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Background: There is sparse comparative data on short-term readmissions following Transcatheter aortic valve replacement (TAVR) and surgical aortic valve replacement (SAVR). Methods: The study cohort was derived from the National Readmission Data (NRD) 2013, a subset of the Healthcare Cost and Utilization Project (HCUP) sponsored by AHRQ. TAVR and SAVR were identified using appropriate ICD-9-CM codes (TAVR - 35.05, 35.06 & SAVR - 35.21, 35.22) as either primary or secondary procedural codes. Variables which could affect treatment assignment, were adjusted with propensity score match analysis and Match (1:1) cohort was generated. Readmission causes were identified by ICD 9 code in primary diagnosis. Results: Our analysis included 3,886 TAVR and SAVR procedures each in the propensity matched cohorts. There was no significant difference in terms of readmission rates amongst patients who underwent TAVR vs. SAVR [21.41% vs. 21.07% (OR: 1.02, 95% CI: 0.92 - 1.14) p = 0.702]. Cardiac etiologies were more likely to be responsible for readmissions following SAVR (42.66% vs. 35.91%, p = 0.006). Atrial fibrillation (AF) was a much more common cause of readmission following SAVR (7.81% vs. 3.37%, p <0.001). Overall vascular (3.24% vs. 1.32%, p = 0.006) and bleeding complications (9% vs. 6.2%, p = 0.025) were more likely to result in readmission in patients undergoing TAVR. Cost of care of index admission and readmission was similar in both groups. Readmission mortality was higher amongst patient with TAVR vs. SAVR (6.49 vs. 3.91, p = 0.02). 50% of TAVR and SAVR readmission occur within 11 days post discharge. Conclusion: In our study from a large nationwide database, there was no significant difference in readmission rate, median readmission rate and resource utilization between TAVR and SAVR. Arrhythmias especially AF accounted for more SAVR readmission and Bleeding/vascular complications were more commonly responsible for readmissions following TAVR.

Introduction: Takotsubo cardiomyopathy (TTC) is diagnosed in 1-2% of the patients presenting with troponin positive suspected acute coronary syndromes(ACS). Rising trends of adverse events in patients with TTC, makes it imperative to explore causes and predictors of readmission in this patient population. Methods: National Readmission Data (NRD) 2013-14 was utilized to select study cohort. International Classification of Diseases, 9th Revision (ICD-9-CM) diagnostic code 429.83 was used to identify takotsubo cardiomyopathy. Admissions within 90 day of index admission were considered as early readmissions. Readmission etiologies were identified by ICD-9-CM code in primary diagnosis field of readmissions. Hierarchical multivariate models were used to evaluate predictors of early readmission. Results: A total of 12255 patients were identified during study period out of which 23.92% (n=2932 with 4224 readmissions) patients were readmitted within 90 days of discharge following index admission. Most common etiologies for readmission were cardiac (18.56%), respiratory (17.20%), GI renal (9.10%), infections (13.12%) and neurological complications (5.88%). Among cardiac complications acute heart failure was the most common etiology (7.48%). Highest number of readmissions happened on first day after discharge (n=125) and within 33 days after discharge, >50% of readmissions took place (n=2136). Conclusions: Patients with TTC are highly likely to be readmitted with first month after discharge, most likely secondary to cardiac or respiratory complications. These findings warrant close post discharge transition to reduce morbidity and improve health care outcomes.

Introduction: Catheter ablation is widely accepted intervention for atrial fibrillation (AF), but data is limited on contemporary trends in major complications and mortality due to the procedure. Methods: HCUP’s Nationwide inpatient sample (NIS) database was utilized from 2011-14 to identify the AF patients treated with Catheter Ablation using ICD-9- CM codes. χ 2 test was utilized to compare categorical variables, the student’s t-test for continuous variables and hierarchical mixed-effects logistic regression models for multivariate predictors of post-procedural complications. Results: In total 50,969 patients were identified undergoing AF ablation during the study period (37.6% female, 51.4 age ≥ 65). Overall complication rate was 5.5% with relative increase over study period (+56.4%, p < 0.001). In subgroup analysis of complication trends significant relative increase seen in respiratory (+352.7%, p < 0.001), neurological (+43.9%, p = 0.003) and vascular (+38.7%, p = 0.003) complications. While cardiac complications (+9.1%, p = 0.323) and In-hospital mortality (+ 60%, p = 0.173) showed insignificant change. On multivariate analysis of mortality and complication significant increased risk was associated with female gender (OR, 95% CI, p-value) (1.40, 1.17-1.68, p < 0.001), as well as higher comorbidity burden (CCI ≥ 1). While higher hospital volume (≥ 50 procedures) was associated with significantly decreased complication rates. Conclusions: Patients undergoing AF ablation showed an insignificant change in mortality, with increase trends of complication. Which was likely related to higher comorbidity burden over study period.

