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Objective: Machine learning (ML) may enhance prediction of outcomes such as mortality or acute kidney injury (AKI) among cardiac patients after coronary artery bypass graft (CABG). In this study, we used meta-analyses of reported ML models to assess what ML has been able to accomplish in this field, by evaluating the model performance in studies with CABG patients. Methods: We performed a literature search using Google Scholar and included studies that reported AUC and 95% CI for various models in our analysis. In addition, total participants, year of publication, type of analytical method (gradient boosting, random forest, etc.) and type of outcome (mortality or AKI) were extracted. We combined effect sizes using random effects model, and tested for heterogeneity, and publication bias. Results: 5 models from 5 studies were included in the analysis (patients= 35,152; with outcome mortality =3,080, AKI=933). Combined mean AUC was 0.796 (95% CI: 0.776, 0.815). Test of heterogeneity showed high variation between studies (I 2 = 66.7%). Egger’s test intercept was -1.03 (95% CI: -7.22, 5.17, p > .25) indicating no small study bias. Meta regression showed newer publications had a positive association ( coef = 0.003) and number of variables in the study had a negative association with higher AUC values ( coef = -0.0002). In subgroup analysis, the pooled AUC values for mortality and AKI groups were 0.795 and 0.805 respectively. The highest individual AUC was from ensemble model predicting AKI with AUC 0.84 and lowest was from gradient boosting model predicting mortality with AUC 0.77. Conclusion: Among the presented models for CABG ensemble methods performed well, but surprisingly methods with lesser number of variables tended to have higher predictive power. In near future, ML-based models may form the basis to build intelligent decision support systems for patient selection and risk stratification prior to CABG and could be applied to other cardiac surgeries.

Developing and implementing analytical models for predicting mortality or readmission related outcomes among heart failure (HF) patients are challenging. In this study, we used meta-analyses of reported predictive models to assess what machine learning (ML) has been able to accomplish in this field, by evaluating the ML model performance for studies in HF. We performed a literature search using Google Scholar, Web of Science and PubMed. The studies reporting AUC and 95% CI for various models were included. In addition, total participants, year of publication, type of analytical method (logistic regression, RF, etc.) and type of outcome (mortality, readmission, etc.) were extracted. We combined effect sizes using random effects (RF) model, and tested for heterogeneity, and publication bias. 12 studies were included in the analysis (patients= 123,832; AUC=15, with outcome mortality =17,471, readmission=15,703, hospitalization=67,523). Combined mean AUC was 0.77 (95% CI: 0.72, 0.82). Test of heterogeneity showed high variation between studies (I2=98.9%). Egger’s test intercept was 5.2 (95% CI: -4.2, 14.7, p > .25) indicating no small study effects/bias. Meta regression showed newer publications provide better AUC values (p < 0.03). In subgroup analysis, the pooled AUC for readmission, hospitalization, and mortality groups were 0.71, 0.80, and 0.78 respectively. The highest individual AUC was from neural networks (NN) predicting hospitalization with AUC 0.96 and lowest was from RF predicting readmission with AUC 0.65. Presented models were diverse, ranking in quality from fair to very good, and being varied for different clinical outcomes among HF patients. Situation known from studies using classical statistical methods holds also for methods using ML, with better predictive values for hospitalizations, and lower for other outcomes. Methods using NN and methods using higher numbers of variables performed very well and had highest predictive power.

Objective: Identifying patients at high risk of AE after TAVR is essential to prolong their survival. Current prediction models for AE after TAVR suffer from a lack of accuracy and external validation. Modern ML approaches can account for higher-dimensional relationships among variables, potentially improving the prediction of outcomes. We performed a systematic review and meta-analysis to estimate the discriminative ability of recently developed ML-based models, which predict various AE after TAVR. Methods: We searched Pubmed, Google Scholar, and Web of Science for studies (Jan 2019 to Jan 2022) that used ML approaches to predict AE after TAVR. Inputs in the meta-analysis were study-reported c-index values and 95% CI. Subgroup analyses separated models by outcome (mortality or clinical AE). Combined effect sizes using a random-effects model, test for heterogeneity, and Egger’s test to assess publication bias were considered. Results: Eight studies were included in the systematic review (patients = 26,023; outcomes = 1,014), of which five models had sufficient data for the meta-analysis. The number of features included in each model ranged from 6 to 107. The two most common models were random forest (n=2) and logistic regression (n=2). The most common outcome was mortality (n=5). The meta-analysis showed that models predicting mortality performed better (0.90; 95% CI: 0.81, 1.01) than models predicting clinical AE (0.80; 95% CI: 0.79, 0.95). The combined mean c-index was 0.87 (95% CI: 0.79-0.95). Test of heterogeneity showed high variation among studies ( I 2 =98.5%). Egger’s test did not indicate publication bias ( β = 1.48; 95% CI: –18.14, 21.09, p = 0.848). Conclusion: Although relatively few studies have applied ML for predicting AE after TAVR, the results are very promising. The time of complex sophisticated models has arrived with improved predictive accuracy through advanced ML methods able to help identify patients who are at risk for clinical AE early in their care.

OBJECTIVE The objective of this study was to understand recent trends in direct health care expenditures among cancer survivors using novel cost-estimation methods and a nationally representative database. MATERIALS AND METHODS This study was a retrospective analysis of 193,003 adults, ≥18 years of age, using the Medical Expenditure Panel Survey during the years 2009-2016. Manning and Mullahy two-part model was used to calculate adjusted mean and incremental medical expenditures after adjusting for covariates. RESULTS The mean direct annual health care expenditure among cancer survivors ($13,025.0 [$12,572.0 to $13,478.0]) was nearly 3 times greater than noncancer participants ($4689.3 [$4589.2 to $4789.3]) and were mainly spent on inpatient services, office-based visits, and prescription medications. Cancer survivors had an additional health care expenditure of $4407.6 ($3877.6, $4937.6) per person per year, compared with noncancer participants after adjusting for covariates (P

Background: The prevalence of obesity among people of reproductive age has steadily increased. The rates of both maternal/parental and fetal adverse outcomes increased significantly with higher BMI. In this study, we examined the national estimates of adverse maternal/parental and fetal outcomes among pregnant individuals with pre-pregnancy obesity using a nationally representative database. Methods: This was a retrospective observational analysis of data retrieved from the Nationwide Inpatient Sample database (2010-2014). The primary outcomes of this study were various adverse maternal/parental and fetal outcomes. Delivery related hospitalizations and all outcomes were identified using the ICD-9 codes. Additionally, propensity-score matching analysis was conducted. Results: There were a total of 18,687,217 delivery-related hospitalizations, of which 1,048,323 were among people with obesity. The mean age of pregnant persons with obesity was 28.5 years while among those without obesity was 28.0 years. Between both groups, most pregnant persons were White, followed by Hispanic and Black. Pregnant persons with obesity were more likely to have labor inductions (AOR: 1.51; 95% CI: 1.42, 1.60), cesarean deliveries (1.70; 1.62, 1.79), and greater length of stay after both cesarean deliveries (1.14; 1.08, 1.36) and vaginal deliveries (1.48; 1.23, 1.77). They were also more likely to have risk factors for adverse obstetrical outcomes such as gestational hypertension (2.17; 2.06, 2.29), preeclampsia (2.06; 1.42, 2.99), gestational diabetes (2.75; 2.60, 2.90), premature rupture of membranes (1.17; 1.08, 1.27), chorioamnionitis (1.39; 1.25, 1.55), and venous thromboembolism (1.63; 1.34, 1.99). Additionally, pregnant persons with obesity were more likely to have adverse fetal outcomes such as excessive fetal growth (3.18; 2.96, 3.43) and fetal distress (1.28; 1.21, 1.35). Conclusion: Pregnant persons with obesity had significantly greater risk for adverse obstetrical outcomes. Risk stratification of pregnant individuals based on obesity can inform obstetrical providers’ clinical decision-making and potentially improve patient outcomes and decrease costs. There is an opportunity to address these risks with pre-conception interventions. Future studies could examine the effect of pre-conception interventions such as counseling on pre-pregnancy weight management, lifestyle modifications addressing nutrition and activity, and pre-pregnancy bariatric surgery.

Introduction: Prior research has shown that hospital outcomes such as mortality among COVID-19 patients receiving methylprednisolone and dexamethasone differed despite having similar anti-inflammatory effect. In this study, we compared mortality rate among three groups (usual care with no steroids [NS], methylprednisolone [MP], or dexamethasone [DE]) of COVID-19 patients. Methods: Data was collected retrospectively from a large healthcare system in the South Florida region. All eligible COVID-19 patients from April 1 to Dec 31, 2020 were included in this study. Propensity scores (PS) was utilized to match patients on their demographics and acuity scores (Age Group, Ethnicity, Gender, APR risk of mortality, and APR severity of illness, etc.). All-cause mortality was compared among the three groups after accounting for demographics, length of stay (hospital and ICU), days on MP or DE, ventilator status, days on ventilator, other medication history (HCQ, Tocilizumab, etc.), pO2, and lab values (hCRP, Ferritin, Glucose, etc.). Multivariate Logistic regression and Survival analysis was utilized for the analysis. Results: There were a total of 2445 eligible COVID-19 cases. After PS matching, 292 cases in each group (n = 876) were included in the analysis. There were 42% females and the majority of participants were White Hispanic (81%). The average age (SD) of the PS matched cohort was 64 (17.1) years, and there was a significant difference between LOS among the three groups with MP being the highest (Mean: 12.4; SD: 12.1). All-cause mortalities in the NS, MP, and DE groups were about 6%, 19% and 7% (p < 0.0001) respectively. Logistic regression showed that the odds of mortality among NS (AOR: 1.9, 95% CI: 0.10, 41.8) group were higher, and DE (AOR: 0.15, 95% CI: 0.04, 0.57) group were significantly lower than MP group respectively. Similar results were observed in the survival analysis after accounting for total hospital length of stay. The adjusted hazard ratios suggest that patients who were in the DE group had lower mortality as compared to MP group but, the effect was not significant (HR: 0.70, p < 0.18). In a subgroup survival analysis among patients who were ventilated (n = 69) in the matched cohort, mortality was higher in DE group compared to MP group however the effect was not significant (HR: 1.8, 95% CI: 0.82, 4.0). Conclusions: Among hospitalized COVID-19 cases, preliminary results show that patients who received DE had lower mortality as compared to those who received MP. Among COVID-19 patients who require mechanical ventilation, sufficiently dosed MP may lead to a decreased mortality as compared to DE. However more in depth analysis with higher number of patients and better characterization of variables such as dosage of the drugs, are needed to confirm these findings.

