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  Vol. 289 No. 15, April 16, 2003 TABLE OF CONTENTS
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Complicated Left-Sided Native Valve Endocarditis in Adults

Risk Classification for Mortality

Rodrigo Hasbun, MD; Holenarasipur R. Vikram, MD; Lydia A. Barakat, MD; Joan Buenconsejo, MPH; Vincent J. Quagliarello, MD

JAMA. 2003;289:1933-1940.

ABSTRACT

Context  Complicated left-sided native valve endocarditis causes significant morbidity and mortality in adults. Lack of valid data regarding estimation of prognosis makes management of this condition difficult.

Objective  To derive and externally validate a prognostic classification system for adults with complicated left-sided native valve endocarditis.

Design, Setting, and Patients  Retrospective observational cohort study conducted from January 1990 to January 2000 at 7 Connecticut hospitals among 513 patients older than 16 years who experienced complicated left-sided native valve endocarditis and who were divided into derivation (n = 259) and validation (n = 254) cohorts.

Main Outcome Measure  All-cause mortality at 6 months after baseline.

Results  In the derivation and validation cohorts, the 6-month mortality rates were 25% and 26%, respectively. Five baseline features were independently associated with 6-month mortality (comorbidity [P = .03], abnormal mental status [P = .02], moderate to severe congestive heart failure [P = .01], bacterial etiology other than viridans streptococci [P<.001 except Staphylococcus aureus, P = .004], and medical therapy without valve surgery [P = .002]) and were used to create a prognostic classification system. In the derivation cohort, patients were classified into 4 groups with increasing risk for 6-month mortality: 5%, 15%, 31%, and 59% (P<.001). In the validation cohort, a similar risk among the 4 groups was observed: 7%, 19%, 32%, and 69% (P<.001).

Conclusions  Adults with complicated left-sided native valve endocarditis can be accurately risk stratified using baseline features into 4 groups of prognostic severity. This prognostic classification system might be useful for facilitating management decisions.



INTRODUCTION
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In the preantibiotic era, native valve endocarditis was virtually always fatal. Since the advent of antibiotic therapy, mortality decreased to 24% to 60% in published case series, with heart failure representing the leading cause of death.1-4 During the past 3 decades, studies have suggested that valve surgery should be considered for patients with native valve endocarditis associated with complications that adversely affect prognosis: heart failure,5-10 new valvular regurgitation,11-13 refractory infection (ie, persistent fever or bacteremia, fungemia, or paravalvular abscess),14-15 systemic embolization to vital organs,16-17 and the presence of a vegetation on echocardiography as this represents a plausible risk for embolization.18-20 However, methodological limitations of existing studies, the absence of randomized controlled trials, and the lack of a validated method to classify prognostic severity make management decisions problematic.

Accurate prognostic classification may help facilitate individual treatment decisions and interpretation of therapeutic interventions in clinical trials. In this study, we derived and externally validated a prognostic classification system in 2 contemporaneous cohorts of adults with complicated left-sided native valve endocarditis.


METHODS
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Patients

Research patients were identified through systematic medical record review at the 7 Connecticut hospitals where valve surgery was performed. To create and test a prognostic classification system, we divided patients into derivation and validation cohorts (Figure 1). The derivation cohort (n = 259) was assembled from adults (>16 years) in whom complicated left-sided native valve endocarditis was diagnosed at 1 of 5 hospitals serving New Haven (Yale-New Haven Hospital, Hospital of St Raphael), West Haven (Veterans Administration Connecticut Health Care System), and Bridgeport (Bridgeport Hospital and St Vincent's Hospital), Conn, from January 1990 to January 2000.



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Figure. Eligibility Criteria and Sample Size


The validation cohort (n = 254) was assembled similarly during the same period for patients given a diagnosis at 2 hospitals serving a separate geographic location in Hartford, Conn (Hartford Hospital and St Francis Hospital). Patients were identified as having infective endocarditis if they met the Duke criteria for definite or possible endocarditis.21

Patients were included if they had left-sided involvement of a native valve (aortic valve, mitral valve, or both) and they had exhibited a clinical complication for which valve surgery is considered in current clinical practice: congestive heart failure, new valvular regurgitation, refractory infection, systemic embolization to vital organs, or presence of a vegetation on echocardiography. For patients with multiple episodes of endocarditis, only the first episode was analyzed. Patients were excluded if they were comatose at baseline, if clinical outcome data were not available 6 months after baseline, or if the decision about surgery was not explicitly stated in the medical record. The study was approved by the Human Investigation Committee at Yale University School of Medicine as well as by the institutional review boards of all 7 participating hospitals.

