BackgroundDuchenne muscular dystrophy (DMD) is frequently complicated by development of a cardiomyopathy. Despite significant medical advances provided to DMD patients over the past 2 decades, there remains a group of DMD patients who die prematurely. The current study sought to identify a set of prognostic factors that portend a worse outcome among adult DMD patients.Methods and ResultsA retrospective cohort of 43 consecutive patients was followed in the adult UT Southwestern Neuromuscular Cardiomyopathy Clinic. Clinical data were abstracted from the electronic medical record to generate baseline characteristics. The population was stratified by survival to time of analysis and compared with characteristics associated with death. The DMD population was in the early 20s, with median follow‐up times over 2 years. All the patients had developed a cardiomyopathy, with the majority of the patients on angiotensin‐converting enzyme inhibitors (86%) and steroids (56%), but few other guideline‐directed heart failure medications. Comparison between the nonsurviving and surviving cohorts found several poor prognostic factors, including lower body mass index (17.3 [14.8–19.3] versus 25.8 [20.8–29.1] kg/m2, P<0.01), alanine aminotransferase levels (26 [18–42] versus 53 [37–81] units/L, P=0.001), maximum inspiratory pressures (13 [0–30] versus 33 [25–40] cmH2O, P=0.03), and elevated cardiac biomarkers (N‐terminal pro‐brain natriuretic peptide: 288 [72–1632] versus 35 [21–135] pg/mL, P=0.03].ConclusionsThe findings demonstrate a DMD population with a high burden of cardiomyopathy. The nonsurviving cohort was comparatively underweight, and had worse respiratory profiles and elevated cardiac biomarkers. Collectively, these factors highlight a high‐risk cardiovascular population with a worse prognosis.

Purpose of Review Recognition of subclinical myocardial dysfunction offers clinicians and patients an opportunity for early intervention and prevention of symptomatic cardiovascular disease. We review the data on novel biomarkers in subclinical heart disease in the general population with a focus on pathophysiology, recent observational or trial data, and potential applicability and pitfalls for clinical use. Recent Findings High-sensitivity cardiac troponin and natriuretic peptide assays are powerful markers of subclinical cardiac disease. Elevated levels of these biomarkers signify subclinical cardiac injury and hemodynamic stress and portend an adverse prognosis. Novel biomarkers of myocardial inflammation, fibrosis, and abnormal contraction are gaining momentum as predictors for incident heart failure, providing new insight into pathophysiologic mechanisms of cardiac disease. Summary There has been exciting growth in both traditional and novel biomarkers of subclinical cardiac injury in recent years. Many biomarkers have demonstrated associations with relevant cardiovascular outcomes and may enhance the diagnostic and prognostic power of more conventional biomarkers. However, their use in “prime time” to identify patients with or at risk for subclinical cardiac dysfunction in the general population remains an open question. Strategic investigation into their clinical applicability in the context of clinical trials remains an area of ongoing investigation.

Background: Although hospitalization for acute decompensated heart failure (HF) is common and associated with poor outcomes and high costs, few evidence-based recommendations are available to guide patient management. Thus, management of inpatient HF remains heterogeneous. We evaluated if physician-specific self-reported HF practice patterns were associated with 2 important contributors to resource utilization: length of stay (LOS) and 30-day readmission. Methods and Results: A 5-point Likert scale survey was created to assess physician-specific HF discharge strategies and administered to all cardiologists and hospitalists at a single large academic teaching hospital. Practice patterns potentially impacting LOS and discharge decisions were queried, including use of physical examination findings, approaches to diuretic use and influence of kidney function. Likert scale responses are reported as means with any value above 3.00 considered more influential and any value below 3.00 considered less influential. Physician-specific LOS and 30-day readmission rates from July 1, 2015, to June 30, 2016, were extracted from the electronic record. We received survey responses and HF utilization metrics from 58 of 69 surveyed physicians (32 hospitalists and 26 cardiologists), encompassing 753 HF discharges over a 1-year period. Median LOS was 4.5 days (interquartile range, 4.0–5.8) and total 30-day readmission rate was 17.0% (128 unique readmissions). Physicians with below-median LOS placed less importance on observing a patient on oral diuretics for 24 hours before discharge (Likert 2.54 versus 3.30, P =0.01), reaching documented dry weight (Likert 2.93 versus 3.60, P =0.02), and complete resolution of dyspnea on exertion (Likert 3.64 versus 4.10, P =0.03) when compared with those above-median LOS. In contrast, no surveyed discharge practices were associated with physician-specific 30-day readmission. Conclusions: We identified specific inpatient HF discharge practice patterns that associated with shorter LOS but not with readmission rates. These may be targets for future interventions aimed at cost reduction; additional larger studies are needed for further exploration.

Management of heart failure is a major health care challenge. Healthcare providers are expected to use best practices described in clinical practice guidelines, which typically consist of a long series of complex rules. For heart failure management, the relevant guidelines are nearly 80 pages long. Due to their complexity, the guidelines are often difficult to fully comply with, which can result in suboptimal medical practices. In this paper, we describe a heart failure treatment adviser system that automates the entire set of rules in the guidelines for heart failure management. The system is based on answer set programming, a form of declarative programming suited for simulating human-style reasoning. Given a patient’s information, the system is able to generate a set of guideline-compliant recommendations. We conducted a pilot study of the system on 21 real and 10 simulated patients with heart failure. The results show that the system can give treatment recommendations compliant with the guidelines. Out of 187 total recommendations made by the system, 176 were agreed upon by the expert cardiologists. Also, the system missed eight valid recommendations. The reason for the missed and discordant recommendations seems to be insufficient information, differing style, experience, and knowledge of experts in decision-making that were not captured in the system at this time. The system can serve as a point-of-care tool for clinics. Also, it can be used as an educational tool for training physicians and an assessment tool to measure the quality metrics of heart failure care of an institution.

Management of chronic diseases such as heart failure (HF) is a major public health problem. A standard approach to managing chronic diseases by medical community is to have a committee of experts develop guidelines that all physicians should follow. Due to their complexity, these guidelines are difficult to implement and are adopted slowly by the medical community at large. We have developed a physician advisory system that codes the entire set of clinical practice guidelines for managing HF using answer set programming (ASP). In this paper we show how abductive reasoning can be deployed to find missing symptoms and conditions that the patient must exhibit in order for a treatment prescribed by a physician to work effectively. Thus, if a physician does not make an appropriate recommendation or makes a non-adherent recommendation, our system will advise the physician about symptoms and conditions that must be in effect for that recommendation to apply. It is under consideration for acceptance in TPLP.