Objective: There are several challenges in implementing models for predicting stroke or stroke related outcomes. Most of these models have average concordance, and several of the important variables cannot be modified. In this study, we updated and performed a meta-analysis of commonly utilized models to predict stroke related outcomes. Our primary aim was to evaluate the discriminative ability of the concordance statistic by adding additional studies. Methods: Studies reporting c-index and SE (or 95% CI) for predicting stroke or related outcomes were included in our analysis. In addition to the c-index, total participants, year of publication, type of analytical method (survival, logistic regression, neural network, etc.) and type of outcome (predicting stroke or composite outcome) were utilized. Combined effect sizes with the random model, test for heterogeneity, and publication bias were considered. Egger’s test was used to assess funnel asymmetry. Results: Twenty-seven models were included (patients= 1762461; c-index=14, Harrell’s c-index= 13; only stroke =21, composite=6) in the analysis. Combined mean c-index was 0.76 (95% CI: 0.71, 0.81; 95% predictive interval: 0.59, 0.93). Combined mean Harrell’s c-index was 0.65 (95% CI: 0.61, 0.69; 95% predictive interval: 0.56, 0.74). Test of heterogeneity showed high variation between studies reporting c-index and Harrell’s c-index (I2=97.49% and 80.0% respectively). Egger’s test intercept was -2.1 (95% CI: -7.2, 3.0, P > .40) for c-statistic and 1.2 (95% CI: -1.2, 3.5, P > .32) for Harrell’s c-index studies. Conclusion: Current studies have not improved the prediction interval significantly as compared to our previous meta-analysis for predictive or explanatory model available for stroke risk. However, recent studies were found to be more inclusive of non-traditional biomarkers (e.g., genetic, or polygenic scores) and utilized various machine learning methods that were not used before.

Background: Acute ischemic stroke (AIS) patients show a good prognosis with Carotid endarterectomy (CEA). However, lowering short-term readmissions after CEA for AIS cases remains a significant challenge. Several machine learning (ML) models predicting readmissions fail to explain the predictors. Hence the utility of such ML models in clinical settings is limited. This study used interpretable machine learning (ML) methods to identify the predictors associated with 30-day readmission. Methods: We utilized the National Surgical Quality Improvement Program registry (2014-2017) for this study. Patients aged >18 years and who underwent CEA for AIS were included. ICD-9, ICD-10, and CPT codes were used to identify AIS and CEA cases. Decision Trees and Random Forest classification techniques were utilized to identify predictors of 30-day readmission. Results: A total of 22,373 AIS patients underwent CEA during the study period. The mean (SD) age of the patients was 70.7 (9.4) years, and the majority (61%) were males. About 80% were Non-Hispanic White, followed by non-Hispanic Black (4.6%). About 7% of AIS patients who underwent CEA had 30-day readmission. Random Forest classification and Decision Tree were able to provide clinically relevant predictors and cut-off values. For example, one of the top predictors was pre-operative Hematocrit, and its cut-off value of ≤33% with Diabetes showed a higher risk for readmission. Conclusion: Our study showed that interpretable ML models could be helpful for clinicians to stratify patients based on their pre-operative risk for a 30-day readmission and could help optimize management strategies for improving patient outcomes. Incorporating these cut-off values in EMR could help clinical decision-making and plan interventions to reduce readmissions by managing risk factors. This would improve the quality of care and save high healthcare costs.

Background: Carotid endarterectomy (CEA) is associated with improved overall clinical outcomes in patients with acute ischemic stroke (AIS). However, studies on rates and factors associated with readmission following CEA for AIS are scarce. In this study, we used machine learning (ML) methods to identify the factors associated with readmission using a large-scale national database. Methods: We used National Surgical Quality Improvement Program (NSQIP) registry (2014-2017) and included patients 18 years or older, who underwent CEA for AIS. AIS and CEA were identified using ICD-9 and ICD-10 diagnosis and CPT procedure codes, respectively. We used Naïve Bayes, Boosted Decision Trees, and Bootstrapped Random Forest classification techniques to explore the predictors of 30-day readmission using demographics, past medical history, and preoperative variables. Results: There were a total of 22,373 AIS patients who underwent CEA. Mean (SD) age of the patients was 70.7 (9.4) years, and 61% were men. Majority were non-Hispanic White (80%), followed by non-Hispanic Black (4.6%). During the study period, 1 in 15 AIS patients who underwent CEA experienced 30-day readmission. Bootstrapped Random Forest classification performed best and Naïve Bayes worst with an AUROC of 92% and 59% respectively. The top 5 predictors of 30-day readmission after CEA were Hematocrit, BUN, Creatinine, WBC count, and Platelet count, all collected pre-operatively. Conclusion: Our study showed that ML techniques could accurately predict 30-day readmission using pre-operative risk factors. This ML model could be incorporated in EMR as a potential clinical decision support system. Implementing this system could help in early identification of patients who are at high risk for readmission following CEA. This could help physicians to plan and intervene effectively and prevent short-term readmissions; thereby improving quality of care and saving healthcare costs.

Background: Studies report that acute ischemic stroke (AIS) affects males and females differently. For example, the treatment outcomes of intra-arterial thrombolysis differ between males and females. In this study, we examined mortality and 30-day readmission differences by sex among AIS patients who had carotid endarterectomy (CEA). Methods: We used data from National Surgical Quality Improvement Program (NSQIP) registry (2014-2017). Patients ≥18 years of age, with CEA for AIS were included. AIS and CEA were identified using ICD-9 and ICD-10 diagnosis, and CPT codes, respectively. Using machine learning methods such as Hierarchical clustering, we grouped patients (low, medium, and high-risk clusters) based on their demographics, past medical history, and preoperative variables. Differences in means, and differences in proportions were calculated. Logistic regression was conducted for 30-day readmission and survival analysis for mortality, accounting for cluster groups and sex. Results: There were a total of 22,373 AIS patients who received CEA treatment. Mean (SD) age of the sample was 70.7 (9.4) years, and 61% were males while 39% were females. Mortality rates were 0.8% and 0.7% for men and women (p=0.113), respectively. Thirty-day readmission rates were 6.3% and 7.6% for men and women (p Conclusion: Our study found sex related disparities in short-term readmissions as it was higher among females. This could be because of underlaying sex specific pathophysiology of AIS. Healthcare providers should consider sex-specific management to improve post-stroke recovery for women and reduce their excess burden.

Background: FGF-23 is an endocrine regulator of phosphate metabolism as well as also a potent biomarker that mediates cardiovascular remodeling, with markedly elevated plasma concentration associated with the occurrence of morbid cardiovascular events such as myocardial infarction. This association usually indicates risk of developing further adverse cardiovascular events in individuals that are already susceptible to repeat morbid cardiovascular outcomes. This cross-sectional epidemiological study aims at investigating the risk association between FGF-23 and individuals in the 8 th year cohort of the Boston Puerto Rican Health Study (BPRHS) that have self-reported clinical cardiovascular disease in the form of myocardial infarction. Methods: FGF-23 plasma concentration was measured by ELISA in 496 participants of the fourth wave of the Boston Puerto Rican Health Study (BPRHS). Multivariate logistic regressions were used to analyze the cross-sectional association of plasma FGF-23 quartile distribution with self-reported clinical diagnosis of myocardial infarction (MI). Results: The crude model for the association between FGF-23 and MI showed increased risk across the 2 nd , 3 rd and 4 th quartiles, OR (95% CI); 1.27 (0.48-3.34), 1.13 (0.42-3.04), and 3.13 (1.33-7.33), respectively. The relationship with the highest vs lowest quartile remained significant after adjusting for age, sex and BMI, OR (95% CI); 2.91 (1.15-7.36). With further adjustment for diabetes, smoking, plasma total cholesterol, HDL cholesterol and triglycerides, results were attenuated, and the latter comparison was no longer statistically significant, OR (95% CI); 2.15 (0.79-5.79). The test for trend across the quartiles yielded a p value of 0.03. Conclusion: Within this population of older Puerto Rican adults, FGF-23 was not significantly associated with increased likelihood of self-reported history of myocardial infarction. Longitudinal studies, using clinical parameters that objectively measure the progression of cardiovascular disease are needed to assess the prognostic value of FGF-23 for future cardiovascular outcomes.

Introduction: Statins use for secondary cardiovascular disease (CVD) prevention is associated with better health outcomes and lower cost among adults with ASCVD. We aimed to examine the prevalence of statin use among adults with ASCVD in the US and to assess for gender and racial differences in statin use. Methods: We identified adults aged 40-75 years with ASCVD (defined using ICD codes and self-reported history) from the 2008-17 Medical Expenditure Panel Survey (MEPS) data. We estimated the trends in statin use among them, and used joint point regression (JPR) to estimate the annual percentage change in statin use. Logistic regression was used to assess the racial variation in statin use. We applied the weights in the MEPS complex survey design to estimate population sizes, so all results are nationally representative. Results: Between 2008 and 2017, 24896 adults aged 40-75 years with ASCVD were identified. In 2017, there were 2445 patients with ASCVD (equivalent to 24.5 million adults). In 2017, the mean age [SE] was 62.2 [0.3] years, and 42.9% were females. The overall proportion of adults with ASCVD using statin increased from 50.0% in 2008 to 58.7% in 2017, with an average annual percentage change of 0.95% between 2010 and 2017 ( p= 0.01). As shown in Figure 1a , among those with ASCVD, statin use was persistently lower in women than in men. In 2017, compared to White adults with ASCVD, Blacks (OR=0.69; 95% CI: 0.51-0.92) and Hispanics (OR=0.62; 95% CI: 0.45-0.85) were less likely to be on statin. Each year, over 3 million women with ASCVD were not on statin, and majority of them were Blacks and Hispanics. (Figure 1b) Conclusion: Millions of adults with ASCVD are not on statins in the US while gender and racial inequalities in statin use remains, despite persistent guideline recommendations. Herein lies an opportunity to improve CVD-related outcomes and cost by intensifying efforts to use statins for the secondary prevention of CVD and closing gender and racial gaps, especially with the 2030 sustainable development goals in view.

