Readmission In Heart Failure Patients Research Articles

Lung Ultrasound May Reduce Heart Failure Hospitalizations: Preliminary Results from the LUS-HF Trial

Purpose Pulmonary congestion is expressed in the form of B-lines detected by lung ultrasound (LUS) which has proven to be a potent prognostic predictor of hospitalization and mortality in heart failure (HF). However, it is still unknown if a treatment strategy guided by LUS in HF patients may improve outcomes. Hypothesis LUS guided treatment in ambulatory patients after an admission for HF will reduce the combined end-point of readmission or unexpected visit for HF worsening or death in a 6-month follow-up. Methods LUS-HF (NCT02959372 at ClinicalTrials.gov) is a randomized, single center, simple blind clinical trial. Eligible patients are patients older than 18 years of age who have been hospitalized for HF (defined as shortness of breath , pulmonary congestion in chest X ray, NT-proBNP in the first 24 hours of admission: 450 ng/L, 50-75 years: >900 ng/L; >75 years: >1800 ng/L). The exclusion criteria are life expectancy of less than 6 months or severe lung disease . Eligible patients are randomized into either the “LUS group” or the “control group”. The follow-up consists of visits to the HF clinic at periods of 15 days, 1, 3 and 6 months after the initial hospitalization. Only in relation to the “LUS group”, the treating physician will have the result of the examination. The final estimated sample is 102 patients. Results We present the results of the first 52 patients included (26 in each group). Clinical characteristics are summed-up in the table. With a median follow-up of 180 days, 11 events were registered in the control group and 5 in the LUS group (42.3% vs 19.2%, log-rank test 0.077, figure). Conclusion According to the preliminary results of the LUS-HF trial, LUS guided treatment may reduce readmissions in HF patients.

Abstract P347: Lower Optimism is Associated With Heart Failure Readmissions

Introduction: Heart failure is one of the most common reasons for hospitalizations in the U.S. and within 30 days of discharge, nearly one in four patients have been readmitted. While optimism is associated with favorable cardiovascular outcomes, including incident coronary heart disease events and readmission post coronary artery bypass surgery, no data exist for the role of optimism in heart failure patients. Hypothesis: We assessed the hypothesis that optimism is associated with 30 day hospital readmission in heart failure patients. Methods: Optimism is measured using the revised Life Orientation Test (LOT-R) a brief, well-validated scale of optimism. This test was administered by convenience sampling to hospitalized adult (>18 years) heart failure patients to determine if low LOT-R scores (less optimistic) were associated with 30 day hospital readmission. Results: Patients in the lower quartile of optimism scores (or pessimistic) had a higher rate of all cause 30 day readmission compared with those in the highest quartile (p=0.0290). Conclusion: In a single center series of hospitalized heart failure patients, those patients with low optimism scores had a significantly higher all-cause 30 day readmission rate compared with those in the highest quartile of optimism scores. Optimism is trait-like yet may be modifiable, thus presenting an opportunity for intervention in heart failure.

THE IMPACT OF INSULIN USE IN DIABETIC PATIENTS ON HEART FAILURE ADMISSIONS

The use of insulin in patients with diabetes mellitus (DM) is associated with an increased incidence of heart failure (HF) and mortality. However, there is incomplete knowledge regarding the rate of HF readmissions in patients with comorbid insulin-dependent DM (IDDM). We investigated whether HF

ELECTROCARDIOGRAPHIC PREDICTORS OF READMISSION IN HEART FAILURE PATIENTS ON MODERN MEDICAL THERAPY

Heart failure readmissions remain a major public health concern. Data on ECG predictors of heart failure readmission in patients treated with modern medical therapy is lacking. The study cohort included 3189 consecutive heart failure patients with non-paced atrial rhythm, who were enrolled in the

