Higher Risk Of Rehospitalization Research Articles

Exploring the temporal relationship between atrial fibrillation and heart failure development. Analysis from nationwide database

Abstract Background Atrial fibrillation (AF) and heart failure (HF) often coexist and are closely intertwined, each condition worsening the other. The temporal relationships between these two disorders have not yet been fully explored. We assessed, on a nationwide scale, the prognosis of patients hospitalized with HF and AF, based on the timing of AF and HF development. Methods From the administrative database covering hospital care for the whole French population, we identified 1,349,638 patients diagnosed with both AF and HF between 2010 and 2018: 956,086 of these AF patients developed HF first (prevalent HF) and 393,552 developed HF after AF (incident HF). The outcome analysis (all-cause death, cardiovascular [CV] death, ischemic stroke or hospitalization for HF) was performed with follow-up starting at the time of last event between AF or HF in the whole cohort and in 427,848 propensity-score-matched patients (213,924 with incident HF and 213,924 with prevalent HF). Results During follow-up (mean follow-up 1.6±1.9 year), matched patients with prevalent HF had a higher risk of all-cause death (21.6 vs 19.2%/year), CV death (7.6 vs 6.5%/year) as well as non-cardiovascular death (13.9 vs 12.7%/year) than those with incident HF. The risk for ischemic stroke was lower in the prevalent HF group (1.2 vs 2.4%/year). Conclusion In patients hospitalized with both AF and HF, we identified two distinct clinical entities based on the chronological sequence of the two disorders. Patients in whom HF preceded AF (prevalent HF) had higher mortality and higher risk of rehospitalization for HF. Funding Acknowledgement Type of funding sources: None.

CA125: An Increasingly Promising Biomarker of Heart Failure.

CA125 is a well-known tumor marker for diagnosis, monitoring, and risk stratification in ovarian cancer. It is not specific for malignant tumors and may be elevated in benign disease. In the past two decades, increasing evidence has emerged suggesting that the plasma level of CA125 can serve as a novel surrogate of heart failure (HF). CA125 in patients with HF is synthesized by serous epithelial cells in response to both mechanical and inflammatory stimuli. In patients with HF, regardless of etiology, CA125 levels correlate with the severity of clinical, hemodynamic, and echocardiographic parameters and with other biomarkers. Elevated CA125 can identify patients at high risk of rehospitalization and mortality, whether short- or long-term. Serial measurements and combination with different pathophysiology biomarkers can provide a more accurate prognosis value. It also can guide treatment as a robust biomarker of fluid overload and inflammation, particularly for diuretic dose optimization. These properties make it a very promising candidate for risk stratification and treatment guidance of HF.

Home telemonitoring in heart failure patients and the effect of study design on outcome: A literature review

Introduction A wide range of study designs have been utilized in evaluations of home telemonitoring and these studies have produced conflicting outcomes over the years. While some of the research has shown that telemonitoring is beneficial in reducing all-cause mortality, hospital admission, length of stay in hospital and emergency room visits, other studies have not shown such benefits. This study, therefore, aims to examine several home telemonitoring study designs and the influence of study design on study outcomes. Method Articles were obtained by searching PubMed database with the term heart failure combined with the following terms: telemonitoring, telehealth, home monitoring, and remote monitoring. Searches were limited to randomized controlled trial conducted between year January 1, 2000 and February 6, 2021. The characteristics of the study designs and study outcomes were extracted and analyzed. Result Our review of 34 randomized controlled trials of heart failure telemonitoring did not show any significant influence of study design on reduction in number of hospitalizations and/or decrease in mortality. Studies that were done outside North America (USA and Canada) and studies that selected patients at high risk of re-hospitalization were more likely to result in decreased hospitalization and/or mortality, though this was not statistically significant. All the studies that met our inclusion criteria were from high-income countries and only one study enrolled patients at high risk of re-hospitalization. Conclusion There is a need for more studies to understand why telemonitoring studies in Europe were more likely to reduce hospital admission and mortality compared to those in North America. There is also a need for more studies on the effect of telemonitoring in patients at high risk of hospital readmission.