Background: Major adverse cardiovascular and cerebrovascular events (MACCE) are significant causes of perioperative morbidity and mortality but, the incidence and effects following cancer surgeries are unknown. The aims of this study were to evaluate national trends in MACCE after major cancer surgeries and to identify cancer types associated with cardiovascular events using a large national database. Methods: Patients who had major cancer surgeries from 2005 to 2014 were identified from the National Inpatient Sample database. Hospitalizations for surgeries for cancer of prostate, bladder, esophagus, pancreas, lung, liver, breast, colon and rectum were identified by ICD9 diagnosis and procedure codes. The main outcome was perioperative MACCE, defined as in-hospital, all-cause death, acute myocardial infarction (AMI), or acute ischemic stroke, and was evaluated over time. Results: Among 2,854,810 hospitalizations for major cancer surgeries, perioperative MACCE occurred in 67,316 hospitalizations (2.4%). Mean (SE) age of patients was 65.4 (0.07) years and 54.2% were male patients. MACCE occurred most frequently in patients undergoing surgeries for lung (6.8%), pancreatic (4.5%), and colorectal (3.3%) cancers. Between 2005 and 2014, the frequency of MACCE declined from 2.7% to 2.2% ( P P P = 0.002). However, no significant changes were observed for acute ischemic stroke ( P = 0.6) during the study period. Conclusion: Perioperative MACCE occurs in 1 out of every 42 hospitalizations for major cancer surgeries. Despite reductions in the rate of death and AMI among patients undergoing major cardiac surgeries, perioperative ischemic stroke remained constant over time. The lack of improvements in perioperative ischemic stroke rate is concerning and requires additional interventions. Significant efforts should be directed towards improving cardiovascular care during the perioperative period of cancer surgeries.

Introduction: Cardiometabolic syndrome consists of a cluster of metabolic dysfunctions such as impaired glucose tolerance, insulin resistance, dyslipidemia, central adiposity, and hypertension. According to the latest estimates, globally, nearly 25% of all adults have cardiometabolic syndrome. Both cardiometabolic syndrome and cancer pathophysiology commonly involve inflammation and oxidative stress. The objective of this systematic review was to evaluate existing evidences that support the association between cardiometabolic syndrome and risk of developing cancer. Methods: We searched MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials and Scopus for relevant articles published from the database inception until October 2019. We followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines for this review. Using the Oxford Center for Evidence-Based Medicine guidelines individual studies were evaluated. A total of 59 articles were included in this study. Results: Our review showed that cardiometabolic syndrome was associated with increased risk for colorectal, hepatic, endometrial, breast, and bladder cancers. These associations showed variations for sex and geographical locations. For example, the associations were stronger for pancreatic and rectal cancers among women. The strength of these associations was also stronger for sex specific cancers such as breast and endometrial cancers. Studies on European populations showed that these associations were stronger for colorectal cancer among women. However, one study showed that presence of cardiometabolic syndrome contributed protective effects to prostate cancer among American men. In general, strongest associations were found for colorectal cancer among both men and women and hepatic cancer among men. Among cardiometabolic factors, impaired glucose tolerance and central adiposity were the greatest contributors towards increased risk for cancers. Conclusion: Given these results, there should be greater focus on primary prevention to identify and treat cardiometabolic risk factors. In addition, patients with greater cardiometabolic risk factors should be screened earlier and more frequently for cancers. A number of gender and geographical gaps identified in this review could be targeted for improvements as per the goals of 2030 sustainable development initiatives. Future studies should consider cardiometabolic syndrome and cancer together and develop effective interventions for decreasing the incidence and morbidity associated with both the conditions.

Background: In August 2019, FDA approved TAVR for low-risk patients, a paradigm shift in the field of Cardiology. This approval will pave the way for TAVR to rapidly become mainstream, and it will be a preferred procedure for patients with symptomatic aortic stenosis in the coming years. In this study, we considered creating a useful tool to assess the risk of 30-day readmission after TAVR. Methods: We utilized data from ACS National Surgical Quality Improvement Program (ACS NSQIP) between 2015 and 2017. We selected 35 past medical history (such as history of CHF, COPD, etc.) and preoperative lab (such as BUN, WBC count, etc.) variables. A binary variable for 30-day readmission was created. Elastic net, random forest, and gradient boosted classification trees machine learning models were run and best performing model was selected based on the AUROC. Variables were plotted according to the importance. We created a nomogram using logistic regression by including important variables. Methods: About 594 patients underwent TAVR between 2015 and 2017; 56% patients were 80 years or older; and 45% were females. Majority of patients (62.8%) were Non-Hispanic White, had BMI ≥ 25 (71%), and took antihypertensive medication (82%). History of CHF was reported by 26%, and COPD by 17%. There were 68 (11.4%) patients who were readmitted within 30-days for any cause. Gradient boosted classification performed best. Top 15 variables were selected for logistic regression analysis to construct a nomogram. Five of the top variables were Total hospital LOS, pre-op platelet count, pre-op serum sodium, general anesthesia, pre-op BUN. Conclusion: In the US, 1 in 6 patients with TAVR could be readmitted within 30-days due to any cause after TAVR. We presented an interpretable model based on past medical history and pre-operative variables, which can be used to identify high risk patients so that their hospital readmission risk and can be reduced. This will also lower financial burden among patients.

Diabetes mellitus (DM) and atherosclerotic cardiovascular disease (ASCVD) both increase the risk for a major adverse cardiac event, and are therefore considered priority conditions clinically. Although guidelines encourage clinicians to treat them similarly, many researchers do not consider DM an ASCVD risk-equivalent. However, from a healthcare system standpoint it is more important to determine whether DM is an economic burden equivalent to ASCVD. Using data from the Household Component of the 2010–2013 Medical Expenditure Panel Survey, we determined that the diagnosis of DM yields significantly lower healthcare expenditures and resource utilization when compared with ASCVD. In fact, the healthcare cost associated with DM alone is almost $1000 less than ASCVD. That being said, the cost and resource utilization was highest among those individuals diagnosed with ASCVD+DM, underscoring the importance of primary and secondary prevention to help detect individuals early and initiate proper lifestyle and aggressive therapeutic managements.

Objective: Maternal pre-pregnancy hypertension is an established risk factor for preterm births and infant deaths. We sought to investigate the effects of maternal pre-pregnancy hypertension and tobacco use on preterm and infant deaths. Methods: We analyzed National Vital Statistics System’s 2013 and 2015 linked birth/ infant death data from a total sample of 6,629,652 live births. There were 11,782 preterm deaths due to “Newborn affected by maternal factors and by complications.” Maternal factors and complications were defined as deaths at less than 1 year of age with ICD-10 codes P00-P04. Regression model was accounted for tobacco use, cigarette use before and during pregnancy, prenatal care, maternal age and demographics. Results: Disease specific preterm mortality due to pre-pregnancy hypertension was 1.9 per/1000 live births. Preterm risk increased by two folds (adjusted odds ratio (AOR)=2.12; 95% confidence interval (CI) 1.92-2.18) with maternal pre-pregnancy hypertension history. Presence of pre-pregnancy hypertension and tobacco use doubled the risk of preterm (AOR=3.82 (95% CI: 3.67-4.82). African American mothers with pre-pregnancy hypertension were 1.72 time more likely to have preterm mortality than White females. Conclusion: Black race, maternal risk factor pre-pregnancy hypertension and tobacco use during pregnancy were associated with higher risk of preterm mortality. Further investigation is crucial to better understand the risk factors for the disparities in preterm so that women who are at risk pre-pregnancy can be identified and provided risk-specific services.

Background: Studies have shown that implantation of cardiac resynchronization therapy (CRT) devices could reduce morbidity and mortality in heart failure patients. Aims of this study are to examine the temporal trends and outcomes in CRT device implanted cancer survivors. Method: This study was a retrospective analysis of Nationwide Inpatient Sample during the period 2005-2014. Patients ≥18 years and who underwent CRT device implantation were included in the study. CCS codes 11-44 were used to identify cancer survivors. The International Classification of Diseases-9th Revision-Clinical Modification (ICD-9-CM) primary procedure codes 00.50 and 00.51 were used to identify patients with device implantation. Association between cancer diagnosis and in-hospital mortality and complications were determined using multivariable analyses. Result: During 2005 to 2014, a total of 392,758 inpatient CRT implantations were performed in the United States. Nearly 8.3% of these procedures were performed among patients with history of cancer. Number of procedures among cancer survivors decreased from 3127 in 2005 to 2115 in 2015. However, proportion of cancer patients undergoing CRT implantations increased from 6.8% in 2005 to 10.3% in 2014 (relative increase: 51.4%, P Discussion: Our study found that proportion of CRT implantations among cancer survivors increased from 6.8% to 10.3% during the study period. In addition, CRT implantations among cancer survivors were associated higher in-hospital complications. Strategies like prehabilitation and close collaboration between cardiologists and oncologists could improve outcome and general well-being of cancer survivors undergoing CRT implantations.

