Importance of In-Hospital Prospective Registry and Infectious Endocarditis Heart Team to Monitor and Improve Quality of Care in Patients with Infectious Endocarditis.

AIM: To investigate the value of prospective in-hospital registry data and the impact of an infectious endocarditis heart team approach (IEHT) on improvement in quality of care and monitor outcomes in hospitalized patients with IE. METHODS: Between December 2014 and the end of 2019, 160 patients were hospitalized in one centre with the definite diagnosis of infectious endocarditis (IE) and entered in a prospective registry. From 2017, an IEHT was introduced. Propensity score matching was used to assess the impact of an IEHT approach on clinical outcomes. RESULTS: Median age was 72.5 y (62.75-80.00), diabetes was present in 33.1%, chronic kidney disease in 27.5%, COPD in 17.5%, and a history of ischaemic heart disease in 30.6%. Prosthetic valve IE was observed in 43.8% and device-related IE in 16.9% of patients. Staphylococcus (37.5%) was the most frequent pathogen followed by streptococcus (24.4%) and enterococcus (23.1%). Overall, 30-day and 1-year mortality were 19.4% and 37.5%, respectively. The introduction of prospective data collection and IE heart team was associated with a trend towards reduction of adjusted 1-year mortality (26.5% IEHT vs. 41.2% controls, p = 0.0699). An IEHT clinical decision-making approach was independently associated with a shorter length of stay (p = 0.04). CONCLUSIONS: Use of a prospective registry of IE coupled with a heart team approach was associated with more efficient patient management and a trend towards lower mortality. Prospective data collection and dedicated IEHT have the potential to improve patient care and clinical outcomes.

Laboratory information system requirements to manage the COVID-19 pandemic: A report from the Belgian national reference testing center.

OBJECTIVE: The study sought to describe the development, implementation, and requirements of laboratory information system (LIS) functionality to manage test ordering, registration, sample flow, and result reporting during the coronavirus disease 2019 (COVID-19) pandemic. MATERIALS AND METHODS: Our large (>12 000 000 tests/y) academic hospital laboratory is the Belgian National Reference Center for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing. We have performed a moving total of >25 000 SARS-CoV-2 polymerase chain reaction tests in parallel to standard routine testing since the start of the outbreak. A LIS implementation team dedicated to develop tools to remove the bottlenecks, primarily situated in the pre- and postanalytical phases, was established early in the crisis. RESULTS: We outline the design, implementation, and requirements of LIS functionality related to managing increased test demand during the COVID-19 crisis, including tools for test ordering, standardized order sets integrated into a computerized provider order entry module, notifications on shipping requirements, automated triaging based on digital metadata forms, and the establishment of databases with contact details of other laboratories and primary care physicians to enable automated reporting. We also describe our approach to data mining and reporting of actionable daily summary statistics to governing bodies and other policymakers. CONCLUSIONS: Rapidly developed, agile extendable LIS functionality and its meaningful use alleviates the administrative burden on laboratory personnel and improves turnaround time of SARS-CoV-2 testing. It will be important to maintain an environment that is conducive for the rapid adoption of meaningful LIS tools after the COVID-19 crisis.

Regression of left ventricular mass by antihypertensive treatment: a meta-analysis of randomized comparative studies.

Blood pressure-lowering therapy reduces left ventricular mass, but the question of whether differences exist among drug classes has not been fully resolved. Our aim was to compare the effects of diuretics, beta-blockers, calcium channel blockers, angiotensin-converting enzyme inhibitors, and angiotensin receptor blockers on left ventricular mass regression in patients with hypertension on the basis of prospective, randomized comparative studies. We performed meta-analyses, involving pooled pairwise comparisons of the drug classes and of each class versus other classes statistically combined, and meta-regression analyses to identify the determinants of the regression. The 75 relevant publications involved 84 pairwise comparisons and 6001 patients. Regression of left ventricular mass was significantly less (P=0.01) with beta-blockers (9.8%) than with angiotensin receptor blockers (12.5%), but none of the other analyzable pairwise comparisons between drug classes revealed significant differences (P>0.10). In addition, beta-blockers showed less regression than the other 4 classes statistically combined (P<0.01), and regression was more pronounced with angiotensin receptor blockers versus the others (P<0.01). In multivariable meta-regression analysis on all of the treatment arms, beta-blocker treatment was a significant and negative predictor of the regression (-3.6%; P<0.01), but this was not the case for the other drug classes, including angiotensin receptor blockers. In conclusion, beta-blockers show less regression of left ventricular mass, whereas angiotensin receptor blockers may induce larger regression. The inferiority of beta-blockers appears to be more convincing than the superiority of angiotensin receptor blockers.

Preoperative prediction of early mortality and morbidity in coronary bypass surgery.

OBJECTIVE: A scoring system to predict early mortality and morbidity in CABG, distinguishing low and high risk patients. METHODS: 563 patients (1998) served as development dataset, 969 patients as validation set. Univariate and logistic regression analysis was used to identify risk factors. RESULTS: Gender, hypertension, pulmonary disease, reoperation, age, operative status and left-ventricular function were predictive variables for early mortality. The area under the ROC curve was 0.81. We identified a low risk, mortality of 1.8% and a high-risk group, mortality of 13.4%. Diabetes, hypertension, kidney and lung disease, reoperation, operative status and left ventricular function were predictive variables for morbidity. The area under the ROC curve was 0.73. We identified a low risk, morbidity of 17%, and a high-risk group, morbidity of 41%. CONCLUSION: This scoring system is a simple system identifying a low and high-risk group for morbidity and early mortality.