Development of a Palliative Telehealth Pilot to Meet the Needs of the Nursing Home Population.

Many older adults will spend their final days in a skilled nursing facility because of multiple complex conditions. Patients with unclear goals of care are at higher risk of rehospitalization and burdensome care at end of life. Palliative care has been shown to improve outcomes for this patient population; however, access is limited because of the small number of boarded specialists nationwide. Telehealth offers the ability to expand the reach of palliative care to both underserved geographies and community settings. This quality improvement pilot project details the development and implementation of a telehealth palliative care program available to nursing home residents. Eight nursing homes, in the New England region of the United States, participated in the 4-month pilot. The palliative telehealth program offered real-time access to a palliative care specialist able to provide symptom management, goals-of-care discussions, and Medical Orders for Life-Sustaining Treatment completion. The pilot shows promising outcomes including code status change, Medical Order for Life-Sustaining Treatment form completion, and reduced hospitalizations supporting the benefit of comprehensive goals-of-care discussions for frail older adults living in a nursing home. As health care moves into the digital age, telemedicine plays a large role in the delivery of essential patient care. Provision of palliative specialists by telehealth allows the opportunity to address the unmet needs of this frail population.

Temporal Trends and Patient Characteristics Associated with 30-Day Hospital Readmission Rates after a First Acute Myocardial Infarction

BackgroundLimited data exist about relatively recent trends in the magnitude and characteristics of patients who are re-hospitalized after hospital admission for an acute myocardial infarction. This study examined trends in the frequency and sociodemographic and clinical characteristics of patients readmitted to the hospital within 30 days after an initial acute myocardial infarction. MethodsWe reviewed the medical records of 3116 individuals who were hospitalized for a validated first acute myocardial infarction in 6 study periods between 2003 and 2015 at the 3 major medical centers in central Massachusetts. ResultsThe median age of our population was 67 years, and 42% were women. The risk of being readmitted to the hospital within 30 days after an initial acute myocardial infarction increased slightly during the most recent study years after controlling for potentially confounding factors. Overall, older adults and patients with previously diagnosed atrial fibrillation, heart failure, diabetes, chronic kidney disease, stroke, and peripheral vascular disease were at higher risk for being readmitted to the hospital than respective comparison groups. For those hospitalized in the most recent study years of 2011/2015, a higher risk of rehospitalization was associated with a previous diagnosis of chronic kidney disease, peripheral vascular disease, the presence of 3 or more chronic conditions, and having developed atrial fibrillation or heart failure during the patient's hospitalization for a first acute myocardial infarction. ConclusionsWe identified several groups at higher risk for hospital readmission in whom enhanced surveillance efforts as well as tailored educational and treatment approaches remain needed.

Derivation and validation of a prediction model for neonate unplanned rehospitalization in a tertiary center in China.

BackgroundTo construct and externally validate a prediction model for neonate unplanned rehospitalization within 31 days of discharge.MethodsA retrospective study was performed in the Department of Neonatology of the Children’s Hospital of Fudan University. A binominal regression method was applied to construct and validate the prediction model. Analysis was performed on a total of 11,116 neonates with an index admission between 11/1/2016 and 12/31/2018. Neonates admitted from 11/1/2016 to 1/31/2018 were used for the selection of prognostic variables and construction of the model. Model validation was then performed with neonates admitted from 2/1/2018 to 12/31/2018.ResultsThe rehospitalization rate for neonates was 3.27% (373/11,116). A total of 512 neonates were enrolled for the construction of the prediction model. Gestational age (GA), NICU length of stay (LOS), nonmedical order discharge and younger maternal age were strongly correlated with rehospitalization. By incorporating these 4 strong risk factors, we constructed a model to predict neonate unplanned rehospitalization within 31 days of discharge. The formula was turned into a nomogram for use in clinical practice. The nomogram has a total score of 180, with a predicted risk from 0 to 100%. Neonates are at high risk for rehospitalization if they have a total score greater than 39 points, according to the cutoff point established by the Youden index. The model was shown to have good discriminatory ability, with area under the receiver operating characteristic curves of 0.68 and 0.65 in the model construction and validation datasets, respectively. A total of 39 points is the cutoff for follow-up.ConclusionsThe model is able to predict neonate unplanned rehospitalization well. A total score greater than 39 indicates that follow-up is necessary.