Background: Self-insured employers, which are majority in US, face an increasing financial burden as health care costs have increased relative to savings. By applying machine learning (ML) techniques, we may decrease unnecessary hospitalizations by identifying low risk patients, who are on the path to become high risk, and eventually high cost. In this complex simulation, we applied and compared several ML techniques on data gathered from medical insurance claims. Methods: The analysis was limited to employees and their spouses only. We identified about 8000 employees and spouses who were covered by employer sponsored health insurance plan between 2011 and 2016. De-identified data were used to predict high cost claimants. High cost was defined as annual spending of over $10,000 in medical claims. We utilized and compared methods namely: bootstrapped random forest, gradient boosted tree, neural networks, Naïve Bayes classifier, and logistic regression with LASSO. Variables in the model included yearly inpatient and ER visits, CCS categories, CPT codes, and demographic information. Results: The mean (SD) age of eligible population was 49.7 (11.0) years. Approximately, the employee to spouse ratio each year was 3.5:1. Results show that bootstrapped random forest performed better than other techniques (AUROC: 80.33%). All other algorithms also performed extremely well. Future progress of these models will be oriented towards including employee health fair data and also strategies to avoid over fitting. Conclusion: Healthcare is way behind other industries in successfully using ML to improve processes and disrupt one industry that is admittedly in need of positive disruption. Models allowing successful preventive actions will both increase revenue and lower costs. Application of modern ML techniques can identify high cost claimants earlier. Our approach is one of the first applications of significant recent advances in ML algorithms and computer technologies, opening new opportunities for the future analysis of high healthcare costs.

Objective: The accuracy and applicability of various cardiovascular disease (CVD) risk calculators may not be same in different populations. Wecompared 5 RFS for CVD risk on patients from Bosnia and Herzegovina to explore relations between different RFS and estimate use of theircombination. Methods: We utilized demographic, medical history, and lipid profile data gathered from patients seen in primary care clinic in 2013. FiveRFS namely, 10 year Framingham CHD score, QRISK 2, AHA/ACC ASCVD risk score, Framingham ATP III score, and EU SCORE were calculatedusing demographic, history of diabetes and hypertension, taking any hypertension medication, and lipid profile variables. Additionally, we entered these scores as dimensions in hierarchical cluster analysis to group people based on their risk of developing CVD. Results: There were 1277 patients in thisstudy and majority (65%) were women. The mean (SD) age of the sample was 56.2 (11.4) years. Correlation between these scores are presented inTable 1. We obtained 4 clusters with significant different cluster centers. Clusters were ordered from lowest to highest risk; cluster 1 containing patients with lowest and cluster 4 with highest mean RFS. Cluster centers, which represents mean values for all the RFS are given in Table 2. Conclusion: All risk scores performed well in this population. Only EU SCORE correlated less with other RFS. Obtained clusters are more homogenous and were ableto classify patients better. This novel method of using calculated RFCs as dimensions in clustering produced very good estimates of patient’s risk ofdeveloping CVD by combining several RFS, even in a case where originally RFS were created for and from different population.

Background: Hospital Readmissions Reduction Program requires CMS to reduce payments to hospitals with excess readmissions. Trend in 30 days readmission among patients with index hospitalization for stroke in the United States is largely unknown. In this study, national trend was examined to estimate quality of care in the US population. Methods: Patients, ≥40 years, with index hospitalization for stroke were extracted from the Nationwide Readmission Database (2010-2015). They were identified using ICD9 and ICD10 codes (433.x, 434.x, 435.x, 436.x, I63.x). Readmissions were defined as all cause readmission during 30 days post index hospitalization discharge, and were divided into planned and unplanned according to AHRQ guidelines. Weighted percentages and Joinpoint analysis were used to evaluate 30 days readmission trends and the annual percentage change (APC). Results: Older patients (≥75 years) and those with a higher comorbidity burden were readmitted frequently. Overall, there was a downward trend in unplanned 30 days readmissions between 2010 and 2015; the lowest rate (95% CI), was seen in 2014 (10.7%; 10.5% - 10.8%) and the highest in 2010 (11.6%; 11.4% - 11.8%). From 2010 to 2015, reduction in APC was 1.3% ( P > .08). Conclusions: Around 10%-12% of patients with stroke get readmitted within 30 days post discharge. Not only there is a high clinical and economic burden associated with readmissions due to stroke, it is also associated with poor survival. This highlights the need for interventions ensuring appropriate level of service and early outpatient follow-up after discharge. Reducing postoperative complications; managing behavioral risk factors (smoking, alcohol, diabetes management); or choosing appropriate carotid revascularization technique such as endarterectomy over stenting may reduce 30 days unplanned readmission and the high risk of mortality among stroke patients. Efforts should be made among elderly patients so that there is a decrease in trend.

Objective: Models predicting stroke suffer from several problems: they are not accurate, contain mostly non-modifiable factors, and they explain more than they predict. We performed a meta-analysis of frequently used stroke models. Our goal was to estimate the discriminative ability of the concordance statistic by establishing confidence and predictive intervals. Methods: Studies with most representative predictive methods were used in our analysis. Inputs in analysis were study-reported c-index values and corresponding 95% CI. Subgroup analysis, separating survival and logistic regression models, and separating models by outcome (predicting stroke or composite outcome) were executed. Combined effect sizes with the random model, test for heterogeneity, and publication bias were considered. Egger’s test was used to assess for funnel asymmetry. Results: Fifteen models were included (patients= 13177; LR=7, Cox= 8; only stroke =9, composite=6) in the analysis. Models predicting composite outcomes performed worse (0.62; 95% CI: 0.59, 0.65) than model predicting only stroke (0.70; 95% CI: 0.64, 0.75); combined mean c-index was 0.66 (95% CI: 0.62, 0.70; 95% predictive interval: 0.55, 0.78). Test of heterogeneity showed high variation between studies (I 2 =74.9%). Egger’s test intercept was 1.59 (95% CI: –0.80, 3.98, P > .17). Conclusion: At the moment, there is no good quality predictive or explanatory model available for stroke risk. Current models do not indicate towards risk factors exclusive only to stroke. Because of this, models predicting stroke mostly have non-modifiable risk factors. In addition to this, models orienting toward explanation are borrowing heavily from models developed for predicting composite cardiovascular diseases.

Women are entering medicine at increasing rates, particularly in dermatology. In this study, we compared women’s influence and status in academic dermatology with that of men by examining authorship roles in peer-reviewed dermatology literature. We examined the literature in 2009 and compared that to 10 years prior (1999). A total of 1399 articles were reviewed, 594 of which met study criteria and were included in statistical analysis. There was a marked increase in senior female authorship over a decade (22% vs. 38%, p < 0.001). Female first authorship increased as well (41% vs. 51%, p < 0.001). In contrast, changes in male senior and first authorship were not statistically significant. Federal funding for female senior authors increased over a decade (19% vs. 37%, p = 0.05), and female senior authors in the 2009 cohort were more likely to hold a dual MD/PhD degree (0% vs. 11%, p = 0.04) or pure PhD degree (11% vs. 27%, p = 0.04). Women are approaching parity with men in terms of authorship in the dermatology literature, and additional research training and attainment of federal funding have helped women publish as senior authors.

There is a paucity of studies investigating laser resurfacing in Fitzpatrick skin phototypes (SPT) IV to VI.To assess the efficacy and safety of fractional nonablative laser resurfacing in the treatment of acne scarring in patients with SPT IV to VI.The authors conducted a randomized, investigator-blinded and rater-blinded, split-face comparative study of adults with SPT IV to VI and facial acne scars treated with 2 different density settings and the same fluence.Quantitative global scarring grading system (QGSGS) scores were significantly improved from baseline at 16 and 24 weeks (p = .0277). Improvements in QGSGS scores after higher and lower density treatments were statistically similar (p = .96). The live-blinded dermatologist, the blinded dermatologist photoraters, and the patients rated scars as being significantly more improved by visual analog scale at weeks 16 and 24 compared with baseline (p.001) for both treatment densities. Five of 7 and 3 of 7 patients in the higher and lower density group, respectively, experienced mild or moderate hyperpigmentation as an investigator observed site reaction.The nonablative 1550-nm fractional laser is safe and efficacious in treating acne scaring in Fitzpatrick skin types IV to VI. Self-limited postinflammatory hyperpigmentation was a common occurrence, especially with higher treatment densities.

Background— Free radical scavengers have failed to improve patient outcomes, promoting the concept that clinically important oxidative stress may be mediated by alternative mechanisms. We sought to examine the association of emerging aminothiol markers of nonf ree radical mediated oxidative stress with clinical outcomes. Methods and Results— Plasma levels of reduced (cyst ei ne and glutathione) and oxidized (cyst i ne and glutathione disulphide) aminothiols were quantified by high performance liquid chromatography in 1411 patients undergoing coronary angiography (mean age 63 years, male 66%). All patients were followed for a mean of 4.7±2.1 years for the primary outcome of all-cause death (n=247). Levels of cystine (oxidized) and glutathione (reduced) were associated with risk of death ( P +1 SD and Conclusions— A high burden of oxidative stress, quantified by the plasma aminothiols, cystine, glutathione, and their ratio, is associated with mortality in patients with coronary artery disease, a finding that is independent of and additive to the inflammatory burden. Importantly, these data support the emerging role of nonfree radical biology in driving clinically important oxidative stress.

Introduction: Every year more than 75 million adults are diagnosed with HTN in the US. Despite spending $50 billion/ year to lower mortality related to HTN, only about 54% of patients have this condition managed. In 2014, mortality due to HTN or related complications was 410,000. AMI is a more severe manifestation of coronary artery disease with 735,000 people diagnosed yearly. It is estimated that hospitals lose $4493-$7940 per patient due to AMI. We studied costs for events associated with HTN and AMI in MEPS. Methods: Individuals aged ≥20 in MEPS (2014) were included. Hierarchical clustering was used for analysis. Age, sex, education status, race, Hispanic ethnicity, US citizenship status, family income, insurance, people who reported HTN and/ or AMI events were entered as dimensions. Cluster and descriptive analyses were adjusted for survey weights. Results: About 236 million weighted individuals were eligible for the analysis (Female: 51.7%; White: 79.1%; High school or above: 61%; Any private insurance: 66%; and Income≥ 400% of poverty line: 41%). Out of these, about 4.9 million participants reported costs/ events related to AMI and 61.8 million related to HTN. Five groups were identified based on similarity within each cluster (Table 1). The maximum number of participants were present in cluster 1 (weighted n = 101 million) with the most number of participants (21.5%) who reported HTN among all cluster groups. In general, cluster 5 had the lowest annual total of direct health care payments and events. Selected medical history is described in Table 2. Conclusion: Results show insights into the cost of HTN and AMI events, and their relationship with other comorbid conditions. Being computationally demanding, clustering methodologies are rarely utilized in survey data analysis. This could be the first example of clustering approach applied to data from MEPS. Once clustering methods are improved in weighted survey data, estimates will be more reliable.