Introduction: Heart failure with preserved ejection fraction(HFpEF) is a syndromemwith limited treatment modalities. Our control over 30 day readmissions and readmission outcomes is limited. Methods: HCUP’s Nationwide Readmissions Database (NRD) from 2013-14 was used for HFpEF related hospitalizations using ICD-9- CM diagnostic code:428.3x in primary diagnosis field. 30-day readmissions were identified and classified into two groups: same-hospital readmissions and different-hospital readmissions. A comparative analysis was conducted focused on three metrics - mortality, length of stay (LOS) and cost of hospitalization. We used hierarchical two-level modeling and propensity score matching to adjust for confounders. Results: Of the 94,988 readmitted patients (age &gt;65 years: 79%, Females: 61.45%) - 76,665 (80.70%) to the same hospital and rest to different hospitals. After adjusting extensive list of confounders, same hospital readmission was associated with better outcomes including in hospital mortality (OR: 0.73, 95% CI: 0.66 - 0.80, p&lt;0.001), LOS (Days: -1.14, 95% CI: -1.31 - -0.97, p&lt;0.001), Cost of care ($: -4208, 95% CI: - 4681 - -3734, p&lt;0.001). For validation of our results, we ran propensity score matching, showed similar results - in hospital mortality (6.23% vs 8.07%), LOS (6.30 ± 0.08 vs 7.47 ± 0.095), Cost of care (14042.7 ± 215.7 vs 18685.4 ± 279.2). Post hoc high-risk subgroup analysis were conducted and showed similar results (Figure). Number needed to treat (for mortality) was 74 patients. Up to ~ 100 million dollars could have been saved over 2 years. Conclusions: Considering scale of problem and limited option to prevent worse outcomes, Simple interventions such as redirecting patient to same hospital as previous admission would be beneficial.

Introduction: Role of therapeutic hypothermia in out of hospital cardiac arrest is well studied but data is sparse for in-hospital cardiac arrest (IHCA). Methods: Nationwide Inpatient Sample (NIS) database from 2011-2014 was utilized to identify ICHA using the ICD-9-CM procedural codes 99.60(CPR) and 99.63(closed cardiac massage) in any procedural fields. Therapeutic hypothermia was identified by 99.81 in any procedural field. Patient with age<18 years and missing information on age, gender and mortality was removed. Primary outcome was hospitalization survival. We used Greedy’s algorithm for propensity score match (1:20) to adjust for extensive list of clinically important confounders. We used simple logistic regression to generate odds ratio on matched cohort. Results: 86,593 patients (Age>65 years: 58.48%, female: 44.12%) with In hospital cardiac arrest was identified,of which 1777 (2.05 %) received therapeutic hypothermia. Overall survival was 30%- with or without hypothermia. After propensity score matching (1:20) we identified 1537 matched pairs (32,277 patients) without any statically significant difference in baseline characteristics between two groups. C- index for the model was 0.714. Worse survival was observed in patients with hypothermia in matched cohort [Survival: (31.82% without hypothermia vs. 28.1% with hypothermia with p-value- 0.002) (OR:0.84, 95% CI:0.75-0.94, p-0.002)]. About a quarter of in-hospital cardiac arrest were Vfib/Vtach arrest and Subgroup propensity score match analysis in Vfib/Vtach arrest showed better survival without hypothermia, similar results were observed in PEA/asystole cardiac arrest. Conclusion: Worst survival was observed with hypothermia in hospital cardiac arrest patients. Risk of hypothermia complications outweighs the benefit of preserving brain in patients who received almost immediate resuscitation. Future clinical trials and prospective studies will be needed to concur our results.