Demographic, clinical characteristics and medications of rehospitalized patients for acute coronary syndrome: boomerang study

Background: Rehospitalizations with acute coronary syndromes (ACSs) have declined over the last years, but there is a remaining need for potential further reduction of rehospitalization after ACS to determine the most predominant predictors that can guide strategies to reduce re-hospitalizations burden. Aim: This multi-center study aimed to evaluate the demographic, clinical characteristics, and medications of rehospitalized patients who suffered a new cardiac event in 12 months after admission due to ACS. Material and Methods: Patients age >18 years who have been hospitalized between November 1 2017, and April 1 2018, for ACS within12 months before the readmission for a new acute coronary event were enrolled. Results: The present study included a total of 628 (65.9% from Turkey) consecutive patients rehospitalized with ACS (ST-elevation myocardial infarction [STEMI], 23.0%; ACS without ST-elevation [NSTE-ACS], 76.9%) from 15 different countries. The majority of the rehospitalized patients were men (67.9%), and the mean age was 63.1 ± 12.53 years. 406 (64.6%) had typical, 209 (33.2%) of patients had atypical chest pain and 13 (2.07%) had not any chest pain complaint during readmission. 304 (48.41%) of patients were discharged from hospital earlier than 3 days and 107 (17.04%) of patients stayed more than 7 days. The subcategories of first index diagnosis were 227 (36.1%) STEMI; 401 (63.8%) NSTE-ACS. The mean time from index discharge to rehospitalization was 189.25 ± 118 days. 248 (39.4%) patients were re-hospitalized more than once after index discharge. The most common risk factors were diabetes mellitus (471, 75.0%). 175 (27.87%) of patients stopped taking medication before re-hospitalization. Most of the patients (69.4%) had multivessel disease. Conclusion: Several factors identify patients at higher risk of rehospitalization with ACS. Understanding and preventing these causes can prevent rehospitalization and improve their outcome.

Machine-learning prediction of unplanned 30-day rehospitalization using the French hospital medico-administrative database.

Predicting unplanned rehospitalizations has traditionally employed logistic regression models. Machine learning (ML) methods have been introduced in health service research and may improve the prediction of health outcomes. The objective of this work was to develop a ML model to predict 30-day all-cause rehospitalizations based on the French hospital medico-administrative database.This was a retrospective cohort study of all discharges in the year 2015 from acute-care inpatient hospitalizations in a tertiary-care university center comprising 4 French hospitals. The study endpoint was unplanned 30-day all-cause rehospitalization. Logistic regression (LR), classification and regression trees (CART), random forest (RF), gradient boosting (GB), and neural networks (NN) were applied to the collected data. The predictive performance of the models was evaluated using the H-measure and the area under the ROC curve (AUC).Our analysis included 118,650 hospitalizations, of which 4127 (3.5%) led to rehospitalizations via emergency departments. The RF model was the most performant model according to the H-measure (0.29) and the AUC (0.79). The performances of the RF, GB and NN models (H-measures ranged from 0.18 to 0. 29, AUC ranged from 0.74 to 0.79) were better than those of the LR model (H-measure = 0.18, AUC = 0.74); all P values <.001. In contrast, LR was superior to CART (H-measure = 0.16, AUC = 0.70), P < .0001.The use of ML may be an alternative to regression models to predict health outcomes. The integration of ML, particularly the RF algorithm, in the prediction of unplanned rehospitalization may help health service providers target patients at high risk of rehospitalizations and propose effective interventions at the hospital level.

Real-World Analysis of Guideline-Based Therapy After Hospitalization for Heart Failure.

BackgroundPatients 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 ResultsThis 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.ConclusionsIn 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.

