Short- and long-term mortality in patients with left-sided infective endocarditis not undergoing surgery despite indication

Characterization of patients receiving surgical versus non-surgical treatment for infective endocarditis in West Virginia

BACKGROUND

Infective endocarditis (IE) has increased in rural states such as West Virginia (WV) with high injection drug use. IE is medically managed with antimicrobial treatment alone or combined with surgical treatment. This study aimed to characterize the predictors associated with surgical treatment and rates of inpatient mortality and readmission among IE patients in WV's rural centers.

METHODS

This retrospective review of electronic health records includes all adults hospitalized for IE at major rural tertiary cardiovascular centers in WV during 2014-2018. Descriptive statistics were presented on demographics, history of injection drug use, clinical characteristics, and hospital utilization by surgery status, and multivariable logistic regression examined the association of surgery with key predictor variables, generating odds ratios (OR).

RESULTS

Of the 780 patients with IE, 38% had surgery, with a 26-fold increase in patients undergoing surgery between 2014-2018. Comparing surgery and non-surgery patients revealed significant differences. Surgery patients were significantly younger (median age 35.6 vs. 40.5 years; p<0.001); had higher rates of drug use history (80% vs. 65%; p<0.001), psychiatric disorders (57% vs. 31%; p<0.001), and readmissions (18% vs.12%; p = 0.015). Surgery patients had lower rates of discharge against medical advice (11% vs.17%; p = 0.028) and in-hospital mortality (5% vs.12%; p<0.001). In the multivariable logistic regression, surgery was associated with injection drug use (OR: 1.9; 95% CI:1.09-3. 3), indications for surgery (OR: 1.68; 95% CI:1.48-1.91), left-sided IE (OR: 2.14; 95%CI:1.43-3.19) and later years (OR:3.75; 95%CI:2.5-5.72).

CONCLUSION

This study characterizes the predictors associated with surgical treatment and rates of inpatient mortality and readmission among IE patients across rural WV. The decision to perform cardiac surgery on IE patients is complex. Results with increased injection drug use-associated IE emphasize the importance of comprehensive care by a multidisciplinary team for optimal management of patients with IE.

Machine Learning-Based Risk Model for Predicting Early Mortality After Surgery for Infective Endocarditis

Background

The early mortality after surgery for infective endocarditis is high. Although risk models help identify patients at high risk, most current scoring systems are inaccurate or inconvenient. The objective of this study was to construct an accurate and easy‐to‐use prediction model to identify patients at high risk of early mortality after surgery for infective endocarditis.

Methods and Results

A total of 476 consecutive patients with infective endocarditis who underwent surgery at 2 centers were included. The development cohort consisted of 276 patients. Eight variables were selected from 89 potential predictors as input of the XGBoost model to train the prediction model, including platelet count, serum albumin, current heart failure, urine occult blood ≥(++), diastolic dysfunction, multiple valve involvement, tricuspid valve involvement, and vegetation >10 mm. The completed prediction model was tested in 2 separate cohorts for internal and external validation. The internal test cohort consisted of 125 patients independent of the development cohort, and the external test cohort consisted of 75 patients from another center. In the internal test cohort, the area under the curve was 0.813 (95% CI, 0.670–0.933) and in the external test cohort the area under the curve was 0.812 (95% CI, 0.606–0.956). The area under the curve was significantly higher than that of other ensemble learning models, logistic regression model, and European System for Cardiac Operative Risk Evaluation II (all, P<0.01). This model was used to develop an online, open‐access calculator (http://42.240.140.58:1808/).

Conclusions

We constructed and validated an accurate and robust machine learning–based risk model to predict early mortality after surgery for infective endocarditis, which may help clinical decision‐making and improve outcomes.

Prognostic value of D-dimer for adverse outcomes in patients with infective endocarditis: an observational study

BACKGROUND

Increased D-dimer levels have been shown to correlate with adverse outcomes in various clinical conditions. However, few studies with a large sample size have been performed thus far to evaluate the prognostic value of D-dimer in patients with infective endocarditis (IE).

METHODS

613 patients with IE were included in the study and categorized into two groups according to the cut-off of D-dimer determined by receiver operating characteristic (ROC) curve analysis for in-hospital death: > 3.5 mg/L (n = 89) and ≤ 3.5 mg/L (n = 524). Multivariable regression analysis was used to determine the association of D-dimer with in-hospital adverse events and six-month death.

RESULTS

In-hospital death (22.5% vs. 7.3%), embolism (33.7% vs 18.2%), and stroke (29.2% vs 15.8%) were significantly higher in patients with D-dimer > 3.5 mg/L than in those with D-dimer ≤ 3.5 mg/L. Multivariable analysis showed that D-dimer was an independent risk factor for in-hospital adverse events (odds ratio = 1.11, 95% CI 1.03-1.19, P = 0.005). In addition, the Kaplan-Meier curve showed that the cumulative 6-month mortality was significantly higher in patients with D-dimer > 3.5 mg/L than in those with D-dimer ≤ 3.5 mg/L (log-rank test = 39.19, P < 0.0001). Multivariable Cox regression analysis showed that D-dimer remained a significant predictor for six-month death (HR 1.11, 95% CI 1.05-1.18, P < 0.001).

CONCLUSIONS

D-dimer is a reliable prognostic biomarker that independently associated with in-hospital adverse events and six-month mortality in patients with IE.

Long-term antibiotic therapy in patients with surgery-indicated not undergoing surgery infective endocarditis

BACKGROUND

To date, there is little information regarding management of patients with infective endocarditis (IE) that did not undergo an indicated surgery. Therefore, we aimed to evaluate prognosis of these patients treated with a long-term antibiotic treatment strategy, including oral long term suppressive antibiotic treatment in five referral centres with a multidisciplinary endocarditis team.

METHODS

This retrospective, multicenter study retrieved individual patient-level data from five referral centres in Spain. Among a total of 1797, 32 consecutive patients with IE were examined (median age 72 years; 78% males) who had not undergone an indicated surgery, but received long-term antibiotic treatment (LTAT) and were followed by a multidisciplinary endocarditis team, between 2011 and 2019. Primary outcomes were infection relapse and mortality during follow-up.

RESULTS

Among 32 patients, 21 had IE associated with prostheses. Of the latter, 8 had an ascending aorta prosthetic graft. In 24 patients, a switch to long-term oral suppressive antibiotic treatment (LOSAT) was considered. The median duration of LOSAT was 277 days. Four patients experienced a relapse during follow-up. One patient died within 60 days, and 12 patients died between 60 days and 3 years. However, only 4 deaths were related to IE.

CONCLUSIONS

The present study results suggest that a LTAT strategy, including LOSAT, might be considered for patients with IE that cannot undergo an indicated surgery. After hospitalization, they should be followed by a multidisciplinary endocarditis team.