Using graph visualization to look at the trajectories of events that lead to readmission

Information on specific sequence of healthcare utilization events in heart failure patients may be useful for identifying distinct subpopulations of patients with HF. Knowledge of patient trajectories may help to improve prediction of future readmission which can be used to tailor management to the individual needs of the patient. This research introduces a new approach to mining administrative and clinical datasets by incorporating graph networks to identify & visualize the trajectories of sequences of events

Using Graphs to Characterize Nationwide Physician Referral Networks

AIM: Evaluating physician referral network characteristics can help to understand how physicians and hospitals interact to provide patient services within the US healthcare system and ultimately how this may influence patient outcomes. METHOD: We used the 2012-2013 national Physician Referral data from the Centers for Medicare & Medicaid Services (CMS), which consists of 73,071,804 pairs of referrals from one health provider to another in calendar year 2012 and the first two quarters of year 2013 within 30 days of care. These referrals are from 642,144 national-wide physicians and 4,811 hospitals. We obtained information for each provider, physician or hospital, from CMS. We then generated a nationwide referral network. We described the network with graphs and potential important network characteristics using graph theory and social network theory. Further, we described the sub-network by Exponential random graph models (ERGM). The ERGM coefficients from such models can reflect the properties of the network nodes and help illustrate how the network outcomes are influenced. RESULTS: Our results show that 1) the graphs and characteristics vary substantially across the geographic areas and 2) graphs and the characteristics depicting the same area are strongly associated. The ERGM model shows that physicians in cardiology, diagnostic radiology and geriatric medicine are more likely to send and receive referrals than physicians in family care and internal medicine in certain hospitals. CONCLUSION: We demonstrate the use of graph-based approaches to describe and evaluate nationwide physician referral networks. Further work will study how these network characteristics are associated with hospital outcomes

Long-term survival and life expectancy following an acute heart failure hospitalization in Australia and New Zealand

Aims: Contemporary long-term survival following a heart failure (HF) hospitalization is uncertain. We evaluated survival up to 10 years after a HF hospitalization using national data from Australia and New Zealand, identified predictors of survival, and estimated the attributable loss in life expectancy. Methods and results: Patients hospitalized with a primary diagnosis of HF from 2008–2017 were identified and all-cause mortality assessed by linking with Death Registries. Flexible parametric survival models were used to estimate survival, predictors of survival and loss in life expectancy. A total of 283 048 patients with HF were included (mean age 78.2 ± 12.3 years, 50.8% male). Of these, 48.3% (48.1–48.5) were surviving by 3 years, 34.1% (33.9–34.3) by 5 years and 17.1% (16.8–17.4) by 10 years (median survival 2.8 years). Survival declined with age with 53.4% of patients aged 18–54 years and 6.2% aged ≥85 years alive by 10 years (adjusted hazard ratio [aHR] for mortality 4.84, 95% confidence interval [CI] 4.65–5.04 for ≥85 years vs. 18–54 years) and was worse in male patients (aHR 1.14, 95% CI 1.13–1.15). Prior HF (aHR 1.20, 95% CI 1.18–1.22), valvular and rheumatic heart disease (aHR 1.11, 95% CI 1.10–1.13) and vascular disease (aHR 1.07, 95% CI 1.04–1.09) were cardiovascular comorbidities most strongly associated with long-term death. Non-cardiovascular comorbidities and geriatric syndromes were common and associated with higher mortality. Compared with the general population, HF was associated with a loss of 7.3 years in life expectancy (or 56.6% of the expected life expectancy) and reached 20.5 years for those aged 18–54 years. Conclusion: Less than one in five patients hospitalized for HF were surviving by 10 years with patients experiencing almost 60% loss in life expectancy compared with the general population, highlighting the considerable persisting societal burden of HF. Concerted multidisciplinary efforts are needed to improve post-hospitalization outcomes of HF

Successful negative inotropic treatment of acute left ventricular outflow tract obstruction by elongated mitral valve leaflet

Elongated anterior mitral valve leaflet (EAMVL) has not been reported to cause left ventricular outflow tract obstruction (LVOTO) in the absence of left ventricular hypertrophy. We report the case of an elderly male patient who presented with acute heart failure and severe mitral regurgitation in the setting of dehydration. Echocardiography revealed acute LVOTO secondary to EAMVL. The patient was ineligible for surgery and was treated with negative inotropic agents, which ensured resolution of heart failure and marked improvement in the degree of LVOTO. This case demonstrates that, under certain circumstances, EAMVL without associated left ventricular hypertrophy may produce hemodynamic compromise that can be successfully treated medically

Coexisting vasospastic angina and undiagnosed Brugada Syndrome resulting in cardiac arrest

The coexistence of Brugada Syndrome and resting vasospastic angina resulting in cardiac arrest is rare. We describe a 64 year-old man presenting with cardiac arrest and vasospastic angina with diagnostic criteria of symptomatic Brugada Syndrome. Recognition of the coexistence of these potentially fatal conditions has important therapeutic implications when using calcium channel antagonists and may shed light on the mechanisms of coronary spasm. A common pathogenesis, such as a common underlying channelopathy, may explain its coexistence with Brugada Syndrome