Clinical Data

From medical records, baseline clinical information was systematically extracted on sociodemographic data, comorbid conditions, previous heart disease, exposures, symptoms, physical findings, blood cultures, electrocardiogram, echocardiography, as well as the type and duration of therapy (Table 1). Baseline features were assessed at a specified baseline defined as the date of valve surgery or the date that the decision not to operate was recorded in the medical record. Comorbidity was assessed by using the Charlson comorbidity scale,22 which assigns weights to specific comorbid disease states: 1 point (myocardial infarction, congestive heart failure, peripheral vascular disease, cerebrovascular disease, dementia, chronic pulmonary disease, connective tissue disease, ulcer disease, mild liver disease, diabetes), 2 points (hemiplegia, moderate to severe renal disease, diabetes with end-organ damage, any tumor, leukemia, lymphoma), 3 points (moderate to severe liver disease), and 6 points (metastatic solid tumor or acquired immunodeficiency syndrome).


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Table 1. Patient Characteristics and Microbiological Causes*


Outcomes

The primary outcome was all-cause mortality at 6 months after baseline. All patient episodes were followed up for the 6-month period after baseline for survival or death. For patients whose medical records lacked documentation of survival or death 6 months after baseline, the National Death Index was used to determine outcome. The National Death Index has demonstrated accuracy of 97% to 100% in determining vital status, and may have superiority over other databases in determining date of death.23-25

Statistical Analyses

After a comprehensive descriptive comparison of derivation and validation cohorts, bivariate analyses were performed to detect associations of clinically plausible baseline features with 6-month mortality. Cutoff levels of continuous variables were chosen to be clinically meaningful. Differences in proportions were tested by using the {chi}2 test or the Fisher exact test. For contrasts of continuous variables, the t test and the Wilcoxon rank sum test were used. Baseline features of the derivation cohort associated with death in bivariate analyses were subject to multivariable analyses using stepwise logistic regression modeling to identify predictors based on the likelihood ratio test. Clinically plausible interactions among baseline variables were also tested. The adjusted odds ratio (OR) from the logistic regression was converted to relative risk (RR) using the formula:

RR = OR/[(1 - P) + (P x OR)],

where P is the incidence of the outcome event in the nonexposed group.26 No more than 1 variable per 10 outcome events was entered in logistic models to avoid overfitting.27 The goodness-of-fit of the final model was examined by using the Hosmer-Lemeshow test. Using the independently prognostic baseline variables identified in logistic modeling, we developed a weighted scoring assignment using linear transformation of parameter coefficients that classified patients into 4 quartiles of risk for death 6 months after baseline.

Model calibration was assessed by comparing predicted and observed mortality rates in the validation cohort. Model discrimination was measured by using the concordance index.28 This statistic describes the likelihood that among any 2 randomly chosen patients where 1 died and 1 did not the model would have correctly chosen which one was at more risk. All analyses were conducted by using SAS version 8.02 (SAS Institute, Cary, NC). P<.05 was considered statistically significant.


RESULTS
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Cohort Identification

After initial screening of 1611 medical records at the 7 hospitals, 513 patient episodes met eligibility criteria for inclusion in the study as having complicated left-sided native valve endocarditis: 259 patients in the derivation cohort and 254 patients in the validation cohort (Figure 1).

Baseline Features, Microbial Etiologies, and Clinical Outcome

Baseline patient features and microbial etiologies are shown in Table 1; imaging studies, clinical complications, surgical findings, and clinical outcome are shown in Table 2. The derivation and validation cohorts were similar with respect to age, sex, race, presence of comorbid disease, immunocompetence, and underlying cardiac disease. Baseline clinical features were also similar, but significantly more patients in the validation cohort had a heart murmur, echocardiographic evidence of an intracardiac abscess, combined aortic and mitral valve involvement, operative documentation of a valvular vegetation and myocardial abscess, and surgery performed primarily related to a greater proportion of bioprosthetic valve replacements.