Introduction: Risk stratification of the pregnant population is critical to improving outcomes associated with pregnancy-related Acute myocardial infarction (AMI). Methods: Pregnancy-related hospitalizations (antepartum as well as postpartum) and AMI were identified using appropriate International classification of disease-Ninth revision (ICD-9) codes from nationwide inpatient sample database (2005-2014). Simple logistic regression was used to calculate predictors of AMI during pregnancy. Results: We identified 3,786 cases of AMI from a total of 43,437,621 pregnancy related hospitalization during study period. Compared to pregnant women <20-year, we noted more than 10-fold risk of AMI among patients ≥ 40 years (OR 10.1, 95% CI 5.3-19.0, p<0.001). Other significant predictors of AMI during pregnancy were black race compared to white ( OR 1.6, 95% CI 1.3-1.9, p<0.001), co-existing comorbidities such as hypertension (OR 1.9, 95% CI 1.5-2.5, p<0.001),, thrombophilia (OR 4.8, 95% CI 2.7-8.5, p<0.001), diabetes milletus (OR 1.4, 95% CI 1.0-1.9, p<0.027),hyperlipidemia (OR 13.2, 95% CI 9.9-17.6, p<0.001),smoking (OR 3.3, 95% CI 2.3-4.6, p<0.001), substance abuse (OR 1.7, 95% CI 1.2-2.6, p=0.007), congestive heart failure (OR 26.0, 95% CI 20.3-33.2 p<0.001), deep venous thrombosis (OR 2.8, 95% CI 1.3-6.2, p=0.010) as well as obstetric condition including postpartum hemorrhage (OR 1.8, 95% CI 1.3-2.4, p<0.001),, transfusion during pregnancy (OR 3.2, 95% CI 2.4-4.2, p<0.001), postpartum infection (OR 2,7, 95% CI 1.9-3.9, p<0.001),, fluid and electrolyte imbalance (OR 5.2, 95% CI 4.2- 6.6, p<0.001), and postpartum depression (OR 1.4, 95% CI 1.1-1.9 p=0.013). Conclusions: We identified certain patient-level characteristics which correlated to high risk of AMI. This information can be utilized to decide resource allocation and the introduction of early multidisciplinary intervention among high-risk population

Introduction: Acute myocardial infarction (AMI) during pregnancy is a rare but fatal complication. Recent trends in incidence of pregnancy-related AMI and associated outcomes are unclear. Methods: Nationwide inpatient sample (NIS) database was utilized for years 2005-2014. International classification of disease-Ninth revision (ICD-9) was used to identify pregnancy-related (antepartum as well as postpartum) admissions and acute myocardial infarction (AMI). The primary outcome was incidence and trend of AMI related to pregnancy during the study period. Secondary outcomes were trends in mortality and resource utilization. P-values for trends were generated by Cochrane-Armitage test for categorical variables and simple linear regression for continuous variables. Results: We identified a total of 43,437,621 pregnancy-related hospitalization and 3,786 cases of AMI (86% antepartum and 14% post-partum) were noted during the study period. The incidence of AMI during the study period was 8.7 per 100,000 pregnancies with an overall increase in incidence during study period (relative increase of 18.9%, p <0.001) and concomitant decrease in mortality (relative decrease of 40.05%, p <0.001), cost of care (relative decrease of 8.70%, p<0.001) and length of stay (relative decrease of 13.53%, p<0.001). Conclusions: Incidence of AMI during the period is on the rise in recent years with concomitant improvement in mortality and resource utilization. This reflects improved diagnostic capability and a better understanding of non-atherosclerotic mechanisms of AMI during pregnancy such as spontaneous coronary artery dissection, coronary spasm, and coronary thrombus.

Introduction: Recent trials have suggested potential benefits of performing multivessel percutaneous coronary intervention (MVPCI) on non-infarct related artery (non-IRA) in ST-segment elevation myocardial infarction (STEMI) patients with multivessel disease. Methods: National Readmissions Database (NRD) 2010-14 was utilized to select study cohort. Appropriate International Classification of Diseases, 9th Revision (ICD-9-CM) diagnostic and procedural codes were utilized to identify STEMI patients undergoing multivessel PCI and infarct-related artery only PCI (IRA-PCI). Propensity score matched cohorts using greedy matching algorithm were generated for comparison of outcomes. Results: We identified 116592 IRA-PCI (83.97%) and 22257 MVPCI (16.03%) cases. With 1:3 propensity matched cohorts accounting for confounders such as age, gender, race and comorbidities, in comparison to IRA-PCI, MVPCI patients have higher 30-day readmission rate (10.40% vs 9.40%, p=0.001), in-hospital mortality (1.96% vs 1.57%,p<0.001), mechanical circulatory support utilization (4.27 vs 2.44%,p<0.001) as well as higher complication including vascular (0.51% vs 0.28%, p<0.001), cardiac (5.97% vs 3.97%, p<0.001), respiratory (4.89% vs 4.02%,p<0.001), neurologic complications (0.77% vs 0.58%,p=0.003), major bleeding (1.01% vs 0.79%, p=0.002) and cardiac arrest(3.48% vs 3.17%, p=0.027). We also noted higher cost of care ($27100 vs $20900, p<0.001) and length of stay (3.8 days vs 3.4 days, p<0.001) in MVPCI group compared to IRA-PCI group. Conclusions: We noted higher 30- day readmission rate, in-hospital mortality, complications and resource utilization with MVPCI compared to IRA-PCI approach among STEMI patients which further demands large-scale randomized control trials to determine the utility of MVPCI in the “real world”.