Predicting the Readmission of Heart Failure Patients through Data Analytics

Reducing the costs and improving the quality of treatment in hospital systems as well as demands for better treatment from patients in order to keep them away from readmissions are two main issues healthcare systems have faced. In order to solve such challenges, predicting the occurrence of re-hospitalisation with data mining techniques would be so worthwhile. In this study, we are seeking to predict the occurrence of re-hospitalisation of the heart failure patients in two time-horizons (1-month and 3-month) via deployment of classification algorithms (i.e. decision trees, artificial neural networks, support vector machines and logistic regression). Two criterions (as main criterions) such as AUC (area under curve) and ACC (accuracy) have been calculated and assessed for classifying the prediction-power of the models in each time-horizon (outcome/target). We also have calculated some other criterions such as recall, precision and F1-Score. Then, we identified the importance and contribution of the variables for each outcome. Therefore, the variables whose contribution/importance changes over time are differentiated. It is noteworthy to say that this study is done under the scrutiny of an expert cardiologist. Trained nurses and expert cardiologist monitored the dataset every day, which was a hard and valuable measure to conduct. Finally, the dataset does not have missing values and noises. This research can be the basis for prospective medical studies and projects.

Symptom Management and Hospital Readmission in Heart Failure Patients: A Qualitative Study From Portugal.

This article reports a study aimed at identifying the factors that result in hospital readmissions for patients with heart failure. The high rates of readmission are often due to a lack of knowledge about symptoms and signs of disease progression, and these Portuguese nurses believed that readmissions could be decreased through disease management programs in which patients assumed a more active role in self-care. A study was designed to identify broad categories of problems that lead Portuguese patients with heart failure to be readmitted to hospital. Semistructured interviews were conducted, recorded, and submitted for content analysis, revealing 3 main categories for targeting: health management, behavioral management, and psychological support. This study revealed that patients with heart failure seem to struggle with management of multiple treatment regimens during the long course of their chronic illness. Based on these interviews, authors conclude that a disease management program be tailored expressly for the Portuguese culture and their lifestyle.

Constructing Large Scale Cohort for Clinical Study on Heart Failure with Electronic Health Record in Regional Healthcare Platform: Challenges and Strategies in Data Reuse.

Regional healthcare platforms collect clinical data from hospitals in specific areas for the purpose of healthcare management. It is a common requirement to reuse the data for clinical research. However, we have to face challenges like the inconsistence of terminology in electronic health records (EHR) and the complexities in data quality and data formats in regional healthcare platform. In this paper, we propose methodology and process on constructing large scale cohorts which forms the basis of causality and comparative effectiveness relationship in epidemiology. We firstly constructed a Chinese terminology knowledge graph to deal with the diversity of vocabularies on regional platform. Secondly, we built special disease case repositories (i.e., heart failure repository) that utilize the graph to search the related patients and to normalize the data. Based on the requirements of the clinical research which aimed to explore the effectiveness of taking statin on 180-days readmission in patients with heart failure, we built a large-scale retrospective cohort with 29647 cases of heart failure patients from the heart failure repository. After the propensity score matching, the study group (n=6346) and the control group (n=6346) with parallel clinical characteristics were acquired. Logistic regression analysis showed that taking statins had a negative correlation with 180-days readmission in heart failure patients. This paper presents the workflow and application example of big data mining based on regional EHR data.

Impact of non-cardiovascular disease burden on thirty-day hospital readmission in heart failure patients.

Little is known about the impact of non-cardiovascular disease (CVD) burden on 30- -day readmission in heart failure (HF) patients. The aim of the study was to assess the role of non-CVD burden on 30-day readmission in HF patients. \ METHODS: We analyzed the effect of non-CVD burden by frequency of ICD-9 code categories on readmis-sions of patients discharged with a primary diagnosis of HF. We first modeled the probability of readmis-sion within 30 days as a function of demographic and clinical covariates in a randomly selected training dataset of the total cohort. Variable selection was carried out using a bootstrap LASSO procedure with 1000 bootstrap samples, the final model was tested on a validation dataset. Adjusted odds ratios and confidence intervals were reported in the validation dataset. There were a total of 6228 HF hospitalizations, 1523 (24%) with readmission within 30 days of discharge. The strongest predictor for 30-day readmissions was any hospital admission in the prior year (p < 0.001). Cardiovascular risk factors did not enter the final model. However, digestive system diseases increased the risk for readmission by 17% for each diagnosis (p = 0.046), while respiratory diseases and genitourinary diseases showed a trend toward a higher risk of readmission (p = 0.07 and p = 0.09, respectively). Non-CVDs out-competed cardiovascular covariates previously reported to predict readmission. In patients with HF hospitalization, prior admissions predicted 30-day readmission. Diseases of the digestive system also increase 30-day readmission rates. Assessment of non-CVD burden in HF patients could serve as an important risk marker for 30-day readmissions.