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Table 2. Imaging Studies, Surgical Therapy, and Clinical Outcomes of the Study*


For the total cohort, fever (78%, n = 400) and dyspnea (33%, n = 169) were the most common presenting symptoms; mitral valve involvement was observed in 257 patients (50%), aortic valve involvement in 180 patients (35%), and both mitral and aortic valves were involved in 76 patients (15%). Clinical complications raising the issue of surgery for the total cohort included anatomic abnormalities in 511 patients (echocardiographic evidence of vegetation in 443 patients [86%]; new valve regurgitation in 335 patients [65%]), moderate or severe congestive heart failure in 222 patients (44%), symptomatic embolic disease in 116 patients (23%), and refractory infection in 109 patients (21%). Overall, 499 patients (97%) of the total cohort met Duke criteria for definite endocarditis with the most common bacterial etiologies being viridans streptococci (36%, n = 183), Staphylococcus aureus (28%, n = 143), Enterococcus (11%, n = 58), and other streptococci (11%, n = 57). Valve surgery was performed on 230 patients (45%) in the total cohort: 109 (21%) had mechanical valve replacement, 102 (20%) had bioprosthetic valve replacement, and 20 (4%) had valve repair (1 patient in the validation cohort had >1 procedure performed). The mortality rate for the total cohort was 26% (n = 131) and was similar in the derivation and validation cohorts (25% and 26%, respectively).

Associations of Baseline Features With 6-Month Mortality

Bivariate analyses relating baseline features to 6-month mortality in the derivation cohort are shown in Table 3. Comorbidity (Charlson score >=2), an immunocompromised state, fever by physical examination, abnormal mental status, and moderate to severe congestive heart failure were clinical features that all showed bivariate association with 6-month mortality. Similarly, bacterial etiologies other than viridans streptococci (particularly S aureus and Enterococcus) were associated with 6-month mortality as well as medical therapy without valve surgery.


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Table 3. Bivariate Association of Baseline Dichotomous Variables and 6-Month Mortality for the Derivation Cohort (n = 259)


Development and Validation of Prognostic Classification System

To determine independent associations with 6-month mortality, all biologically plausible variables showing bivariate associations were entered into a logistic regression model (Table 4). In this model, abnormal mental status, comorbidity, moderate to severe congestive heart failure, S aureus, and other nonviridans streptococci bacterial etiologies remained independently associated with 6-month mortality. Medical therapy without valve surgery also remained significantly associated with 6-month mortality. Using the 5 independently predictive features from the logistic regression model, we developed a prognostic classification system. As an initial step, the 5 predictive baseline features were assigned point scores based on a linear transformation of the parameter coefficients rounded to the closest integer. The resulting scoring system of the 5 predictive features is shown in Table 4. Using this scoring system, prognostic classification was developed in which patients were assigned to 4 prognostic groups based on quartiles of risk for 6-month mortality as follows: group 1 (<=6 points), group 2 (7-11 points), group 3 (12-15 points), and group 4 (>15 points). As shown for the derivation cohort in Table 5, the observed number of patients who died in the 6-month follow-up period were 3 (5%) in group 1, 10 (15%) in group 2, 22 (31%) in group 3, and 31 (59%) in group 4 (P<.001).


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Table 4. Scoring System for the Independent Variables Significantly Associated With 6-Month Mortality*



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Table 5. Prognostic Classification System of Adults With Complicated Left-Sided Native Valve Endocarditis*


For the validation cohort, the observed number of patients who died in the 6-month follow-up period were 6 (7%) in group 1, 15 (19%) in group 2, 17 (32%) in group 3, and 27 (69%) in group 4 (P<.001). The Hosmer-Lemeshow goodness-of-fit test yielded P = .32 for the derivation cohort and P = .39 for the validation cohort, demonstrating that no strong evidence supports lack of fit of the model. Calculation of model discrimination by using the concordance index was 0.80 (95% confidence interval [CI], 0.73-0.87) for the derivation cohort; the concordance index for the validation cohort was 0.81 (95% CI, 0.74-0.88).