Different Effects of Thiazolidinediones on Cardiovascular Events among Type 2 Diabetic Patients Implanted with Bare Metal Stents: A Nationwide Study

Background: This study aimed to evaluate the effect of thiazolidinediones (TZDs) on re-hospitalization rates for revascularization after bare-metal stent (BMS) implantation. Methods: Data from the National Health Insurance Research Database (NHIRD), a government-operated, population-based database, were analyzed from March, 2000 to December, 2006. Type 2 diabetes subjects treated with BMS implantations who used TZDs (either rosiglitazone or pioglitazone) were compared with subjects not on TZDs (non-TZD group) to evaluate the risk of readmission for coronary revascularization. Endpoints were acute coronary syndrome (ACS) and readmission for revascularization (percutaneous coronary intervention or coronary artery bypass graft surgery) after 3, 6, and 12 months. Results: In total, 6911 type 2 diabetes patients were hospitalized for BMS implantation (average follow-up, 294.4 ± 108.9 days). Rosiglitazone treatment in patients who received BMSs was associated with a higher risk of re-hospitalization for revascularization at 6 and 12 months (hazard ratio (HR) = 1.33; 95% CI: 1.08-1.64 and HR = 1.20 95% CI: 1.01-1.43). However, there were no significant differences between the pioglitazone and non-TZD groups. Conclusion: The use of rosiglitazone in type 2 diabetes patients after BMS implantation may increase the risk of re-hospitalization for revascularization. Our study suggests that rosiglitazone should be used cautiously in diabetes patients with BMS implantation.

Rate and risk factors for rehospitalisation in sepsis survivors: systematic review and meta-analysis.

PurposeSepsis survivors have a higher risk of rehospitalisation and of long-term mortality. We assessed the rate, diagnosis, and independent predictors for rehospitalisation in adult sepsis survivors.MethodsWe searched for non-randomized studies and randomized clinical trials in MEDLINE, Cochrane Library, Web of Science, and EMBASE (OVID interface, 1992–October 2019). The search strategy used controlled vocabulary terms and text words for sepsis and hospital readmission, limited to humans, and English language. Two authors independently selected studies and extracted data using predefined criteria and data extraction forms.ResultsThe literature search identified 12,544 records. Among 56 studies (36 full and 20 conference abstracts) that met our inclusion criteria, all were non-randomised studies. Studies most often report 30-day rehospitalisation rate (mean 21.4%, 95% confidence interval [CI] 17.6–25.4%; N = 36 studies reporting 6,729,617 patients). The mean (95%CI) rehospitalisation rates increased from 9.3% (8.3–10.3%) by 7 days to 39.0% (22.0–59.4%) by 365 days. Infection was the most common rehospitalisation diagnosis. Risk factors that increased the rehospitalisation risk in sepsis survivors were generic characteristics such as older age, male, comorbidities, non-elective admissions, hospitalisation prior to index sepsis admission, and sepsis characteristics such as infection and illness severity, with hospital characteristics showing inconsistent associations. The overall certainty of evidence was moderate for rehospitalisation rates and low for risk factors.ConclusionsRehospitalisation events are common in sepsis survivors, with one in five rehospitalisation events occurring within 30 days of hospital discharge following an index sepsis admission. The generic and sepsis-specific characteristics at index sepsis admission are commonly reported risk factors for rehospitalisation.RegistrationPROSPERO CRD 42016039257, registered on 14-06-2016.Electronic supplementary materialThe online version of this article (10.1007/s00134-019-05908-3) contains supplementary material, which is available to authorized users.