Association of Renin-Angiotensin Inhibitor Treatment With Mortality and Heart Failure Readmission in Patients With Transcatheter Aortic Valve Replacement

Data are lacking on the effect of a renin-angiotensin system (RAS) inhibitor prescribed after transcatheter aortic valve replacement (TAVR). Treatment with a RAS inhibitor may reverse left ventricular remodeling and improve function. To investigate the association of prescription of a RAS inhibitor and outcomes after TAVR. Retrospective cohort study of TAVR procedures performed in the United States (using the Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapies Registry) between July 2014 and January 2016 that were linked to Medicare claims data (final date of follow-up: March 31, 2017). To account for differences in demographics, echocardiographic findings, and in-hospital complications, 1:1 propensity matching was performed. Initial hospital discharge prescription of a RAS inhibitor after TAVR. Primary outcomes were all-cause death and readmission due to heart failure at 1 year after discharge, which were considered separately. The secondary outcome was health status assessed by the Kansas City Cardiomyopathy Questionnaire (KCCQ; score range: 0-100, with a higher score indicating less symptom burden and better quality of life; a small effect size was defined as 5 points) at 1 year. Among 21 312 patients who underwent TAVR at 417 US sites, 8468 patients (39.7%) were prescribed a RAS inhibitor at hospital discharge. After propensity matching, 15 896 patients were included (mean [SD] age, 82.4 [6.8] years; 48.1% were women; mean [SD] left ventricular ejection fraction [LVEF], 51.9% [11.5%]). Patients with a prescription for a RAS inhibitor vs those with no prescription had lower mortality rates at 1 year (12.5% vs 14.9%, respectively; absolute risk difference [ARD], -2.4% [95% CI, -3.5% to -1.4%]; hazard ratio [HR], 0.82 [95% CI, 0.76 to 0.90]) and lower heart failure readmission rates at 1 year (12.0% vs 13.8%; ARD, -1.8% [95% CI, -2.8% to -0.7%]; HR, 0.86 [95% CI, 0.79 to 0.95]). When stratified by LVEF, having a prescription for a RAS inhibitor vs no prescription was associated with lower 1-year mortality among patients with preserved LVEF (11.1% vs 13.9%, respectively; ARD, -2.81% [95% CI, -3.95% to -1.67%]; HR, 0.78 [95% CI, 0.71 to 0.86]), but not among those with reduced LVEF (18.8% vs 19.5%; ARD, -0.68% [95% CI, -3.52% to 2.20%]; HR, 0.95 [95% CI, 0.81 to 1.12]) (P = .04 for interaction). Of 15 896 matched patients, 4837 (30.4%) were included in the KCCQ score analysis and improvements at 1 year were greater in patients with a prescription for a RAS inhibitor vs those with no prescription (median, 33.3 [interquartile range, 14.2 to 51.0] vs 31.3 [interquartile range, 13.5 to 51.1], respectively; difference in improvement, 2.10 [95% CI, 0.10 to 4.06]; P < .001), but the effect size was not clinically meaningful. Among patients who underwent TAVR, receiving a prescription for a RAS inhibitor at hospital discharge compared with no prescription was significantly associated with a lower risk of mortality and heart failure readmission. However, due to potential selection bias, this finding requires further investigation in randomized trials.

Transitional care interventions in reducing readmission for patients with heart failure: a literature review

This paper shows the concept and current research situation of heart failure readmission, and transitional care providers. It focuses on eight transitional care models which can be applied to decrease the readmission for heart failure patients, and puts forward current challenges, so as to provide references for applying transitional care to reduce heart failure readmission in China. Key words: Review; Heart failure; Transitional care; Readmission

Usefulness of Estimated Plasma Volume at Postdischarge Follow-Up to Predict Recurrent Events in Patients With Heart Failure