COMMENT
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This study analyzed the largest cohort to date of adults with complicated left-sided native valve endocarditis. Five baseline features predicted 6-month mortality and stratified patients into distinct prognostic groups. The prognostic group classification in the derivation cohort worked well in the validation cohort in terms of both calibration and discrimination.

The decision to perform valve surgery in adults with complicated left-sided native valve endocarditis has been controversial since the advent of valve replacement.5 Published recommendations have been based on uncontrolled observational data and expert opinions of experienced clinicians; no prospective randomized trials have been performed. As a result, clinical decisions are often based on anecdotal prognostic estimates of individual patients by practicing physicians without validated evidence. In this study, a rigorously identified cohort of adults with complicated native valve endocarditis was analyzed to derive and validate a prognostic classification system for adults with complicated left-sided native valve endocarditis. This system may assist management decisions for individual patients.

Baseline clinical features and microbial etiologies of our cohort were similar to previous cohorts of adults with left-sided native valve endocarditis. The mortality rate of 26% for the total cohort is higher than in most case series but likely reflected the strict inclusion only of patients with complicated disease at baseline.1 For developing a prognostic classification system, all-cause 6-month mortality was used as the end point to reflect a clinically logical outcome and to minimize detection bias by using the National Death Index to supplement medical record information.

Our study design provided several advantages and avoided the methodological limitations of previous observational cohorts. First, our study cohort was large, yet restricted to adults with left-sided native valve endocarditis who manifested complications at baseline for which valve surgery is considered in contemporary clinical practice (ie, congestive heart failure, new valvular regurgitation, systemic embolization to major organs, refractory infection, or the presence of an echocardiographically identifiable vegetation). Second, our study specified a baseline at which clinical features were assessed for each patient.29 The definitions used resulted in the same median duration of time from admission to baseline for patients who underwent surgery and those who did not (6 days; comparing medically and surgically treated patients, P = .97), and they fostered reproducibility of the prognostic classification system between the derivation and validation cohorts. Identification of a specific baseline fosters generalizability of prognostic assessment among different cohorts of patients; it is particularly important for patients with endocarditis as clinical findings can evolve rapidly. Third, our study used a validated comorbidity index to analyze the impact of comorbidity on risk of death. This index incorporates both the number and severity of underlying disease and was demonstrated to independently predict 6-month mortality in our cohort. Fourth, our prognostic model and classification system were created by using baseline variables that were explicitly defined, clinically plausible, and identifiable by the physician at the bedside, which also fostered reproducibility and practical use. Finally, we tested the model and prognostic classification system in a distinct validation cohort during the same 10-year period.

The 5 baseline features (comorbidity, moderate-to-severe congestive heart failure, altered mental status, bacterial etiology other than viridans streptococci, and medical therapy without valve surgery) that were independently associated with 6-month mortality represent plausible predictors from clinical experience and published literature. Comorbidity, as measured by the Charlson comorbidity scale, has already been validated as predictor of short-term and long-term mortality in adult patients.22 Higher rates of microbiological relapse and mortality have been traditionally recognized for S aureus, Enterococcus, and other species when compared with viridans streptococci.1 Congestive heart failure (primarily related to severe valve dysfunction) has been repeatedly reported as the most common cause of death in native valve endocarditis,6-10 and altered mental status (defined as lethargy or disorientation) has biological plausibility as it represents a marker of overall disease severity (eg, poor cerebral perfusion, metabolic instability, and inflammatory cytokine release) of the microbial sepsis syndrome. Medical therapy without valve surgery has been associated with poor outcome for patients with complicated endocarditis,6-20 particularly in observational studies of patients with congestive heart failure and S aureus bacterial etiology.9, 30-31

Although our study had several methodological advantages, there were limitations. Our cohort of patients was assembled retrospectively, making detection bias in determination of baseline features and clinical outcome an unavoidable possibility. However, our established baseline, rigorous definitions of baseline clinical features, and use of 6-month mortality as the clinical end point all decreased this potential bias. The reproducibility of the classification system in both derivation and validation cohorts supports the contention that this bias was minimized. Our strategy of using mortality as the end point limited the value of the classification system. Prognostic classification of morbidity outcomes (eg, stroke, persistent congestive heart failure, hospitalization, and overall quality of life) are equally valuable and could not be performed using our study design.

