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BACKGROUND: Atrial fibrillation (AF) is highly prevalent in CKD and is associated with worse cardiovascular and kidney outcomes. Limited data exist on use of AF pharmacotherapies and AF-related procedures by CKD status. We examined a large “real-world” contemporary population with incident AF to study the association of CKD with management of AF. METHODS: We identified patients with newly diagnosed AF between 2010 and 2017 from two large, integrated health care delivery systems. eGFR (≥60, 45–59, 30–44, 15–29, 60 ml/min per 1.73 m(2), patients with eGFR 30–44 (adjusted hazard ratio [aHR] 0.91; 95% CI, 0.99 to 0.93), 15–29 (aHR, 0.78; 95% CI, 0.75 to 0.82), and 60 ml/min per 1.73 m(2). These associations were even stronger for eGFR 60 ml/min per 1.73 m(2)): eGFR 30–44 ml/min per 1.73 (aHR, 0.78; 95% CI, 0.70 to 0.87), eGFR 15–29 ml/min per 1.73 m(2) (aHR, 0.73; 95% CI, 0.61 to 0.88), and eGFR

BACKGROUND:Few studies describe both inpatient and outpatient treatment and outcomes of patients with acute venous thromboembolism in the United States. METHODS:A multi-institutional cohort of patients diagnosed with confirmed pulmonary embolism or deep venous thrombosis during the years 2004 through 2010 was established from 4 large, US-based integrated health care delivery systems. Computerized databases were accessed and medical records reviewed to collect information on patient demographics, clinical risk factors, initial antithrombotic treatment, and vital status. Multivariable Cox regression models were used to estimate the risk of death at 90 days. RESULTS:The cohort comprised 5497 adults with acute venous thromboembolism. Pulmonary embolism was predominantly managed in the hospital setting (95.0%), while 54.5% of patients with lower extremity thrombosis were treated as outpatients. Anticoagulant treatment differed according to thromboembolism type: 2688 patients (92.8%) with pulmonary embolism and 1625 patients (86.9%) with lower extremity thrombosis were discharged on anticoagulants, compared with 286 patients (80.1%) with upper extremity thrombosis and 69 (54.8%) patients with other thrombosis. While 4.5% of patients died during the index episode, 15.4% died within 90 days. Pulmonary embolism was associated with a higher 90-day death risk than lower extremity thrombosis (adjusted hazard ratio 1.23; 95% confidence interval, 1.04-1.47), as was not being discharged on anticoagulants (adjusted hazard ratio 5.56; 95% confidence interval, 4.76-6.67). CONCLUSIONS:In this multicenter, community-based study of patients with acute venous thromboembolism, anticoagulant treatment and outcomes varied by thromboembolism type. Although case fatality during the acute episode was relatively low, 15.4% of people with thromboembolism died within 90 days of the index diagnosis.

Background Heart failure (HF) carries a high burden of comorbidity with approximately one half of patients with HF having at least one additional comorbid condition present. Rates of comorbidity in patients with HF have steadily increased over the past 2 decades. Objective To examine patterns of comorbidity among older patients with HF in the Cardiovascular Research Network PRESERVE cohort. Methods PRESERVE Cohort Data are from the CVRN PRESERVE cohort which is a multicenter cohort of 37,054 patients [mean age = 74 years (SD = 12.4 yrs); 46% female] with HF diagnosed between 2005 and 2008 currently being conducted at 4 CVRN sites: KPNC, KPCO, KPNW, and FCHP. The primary data source for the PRESERVE cohort was the HMO Research Network Virtual Data Warehouse. Identification of Coexisting Diseases Coexisiting illnesses at the time of HF diagnosis were based on diagnoses and procedures mapped to relevant International Classification of Diseases, Ninth Edition (ICD-9) codes. For the purposes of characterizing clusters of comorbidities, we focused on coexisting conditions with a prevalence rate of ≥3%. Statistical Analysis We used the Agglomerative Clustering technique to characterize patterns of comorbidity. Over multiple iterations, each condition is clustered with the condition with which it has the highest squared correlation. This process is repeated to determine whether assigning a condition to a different cluster increases the amount of explained variance [ranging from 1.0 (all variance explained) to 0.0 (no variance explained)]. The conditions in each cluster are as correlated as possible among themselves and as uncorrelated as possible with conditions in other clusters. Results Burden of Comorbidity There was a high degree of comorbidity and multi-morbidity among patients with HF. (Table 1) Hypertension and arrhythmias were the comorbidities of HF that occurred most often in the absence of other chronic conditions (4.8% and 4.7%, respectively). The average number of comorbid conditions varied from 3.5 to 5.2. Patients with HF and unstable angina or other thromboembolic disorders had the highest multi-morbidity (mean = 5.2 conditions), whereas those with HF and hypertension had the lowest (mean = 3.5). Clustering of Comorbiditites A five-cluster structure was derived. Cluster 1: Dyslipidemia, Hypertension, Diabetes Mellitus, Visual Impairment Cluster 2: Acute Myocardial Infarction, Unstable Angina, Thromboembolic Disorder, Dementia Cluster 3: Aortic Valvular Disease, Cancer, Hearing Impairment, Arrthythmia Cluster 4: Peripheral Arterial Disease, Stroke Cluster 5: Lung Disease, Liver Disease, Depression Discussion and Conclusions Cluster analysis is an innovative approach to examining the co-occurrence of diseases and allows for identification of broad patterns of multi-morbidity beyond the pairings of diseases or disease counts. Patients with HF have a high rate of multi-morbidity, with an average of 4 co-occurring conditions. Intuitive and unintuitive patterns of clustering were identified. Randomized clinical trials in HF will need to include more diverse patient populations in order to adapt to the increasingly complex patient population. A cluster analysis approach to characterizing patterns of comorbidity may help indentify important patient subgroups.