Hospital readmission for patients admitted with heart failure is a persistent problem. Better identification of patients at high risk of readmission for volume overload could have clinical implications. We evaluated estimated plasma volume (ePV), a marker of congestion, to predict readmission for patients seen early after discharge for heart failure. We identified patients hospitalized with a primary heart failure diagnosis and were then seen in a postdischarge clinic. We assessed clinical factors, ePV (derived from hemoglobin and hematocrit), and B-type natriuretic peptide (BNP). The primary outcome was death or readmission for heart failure within 90 days of discharge. We identified 218 patients, of whom 23% experienced the primary outcome. No clinical variables at time of admission were different between those who did and did not experience the primary outcome, nor were BNP (1,581 vs 1,267 pg/ml, p = 0.33) or ePV (6.00 vs 5.80, p = 0.36). At clinic follow-up, both BNP (1,164 vs 636, p = 0.002) and ePV (6.18 vs 5.58, p = 0.02) were higher in those with subsequent events. Kaplan-Meier survival analysis showed that the lowest tertile of ePV had significantly lower incidence of the primary outcome than the other 2 tertiles (12% vs 29% and 27%, p = 0.02). Estimated plasma volume remained independently predictive of outcomes after controlling for BNP (p <0.05). In conclusion, EPV may be predictive of death or hospital readmission in heart failure patients seen soon after discharge, independent of BNP. Its potential warrants future prospective research evaluating its utility in larger heart failure cohorts.

Symptom Clusters and Their Impacts on Hospital Readmission in Patients With Heart Failure: A Cross-Sectional Study.

Readmissions after hospitalization due to multiple symptoms in heart failure (HF) are common and costly. Patients have difficulty differentiating HF symptoms from comorbid illness or aging. Therefore, early identification of symptom clusters could improve symptom recognition and reduce hospital readmission. However, little is known about the relationship between symptom clusters and readmission in HF patients. This study aimed to identify symptom clusters among Korean patients with HF and the relationship between symptom clusters and hospital readmission. This cross-sectional study included 306 HF outpatients within 12 months after discharge. Exploratory factor analysis was used to identify the symptom clusters. Multiple logistic regression analysis was used to examine the effect of symptom clusters on readmission, after adjusting for sociodemographic and clinical characteristics. Three symptom clusters were identified in HF patients: the "respiratory distress" cluster, "bodily pain and energy insufficiency" cluster, and "circulatory and gastrointestinal distress" cluster. Patients with class III or IV of HF functional class experienced three symptom clusters at a higher level. This study showed that the "bodily pain and energy insufficiency" cluster was the strongest predictor of hospital readmission in HF patients (adjusted odds ratio = 6.59, 95% confidence interval (CI) [1.29, 32.79]). A higher level of "bodily pain and energy insufficiency" cluster was associated with hospital readmission in Korean HF patients. Health-care providers should be encouraged to consider patients' cultural backgrounds to recognize differences in symptom clusters. Further studies are needed to evaluate symptom clusters across international cohorts and their impacts on patients' outcomes.

The Subclinical Hypothyroid State might Predict 30 Day Readmission in Patients with an Acute Heart Failure Syndrome and Reduced Left Ventricular Ejection Fraction.

Introduction Thyroid hormone has an essential role on the functional capability of cardiac muscle with its gene modulation and induction of vasodilatory effects. There is a considerable evidence to suggest the role of thyroid hormone in acute coronary syndrome (ACS) patients but less is known about its prognostic role in heart failure (HF) patients. We aim to evaluate the association between the subclinical hypothyroid state and event rates including 30-day all-cause and HF readmission in patients with an index hospitalization for an acute HF syndrome (AHFS). Methods A retrospective chart review analysis of 1,020 patients, who were admitted to Bronx-Care Hospital Center with the diagnosis of an AHFS was conducted. We reviewed cases from January 1, 2012 to December 31, 2017. The subclinical hypothyroid state was defined as thyroid stimulating hormone (TSH) level>4.50 mIU/L with a normal thyroxine (T4) level. Subjects with preexisting thyroid disease or receiving thyroid replacement therapy were excluded. HF with preserved ejection fraction (HFpEF) was defined as left ventricular ejection fraction (LVEF)>40% and HF with reduced ejection fraction (HFrEF) was defined as having LVEF≤40%. Percentage of 30-day all-cause readmission and mortality was calculated in both cohorts of AHFS (HFpEF and HFrEF) with and without subclinical hypothyroidism. Results The mean age of our 1,020 AHFS population was 66 ± 15.1 years. Of 1,020 patients admitted with AHFS, 635 (63%) patients were found to have HFrEF and 385 with HFpEF(37%). There were 64 (6.27%) patients with AHFS found to have subclinical hypothyroidism. There were more males than females (52% versus 48%). The percentage of hospital readmission within 30 days was higher for patients with subclinical hypothyroidism compared to those without subclinical hypothyroidism in the HFrEF group (42.9% versus 27.2%, P = 0.029). Hospital readmission within 30 days for patients with subclinical hypothyroidism compared to those without subclinical hypothyroidism in HFpEF group did not differ (30% versus 22%, P = 0.675). Additionally, all-cause mortality was higher among patients with subclinical hypothyroidism compared to patients without subclinical hypothyroidism in the HFrEF group (20% versus 6.0%, P Conclusion Subclinical hypothyroidism during an index hospital admission for an AHFS was an independent predictor of readmission in 30 days in patients with HFrEF but not in patients with HFpEF. It is also related to an adverse outcome such as all-cause mortality. Further studies regarding the concept of tissue thyroid and the potential for a therapeutic target are warranted.