Although valve surgery was associated with a decreased risk of 6-month mortality in the multivariable model adjusting for other prognostic variables, this was a nonrandomized treatment assignment. Therefore, other potential confounding and treatment selection biases may have existed that limit conclusions about the benefit of surgery. The fact that patients treated at hospital sites in the validation cohort underwent valve surgery more frequently than patients in the derivation cohort supports the possibility of regional treatment selection biases. Further investigations using methods (eg, propensity analyses) that account for these potential confounding and treatment selection biases will be required to render a more rigorous adjustment than would be possible with standard multivariable techniques.32-33 Our current study cannot be used as evidence that switching from a medical to surgical strategy will necessarily improve survival. Finally, given that the decision to treat medically or surgically may vary between physicians, the actual predictive value of our system may vary according to when or how that decision is made and the system has unknown ability when applied at different points in a patient's course; further study is needed.

Physicians must recognize that our results apply to a restricted group of patients with complicated left-sided native valve endocarditis and not to all patients with endocarditis. Nonetheless, the observations in this study will provide immediate and future guidance for the practicing clinician. Accurate prognostic classification of risk for 6-month mortality among patients with complicated left-sided native valve endocarditis can be performed using available clinical data at the bedside. This may facilitate more reliable discussions among patients and their physicians as to the intensity, type, and expectations of treatment. They provide quantitative stratification of mortality risk for future observational assessments and potential randomized clinical trials of valve surgery for adults with left-sided native valve endocarditis. Future studies of prospective cohorts are needed to stratify risk for important morbidity outcomes.


AUTHOR INFORMATION 
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Corresponding Author and Reprints: Vincent J. Quagliarello, MD, PO Box 208022, 800 LCI, Yale University School of Medicine, New Haven, CT 06520 (e-mail: vincent.quagliarello{at}yale.edu).

Author Contributions: Study concept and design: Hasbun, Quagliarello.

Acquisition of data: Hasbun, Vikram, Barakat.

Analysis and interpretation of data: Hasbun, Vikram, Buenconsejo, Quagliarello.

Drafting of the manuscript: Hasbun, Vikram, Buenconsejo, Quagliarello.

Critical revision of the manuscript for important intellectual content: Hasbun, Vikram, Barakat, Buenconsejo, Quagliarello.

Statistical expertise: Buenconsejo, Quagliarello.

Obtained funding: Quagliarello.

Administrative, technical, or material support: Hasbun, Vikram, Barakat, Quagliarello.

Study supervision: Quagliarello.

Funding/Support: This study was supported by grants from The Donaghue Medical Research Foundation (DF97-030) and the American Heart Association (0050005N).

Author Affiliations: Infectious Disease Section, Tulane University School of Medicine, New Orleans, La (Dr Hasbun); Infectious Disease Section, Hospital of St Raphael, New Haven, Conn (Dr Vikram); Infectious Diseases, Griffin Hospital, Derby, Conn (Dr Barakat); Yale University School of Epidemiology and Public Health, New Haven, Conn (Ms Buenconsejo); and Department of Internal Medicine, Yale University School of Medicine, New Haven, Conn (Dr Quagliarello).


REFERENCES
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Prognostic Value of Serial C-Reactive Protein Measurements in Left-Sided Native Valve Endocarditis
Verhagen et al.
Arch Intern Med 2008;168:302-307.
ABSTRACT | FULL TEXT  

Surgical treatment of right-sided active infective endocarditis with or without involvement of the left heart: 20-year single center experience
Musci et al.
Eur. J. Cardiothorac. Surg. 2007;32:118-125.
ABSTRACT | FULL TEXT  

Impact of cerebrovascular complications on mortality and neurologic outcome during infective endocarditis: a prospective multicentre study
Thuny et al.
Eur Heart J 2007;28:1155-1161.
ABSTRACT | FULL TEXT  

The Impact of Valve Surgery on 6-Month Mortality in Left-Sided Infective Endocarditis
Tleyjeh et al.
Circulation 2007;115:1721-1728.
ABSTRACT | FULL TEXT  