AbstractBackgroundThe improved life expectancy observed in patients living with human immunodeficiency virus (HIV) infection has made age‐related cardiovascular complications, including arrhythmias, a growing health concern.HypothesisWe describe the temporal trends in frequency of various arrhythmias and assess impact of arrhythmias on hospitalized HIV patients using the Nationwide Inpatient Sample (NIS).MethodsData on HIV‐related hospitalizations from 2005 to 2014 were obtained from the NIS database using International Classification of Diseases, 9th Revision (ICD‐9) codes. Data was further subclassified into hospitalizations with associated arrhythmias and those without. Baseline demographics and comorbidities were determined. Outcomes including in‐hospital mortality, cost of care, and length of stay were extracted. SAS 9.4 (SAS Institute Inc., Cary, NC) was utilized for analysis. A multivariable analysis was performed to identify predictors of arrhythmias among hospitalized HIV patients.ResultsAmong 2 370 751 HIV‐related hospitalizations identified, the overall frequency of any arrhythmia was 3.01%. Atrial fibrillation (AF) was the most frequent arrhythmia (2110 per 100 000). The overall frequency of arrhythmias increased over time by 108%, primarily due to a 132% increase in AF. Arrhythmias are more frequent among older males, lowest income quartile, and nonelective admissions. Patients with arrhythmias had a higher in‐hospital mortality rate (9.6%). In‐hospital mortality among patients with arrhythmias decreased over time by 43.8%. The cost of care and length of stay associated with arrhythmia‐related hospitalizations were mostly unchanged.ConclusionsArrhythmias are associated with significant morbidity and mortality in hospitalized HIV patients. AF is the most frequent arrhythmia in hospitalized HIV patients.

AbstractAims The Food and Drug Administration (FDA) approval of the Watchman device [percutaneous left atrial appendage occlusion (LAAO)] has resulted in the widespread use of this procedure in many centres across the USA. We sought to estimate the nationwide utilization and frequency of adverse outcomes associated with Watchman device implantation. The objective of this study was to evaluate the Watchman device implantation peri-procedural complications and comparison of the results with the previous studies.Methods and results The National Inpatient Sample (NIS) was queried for all hospitalizations with a primary diagnosis of atrial fibrillation or atrial flutter during the year 2016 with percutaneous LAAO during the same admission (ICD-10 code—02L73DK). The frequency of peri-procedural complications, including mortality, procedure-related stroke, major bleeding requiring blood transfusion, and pericardial effusion, was assessed. We compared the complication rates with the published randomized controlled trials and the European Watchman registry. An estimated 5175 LAAO procedures were performed in 2016. The majority of procedures was performed in males (59.1%), age ≥75 years (58.7%), and White (83.1%). The overall complication rate was 1.9%. The in-hospital mortality was 0.29%. Pericardial effusion requiring pericardiocentesis was the most frequent complication (0.68%). Bleeding requiring transfusion was noted in 0.1% of device implants. The rates of post-procedure stroke and systemic embolism were 0% and 0.29%, respectively.Conclusion Percutaneous LAAO with the Watchman device in the USA is associated with low in-hospital complications and a similar safety profile to a recently published EWOLUTION cohort. The complication rates were lower than those reported in the major randomized clinical trials (RCTs). We report the frequency of peri-procedural complications of the LAAO using the Watchman device from the NIS database. We also compare the frequency of peri-procedural complications with the previously published RCTs and EWOLUTION cohort. Our findings are in concordance with findings from EWOLUTION cohort and compare favourably with RCTs.