Effectiveness of Cognitive Behavioral Therapy to Reduce Depression, Anxiety and Stress among Hospitalized Patients with Congestive Heart Failure in Central Java

Introduction: Psychological problems in patients with heart failure are the result of a combination of the influence of behavior and interactions with physiological responses, which if not handled properly will contribute to worsening clinical symptoms and have a higher risk of rehospitalization. The objective of the study was to evaluate the effects of cognitive behavior therapy (CBT) on psychological symptoms among CHF patients.Methods: This was a quasi-experimental, pretest-posttest control study that applying a CBT to overcome depression, anxiety, and stress. Thirty eligible respondents were recruited and were randomly divided into a case group and waiting list group. Psychological symptoms of respondents were measured using Depression, Anxiety and Stress Scale – 21 questionnaires (DASS-21). Chi-square was used to compare demographic data between groups and T-test analysis was used to describe changes in mean scores between and within groups. Both groups had similar characteristics and psychological symptoms level at baseline.Results: The mean score of depression, anxiety and stress showed a significant difference within the group after the intervention (p&lt;0.05).Conclusion: A recent study found that CBT was effective to reduce psychological symptoms among CHF patients. Based on the study results it can be highlighted that it is important for nurses to provide brief CBT to hospitalized patients in an effort to reduce short term psychological symptoms.

Rate of Rehospitalization in 60 Days of Discharge and It's Determinants in Patients with Heart Failure with Reduced Ejection Fraction in a Tertiary Care Centre in India

Background and ObjectivesIdentifying the patients with acute heart failure (HF) at high risk for rehospitalization after hospital discharge will enable proper optimization of treatment. This study is aimed to evaluate the rehospitalization rate at 60 days of discharge and their predictors in patients of chronic heart failure with reduced ejection fraction (HFrEF).MethodsThis prospective observational study enrolled patients with left ventricle ejection fraction (LVEF) <40%, who were admitted because of acute decompensation. Patients were followed for 60 days to analyze rehospitalization rate and its predictors.ResultsOf 103 HFrEF patients (74% male; mean age 55.8 years) enrolled, 7 patients died during index admission and 3 patients lost to follow up. The 60-day rehospitalization rate was 37% (34/93). We studied 23 clinical and 9 biochemical predictors of rehospitalization. Out of 34 events of rehospitalization, 79.41% (n=28) was due to cardiac cause followed by respiratory 5.8% (n=2), renal 5.8% (n=2) and others 5.8% (n=2). Among all the parameters, on logistic regression analysis having longer length of index hospital stay (>7 days) (52.8% vs. 28.8%; odds ratio [OR], 1.79; confidence interval [CI], 1.2–7.25; p=0.040) and chronic kidney disease (CKD) (26.5% vs. 8.5%; OR, 3.06; CI, 1.1–57.04; p=0.050) independently increased the risk of rehospitalization at 60 days of discharge. Further higher haemoglobin level (11.3 vs. 9.9 gm/dL; OR, 0.71; CI, 0.48–0.97; p=0.050) and higher LVEF at index admission (30.4% vs. 26.5%; OR, 0.87; CI, 0.75–0.99; p=0.049) were associated with decreased the risk of rehospitalization.ConclusionsOur study reveals that patients with HFrEF have significantly higher rehospitalization rate (37%) and in-hospital mortality rates (6.78%) of any chronic cardiac disease conditions. Correction of low hemoglobin and special care in those who are having very low LVEF, CKD and longer length of stay, including tailored therapy and frequent visits may play an important role in preventing future rehospitalization in these patients.

READMISSION RISK BY INSURANCE TYPE FOR PATIENTS WITH HEART FAILURE IN SKILLED NURSING FACILITIES

Heart failure (HF) is a leading cause of potentially preventable hospital readmissions for Medicare beneficiaries from skilled nursing facilities (SNFs). This research seeks to determine if a HF patient’s insurance type (Medicare Fee-for-Service (FFS) vs. Medicare Advantage (MA)) influences their risk for readmission within 30 days of hospital discharge to a SNF. MA beneficiaries receive benefits through managed care plans with restricted networks, but typically expanded benefits. This research is particularly timely in light of CMS’ new penalties under the Protecting Access to Medicare Act (PAMA) directed at SNFs for 30-day rehospitalizations. Outcomes data on readmissions from a randomized controlled trial of HF Disease Management in SNFs conducted from 2014-2017 were used to evaluate the risk of readmission. Patients with HF receiving SNF care were enrolled and followed for 30 days from SNF admission. Patients were recruited from 29 primarily for-profit (93%) SNFs that contracted with an average of 4.07 (±5.48) MA plans. Of the 340 study participants followed, 62% had FFS Medicare coverage (n=212) and 38% had MA (n=128). In total, 23% (n=79) of patients experienced at least one readmission within 30 days of hospital discharge. FFS patients had a higher risk of rehospitalization within 30 days of hospital discharge than MA patients (25% vs. 20%), but the association between insurance type and rehospitalization was not statistically significant (p-value=0.177). Findings suggest that insurance type may be an important risk factor for rehospitalizations for patients with HF from SNF; however, a larger sample will need to confirm this relationship.

