How Good Are Cardiologists at Predicting Major Adverse Events in Fontan Patients?

Background: It is unknown how well cardiologists predict which Fontan patients are at risk for major adverse events (MAEs). Objectives: The purpose of this study was to examine the accuracy of cardiologists' ability to identify the "good Fontan" patient, free from MAE within the following year, and compare that predicted risk cohort to patients who experienced MAE. Methods: This prospective, multicenter study included patients ≥10 years with lateral tunnel or extracardiac Fontan. The cardiologist was asked the yes/no "surprise" question: would you be surprised if your patient has a MAE in the next year? After 12 months, the cardiologist was surveyed to assess MAE. Agreement between cardiologist predictions of MAE and observed MAE was determined using the simple kappa coefficient. Multivariable generalized linear mixed effects models were performed to identify factors associated with MAE. Results: Overall, 146 patients were enrolled, and 99/146 (68%) patients w`ere predicted to be a "good Fontan." After 12 months, 17 (12%) experienced a MAE. The simple kappa coefficient of cardiologists' prediction was 0.17 (95% CI: 0.02-0.32), suggesting prediction of MAE was 17% better than random chance. In the multivariable cardiologist-predicted MAE (N = 47) model, diuretic/beta-blocker use (P ≤ 0.001) and systolic dysfunction (P = 0.005) were associated with MAE. In the observed multivariable MAE (N = 17) model, prior unplanned cardiac admission (P = 0.006), diuretic/beta-blocker use (P = 0.028), and ≥moderate atrioventricular valve regurgitation (P = 0.049) were associated with MAE. Conclusions: Cardiologists are marginally able to predict which Fontan patients are at risk for MAE over a year. There was overlap between factors associated with a cardiologist's prediction of risk and observed MAE, namely the use of diuretic/beta-blocker.

Improvement Science Increases Routine Lipid Screening in General Pediatric Cardiology.

OBJECTIVE: To evaluate the effectiveness of patient education, physician counseling, and point-of-care (POC) testing on improving adherence to lipid screening national guidelines in a general pediatric cardiology practice (2017-2023). STUDY DESIGN: Regional primary care providers were surveyed regarding lipid screening practices. Key drivers were categorized (physician, patient, and system) with corresponding interventions. Pediatric cardiologists started offering lipid screening during regular visits by providing families with preventive cardiovascular education materials and lab phlebotomy testing. System redesign included educational posters, clinical intake protocol, physician counseling, electronic health record integration, and POC testing. Run charts and statistical process control charts measured screening rates and key processes. RESULTS: The primary care survey response rate was 32% (95/294); 97% supported pediatric cardiologists conducting routine lipid screening. Pediatric cardiology mean baseline lipid screening rate was 0%, increased to 7% with patient education, and to 61% after system redesign including POC testing. Screening rates among 1467 patients were similar across age groups (P = .98). More patients received lipid screening by POC (91.7%) compared with phlebotomy (8.3%). Lipid abnormalities detected did not differ by screening methodology (P = .49). CONCLUSION: Patient education, counseling, and POC testing improved adherence to national lipid screening guidelines, providing a possible model for primary care implementation.

Dyslipidemia Among Adults With Congenital Heart Disease.

Background: Atherosclerotic disease is an important cause of morbidity among adults with congenital heart disease (CHD). Prevalence of dyslipidemia in this group is poorly described. Objectives: This study aimed to describe the prevalence of dyslipidemia among adults with CHD. Methods: A prospective, outpatient screening study was conducted among adults aged ≥18 years at 4 New England ambulatory congenital cardiology centers. Participants were surveyed regarding cardiovascular risk factors. Nonfasting fingerstick samples were obtained for analysis using a point-of-care lipid analyzer. Results: Lipid screening was completed on 186 participants (median age 30 [range 18-71] years, 50% female). Eighteen (10%) had simple CHD anatomy, and 63 (34%) had complex anatomy. Only 15% of 169 respondents reported history of high cholesterol. Eighty-five (46%) participants met National Cholesterol Education Program definition of dyslipidemia with 60 (32%), 62 (34%), and 37 (20%) having low high-density lipoprotein cholesterol (HDL-C <40 mg/dL), high non-HDL-C (≥130 mg/dL), and high total cholesterol (TC ≥200 mg/dL), respectively. TC was higher among participants with simple CHD than among those with moderate and complex lesions (mean 178.4 ± 48.7 vs 170.1 ± 35.0 vs 157.6 ± 34.5 mg/dL; P = 0.03). HDL-C was lower among participants with complex CHD than among those with simple and moderate lesions (mean 44.1 ± 13.5 vs 46.9 ± 12.5 vs 49.8 ± 15.3 mg/dL; P = 0.05). Conclusions: Dyslipidemia is highly prevalent among our cohort of adults with CHD, despite <15% reporting a prior diagnosis. Low HDL-C was more common in complex CHD, and high TC was more common in simple or moderate CHD. Lipid screening should be part of preventive health maintenance for all adults with CHD.