Faculty Bibliography

BACKGROUND: Interventions to reduce readmissions following acute heart failure hospitalization require early identification of patients. The purpose of this study was to develop and test accuracies of various approaches to identify patients with acute decompensated heart failure (ADHF) using data derived from the electronic health record. METHODS AND RESULTS: We included 37,229 hospitalizations of adult patients at a single hospital in 2013-2015. We developed four algorithms to identify hospitalization with a principal discharge diagnosis of ADHF: 1) presence of one of three clinical characteristics; 2) logistic regression of 31 structured data elements; 3) machine learning with unstructured data; 4) machine learning with both structured and unstructured data. In data validation, Algorithm 1 had a sensitivity of 0.98 and positive predictive value (PPV) of 0.14 for ADHF. Algorithm 2 had an area under the receiver operating characteristic curve (AUC) of 0.96, while both machine learning algorithms had AUCs of 0.99. Based on a brief survey of three providers who perform chart review for ADHF, we estimated providers spent 8.6 minutes per chart review; using this this parameter, we estimated providers would spend 61.4, 57.3, 28.7, and 25.3 minutes on secondary chart review for each case of ADHF if initial screening was done with algorithms 1, 2, 3, and 4, respectively. CONCLUSION: Machine learning algorithms with unstructured notes had best performance for identification of ADHF and can improve provider efficiency for delivery of quality improvement interventions.

BACKGROUND: The prevalence and significance of right ventricular dysfunction (RVD) in patients with cardiogenic shock due to acute myocardial infarction (AMI-CS) has not been well characterized. We hypothesized that RVD is common in AMI-CS and associated with worse clinical outcomes. METHODS AND RESULTS: We retrospectively analyzed patients with available hemodynamics enrolled in the SHould we emergently revascularize Occluded coronaries for Cardiogenic shocK (SHOCK) Trial (n=139) and Registry (n=258) to identify RVD in AMI-CS. RVD was defined by an elevated central venous pressure (CVP), elevated CVP/ pulmonary capillary wedge pressure (PCWP) ratio, decreased pulmonary artery pulsatility index (PAPi), and decreased right ventricular stroke work index (RVSWI). A p value of less than 0.01 was used to infer significance. In both the SHOCK trial and registry, 38% and 37% of patients had RVD, however RVD was not associated with 30-day or 6-month survival (HR 1.51 (0.92, 2.49) p=0.10). RV failure using inclusion criteria from the Recover Right Trial for RV failure (RR-RVF) requiring percutaneous mechanical circulatory support included an elevated CVP, CVP/PCWP ratio, and a low cardiac index despite >/=1 inotrope or vasopressor. In both the SHOCK trial and registry, 45% (n=63/139) and 38% (n=98/258) of patients met RR-RVF criteria respectively. The RR-RVF criteria were not significantly associated with 30-day mortality in the registry cohort (HR 1.44 (1.01,2.04), p=0.04), or in the trial cohort (HR 1.51(0.92,2.49), p=0.10). CONCLUSIONS: Hemodynamically defined RVD is common in AMI-CS. Routine assessment with PA catherization allows detection of RVD; however, further work is needed to identify interventions that will result in improved outcomes for these patients.

Heart failure is a common form of heart disease associated with progressive exercise intolerance and high risk of adverse clinical outcome events. The pathophysiology of chronic systolic heart failure is fundamentally determined by the failure of the circulatory system to deliver oxygen sufficient for metabolic needs, and it is best explained by a complex interplay between intrinsic abnormalities of ventricular pump function and extracardiac factors that limit oxygen use in metabolically active tissues. This brief review highlights the role of extracardiac factors (peripheral factors) that may impact exercise capacity in patients with chronic systolic heart failure. Reduced metabolic vasodilation limits delivery of available cardiac output reserve to skeletal muscle during exercise, and it is associated with reduced peak oxygen capacity. Abnormal substrate use in skeletal muscle due to reduced skeletal muscle mass, change in skeletal muscle fiber type, and mitochondrial dysfunction reduces work efficiency and submaximal exercise endurance capacity in patients with systolic heart failure. These extracardiac peripheral mechanisms of impaired exercise tolerance in chronic heart failure may be targets for novel therapeutic development in this patient population.

Patients with complex chronic diseases usually must make multiple lifestyle changes to limit and manage their conditions. Numerous studies have shown that education alone is insufficient for engaging people in lifestyle behavior change, and that theory-based behavioral approaches also are necessary. However, even the most motivated individual may have difficulty with making lifestyle changes because of the information complexity associated with multiple behavior changes. The goal of the current Healthy Hearts and Kidneys study was to evaluate, different mobile health (mHealth)-delivered intervention approaches for engaging individuals with type 2 diabetes (T2D) and concurrent chronic kidney disease (CKD) in behavior changes. Participants were randomized to 1 of 4 groups, receiving: (1) a behavioral counseling, (2) technology-based self-monitoring to reduce information complexity, (3) combined behavioral counseling and technology-based self-monitoring, or (4) baseline advice. We will determine the impact of randomization assignment on weight loss success and 24-hour urinary excretion of sodium and phosphorus. With this report we describe the study design, methods, and approaches used to assure information security for this ongoing clinical trial. Clinical Trials.gov Identifier: NCT02276742.

BACKGROUND:Thyroid dysfunction and myocardial fibrosis are both associated with cardiovascular events in patients with dilated cardiomyopathy (DCM). HYPOTHESIS/OBJECTIVE:The combination of thyroid hormone (TH) and myocardial fibrosis (detected by late gadolinium enhancement [LGE]) is an independent and incremental predictor of adverse events in DCM. METHODS:We consecutively enrolled 220 idiopathic DCM patients with thyroid function and LGE assessment at Fuwai Hospital (China) from January 2010 to October 2011 and followed up through December 2015. Patients were divided into 4 groups according to the presence or absence of LGE and FT3 value (median level of 2.79 pg/mL): LGE-positive + FT3 < 2.79 pg/mL, LGE-positive + FT3 ≥ 2.79 pg/mL, LGE-negative + FT3 < 2.79 pg/mL, and LGE-negative + FT3 ≥ 2.79 pg/mL. RESULTS:During a median follow-up of 61 months, 56 patients (25.5%) died, with 27/56 (48.2%), 8/45 (17.8%), 12/54 (22.2%), and 9/65 (13.8%) among 4 groups (P = 0.009), respectively. Multivariable Cox regression analysis identified LGE-positive and FT3 < 2.79 pg/mL as a significant independent predictor of all-cause mortality (hazard ratio: 2.893, 95% confidence interval: 1.323-6.326, P = 0.008). Combining the predictive value of FT3 and LGE status significantly improved risk reclassification for all-cause mortality, as indicated by the net reclassification improvement (0.28; P = 0.005) and integrated discrimination improvement (0.058; P = 0.001). CONCLUSIONS:The findings suggest that the combination of FT3 and LGE yielded a more accurate predictive value for long-term prognosis in patients with DCM, which may improve patient selection for intensive interventions.