The potential prognostic utility of salivary galectin-3 concentrations in heart failure.

Patients with HF are at a higher risk of rehospitalisation and, as such, significant costs to our healthcare system. A non-invasive method to collect body fluids and measure Gal-3 could improve the current management of HF. In this study, we investigated the potential prognostic utility of salivary Galectin-3 (Gal-3) in patients with heart failure (HF). We collected saliva samples from patients with HF (n = 105) either at hospital discharge or during routine clinical visits. Gal-3 concentrations in saliva samples were measured by ELISA. The Kaplan-Meier survival curve analysis and Cox proportional regression model were used to determine the potential prognostic utility of salivary Gal-3 concentrations. The primary end point was either cardiovascular death or hospitalisation. Salivary Gal-3 concentrations were significantly higher (p < 0.05) in patients with HF who subsequently experienced the primary endpoint compared to those who did not. HF patients with salivary Gal-3 concentrations > 172.58ng/mL had a significantly (p < 0.05) higher cumulative risk of the primary endpoint compared to those with lower salivary Gal-3 concentrations. In patients with HF, salivary Gal-3 concentration was a predictor of the primary endpoint even after adjusting for other covariates. In our pilot study, HF patients with salivary Gal-3 concentrations of > 172.58ng/mL demonstrated a higher cumulative risk of the primary outcome compared to those with lower Gal-3 levels, even after adjusting for other variables. Confirming our findings in a larger multi-centre clinical trial in the future would enable salivary Gal-3 measurements to form part of routine management for patients with HF.

P6485Incremental prognostic value of electrocardiographic strain after transcatheter aortic valve replacement for aortic stenosis

Abstract Background Electrocardiographic (ECG) strain pattern has recently been associated with increased adverse outcome in aortic stenosis (AS) and after surgical aortic valve replacement (AVR). However, the relation linking ECG strain and cardiovascular MACE in patients with transcatheter aortic valve replacement (TAVR) has not been yet described. Objectives The aim of our study was to determine the impact and incremental value of ECG Strain pattern in predicting adverse outcome after TAVR. Methods 585 patients with severe AS (mean age: 83±7 male 39.8%) were enrolled from November 2012 to May 2018. ECG strain pattern was defined as ≥1 mm concave down-sloping ST-segment depression and asymmetrical T-wave inversion in the lateral leads. Patients with baseline left bundle branch block (LBBB), right bundle branch block (RBBB) or ventricular paced rhythm were excluded. All patients underwent transthoracic echocardiography (TTE) before TAVR and at 30 days follow up. The primary endpoints of the study were the overall all-cause mortality after TAVR, rehospitalization for Hearth failure (HF), myocardial infarction and stroke. Results 178 (30.4%) patients were excluded from analyses owing to the presence of either LBBB (n=103) or RBBB (n=75). Among the 407 remaining patients, 106 had ECG strain pattern (26.04%). Patients with ECG strain were significantly younger (81.6±8 years vs 83.5±6.8 years; p=0.022), had lower BMI (23±4.5 kg.m2 vs 27.9±6.8 kg.m2; p=0.02) more severe AS (mean gradient 52.3±15.2 mmHg vs 47.9±11.8 mmHg; p=0.003), significant lower LVEF (51.8±15% vs 58.4±10.7%; p&lt;0.001). Left ventricular hypertrophy (LVH) was more frequent in patients with ECG Strain (indexed left ventricular mass (135.9±33.4 g.m2 vs 123.6±31.9 g.m2; p=0.002)). Death from any cause (22 (20.8%) vs 61 (20.3%); p=0.508) did not differ significantly between groups. Major adverse cardiovascular events (MACE) including death, stroke and heart failure at 1 month showed similar incidence (7 (6.6%) vs 17 (5.6%), p=0.439). Rehospitalization for hearth failure (HF) was significantly higher (33 (31.1%) vs 33 (11%); p&lt;0.001) in patients with ECG strain pattern. In univariate model, ECG Strain was a strong predictor of rehospitalization for HF (HR 2.621 95% CI (1.607–4.277), p=0.001), independently of LVH assessed either by ECG criteria (HR 1.181 95% CI (0.698–1.997; p=0.536) or TTE (HR 1.557 95% (CI 0.701–3.458; p=0.277). ECG Strain remained associated with a higher risk of rehospitalization for hearth failure in multivariate analyses (HR 2.747 95% (CI 1.614- 4.674); p&lt;0.001) Conclusion In patients with AS eligible for TAVR, ECG Strain Pattern is frequent and associated with an increased risk of post interventional heart failure regardless of preoperative LVH. ECG Strain pattern represents an easy, objective, reliable and low-cost tool to identify patients who may benefit from an extend and intensified post-interventional follow-up.