Six-Minute Walk Distance Under 135 Meters Predicts Early and Frequent 30-day Heart Failure Readmissions in Patients with Stage C and D Heart Failure

Introduction With a 30-day all cause readmission rate around 23%, individuals with heart failure (HF) are a medically high risk and costly patient population. Though predictive models have been developed for readmission based on descriptive variables, many of these tools are cumbersome and limited in prognosticative capacity. A few studies have examined the role of the six-minute walk test (6MWT) and found good predictive ability for both 30-day and 1-3-year readmission rates. The goal of this study was to further elucidate the prognostic ability of the 6MWT in stage C/D HF patients with NYHA class IIIb-VI symptoms. Methods We prospectively enrolled 97 patients who from our step-down units with a primary diagnosis of heart failure between October 2016 and March 2017. Every patient who was enrolled had a standardized 6MWT prior to discharge. Multivariate logistic regression analysis was constructed to determine relationships between 6MW distance and 30-day survival free of readmission. Results Baseline characteristics were compared between the 6-minute walk test distance groups using Wilcoxon rank-sum tests for continuous variables and Fisher's exact tests for categorical variables, and no significant differences were found between the patients. The 135-meter cut-point was selected as the threshold which maximizes the sum of sensitivity and specificity of a logistic regression model for 30-day readmission with 6-minute walk test distance as a continuous predictor. Approximately 25.7% of the patients walked less than 135 meters. Out of these about 32% were admitted within 30 days [p= .026]. Among the patients who walked > 135 meters, 11.1% were admitted within 30 days [p= 0.026]. Furthermore, patients who walked Conclusions 6MWT distance less than 135m was associated with not only increased risk of 30 day readmission but also correlated with increased frequency of admissions in patients admitted with stage C/D heart failure.

A machine learning model to predict the risk of 30-day readmissions in patients with heart failure: a retrospective analysis of electronic medical records data

BackgroundHeart failure is one of the leading causes of hospitalization in the United States. Advances in big data solutions allow for storage, management, and mining of large volumes of structured and semi-structured data, such as complex healthcare data. Applying these advances to complex healthcare data has led to the development of risk prediction models to help identify patients who would benefit most from disease management programs in an effort to reduce readmissions and healthcare cost, but the results of these efforts have been varied. The primary aim of this study was to develop a 30-day readmission risk prediction model for heart failure patients discharged from a hospital admission.MethodsWe used longitudinal electronic medical record data of heart failure patients admitted within a large healthcare system. Feature vectors included structured demographic, utilization, and clinical data, as well as selected extracts of un-structured data from clinician-authored notes. The risk prediction model was developed using deep unified networks (DUNs), a new mesh-like network structure of deep learning designed to avoid over-fitting. The model was validated with 10-fold cross-validation and results compared to models based on logistic regression, gradient boosting, and maxout networks. Overall model performance was assessed using concordance statistic. We also selected a discrimination threshold based on maximum projected cost saving to the Partners Healthcare system.ResultsData from 11,510 patients with 27,334 admissions and 6369 30-day readmissions were used to train the model. After data processing, the final model included 3512 variables. The DUNs model had the best performance after 10-fold cross-validation. AUCs for prediction models were 0.664 ± 0.015, 0.650 ± 0.011, 0.695 ± 0.016 and 0.705 ± 0.015 for logistic regression, gradient boosting, maxout networks, and DUNs respectively. The DUNs model had an accuracy of 76.4% at the classification threshold that corresponded with maximum cost saving to the hospital.ConclusionsDeep learning techniques performed better than other traditional techniques in developing this EMR-based prediction model for 30-day readmissions in heart failure patients. Such models can be used to identify heart failure patients with impending hospitalization, enabling care teams to target interventions at their most high-risk patients and improving overall clinical outcomes.

