Purpose of Review Sepsis, defined by the presence of infection and host inflammation, is a lethal clinical syndrome with an increasing mortality rate worldwide. In severe disease, the coagulation system becomes diffusely activated, with consumption of multiple clotting factors resulting in Disseminated Intravascular Coagulation (DIC). When present, DIC portends a higher mortality rate. Understanding the mechanisms that tie inflammation and diffuse thrombosis will allow therapeutic interventions to be developed. The Coagulopathy of Acute Sepsis is a dynamic process that is time and disease burden specific. Whole blood testing of coagulation may provide more clinically useful information than classical tests. Natural anticoagulants that regulate thrombosis are down regulated in sepsis. Patients may benefit from modulation of the coagulation system when systemic inflammation and hypercoagulopathy exist. Proper timing of anticoagulant therapy may ultimately lead to decreased incidence of multisystem organ dysfunction (MODS). Recent Findings The pathogenesis of coagulopathy in sepsis is driven by an up-regulation of procoagulant mechanisms and simultaneous down-regulation of natural anticoagulants. Inflammation caused by the invading organism is a natural host defense than cannot be eliminated during treatment. Successful strategies to prevent MODS center on stratifying patients at high risk for DIC and restoring the balance of inflammation and coagulation. Summary The prevention of DIC in septic patients is a key therapeutic target in preventing death from multisystem organ failure. Stratifying patients for therapy using thromboelastometry, specific markers for DIC, and composite scoring systems is an area of growing research.

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Background Patients hospitalized with heart failure (HF) with reduced ejection fraction have high risk of rehospitalization or death. Despite guideline recommendations based on high‐quality evidence, a substantial proportion of patients with HF with reduced ejection fraction receive suboptimal care and/or do not comply with optimal care following hospitalization. Methods and Results This retrospective observational study identified 17 106 patients with HF with reduced ejection fraction with an incident HF‐related hospitalization using the Humana Medicare Advantage database (2008–2016). HF medication classes (beta‐blockers, angiotensin‐converting enzyme inhibitors, angiotensin receptor blockers, angiotensin receptor neprilysin inhibitors, or mineralocorticoid receptor antagonists) received in the year after hospitalization were recorded, and categorized by treatment intensity (ie, number of concomitant medication classes received: none [23% of patients; n=3987], monotherapy [22%; n=3777], dual therapy [41%; n=7056], or triple therapy [13%; n=2286]). Compared with no medication, risk of primary outcome (composite of death or rehospitalization) was significantly reduced (hazard ratio [95% CI]) with monotherapy (0.68 [0.64–0.71]), dual therapy (0.56 [0.53–0.59]), and triple therapy (0.45 [0.41–0.50]). Nearly half (46%) of patients who received post‐discharge medication had no dose escalation. Overall, 59% of patients had follow‐up with a primary care physician within 14 days of discharge, and 23% had follow‐up with a cardiologist. Conclusions In real‐world clinical practice, increasing treatment intensity reduced risk of death and rehospitalization among patients hospitalized for HF, though the use of guideline‐recommended dual and triple HF therapy remained low. There are opportunities to improve post‐discharge medical management for patients with HF with reduced ejection fraction such as optimizing dose titration and improving post‐discharge follow‐up with providers.

Aims Approximately 50% of patients with heart failure have preserved (≥50%) ejection fraction (HFpEF). Improved understanding of the phenotypic heterogeneity of HFpEF might facilitate development of targeted therapies and interventions. Methods This retrospective study characterized a cohort of patients with HFpEF based on similar clinical profiles and evaluated 1-year heart failure related hospitalization. Enrolment, medical and pharmacy data were used to identify patients newly diagnosed with heart failure enrolled in a Medicare Advantage Prescription Drug or commercial healthcare plan. To identify only those patients with HFpEF, we used natural language processing techniques of ejection fraction values abstracted from a linked free-text clinical notes data source. The study population comprised 1515 patients newly identified with HFpEF between 1 January 2011 and 31 December 2015. Results Using unsupervised machine learning, we identified three distinguishable patient clusters representing different phenotypes: cluster-1 patients had the lowest prevalence of heart failure comorbidities and highest mean age; cluster-2 patients had higher prevalence of metabolic syndrome and pulmonary disease, despite younger mean age; and cluster-3 patients had higher prevalence of cardiac arrhythmia and renal disease. Cluster-3 had the highest 1-year heart failure related hospitalization rates. Within-cluster analysis, prior use of diuretics (cluster-1 and cluster-2) and age (cluster-2 and cluster-3) was associated with 1-year heart failure related hospitalization. Combination therapy was associated with decreased 1-year heart failure related hospitalization in cluster-1. Conclusion This study demonstrated that clustering can be used to characterize subgroups of patients with newly identified HFpEF, assess differences in heart failure related hospitalization rates at 1 year and suggest patient subtypes may respond differently to treatments or interventions.