P6360Prognostic value of polypharmacy in patients with heart failure

Abstract Background Polypharmacy creates an increased patient's burden by drug-drug interactions and poor adherence. However, there are very few studies available evaluating the association of polypharmacy with hospital readmission in patients with heart failure (HF). Purpose The aim of this study was to investigate the impact of polypharmacy on hospital readmission for HF. Methods We enrolled 1253 patients who were hospitalized with acute heart failure (AHF) or acute exacerbation of chronic heart failure in the Kitakawachi Clinical Background and Outcome of Heart Failure Registry (KICKOFF Registry) from April 2015 to July 2018 (age 78.1±11.5 years, male 51.4%). Our Registry is a prospective multicenter community-based cohort study of HF patients in Japan. The inclusion criteria for the registry was a diagnosis of HF during hospitalization according to the Framingham criteria, and there were no exclusion criteria. From data at discharge, we collected data on clinical characteristics, medication schedule, and social backgrounds. We defined polypharmacy as the use of seven or more medications. The primary end point was HF rehospitalization within 1 year after discharge. Cox proportional hazards regression analysis was used to describe the association between polypharmacy and 1-year HF rehospitalization, controlling for potential confounding factors. Results In this study, the prevalence of polypharmacy was 59.7% of all patients. Patients with polypharmacy were more likely to have comorbidities such as hypertension, dyslipidemia, diabetes, chronic kidney disease, coronary artery disease and dementia. They also had lower EF (50.9±0.64 vs 53.6±0.80, p&lt;0.01), compared to patients without polypharmacy. There was no significant difference in age, gender and BMI, compared to patients without polypharmacy. During the follow-up period, a total of 278 patients (24.9%) were readmitted for HF. In Kaplan-Meier analyses, hospital readmission for HF during 1-year follow-up was significantly higher in patients with polypharmacy (p&lt;0.01) (figure). After adjusting for gender, age, EF, and the other co-morbidities, polypharmacy was independently associated with higher risk of rehospitalization for HF (hazard ratio 1.28, 95% confidence interval, 1.07–1.52, p&lt;0.01). Conclusion Polypharmacy is an independent predictor of hospital readmission for HF. Our study suggests the need for developing an effective strategy to choose the appropriate drugs in patients with HF. Acknowledgement/Funding Nakajima Steel Pipe

Early Readmission to Hospital in Patients With Cancer With Malignant Pleural Effusions: Analysis of the Nationwide Readmissions Database

