Mishra, Abhishek

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: 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”.

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.