Citations

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 >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<0.001), LOS (Days: -1.14, 95% CI: -1.31 - -0.97, p<0.001), Cost of care ($: -4208, 95% CI: - 4681 - -3734, p<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: Atrial Fibrillation (AF) has been associated with various behavioral risk factors such as tobacco, alcohol, and/or substance abuse. Hypothesis: The main objective is to describe the national trends and burden of tobacco and substance abuse in AF hospitalizations. Methods: The National Inpatient Sample database from 2007 to 2015 was utilized and the hospitalizations with AF were identified using the international classification of disease, Ninth Revision, Clinical Modification (ICD-9-CM) code 427.31 in the primary diagnosis column. They were stratified into without abuse, tobacco use disorder (TUD), substance use disorder (SUD), alcohol use disorder (AUD), and drug use disorder (DUD). We used the Jonckheere-Terpstra trend test to analyze the trend in this study. Results: Out of 3,631,507 AF hospitalizations, 852,110 (23.46%) had TUD, 1851,170 (5.1%) had SUD, 155,681 (4.29%) had AUD and 42,667 (1.17%) had DUD. The trends of all increased substantially during the study period (Figure) . The prevalence of TUD, SUD, AUD, and DUD was substantially increased across all age groups, races, and gender during the study period. Female sex was associated with lower odds TUD (0.57 (0.56-0.57), P-value <0.001), SUD (0.27 (0.26-0.27), P-value <0.001), AUD (0.22 (0.22-0.22), P-value <0.001), and DUD (0.51 (0.5-0.52), P-value <0.001). Among AF hospitalizations, the black race was associated with higher odds of SUD (1.12 (1.1-1.14), P-value <0.001), and DUD(1.42 (1.38-1.47), P-value <0.001). The younger age group (18-35 years), male, Medicare/Medicaid as primary insurance, and lower socioeconomic status were associated with increased risk of both TUD and SUDs. Conclusions: Tobacco and substance use disorder among hospitalized AF patients in the US mainly affects males, younger individuals, white more than black, and those of lower socioeconomic status which demands the development of preventive strategies to address multilevel influences.

Background Reducing readmission after catheter ablation ( CA ) in atrial fibrillation (AF) is important. Methods and Results We utilized National Readmission Data ( NRD ) 2010–2014. AF was identified by International Classification of Diseases, Ninth Edition, Clinical Modification (ICD‐9‐CM) diagnostic code 427.31 in the primary field, while first CA of AF was identified via ICD‐9 ‐procedure code 37.34. Any admission within 30 or 90 days of index admission was considered a readmission. Cox proportional hazard regression was used to adjust for confounders. The primary outcomes were 30‐ and 90‐day readmissions and the secondary outcome was AF recurrence. In total, 1 128 372 patients with AF were identified from January 1, 2010 to September 30, 2014. Of which 37 360 (3.3%) underwent CA . Patients aged ≥65 years and female sex were less likely to receive CA for AF . Overall, 10.9% and 16.5% of CA patients were readmitted within 30 and 90 days post‐CA, respectively. Most common causes of readmissions were arrhythmia ( AF , atrial flutter), heart failure, pulmonary causes (pneumonia, chronic obstructive pulmonary disease) and bleeding complications (gastrointestinal bleed, intracranial hemorrhage). Patients with diabetes mellitus, heart failure, coronary artery disease ( CAD ), chronic pulmonary and kidney disease, prior stroke/transient ischemic attack (TIA), female sex, length of stay ≥2 and disposition to the facility were prone to higher 30‐ and 90‐day readmissions post ‐CA . Predictors of increase in AF recurrence post‐ CA were female sex, diabetes mellitus, chronic pulmonary disease, and length of stay ≥2. Trends of 90‐day readmission and AF recurrence were found to improve over the study period. Conclusions We identified several demographic and clinical factors associated with the use of CA in AF , and short‐term outcomes of the same, which could potentially help in the patient selection and improve outcomes.

AbstractBackgroundCatheter ablation is widely accepted intervention for atrial fibrillation (AF) refractory to antiarrhythmic drugs, but limited data are available regarding contemporary trends in major complications and in‐hospital mortality due to the procedure. This study was aimed at exploring the temporal trends of in‐hospital mortality, major complications, and impact of hospital volume on frequency of AF ablation–related outcomes.MethodsThe Nationwide Inpatient Sample database was utilized to identify the AF patients treated with catheter ablation. In‐hospital death and common complications including vascular access complications, cardiac perforation and/or tamponade, pneumothorax, stroke, and transient ischemic attack, were identified using International Classification of Disease (ICD‐9‐CM) codes.ResultIn‐hospital mortality rate of 0.15% and overall complication rate of 5.46% were noted among AF ablation recipients (n = 50,969). Significant increase in complications during study period (relative increase 56.37%, P‐trend < 0.001) was observed. Cardiac (2.65%), vascular (1.33%), and neurological (1.05%) complications were most common. On multivariate analysis (odds ratio [OR]; 95% confidence interval [95% CI]; P value), significant predictors of complications were female sex (OR = 1.40; CI = 1.17–1.68; P value < 0.001), high burden of comorbidity as indicated by Charlson Comorbidity Index ≥2 (OR = 2.84; CI = 2.29–3.52; P value < 0.001), and low hospital volume (< 50 procedures).ConclusionOur study noted a decline in AF ablation–related hospitalizations and complications associated with the procedure. These findings largely reflect shifting trends of outpatient performance of the procedure and increasing safety profile due to improved institutional expertise and catheter techniques.

AbstractBackgroundUnderstanding the factors associated with early readmissions following atrial flutter (AFL) ablation is critical to reduce the cost and improving the quality of life in AFL patients.MethodThe study cohort was derived from the national readmission database 2013–2014. International Classification of Diseases, 9th Revision (ICD‐9‐CM) diagnosis code 427.32 and procedure code 37.34 were used to identify AFL and catheter ablation, respectively. The primary and secondary outcomes were 90‐day readmission and complications including in‐hospital mortality. Cox proportional regression and hierarchical logistic regression were used to generate the predictors of primary and secondary outcomes respectively. Readmission causes were identified by ICD‐9‐CM code in primary diagnosis field of readmissions.ResultReadmission rate of 18.19% (n = 1,010 with 1,396 readmissions) was noted among AFL patients (n = 5552). Common etiologies for readmission were heart failure (12.23%), atrial fibrillation (11.13%), atrial flutter (8.93%), respiratory complications (9.42%), infections (7.4%), bleeding (7.39%, including GI bleed–4.09% and intracranial bleed–0.79%) and stroke/TIA (1.89%). Multivariate predictors of 90‐day readmission (hazard ratio, 95% confidence interval, P value) were preexisting heart failure (1.30, 1.13–1.49, P < 0.001), chronic pulmonary disease (1.37, 1.18–1.58, P < 0.001), anemia (1.23, 1.02–1.49, P = 0.035), malignancy (1.87, 1.40–2.49, P < 0.001), weekend admission compared to weekday admission (1.23, 1.02–1.47, P = 0.029), and length of stay (LOS) ≥5 days (1.39, 1.16–1.65, P < 0.001). Note that 50% of readmissions happened within 30 days of discharge.ConclusionCardiac etiologies remain the most common reason for the readmission after AFL ablation. Identifying high risk patients, careful discharge planning, and close follow‐up postdischarge can potentially reduce readmission rates in AFL ablation patients.