
Publisher:
Ovid Technologies (Wolters Kluwer Health)
Publication Date:
2016
detail.hit.zdb_id:
2653953-6
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