Background: Each year in the USA, more than 75 million adults are diagnosed with hypertension (HTN), but less than 54% have it condition under control. Mortality due to HTN or related complications was 410,000 in 2014 and resulted in close to $50 billion spent. Acute Myocardial Infarction (AMI) is the most dramatic manifestation of coronary artery disease. Every year, about 735,000 people are diagnosed with AMI and it is estimated that hospitals lose $4493-$7940 per AMI patient on hospitalization. We studied interplays of expenditures for all events associated with HTN and AMI in the US in 2014. Methods: We used all available subsets from Medical Expenditure Panel Survey (MEPS; 2014) to extract all cost and utilization events related to HTN and AMI, following procedures for complex surveys as described in MEPS specifications to define population influenced by HTN and AMI, number of events, and related costs. Patients were included in this analysis if they were ≥20 years. Results: In 2014, there were about 236 million weighted participants in MEPS. Out of these, about 4.9 million participants reported costs related to AMI and 61.8 million related to HTN. About 3.9 million people reported both. Out of 61 million with HTN, 4 million reported AMI, whereas out of 174 million without HTN, only 1 million had AMI (OR: 11.1; 7.9-15.5). Those who had events associated with AMI, with an average cost of $5328/event, adding to total expenditures of $26.6 billion. Cost of AMI, HTN and both were $6.8 billion, $4.1 billion, and $2.7 billion, respectively. The total cost of hospitalization due to both HTN and AMI was 31.4% of the total healthcare expenditure among these participants. Conclusion: Burden of AMI includes almost 5 million people who live and die with AMI, and pay a high cost to manage this condition. Evidence from this study suggests that there is a significant disparity between the cost of hospitalization due to AMI between people with HTN and without HTN, which has potential implications on outcomes, quality of care, and hospital sustainability for AMI population. Symptom management at primary care settings may decrease the number of AMI events resulting in lower spending and cost savings by hospitals.

Introduction: According to the National Institute on Drug Abuse, lifetime cocaine use has remained stable since 2009. An estimated 1.5 million individuals aged ≥12 years reported cocaine use in 2014. Cocaine use is a significant risk factor for acute myocardial infarction (AMI), especially in the age group 18-45 years. Hence, we examined trends in hospitalizations due to cocaine-induced AMI in the United States. Methods: The current study was a retrospective analysis of the National Inpatient Sample, collected during the period 2005-2014. Participants between 18 and 45 years were included in the analysis. Cocaine-induced AMI hospitalizations were identified using ICD-9-CM codes 304.2X and 305.6X for cocaine dependence or abuse, and 410.XX for AMI diagnosis. We used Cochran Armitage test for categorical variables and Cuzick nonparametric test for trends for continuous variables. Results: A total of 49,715 weighted cocaine-induced AMI hospitalizations were reported during the study period. Cocaine-induced AMI hospitalizations increased from 4,619 in 2005 to 5,065 in 2014 (relative increase, 9.7%, P trend =0.124). Majority of the patients were non-White (55.3%), men (79.3%), in the age group 41-45 years (83.1%), and with Medicare/Medicaid coverage (51.2%). Highest change in trend was observed for non-White population and Medicare/Medicaid payers. Conclusion: Our study showed that cocaine-induced AMI hospitalizations remained stable during the years 2005-2014. Initial results point towards structural and racial disparities in such hospitalizations, especially among non-White men and population with Medicare/Medicaid coverage. Effective interventions to reduce cocaine use are needed, and treatment must be based on 2008 AHA guidelines for cocaine-associated chest pain and myocardial infarction.

Background: Heart disease continues to be the leading cause of death, and the prevalence of coronary artery disease is expected to increase as the population ages. It is important to understand the clinical utility of medical tests, or its lack thereof, in the aging population. The objective of this study was to understand the incremental prognostic value of positron emission tomographic (PET) myocardial perfusion imaging in the elderly (≥85 years of age). Methods and Results: A total of 3343 patients enrolled in a multicenter observational PET registry were analyzed. Participants were initially divided into 3 age categories: 65 to 74.9, 75 to 84.9, and ≥85 years of age and followed for all-cause death. Median follow-up time was 3 years. Of the total patient population, 248 patients (49% men) were ≥85 years old. When compared with younger patients, individuals ≥85 years had a higher prevalence of hypertension (79%) and a lower incidence of dyslipidemia (54%) and diabetes mellitus (24%). On multivariable analysis, %left ventricular stress defect and %left ventricular ischemia were predictors of patient outcome for those Conclusions: The elderly is a high-risk population irrespective of PET myocardial perfusion imaging results, and incremental prognostic value of PET myocardial perfusion imaging appears to wane in those ≥85 years of age. Although PET myocardial perfusion imaging may be diagnostically useful in the elderly, its prognostic value in this population requires further evaluation.

Background: Lipoproteins-rich triglycerides are associated with markers of coronary atherosclerosis such as coronary artery calcification (CAC) in young high-risk population. This study examines differences between sexes associated with lipoprotein sub-fractions and atherosclerosis. Methods: The study presents analysis from baseline data of a randomized trial of employees of Baptist Health South Florida with metabolic syndrome or diabetes. Participants completed lipoprotein sub-fraction analysis at baseline using ion mobility technique. Subjects above 35 years had a CAC test completed. We tested for differences between correlational matrices of the original variables. The same analysis was repeated for sets of 3 principal components (PC) that were computed for the combination of all lipoprotein subclasses. Results: The study population (N=170) was largely female (128) with a mean age of 58 years. Three PCs accounted for 83% variation in the sample. Distribution of atherosclerostic PC2 by sex was entirely different between sexes (Wishart test p=.004). In addition, a significant Jennrich’s test (p < .0045) implied that the inter-correlations among all dependent variables for different groups were dissimilar; with the finding of significant angles between PC components by sex. PC2, with main contributions from VLDL particles, was in the positive direction; however PC3 with large LDL particles was in the negative direction. Atherogenic lipoprotein profiles were significant only for males, with PC keeping their independent predictability. Conclusion: In a relatively young high-risk population, there were sex-specific differences in lipoprotein sub-fractions profiles that are associated with increased risk of atherosclerosis. The relationship was much weaker for males compared to females (see graph). These findings points towards a possible sex-linked lipoprotein sub-fraction association with the atherosclerosis pathogenesis.

Introduction: Previous studies have linked depression and cardiovascular diseases, however gender differences in cost of hospitalization and care associated with events related to depression and myocardial infarction (MI) is not studied in detail. We utilized data from 2014 Medical Expenditure Panel Survey (MEPS) to evaluate national estimates of such costs. Hypothesis: Proportion of depression and MI and corresponding healthcare expenditures are high in general population and differ between genders. Also, payments are appropriated differently between payers. Methods: Participants from 2014 MEPS with events attributed to MI and/ or depression were included in this study. Mean (95% CI) event related cost, and total cost of health care was calculated using survey methods. Expenditure and utilization cost was grouped as related to ambulatory, emergency room, inpatient, home visits and medications. By source, payments were grouped as paid by family, MEDICARE, MEDICAID, private insurance, VA, Tricare and other. Results: There were 23486 participants in the study, representing 242,628,543 individuals in the US who were 20 years or above. Total health expenditure in 2014 among these was $1.5 trillion (Males: $696,940,498,022; Females: $837,486,094,699) with $27,937,582,549 attributed to depression (Males: $10,991,761,342; Females: $16,945,821,207) and $51,142,260,003 to MI (Males: $40,676,887,518; Females: $10,465,372,485). There were around 6,174,408 (2.5%) and 27,269,837 (11.2%) events associated with MI and depression respectively. Approximately 901,762 individuals reported both events. Among males, MI was 4,189,696 (3.6%) and among females, 1,984,711 (1.6%). Depression was reported 8,755,276 (7.5%) among males and 18,514,560 (14.6%) among females. Among females who were depressed, 2.3% reported MI, and 1.4% among those who were not depressed. Among males who were depressed, 5.4% reported MI and 3.4% among those who were not depressed. Among depressed males, AMI hospitalization was 0.31% whereas among depressed females, AMI hospitalization was 0.24%. Conclusion: Among both depressed and non-depressed populations, males had significantly higher proportion of MI and hospitalizations related to AMI when compared to females. But, out of total MI costs for males, less than 1% cost was accrued by depressed; whereas, of total MI cost for females, 9.6% of cost was accrued by depressed females showing gender based disparities in healthcare cost and utilization. With Medicare paying between 78%-83% of all MI costs, treating depression can result in significant savings.

Background: An age, sex, and blood gene expression score (ASGES) has been previously validated to detect obstructive coronary artery disease (CAD) in non-diabetic patients presenting with stable chest pain in the outpatient setting. However, the diagnostic performance of this test in ruling out obstructive CAD in patients presenting with acute chest pain (ACP) to the emergency department (ED) is unknown. Methods: In an ongoing study, 371 low-intermediate risk patients with ACP and no prior history of CAD (TIMI risk score ≤ 2, negative troponins and normal/non-diagnostic ECG) underwent coronary CT angiography (CCTA) using institutional protocols. Patients were classified based on severity of stenosis (obstructive CAD, >50%; high grade stenosis, >70%) and ASGES. The ASGES blood test sample was drawn before ED discharge and analyzed in a commercial reference laboratory (Redwood City, CA). We excluded 23 (6%) patients with unreportable ASGES and 47 (13%) diabetics from this primary analysis. Results: 301 (53±10 years, 45% males, 78% Hispanics) non-diabetic ACP patients undergoing CCTA in an ED setting were included in this analysis. No plaque was detected in 183 (60%) patients, and 22 (7%) patients had obstructive CAD. In this population, 51% of patients had scores below the previously defined threshold of ASGES≤ 15. This threshold yielded sensitivity, specificity, NPV, and PPV of 71% (52-86%), 53% (47-59%), 97% (93-98%), and 12% (9-14%) for obstructive CAD. Furthermore, ASGES≤15 yielded a 100% sensitivity and NPV for patients with high grade stenosis (n=7, 2%). In a multivariable analysis including patient demographics and clinical covariates, ASGES ≤15 was significantly associated with obstructive CAD (OR: 0.15, 95% CI: 0.04-0.62). As a continuous variable, increasing ASGES was positively correlated with the presence of obstructive CAD and CCTA-defined plaque burden (p Conclusions: This is the first study validating the use of this blood-based precision medicine test to rule out obstructive CAD among low-intermediate risk non-diabetic patients presenting with ACP in ED setting. 30-day follow-up is underway to evaluate the prognostic implications of these findings.