Predictors of Death and Impact of Surgery in Staphylococcus aureus Infective Endocarditis
Remadi et al.
Ann. Thorac. Surg. 2007;83:1295-1302.
ABSTRACT | FULL TEXT  

Contemporary Clinical Profile and Outcome of Prosthetic Valve Endocarditis
Wang et al.
JAMA 2007;297:1354-1361.
ABSTRACT | FULL TEXT  

Diabetes mellitus and insulin therapy in infective endocarditis
Wang
Eur Heart J 2007;28:3-4.
FULL TEXT  

Clinical and prognostic profile of patients with infective endocarditis who need urgent surgery
Revilla et al.
Eur Heart J 2007;28:65-71.
ABSTRACT | FULL TEXT  

Diabetes mellitus and infective endocarditis: the insulin factor in patient morbidity and mortality
Duval et al.
Eur Heart J 2007;28:59-64.
ABSTRACT | FULL TEXT  

ACC/AHA 2006 Guidelines for the Management of Patients With Valvular Heart Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Writing Committee to Revise the 1998 Guidelines for the Management of Patients With Valvular Heart Disease) Developed in Collaboration With the Society of Cardiovascular Anesthesiologists Endorsed by the Society for Cardiovascular Angiography and Interventions and the Society of Thoracic Surgeons
Bonow et al.
J Am Coll Cardiol 2006;48:e1-e148.
FULL TEXT  

Surgical Management of Infective Endocarditis: Early Predictors of Short-Term Morbidity and Mortality
Jassal et al.
Ann. Thorac. Surg. 2006;82:524-529.
ABSTRACT | FULL TEXT  

Information technology for optimizing the management of infectious diseases
Drew et al.
Am J Health Syst Pharm 2006;63:957-965.
FULL TEXT  

Translating Clinical Research into Clinical Practice: Impact of Using Prediction Rules To Make Decisions
Reilly and Evans
ANN INTERN MED 2006;144:201-209.
ABSTRACT | FULL TEXT  

Management of infective endocarditis
Habib
Heart 2006;92:124-130.
FULL TEXT  

Risk of Embolism and Death in Infective Endocarditis: Prognostic Value of Echocardiography: A Prospective Multicenter Study
Thuny et al.
Circulation 2005;112:69-75.
ABSTRACT | FULL TEXT  

Infective Endocarditis: Global, Regional, and Future Perspectives
Quagliarello
JAMA 2005;293:3061-3062.
FULL TEXT  

Infective Endocarditis: Diagnosis, Antimicrobial Therapy, and Management of Complications: A Statement for Healthcare Professionals From the Committee on Rheumatic Fever, Endocarditis, and Kawasaki Disease, Council on Cardiovascular Disease in the Young, and the Councils on Clinical Cardiology, Stroke, and Cardiovascular Surgery and Anesthesia, American Heart Association: Endorsed by the Infectious Diseases Society of America
Baddour et al.
Circulation 2005;111:e394-e434.
ABSTRACT | FULL TEXT  

The year in cardiovascular surgery
Jones
J Am Coll Cardiol 2004;43:1706-1714.
FULL TEXT  

Early Predictors of In-Hospital Death in Infective Endocarditis
Chu et al.
Circulation 2004;109:1745-1749.
ABSTRACT | FULL TEXT  

Procalcitonin and the Early Diagnosis of Infective Endocarditis
Mueller et al.
Circulation 2004;109:1707-1710.
ABSTRACT | FULL TEXT  

Impact of Valve Surgery on 6-Month Mortality in Adults With Complicated, Left-Sided Native Valve Endocarditis: A Propensity Analysis
Vikram et al.
JAMA 2003;290:3207-3214.
ABSTRACT | FULL TEXT  

Evaluating and Optimizing Outcomes of Surgery for Endocarditis
Durack
JAMA 2003;290:3250-3251.
FULL TEXT  

Risk-Stratifying Patients with Infective Endocarditis
Journal Watch Cardiology 2003;2003:3-3.
FULL TEXT  

Estimating Endocarditis Outcomes
JWatch Infect. Diseases 2003;2003:2-2.
FULL TEXT  

Risk Stratification and Bedside Prognostication in Infective Endocarditis
Granowitz and Longworth
JAMA 2003;289:1991-1993.
FULL TEXT  





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