Gender Differences in Takotsubo Cardiomyopathy as a Secondary Diagnosis: Higher Hospital Charges, More Procedures, and Longer Length of Stays

Background The incidence of Takotsubo Cardiomyopathy (TC) has risen steadily over the past decade, with current estimates of 15-30 cases per 100,000 per year. Historically, men diagnosed with TC have worse outcomes compared to women. The relationship between total hospital charges, number of procedures performed, and length of stay (LOS) between genders has not been previously reported with TC as a secondary diagnosis. Methods National Inpatient Sample (NIS) data from 2009-2015 was used to identify encounters of adult patients (≥18 years) undergoing coronary angiography that were ultimately given a secondary diagnosis of TC (International Classification of Diseases – 9 code 429.83). Demographics, comorbidities and outcomes including hospital mortality, total charges, and LOS were assessed and stratified by gender. Continuous variables were described using means and compared using independent two-sample t-tests. Total charges and LOS were described using medians and compared using Wilcoxon rank sum test. TC encounters were propensity matched by age, number of chronic conditions, number of procedures performed, and severity of illness. A discharge weight was included in all analyses to account for the complex sample design of the NIS. Results During 2009-2015, 1,448 men and 9,404 women with secondary TC were identified in the dataset, corresponding to a national estimate of 7,124 men and 46,163 women. The median hospital charges were $54,655 for men and$45,455 for women (p Conclusion Compared to women, men with a secondary diagnosis of TC are more likely to have a greater number of procedures, leading to a longer LOS and ∼$10,000 more in hospital charges. Greater awareness of TC as a potential secondary diagnosis is warranted among men

Abstract 13987: Underutilization of Oral Anticoagulant Therapy in At-Risk Patients With Atrial Fibrillation—Insights From a Multistate Healthcare System

Introduction: Oral anticoagulant (OAC) therapy significantly reduces the risk of thromboembolism among at-risk patients with atrial fibrillation (AF). Current guidelines provide strong support for an OAC in men and women with AF and CHA2DS2-VASc scores of \u3e2 and \u3e3, respectively. In spite of this, previous data has suggested that up to 40% of these patients are not treated in accordance with guideline recommendations. Hypothesis: We hypothesized that OAC therapy continues to remain significantly underutilized among at-risk patients with AF in real-world settings. Methods: We sought to evaluate the prevalence of OAC underuse and contributing factors in an ambulatory population of at-risk AF patients within a large multistate healthcare system. EHR and coding (ICD-10) data were used to identify patients with AF, calculate their CHA2DS2-VASc score, and define their current antithrombotic regimen. Demographics were assessed to allow for comparison between those receiving an OAC from those who were not. Chi square or Fisher exact tests were used to examine differences between groups. Results: Data was pulled from our EHR on 8/1/18, identifying 147,455 unique patients with AF, of which 102,728 (76.3%) had a CHA2DS2-VASc score \u3e2 (excluding female gender) (Table). Compared to those on an OAC, patients on antiplatelet therapy were more likely to have coronary artery disease, peripheral vascular disease, and prior MI (p Conclusions: In a contemporary, non-registry setting, OAC underuse remains substantial among at-risk patients with AF. Further investigation into tools that facilitate implementation of guideline-directed medical therapy is needed to limit preventable thromboembolic events in this population

Abstract 14012: Opportunities to Improve the Efficacy and Safety of Oral Anticoagulant Therapy in Atrial Fibrillation—Insights From a Multistate Healthcare System

Introduction: Vitamin K antagonists (VKAs) effectively reduce thromboembolic risk in atrial fibrillation (AF), but are limited by a narrow therapeutic window. Patients with reduced time in the therapeutic range (TTR) also face an increased risk of bleeding and ischemic events. Based in part on this, current guidelines give preference to direct-acting oral anticoagulants (DOACs) over VKAs in AF. Hypothesis: We hypothesized that DOACs are underutilized among those on oral anticoagulant therapy and that TTR remains suboptimal for large numbers of individuals on VKAs in real-world settings. Methods: We sought to evaluate a) the breakdown of OAC type and b) TTR for those on VKAs in an ambulatory population of at-risk AF patients within a large multistate healthcare system. EHR and coding (ICD-10) data were used to identify patients with AF, calculate their CHA2DS2-VASc score, and define their current antithrombotic regimen. For those on a VKA, TTR was assessed with the Rosendaal method and reported as mean values. Demographics were assessed to allow for comparison between those receiving a DOAC and a VKA, as well as, those with high (\u3e70%) vs. low ( Results: Data was pulled from our EHR on 8/1/18, identifying 147,455 unique patients with AF, of which 102,728 (76.3%) had a CHA2DS2-VASc score \u3e2 (excluding female gender). Among these at-risk patients, 61,698 (60.1%) were receiving an OAC, of which 47.8% were on a VKA and 52.2% were on a DOAC. The mean TTR was 56.3%, with 37.1%, 49.9% and 60.8% with TTRs \u3e70%, \u3e60%, and \u3e50%, respectively. Patients on a DOAC were more likely to be female and less likely to have heart failure, coronary artery disease, peripheral vascular disease, diabetes and renal disease (p70% were more likely to be male and less likely to have heart failure, diabetes, and renal disease (p Conclusions: In a contemporary, non-registry setting, VKAs continue to be used in nearly half of at-risk patients on an OAC for AF, with a suboptimal TTR in nearly two thirds. Further investigation is needed into tools that facilitate interchange from a VKA to a DOAC, particularly among those with a suboptimal TTR