Introduction: Higher education and income can modify behavioral risk factors for lifetime cardiovascular disease (CVD) risk. The aim of this study was to observe ethnic differences in the CV health, as measured by inadequate cardiovascular health index (CVHI) category, among a cohort of females with high family income, education, and BMI. We also examined differences in perception about self-reported weight and attitudes toward weight loss and exercise. Methods: Adult non-pregnant females aged 20 years or older from the 2011-2012 NHANES were included in the study. Participants were at least college educated, had a poverty to income ratio of 350% or above, and BMI (≥ 30). Weighted regression was adjusted for demographics, PHQ-9 score, perception about weight, if participant tried to lose weight last year, and history of CVD, angina, or heart attack. Results: The sample represented 2,990,456 eligible females in the US. About 13.2% Hispanic perceived their weight to be about right as compared to 10% Black, and 3.3% White. About 89% Hispanics tried to lose weight in past year compared to 71% White and Black. Weighted regression showed that Hispanic (β: -2.47, 95% CI: -4.44, -0.50) and Black (β: -0.74, 95% CI: -1.93, 0.45) had low CVHI score as compared to White. Higher PHQ9 score (β: -0.12, p > 0.05) and those who did not try to lose weight (β: -1.55, p < 0.01) were associated with lower, and those with positive attitude towards their weight were associated with higher CVHI score (β: 0.38, p > 0.05). Our study suggests huge variations in these characteristics by country of birth and citizenship with corroborated ambiguity in definitions. Conclusion: Previous research is inconclusive about existence of Hispanic paradox in cardiovascular health domain. Our study suggests that Hispanic ethnicity was a significant predictor of negative CVHI, when socioeconomic status (SES) was high among all obese females. There was higher prevalence of history of weight management and low CVHI score among Hispanic females; Hispanic females belonging to higher SES may be at a higher risk for CVD related adverse events. In our study, effect of education and income diminished and SES was not associated with participant’s willingness to lose weight despite being obese. Health disparities expressed as differences in CVHI exist despite high education and family income.

Introduction: As number of elderly Americans is projected to double by 2050, population aged ≥65 years will have the highest impact on Medicare spending. The prevalence of elderly population with hypertension (HTN) is around 65% and if patients receive good primary care or an early intervention, these HTN related hospitalizations could be prevented saving millions in Medicare spending. Our objective was to examine the trends in hospitalizations related to HTN and total cost over 10 years among aged ≥65 years. Methods: Using data from Nationwide Inpatient Sample database from 2005-2014, we explored the existence of trends in HTN admission rates and corresponding hospitalization costs among adults ≥65 years vs other age groups. Weighted estimates for rates and mean total cost were reported using SUDAAN after adjusting for complex survey design. Results: Overall, hospitalizations due to HTN increased by 26% in 2014 from 2005. Hospitalizations were highest among patients ≥65 years (57.8%) followed by 40-64 (32.6%) and 18-39 years (9.6%). During 2005-2014, hospitalization rates among ≥65 years increased significantly (10.7%, p p Conclusion: Hospitalizations and costs associated with HTN, especially Medicare, have increased over the past 10 years among elderly. Although these trends are alarming, these events could be prevented through symptom management at primary care, medication adherence, care coordination, or modifying care-seeking behavior resulting in potential savings of 851M over a year. This would reduce burden of Medicare spending, which is projected to surpass the rate of growth in federal revenues.

Objectives: Extensive data suggests that lesbian, gay and bisexual (LGB) adults are more likely to experience adverse cardiovascular outcomes relative to heterosexuals. However, evidence regarding cardiovascular health (CVH) disparities and sexual orientation is scarce. The aim of this study was to examine the distribution of CVH metrics in a US nationally representative population of heterosexual (HT), and LGB adults. Methods: This cross-sectional study analyzed 2445 participants (representing 115 million) adults aged 18 or over years in the 2011-2012 NHANES survey. The CVH factors of smoking, body mass index (BMI), physical activity (PA), diet, blood pressure (BP), total cholesterol (TC) and glucose (GLU) were measured. Each CVH factor was then classified as ideal; intermediate; or poor. Ideal CVH was defined as presence of >=5 ideal CVH metrics. Results: 95.1% of the weighted sample self-identified as HT (95% CI: 93.5%, 96.6%) compared to 4.9% (95%: 3.3%, 6.5%) LGB. The figure illustrates the distribution of each of the 7 CVH categories according to sexual orientation. In age, gender, and race adjusted analysis, LGB individuals were 36% (AOR: 0.64; 95%: 0.29, 1.4; p > 0.05) less likely to have ideal CVH compared to HT. These proportions go higher after adjusting for age. Conclusions: The results suggest that LGB individuals face a higher risk of being in the category for poor cardiovascular health compared to heterosexuals. Evidence suggests that there are sexual orientation disparities among adults. If confirmed in other studies, results point towards disproportionately higher risk for cardiovascular disease among sexual-minority populations. Figure

Rationale: Low circulating progenitor cell numbers and activity may reflect impaired intrinsic regenerative/reparative potential, but it remains uncertain whether this translates into a worse prognosis. Objectives: To investigate whether low numbers of progenitor cells associate with a greater risk of mortality in a population at high cardiovascular risk. Methods and Results: Patients undergoing coronary angiography were recruited into 2 cohorts (1, n=502 and 2, n=403) over separate time periods. Progenitor cells were enumerated by flow cytometry as CD45 med+ blood mononuclear cells expressing CD34, with additional quantification of subsets coexpressing CD133, vascular endothelial growth factor receptor 2, and chemokine (C-X-C motif) receptor 4. Coefficient of variation for CD34 cells was 2.9% and 4.8%, 21.6% and 6.5% for the respective subsets. Each cohort was followed for a mean of 2.7 and 1.2 years, respectively, for the primary end point of all-cause death. There was an inverse association between CD34 + and CD34 + /CD133 + cell counts and risk of death in cohort 1 (β=−0.92, P =0.043 and β=−1.64, P =0.019, respectively) that was confirmed in cohort 2 (β=−1.25, P =0.020 and β=−1.81, P =0.015, respectively). Covariate-adjusted hazard ratios in the pooled cohort (n=905) were 3.54 (1.67–7.50) and 2.46 (1.18–5.13), respectively. CD34 + /CD133 + cell counts improved risk prediction metrics beyond standard risk factors. Conclusions: Reduced circulating progenitor cell counts, identified primarily as CD34 + mononuclear cells or its subset expressing CD133, are associated with risk of death in individuals with coronary artery disease, suggesting that impaired endogenous regenerative capacity is associated with increased mortality. These findings have implications for biological understanding, risk prediction, and cell selection for cell-based therapies.

Background Atherosclerotic cardiovascular disease ( ASCVD ) causes most deaths in the United States and accounts for the highest healthcare spending. The association between the modifiable risk factors ( MRF s) of ASCVD and pharmaceutical expenditures are largely unknown. Methods and Results We examined the association between MRF s and pharmaceutical expenditures among adults with ASCVD using the 2012 and 2013 Medical Expenditure Panel Survey. A 2‐part model was used while accounting for the survey's complex design to obtain nationally representative results. All costs were adjusted to 2013 US dollars using the gross domestic product deflator. The annual total pharmaceutical expenditure among those with ASCVD was $71.6 billion, 33% of which was for medications for cardiovascular disease and 14% medications for diabetes mellitus. The adjusted relationship between MRF s and pharmaceutical expenditures showed significant marginal increase in average annual pharmaceutical expenditure associated with inadequate physical activity ($519 [95% confidence interval ( CI ), $12–918; P =0.011]), dyslipidemia ($631 [95% CI , $168–1094; P =0.008]), hypertension: ($1078 [95% CI , $697–1460; P CI , $1470–2542]). Compared with those with optimal MRFs (0–1), those with average MRFs (2–3) spent an average of $1184 (95% CI , $805–1564; P MRFs (≥4) spent $2823 (95% CI , $2338–3307; P Conclusions Worsening MRFs were proportionally associated with higher annual pharmaceutical expenditures among patients with established ASCVD regardless of non‐ ASCVD comorbidity. In‐depth studies of the roles played by other factors in this association can help reduce medication‐related expenditures among ASCVD patients.

Background: Each year in the USA, more than 75 million adults are diagnosed with hypertension (HTN), but less than 54% have this condition under control. Due to poor management, mortality due to HTN or related complications was 410,000 in 2014 and resulted in close to $50 billion spent. We sought to examine disparities in the proportion of events and related expenditure due to HTN between 54 million Hispanics, representing 17% in the USA population and non Hispanics. Methods and Population: We used data from the Medical Expenditure Panel Survey (MEPS), the most complete source of data on the cost and use of health care and health insurance coverage for 2013 and 2014. Cost was grouped as related to ambulatory, emergency room, inpatient, home visits and medications. By source, payments were grouped as paid by family, MEDICARE, MEDICAID, private insurance, VA, Tricare and other. Results: Overall, there were 61.2 and 61.9 million total events associated with HTN in 2013 and 2014 respectively; Hispanics accounted for 5.8 (9.5%) and 5.4 (8.7%) million events each year. On an average, HTN events involving Hispanics were costlier up to $90 - $300 more than non Hispanics ($1053 vs. $ 746 in 2013; and $890 vs. $804 in 2014). For Hispanics, payments were mainly covered by MEDICAID (42.1%) and MEDICARE (27.5%), compared to MEDICARE (39.3%) and private insurance (23.7%) for non-Hispanic population. Hispanics HTN expenditures were $6.1 billion (12.9%) in 2013 and 5.3 billion (10.3%) in 2014 and Hispanics had disproportionately fewer number of events than expected 17%, and the structure of their costs for those events was not different from non-Hispanics. In regression model, accounting for demographics and type of insurance, being Hispanic was a significant predictor of the total, ambulatory and inpatient cost, but not emergency room or medication cost. Conclusion and Discussion: Hispanics participate disproportionately less in HTN events and costs compared to their proportion in population, even when age, demographic and socioeconomic factors are accounted for. They also have on average higher and more complex events compared with non Hispanics. Almost 70% of HTN expenditure for Hispanics in 2013-2014 was covered by MEDICAID and MEDICARE indicating socioeconomic disparities.