Hospital readmissions are costly to health-care systems and represent a measure of quality care. Patients with cancer with malignant pleural effusions (MPEs) are at high risk for rehospitalization; however, risk factors for readmissions in this population are not well described. Understanding the incidence and risk factors for readmission could facilitate the development of a readmission reduction strategy in this patient population. We conducted a retrospective cohort study using the Nationwide Readmissions Database (NRD) (2014 sample) to determine the proportion of all-cause, unplanned, 30-day readmissions to hospital among patients with MPEs. Survey weighting methods that accounted for the NRD sampling design were used to generate nationally representative estimates. We used multivariable logistic regression to determine predictors of early readmission. There were 27,900 unplanned readmissions after 108,824 index hospitalizations for MPEs, a rate of 25.6%(95%CI, 25.0%-26.3%). The mortality rate during readmission to hospital was 17.3%(n= 4,840; 95%CI, 16.6%-18.1%). Mean cost per readmission was $15,452 ± $415, with total aggregate costs of > $400 million. Predictors of early readmission included having Medicaid insurance status, treatment with thoracentesis only, and discharge to a care facility or home health care. One in four patients with cancer and MPEs are readmitted to hospital within 30days of discharge, and nearly one in five die during the readmission. Nondefinitive management with thoracentesis led to more readmissions. A further understanding of factors that drive preventable readmissions could significantly improve quality of care in this population.

Prevalence, Reasons, and Predisposing Factors Associated with 30-day Hospital Readmissions in Poland.

There is a growing interest in quality issues associated with hospital care, with readmissions (rehospitalizations) being one of the main areas of interest. Retrospective data from a 914-bed university hospital in Bydgoszcz, Poland, was used to identify 30-day readmissions in 2015. We developed a catalogue of reasons for rehospitalization and differentiated between planned and unplanned readmissions, as well as those related and unrelated to index (initial) hospitalization. Multilevel logistic regression was used to determine factors associated with readmission risk. A total of 12.5% of patients were readmitted within 30 days of being discharged. The highest readmission rates were identified in pediatric, transplantation, and urology patients. The highest share of readmissions was due to the specific nature of a disease and its routine treatment practice. Almost two-thirds of readmission cases were classified as unplanned and related to the index hospitalization. The following characteristics were associated with a higher risk of rehospitalization: female gender, residing >35 km from the hospital, longer than average and very short stays at index admission, higher comorbidity score, and admission to a high-volume hospital sector. Due to the importance of quality issues in health policy, the topic should be further pursued to identify evidence-based practices that would improve hospitals’ performance.

High-Risk Phenotypes of Early Psychiatric Readmission in Bipolar Disorder With Comorbid Medical Illness

Individuals with co-existing serious mental illness and non-psychiatric medical illness are at high risk of acute care utilization. Mining of electronic health record data can help identify and categorize predictors of psychiatric hospital readmission in this population. This study aimed to identify modifiable predictors of psychiatric readmission among individuals with comorbid bipolar disorder and medical illness. This goal was accomplished by applying objective variable selection via machine learning techniques. This was a retrospective analysis of electronic health record data derived from 77,296 episodes of care from 2006 to 2016 within the University of California Health Care System. Data included 1,250 episodes of care involving patients with bipolar disorder and serious comorbid medical illnesses (defined by transfer between medicine and psychiatry services or concomitant primary medical and psychiatric admission diagnoses). Machine learning (classification trees) was used to identify potential predictors of 30-day psychiatric readmission across hospital encounters. Predictors included demographics, medical and psychiatric diagnoses, medication regimen, and disposition. The algorithm was internally validated using 10-fold cross-validation. The model predicted 30-day readmission with high accuracy (98% unbalanced model, 88% balanced model). Modifiable predictors of readmission were length of stay, transfers between medical and psychiatric services, discharge disposition to home, and all-cause acute health service utilization in the year before the index hospitalization. Among bipolar disorder patients with comorbid medical conditions, characteristics of the index hospitalization (e.g., duration, transfer, and disposition) emerged as more predictive than static properties of the patient (e.g., sociodemographic factors and psychiatric comorbidity burden). Findings identified phenotypes of patients at high risk for rehospitalization and suggest potential ways of modifying the risk of early readmission.