Effect of Optimizing Guideline-Directed Medical Therapy Before Discharge on Mortality and Heart Failure Readmission in Patients Hospitalized With Heart Failure With Reduced Ejection Fraction

Guideline-directed medical therapy (GDMT) is recommended for patients with heart failure with reduced ejection fraction (HFrEF). However, the prognostic impact of medication optimization at the time of discharge in patients hospitalized with heart failure (HF) is unclear. We analyzed 534 patients (73 ± 13 years old) with HFrEF. The status of GDMT at the time of discharge (prescription of angiotensin converting enzyme inhibitor [ACE-I]/angiotensin receptor blocker [ARB] and β blocker [BB]) and its association with 1-year all-cause mortality and HF readmission were investigated. Patients were divided into 3 groups: those treated with both ACE-I/ARB and BB (Both group: n = 332, 62%), either ACE-I/ARB or BB (Either group: n = 169, 32%), and neither ACE-I/ARB nor BB (None group: n = 33, 6%), respectively. One-year mortality, but not 1-year HF readmission rate, was significantly different in the 3 groups, in favor of the Either and Both groups. A favorable impact of being on GDMT at the time of discharge on 1-year mortality was retained even after adjustment for covariates (Either group: hazard ratio [HR] 0.44, 95% confidence interval [CI] 0.21 to 0.90, p = 0.025 and Both group: HR 0.29, 95% CI 0.13-0.65, p = 0.002, vs None group). For 1-year HF readmission, no such association was found. In conclusion, optimization of GDMT before the time of discharge was associated with a lower 1-year mortality, but not with HF readmission rate, in patients hospitalized with HFrEF.

Optimizing Management of Heart Failure by Using Echo and Natriuretic Peptides in the Outpatient Unit.

Chronic heart failure (HF) is an important public health problem and is associated with high morbidity, high mortality, and considerable healthcare costs. More than 90% of hospitalizations due to worsening HF result from elevations of left ventricular (LV) filling pressures and fluid overload, which are often accompanied by the increased synthesis and secretion of natriuretic peptides (NPs). Furthermore, persistently abnormal LV filling pressures and a rise in NP circulating levels are well known indicators of poor prognosis. Frequent office visits with the resulting evaluation and management are most often needed. The growing pressure from hospital readmissions in HF patients is shifting the focus of interest from traditionally symptom-guided care to a more specific patient-centered follow-up care based on clinical findings, BNP and echo. Recent studies supported the value of serial NP measurements and Doppler echocardiographic biomarkers of elevated LV filling pressures as tools to scrutinize patients with impending clinically overt HF. Therefore, combination of echo and pulsed-wave blood-flow and tissue Doppler with NPs appears valuable in guiding ambulatory HF management, since they are potentially useful to distinguish stable patients from those at high risk of decompensation.

The relationship between health literacy and knowledge about heart failure with recurrent admission of heart failure patients