Abstract 219: Use of Machine Learning Models to Identify Atherosclerotic Cardiovascular Disease Patients at Very High Risk for Future Events in a Multi-state Health Care System

Background: In the 2018 AHA/ACC Blood Cholesterol Guideline, it is recommended that ASCVD patients be classified as very high-risk (VHR) vs not-VHR (NVHR) to guide treatment decisions. This has important implications for ezetimibe and PCSK9 inhibitor eligibility. We aimed to develop a tool that could assist in more easily identifying VHR patients based on machine learning (ML) techniques. This approach offers a powerful, assumption-free alternative to conventional methods, such as logistic regression, to identify potential interactions among risk factors while incorporating the hierarchy of interaction among variables. Method: We used EHR-derived ICD-10 codes to identify patients within our health system with ASCVD. VHR was defined by ≥2 major ASCVD events (ACS ≤12 months, history of MI \u3e12 months, ischemic stroke, or symptomatic PAD) or 1 major ASCVD event and ≥2 high-risk conditions (age ≥65, diabetes, hypertension, smoking, heterozygous familial hypercholesterolemia, CKD, CHF, persistently elevated LDL-C ≥100 mg/dl, or prior CABG/PCI). Patients not meeting these criteria were classified as NVHR. We randomly assigned patients into a training set and a testing set. Classification and regression tree (CART) modeling was performed on the training set and validated on the testing set. The results were compared with a random forest model. Variables in both models included age, sex, race, ethnicity, and each of the VHR criteria above. The primary outcome for both models was VHR classification. Performance of the two models were compared using area under the curve (AUC). Result: A total of 180,669 ASCVD patients were identified in 2018: 104,123 (58%) were VHR and 76,546 (42%) were NVHR. Mean age and sex were 73.1±11.9 years, 55% male and 70.1±13.4 years, 54% male for the VHR and NVHR groups, respectively. Half the population was randomly selected as the training dataset (n=90,334) and the other half was used as the testing dataset (n=90,335). Both CART and random forest models identified recent ACS, ischemic stroke, hypertension, PAD, and history of MI as the top five predictors of VHR status. Ninety-six percent of patients with recent ACS were classified as VHR. Among patients with no recent ACS, 95% were classified as VHR if they had a stroke and hypertension. Among patients with no ACS or stroke, 89% were classified as VHR if they had PAD. Finally, among patients with no ACS, stroke or PAD, 90% were classified as VHR if they had a history of MI. The misclassification rate of the CART model on the testing set was 4.3%. The AUC for the CART and random forest models was 0.949 and 0.968, respectively. Conclusion: Both ML methods were highly predictive of VHR status among those with ASCVD. Use of this approach affords a simplified means to drive clinical decision making at the point of care

Differential Impact of Serial Measurement of Nonplatelet Thromboxane Generation on Long-Term Outcome After Cardiac Surgery.

BACKGROUND: Systemic thromboxane generation, not suppressible by standard aspirin therapy and likely arising from nonplatelet sources, increases the risk of atherothrombosis and death in patients with cardiovascular disease. In the RIGOR (Reduction in Graft Occlusion Rates) study, greater nonplatelet thromboxane generation occurred early compared with late after coronary artery bypass graft surgery, although only the latter correlated with graft failure. We hypothesize that a similar differential association exists between nonplatelet thromboxane generation and long-term clinical outcome. METHODS AND RESULTS: Five-year outcome data were analyzed for 290 RIGOR subjects taking aspirin with suppressed platelet thromboxane generation. Multivariable modeling was performed to define the relative predictive value of the urine thromboxane metabolite, 11-dehydrothromboxane B CONCLUSIONS: Long-term nonplatelet thromboxane generation after coronary artery bypass graft surgery is a novel risk factor for 5-year adverse outcome, including death. In contrast, nonplatelet thromboxane generation in the early postoperative period appears to be driven predominantly by inflammation and did not independently predict long-term clinical outcome

Clinical Characteristics of Patients Classified as Very High Risk and Not Very High Risk Based on the 2018 AHA/ACC Multi-Society Cholesterol Guideline

Background The 2018 AHA/ACC Cholesterol Guideline recommendation to classify ASCVD patients as very high-risk (VHR) vs not-VHR (NVHR) has important implications for ezetimibe and PCSK9 inhibitor eligibility. We aimed to define the clinical characteristics of these two groups within a large multi-state healthcare system in the Western U.S. Methods We performed a retrospective cohort analysis of patients defined as having ASCVD in 2018 using EHR ICD-10 codes. VHR was defined by ≥2 major ASCVD events (ACS ≤12 months, history of MI \u3e12 months, ischemic stroke, or symptomatic PAD) or 1 major ASCVD event and ≥2 high-risk conditions (age ≥65, DM, HTN, smoking, HeFH, CKD, CHF, persistently elevated LDL-C, or prior CABG/PCI). Patients not meeting these criteria were classified as NVHR. Results A total of 180,669 ASCVD patients were identified: 104,123 (58%) were VHR and 76,546 (42%) were NVHR. Mean age and gender was 70.1±13.4 years, 54% male and 73.1±11.9 years, 55% male for the NVHR and VHR groups, respectively. Among patients with a history of MI or recent ACS, 99% and 96% were classified as VHR, respectively (Table). Age ≥65, HTN and DM were the most prevalent high-risk conditions. Conclusion Criteria used to predict future CV risk largely divide ASCVD patients into groups of similar prevalence. Nearly all ACS/MI patients were VHR. With growing emphasis on individualized risk assessment and intense LDL-C reduction, opportunity exists to further refine risk prediction within these two at-risk groups