Objective: Carotid intima media thickness (CIMT) is well-known marker of cerebrovascular & CVD outcomes. Recent literature has discussed association of sleep duration with stroke &CVD, but still limited evidence exists regarding the true relationship of sleep duration with CIMT. The aim of this study is to determine association of short& long sleep duration with CIMT. Method: Baptist Health South Florida, a not for profit organization, conducted a randomized, non-blinded controlled trial in 2014.This study examined effect of web based interventions on reducing CVD risk in employees. The inclusion criteria were physician diagnosed T2DM and/or Metabolic Syndrome. We used cross sectional data for analysis. Per CDC.gov guidelines, we categorized self-reported sleep duration (hrs) as short ( Result: Study population (n=183; 74% female, 49% Hispanic) with mean age 51±10 years. Mean CIMT(mm) in females [0.879±0.15] and males [0.911±0.19] was not different (p>0.05). Atherosclerotic plaque was defined as any obvious focal luminal encroachment > 1.2 mm. In multivariate logistic regression model, per hour increase in sleep duration was associated with twice the odds of increase in CIMT >1.2mm [OR 2.15;95% CI (1.15-4.02)]. However, once we compared the reference sleep with short and long sleep duration categories, we determined, as compared to 7-9 hrs (ref) of sleep, the odds of CIMT >1.2 in those sleeping Conclusion: Although we observed that per hour increase in sleep was related to increase in CIMT >1.2mm (risk of plaque), but we did not find any significant increased risk of plaque in either short or long sleep duration. Longitudinal studies with larger sample size are needed to clarify this association.

Background: Research shows that subclinical hypothyroidism (SCH) is related to increased carotid intima media thickness (CIMT), a surrogate marker of stroke and subclinical cardiovascular disease (CVD). It is controversial whether SCH should be treated or not to reduce risk of stroke and CVD morbidity and mortality. The aim of this meta-analysis was to determine whether SCH is associated with an increase in CIMT as compared to Euthyroidism (EU) and whether thyroxin therapy in SCH can reverse the change in CIMT. Methods: Two independent reviewers did an extensive database search up to December 2016. Total of 12 randomized clinical trials discussed effect of thyroxin treatment on CIMT values at pre-and-post treatment in SCH subjects. Results: CIMT was significantly higher among SCH (n=280) as compared to EU controls (n=263) at baseline, pooled standardized mean difference (SMD) of CIMT was 0.44 mm [95%CI 0.14, 0.74], SE=0.15; p=0.004 with heterogeneity I 2 = 65%. After treatment with thyroxin in SCH subjects (n=314), there was a statistically significant decrease in CIMT from pre-to-post treatment, pooled SMD of CIMT decrease was [SMD -0.32; 95%CI (-0.47, -0.16), SE=0.08; p2 = 2%], and was no longer different from EU controls [SMD 0.13 mm; 95% CI (-0.04, 0.30); p= 0.14; I 2 = 27%]. The total cholesterol, triglycerides, and low density lipoprotein were higher in SCH as compared to EU controls and decreased significantly after treatment with thyroxin. Conclusion: This meta-analysis shows that thyroxin therapy in SCH subjects significantly decreases CIMT and improves lipid profile, modifiable risk factors for stroke and CVD. Thyroid hormone replacement in SCH subjects might have a role in slowing down or preventing progression of atherosclerosis.

Introduction: Psychological factors including stress are associated with adverse cardiovascular (CV) disease outcomes. Gender differences exist in both the perception of stress and the magnitude of the stress response. We hypothesize that self-perceived psychological stressors would have a greater impact on women compared to men as measured by the American Heart Association Life’s Simple Seven (LS7) health metrics. Methods: This was a cross-sectional study conducted among employees of BHSF. The LS7 metrics (smoking, physical activity, diet, body mass index, blood pressure, cholesterol and glucose) were each scored as ideal (2), intermediate (1), or poor (0), with composite scores ranging from 0 to 14. Total scores were categorized as optimal (11-14), average (9-10) and inadequate (0-8). We used multinomial logistic regression to compare psychological factors obtained by questionnaire (self-perceived stress, life satisfaction, hopelessness, sadness, depression, anxiety) with the LS7 score (inadequate score served as reference). The model was stratified by gender and adjusted for age, ethnicity, and education level. Results: Of the 9,056 participants, 74% were female, 17% white, 57% Hispanic, 16% black, with a mean age of 43±12 years. Self-perceived adverse psychological factors were associated with being less likely to achieve adequate and optimal LS7 scores (Table). For example both women and men, respectively, with self-perceived stress were less likely to have optimal LS7 metrics [OR 0.47 (95% CI 0.40-0.56) vs. 0.50 (0.36-0.69)]. There were some interactions by gender (P Conclusions: In an ethnically diverse population, participants with negative self-perceived psychological factors are more likely to have inadequate CV health as measured by LS7. Contrary to our hypothesis, in general, men and women were similarly affected by adverse psychological factors. Addressing psychological stressors may be one mechanism to improve CV health.

Background: Given the health and cost burden of cardiovascular (CV) disease, we aimed to describe the trends in CV risk factors (CRF) in the US over the last twelve years, and quantify the disparities in healthcare by socioeconomic status (SES). Methods: The 2002-2013 Medical Expenditure Panel Survey (MEPS), a nationally representative sample was the basis for our study. CRFs (hypertension, diabetes mellitus, hypercholesterolemia, smoking, lack of physical activity and obesity) were identified by ICD9CM codes and/or self-report. Individuals were stratified by income level (per the federal poverty level), and proportions and logistic regression models were used to study trends and relationships for each CRF in two-year intervals. All analyses took into consideration the survey’s complex design. Inclusion criteria: age ≥ 18, BMI ≥ 18.5 and a positive sampling weight. Results: The study sample consisted of 250,371 MEPS participants (46 ± 14 years of age, 49% male), translating into 1.3 billion US adults. During the study period, the proportion of individuals with obesity increased overall, though moreso among people of low SES (Table). Trends in diabetes prevalence increased (from 9.6% to 12.8% in “Poor/Near Poor” and 5.6% to 8.3% in “High Income”, both p trend < 0.001) and hypertension (from 28.5% to 36.3% in “Poor/Near Poor” and 24.2% to 33.4% in “High Income”, both p trend < 0.001), though the greatest relative change was observed among the Middle/High Income SES group. Prevalence of inadequate physical activity increased in all SES categories, with the “Poor/Near Poor” group having the most drastic change (32.4% vs. 55.4%, p trend < 0.001), and a relative percent change of 71.1% increase in this category. Smoking declined across time in all SES categories, and hypercholesterolemia showed no significant changes. In pooled analysis, the odds of having a “Poor CRF Profile” (≥ 4 CRFs) for “Poor/Near Poor” SES were 36% higher when compared to “High Income” SES (OR 1.36, 95% CI [1.30, 1.44]) (Table). Conclusion: Disparities in the prevalence of CRFs have increased over the past 12 years, and have worsened for some conditions, including obesity, diabetes, hypertension and physical inactivity. There is a need for healthcare initiatives and policies to target the groups most in need.

Background— Inflammation, coagulation, and cell stress contribute to atherosclerosis and its adverse events. A biomarker risk score (BRS) based on the circulating levels of biomarkers C-reactive protein, fibrin degradation products, and heat shock protein-70 representing these 3 pathways was a strong predictor of future outcomes. We investigated whether soluble urokinase plasminogen activator receptor (suPAR), a marker of immune activation, is predictive of outcomes independent of the aforementioned markers and whether its addition to a 3-BRS improves risk reclassification. Methods and Results— C-reactive protein, fibrin degradation product, heat shock protein-70, and suPAR were measured in 3278 patients undergoing coronary angiography. The BRS was calculated by counting the number of biomarkers above a cutoff determined using the Youden’s index. Survival analyses were performed using models adjusted for traditional risk factors. A high suPAR level ≥3.5 ng/mL was associated with all-cause death and myocardial infarction (hazard ratio, 1.83; 95% confidence interval, 1.43–2.35) after adjustment for risk factors, C-reactive protein, fibrin degradation product, and heat shock protein-70. Addition of suPAR to the 3-BRS significantly improved the C statistic, integrated discrimination improvement, and net reclassification index for the primary outcome. A BRS of 1, 2, 3, or 4 was associated with a 1.81-, 2.59-, 6.17-, and 8.80-fold increase, respectively, in the risk of death and myocardial infarction. The 4-BRS was also associated with severity of coronary artery disease and composite end points. Conclusions— SuPAR is independently predictive of adverse outcomes, and its addition to a 3-BRS comprising C-reactive protein, fibrin degradation product, and heat shock protein-70 improved risk reclassification. The clinical utility of using a 4-BRS for risk prediction and management of patients with coronary artery disease warrants further study.