Introduction: Having good health literacy can improve quality of life and decrease re-hospitalization of the patients including patients with heart failure (HF). Considering the importance of knowledge about HF and health literacy in these patients and the existence of contradictory texts, this study aimed to determine the relationship between health literacy and knowledge of HF, with re-admission of HF patients. Methods: The present study was a cross-sectional study in which 238 patients aged over 18 years old with an ejection fraction of 35% and less with the ability to read, write, and speak, and no psychological, neurological and cognitive disorders were included in the study after they signed the consent form of the research. Data collection was done through demographic information questionnaire, Short-Test of Functional Health Literacy in Adult-16 standard health literacy questionnaire, and Van Der Wal knowledge about HF questionnaire (2005). Both questionnaires were validated and their reliability was investigated before starting the study. The Chi-square test, Fisher's exact test, or the Mann–Whitney tests were used to compare variables. Results: Most of the patients were male (66%) and married (80%). The results showed that the majority of study population had proper health literacy and about half of them had enough information about HF. This study showed that there is a significant relationship between health literacy and knowledge. In other words, the higher the health literacy of the people, the greater their awareness of their illness (P = 0.02). However, the findings showed that there is no significant relationship between health literacy and awareness of HF with the number of admissions. Conclusion: The results of this study show that the higher the health literacy of the people may lead to the higher their knowledge and awareness about HF and better understanding the recommendations regarding their illness.

Abstract 21366: Atrial Fibrillation Adversely Affects Readmission Outcomes for Heart Failure: Observations From the Nationwide Readmissions Database

Introduction: Atrial fibrillation(AF) and heart failure (HF) often coexist. Readmissions in HF is a rising concern. Hypothesis: AF affects 90-day readmissions following admission for HF. Methods: The Nationwide Readmissions Database (NRD) for 2013 was analyzed for the first readmission within 90-days following discharge with a diagnosis of AF and HF. Clinical Classification Software (CCS) from the Health Care Utilization Project (HCUP) was utilized to investigate leading diagnoses and procedures for readmissions. ICD-9-CM codes were used to identify diagnoses not classified in the CCS. All estimates were weighted using the weight variable provided by HCUP for stratified sampling. Results: In 2013, 885,270 adults were admitted with a primary diagnosis of HF of which 364,447(41%) had AF. After discharge, 90-day all-cause readmission rates were significantly higher in HF patients with coexisting AF (41% vs 38%, p&lt;0.001). Multivariate regression analysis showed that AF was independently associated with an increased likelihood of 90-day readmission after discharge for HF (OR: 1.18, CI: 1.14-1.21). In HF patients with coexisting AF, the primary readmission diagnoses were HF (36%), renal failure (4%), AF (4%), sepsis (4%) and respiratory failure (3%) and the most common procedures performed were cardioversion (16 %), echocardiogram (12 %), coronary revascularization (7%), blood transfusion (6%) and hemodialysis (5%). Mean length of stay during readmission in patients with and without coexisting AF was 5.0 vs 5.5 days (p&lt;0.000, t-test). Mean cost of readmission during readmission in patients with and without coexisting AF was $8693 vs $9386 (p&lt;0.000, t-test). Conclusion: In patients with HF, coexisting AF is associated with higher likelihood of 90-day readmission. Most common causes for such readmissions are decompensated HF, AF and renal failure. Adequately controlled AF may reduce readmissions in HF patients.

O57-1 - The Assessment of Right Ventricular Function by Right Ventricular Stroke Work Index in Patients with Pre-Capillary Pulmonary Hypertension

Background: Long-term outcomes of pre-capillary pulmonary hypertension (PH) have been improved. However, morbidity and mortality are still high because of right-sided heart failure (HF). Right-sided HF is closely related to right ventricular (RV) function such as RV stroke work index (RVSWI). The aim of this study was to compare clinical characteristics between low RVSWI and high RVSWI, and to investigate the association between low RVSWI and long-term outcomes in patients with pre-capillary PH. Methods: We included patients admitted to diagnose and evaluate PH by right heart catheterization between 2007 and 2015. Patients with pre-capillary PH were divided into 2 groups according to the median value of RVSWI (low RVSWI group: RVSWI < 19.7 gm/m2/beat; high RVSWI group: RVSWI > 19.7 gm/m2/beat). Multivariate Cox regression analysis were applied to investigate whether the low RVSWI were associated with HF death or HF readmission in patients with pre-capillary PH. Results: A total of 36 patients with pre-capillary PH were allocated into the low RVSWI group (n = 18) and high RVSWI group (n = 18). The low RVSWI group was significantly associated with HF death or HF readmission compared to the high RVSWI group even after adjusting for confounding factors (hazard ratio: 9.80 [95% CI: 1.15 to 83.85], P = .04). Conclusions: Lower RVSWI was significantly associated with HF death or HF readmission in patients with pre-capillary PH.