In this large, prospective, multinational cohort, more than one half of all cases of non-HACEK gram-negative bacillus endocarditis were associated with health care contact. Non-HACEK gram-negative bacillus endocarditis is not primarily a disease of injection drug users.

BackgroundHost 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 ResultsUsing 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.ConclusionsSix‐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.

In this prospective, multinational cohort of patients with S. aureus PVIE, EVS was not associated with reduced 1-year mortality. The decision to pursue EVS should be individualized for each patient, based upon infection-specific characteristics rather than solely upon the microbiology of the infection causing PVIE.

Reducing custom software development effort is an important goal in information retrieval (IR). This study evaluated a generalizable approach involving with no custom software or rules development. The study used documents "consistent with cancer" to evaluate system performance in the domains of colorectal (CRC), prostate (PC), and lung (LC) cancer. Using an end-user-supplied reference set, the automated retrieval console (ARC) iteratively calculated performance of combinations of natural language processing-derived features and supervised classification algorithms. Training and testing involved 10-fold cross-validation for three sets of 500 documents each. Performance metrics included recall, precision, and F-measure. Annotation time for five physicians was also measured. Top performing algorithms had recall, precision, and F-measure values as follows: for CRC, 0.90, 0.92, and 0.89, respectively; for PC, 0.97, 0.95, and 0.94; and for LC, 0.76, 0.80, and 0.75. In all but one case, conditional random fields outperformed maximum entropy-based classifiers. Algorithms had good performance without custom code or rules development, but performance varied by specific application.

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