Introduction: Despite the substantial evidence of health benefits associated with adequate sleep duration, little is known about the relationship between sleep duration and healthcare expenditure. In this study, we examined the relationship between sleep duration and healthcare expenditure in an employee population. Methods: Employees of Baptist Health South Florida voluntarily participated in a Health Risk Assessment in 2014 from which data for this study was obtained. Self-reported sleep duration for each participant was collected via a web-based questionnaire. In addition, participants were assessed for cardiovascular health (CVH) status using the American Heart Association’s ideal CVH construct and categorized as optimal and suboptimal CVH (5 - 7 metrics and 0 - 4 metrics at ideal levels respectively). Annual healthcare expenditure obtained from health insurance claims data was aggregated with participants’ data. Two-part regression models were used to calculate mean and marginal per-capita healthcare expenditures. Results: Among all participants (n=9071), after adjusting for age, sex, educational attainment and ethnicity, the mean healthcare expenditure in persons who slept for between 6-7.9 and ≥8 hours was $6,167 and $6,117, compared to $8,098 in those that slept < 6 hours (see bar chart in figure). This corresponded to about $1932 (6-7.9h) and 1982 (≥8h) less in healthcare expenditure (vs. 2 ) or CVH (2 groups, see above) did not significantly alter these results (figure). In sub-group analyses, persons who achieved optimal CVH (n=3574) had the greater costs benefits (> $3000) from ≥ 6 hours a day while those with suboptimal CVH profiles (n=5497) showed no statistically significant cost benefits associated with ≥6 hours of sleep (see bar charts in figure). Conclusions: Workers who sleep ≥ 6 hours a day incur significantly lower healthcare costs compared to those who sleep < 6 hours a day independent of obesity or CVH status. The greatest reductions in healthcare expenditure were seen among persons with optimal CVH suggesting an effect modification by CVH on the association between sleep duration and healthcare costs. These findings highlight the need for promoting good sleep hygiene as well as heart healthy lifestyles among employee populations.

Background: Recent data from SPRINT trial demonstrated that, intense systolic blood pressure (ISBP) control to Methods: Electronic medical records from 3 different ambulatory clinics were reviewed to identify hypertensive patients with at least 3 consecutive clinic visits. Patients with diabetes, with 120 mm Hg respectively. Results: 1644 non diabetic patients with HTN included in the analysis. 1389 (84.5%) patients had St-SBP control whereas only 255 (15.5%) patients had ISBP control. ISBP group had significantly lower mean (±SD) SBP compared to St-SBP group; 116(±6.4) mm Hg vs. 136(±11.6) mm Hg respectively; P Conclusion: There is significant variation in SBP control in non-diabetic hypertensive patients in clinical practice, despite comparable comorbid profile. Furthermore, ISBP control is not a common practice in real world. Quality improvement measures should focus on promoting ISBP control in non-diabetic hypertensive patients.

Background: Recent data from post hoc analysis of PARADIGM-HF trial demonstrated that Influenza vaccination was associated with reduced risk of all-cause mortality in patients with chronic heart failure. We sought to determine if CHF patients admitted during Influenza season (CDC definition: October to May) are critically ill compared to non-Influenza season Methods: Consecutive patients presented to the ER of a community teaching hospital between January 2007 to January 2016, with the diagnosis of CHF were analyzed for disposition trends. Critical illness was pre-specified as patients being admitted to either Telemetry or Intensive care unit (ICU) Results: A total of 3424 CHF ER-admissions were recorded in 2536 patients; 888 were readmissions. Mean age was 77 ±12 years. 1455 (57.4%) were females. 2356 (68.8%) were disposed to Telemetry, 141 (4.1%) were to ICU and 927 (27.1%) were to either medical floor or stabilized and discharged from ER. 2424 (70.8%) ER-admissions occurred in Flu season whereas only 1000 (29.2%) were in non-Flu season. There was a trend towards peak of critically ill CHF hospitalizations in Flu-season when compared with non-Flu season: 1788 (73.8%) vs 709 (70.9%); P=0.08 (Figure 1). Conclusions: There is a trend towards critically ill CHF hospitalizations in Flu-season. Further studies in larger data sets are needed to validate our findings.

To assess the range of responses to community consultation efforts conducted within a large network and the impact of different consultation methods on acceptance of exception from informed consent research and understanding of the proposed study.A cognitively pretested survey instrument was administered to 2,612 community consultation participants at 12 U.S. centers participating in a multicenter trial of treatment for acute traumatic brain injury.Survey nested within community consultation for a phase III randomized controlled trial of treatment for acute traumatic brain injury conducted within a multicenter trial network and using exception from informed consent.Adult participants in community consultation events.Community consultation efforts at participating sites.Acceptance of exception from informed consent in general, attitude toward personal exception from informed consent enrollment, and understanding of the study content were assessed. Fifty-four percent of participants agreed exception from informed consent enrollment was acceptable in general in the proposed study; 71% were accepting of personal exception from informed consent enrollment. Participants in interactive versus noninteractive community consultation events were more accepting of exception from informed consent in general (63% vs 49%) and personal exception from informed consent inclusion (77% vs 67%). Interactive community consultation participants had high-level recall of study content significantly more often than noninteractive consultation participants (77% vs 67%). Participants of interactive consultation were more likely to recall possible study benefits (61% vs 45%) but less likely to recall potential risks (56% vs 69%).Interactive community consultation methods were associated with increased acceptance of exception from informed consent and greater overall recall of study information but lower recall of risks. There was also significant variability in exception from informed consent acceptance among different interactive consultation events. These findings have important implications for institutional review board and investigators conducting exception from informed consent research and for community engagement efforts in research more generally.

Background The American Heart Association introduced the Life's Simple 7 ( LS 7) metrics to assess and promote cardiovascular health. We examined the association between the LS 7 metrics and noncardiovascular disease. Methods and Results We studied 6506 men and women aged between 45 and 84 years, enrolled in the Multi‐Ethnic Study of Atherosclerosis. Median follow‐up time was 10.2 years. Each component of the LS 7 metrics (smoking, body mass index, physical activity, diet, total cholesterol, blood pressure, and blood glucose) was assigned points, 0 indicates “poor” category; 1, “intermediate,” and 2, “ideal.” The LS 7 score, ranged from 0 to 14, was created from the points and categorized as optimal (11–14), average (9–10), and inadequate (0–8). Hazard ratios and event rates per 1000 person‐years were calculated for outcomes based on self‐reported hospitalizations with the International Classification of Diseases, 9th Revision, diagnoses of cancer, chronic kidney disease, pneumonia, deep venous thromboembolism/pulmonary embolism, chronic obstructive pulmonary disease, dementia, and hip fracture. Analyses were adjusted for age, sex, race/ethnicity, income, and education. Overall, noncardiovascular disease event rates were lower with increasing LS 7 scores. With the inadequate LS 7 score as reference, an optimal score was associated with a decreased risk for noncardiovascular disease events. The hazard ratio for cancer was, 0.80 (0.64–0.98); chronic kidney disease, 0.38 (0.27–0.54); pneumonia, 0.57 (0.40–0.80); deep venous thromboembolism/pulmonary embolism, 0.52 (0.33–0.82), and chronic obstructive pulmonary disease, 0.51 (0.31–0.83). Conclusions The American Heart Association's LS 7 score identified individuals who were vulnerable to multiple chronic nonvascular conditions. These results suggest that improving cardiovascular health will also reduce the burden of cancer and other chronic diseases.

Free radical scavengers have failed to improve patient outcomes, promoting the concept that clinically important oxidative stress may be mediated by alternative mechanisms. We sought to examine the association of emerging aminothiol markers of nonfree radical mediated oxidative stress with clinical outcomes.Plasma levels of reduced (cysteine and glutathione) and oxidized (cystine and glutathione disulphide) aminothiols were quantified by high performance liquid chromatography in 1411 patients undergoing coronary angiography (mean age 63 years, male 66%). All patients were followed for a mean of 4.7 ± 2.1 years for the primary outcome of all-cause death (n=247). Levels of cystine (oxidized) and glutathione (reduced) were associated with risk of death (P0.001 both) before and after adjustment for covariates. High cystine and low glutathione levels (+1 SD and-1 SD, respectively) were associated with higher mortality (adjusted hazard ratio [HR], 1.63; 95% confidence interval [CI], 1.19-2.21; HR, 2.19; 95% CI, 1.50-3.19; respectively) compared with those outside these thresholds. Furthermore, the ratio of cystine/glutathione was also significantly associated with mortality (adjusted HR, 1.92; 95% CI, 1.39-2.64) and was independent of and additive to high-sensitivity C-reactive protein level. Similar associations were found for other outcomes of cardiovascular death and combined death and myocardial infarction.A high burden of oxidative stress, quantified by the plasma aminothiols, cystine, glutathione, and their ratio, is associated with mortality in patients with coronary artery disease, a finding that is independent of and additive to the inflammatory burden. Importantly, these data support the emerging role of nonfree radical biology in driving clinically important oxidative stress.

Background: Atherosclerotic Cardiovascular disease (ASCVD) remains the leading cause of deaths and costs in the US. Despite advancements in therapies, no study has evaluated drivers of pharmaceutical expenditures among individuals with ASCVD. We aimed to assess the economic impact of modifiable risk factors (MRF) on overall pharmaceutical expenditures among ASCVD patients. Methods: We studied the 2012 Medical Expenditure Panel Survey (MEPS) data of adults aged ≥40 years with Body Mass Index ≥18.5Kg/m2 and ICD-9 diagnosis of ASCVD (410, 413, 414, 433, 434, 435, 436, 437, 440, 443, and 447). Using total pharmacy expenditure variable in MEPS as our primary outcome, marginal and actual expenditures associated with predictors were estimated using a two-part econometric model with probit and glm, family(gamma) link (log). Results: Based on the 2012 MEPS, an estimated 140.7 million people in US are aged ≥40 years. An estimated 15.4 million had ASCVD (69±15 years; 41% female). Overall, total pharmaceutical expenditure among those with ASCVD was $52.7 billion (95% CI: $44.2-62.0 billion), which accounted for 33.7% of total pharmaceutical expenditures. Individuals with ASCVD had $1,847 (95% CI: $1,655 - 2,038) incremental pharmaceutical expenditure vs. those without it (p Conclusion: Our study results suggest attainment of favorable modifiable risk status as delineated in AHA 2020 Impact goals can have a beneficial impact on pharmaceutical costs, which accounts for significant proportion of overall healthcare expenditure.