Detection of Left Ventricular Systolic Dysfunction From Electrocardiographic Images.

BACKGROUND: Left ventricular (LV) systolic dysfunction is associated with a >8-fold increased risk of heart failure and a 2-fold risk of premature death. The use of ECG signals in screening for LV systolic dysfunction is limited by their availability to clinicians. We developed a novel deep learning-based approach that can use ECG images for the screening of LV systolic dysfunction. METHODS: Using 12-lead ECGs plotted in multiple different formats, and corresponding echocardiographic data recorded within 15 days from the Yale New Haven Hospital between 2015 and 2021, we developed a convolutional neural network algorithm to detect an LV ejection fraction <40%. The model was validated within clinical settings at Yale New Haven Hospital and externally on ECG images from Cedars Sinai Medical Center in Los Angeles, CA; Lake Regional Hospital in Osage Beach, MO; Memorial Hermann Southeast Hospital in Houston, TX; and Methodist Cardiology Clinic of San Antonio, TX. In addition, it was validated in the prospective Brazilian Longitudinal Study of Adult Health. Gradient-weighted class activation mapping was used to localize class-discriminating signals on ECG images. RESULTS: Overall, 385 601 ECGs with paired echocardiograms were used for model development. The model demonstrated high discrimination across various ECG image formats and calibrations in internal validation (area under receiving operation characteristics [AUROCs], 0.91; area under precision-recall curve [AUPRC], 0.55); and external sets of ECG images from Cedars Sinai (AUROC, 0.90 and AUPRC, 0.53), outpatient Yale New Haven Hospital clinics (AUROC, 0.94 and AUPRC, 0.77), Lake Regional Hospital (AUROC, 0.90 and AUPRC, 0.88), Memorial Hermann Southeast Hospital (AUROC, 0.91 and AUPRC 0.88), Methodist Cardiology Clinic (AUROC, 0.90 and AUPRC, 0.74), and Brazilian Longitudinal Study of Adult Health cohort (AUROC, 0.95 and AUPRC, 0.45). An ECG suggestive of LV systolic dysfunction portended >27-fold higher odds of LV systolic dysfunction on transthoracic echocardiogram (odds ratio, 27.5 [95% CI, 22.3-33.9] in the held-out set). Class-discriminative patterns localized to the anterior and anteroseptal leads (V2 and V3), corresponding to the left ventricle regardless of the ECG layout. A positive ECG screen in individuals with an LV ejection fraction ≥40% at the time of initial assessment was associated with a 3.9-fold increased risk of developing incident LV systolic dysfunction in the future (hazard ratio, 3.9 [95% CI, 3.3-4.7]; median follow-up, 3.2 years). CONCLUSIONS: We developed and externally validated a deep learning model that identifies LV systolic dysfunction from ECG images. This approach represents an automated and accessible screening strategy for LV systolic dysfunction, particularly in low-resource settings.

Severe aortic stenosis detection by deep learning applied to echocardiography.

BACKGROUND AND AIMS: Early diagnosis of aortic stenosis (AS) is critical to prevent morbidity and mortality but requires skilled examination with Doppler imaging. This study reports the development and validation of a novel deep learning model that relies on two-dimensional (2D) parasternal long axis videos from transthoracic echocardiography without Doppler imaging to identify severe AS, suitable for point-of-care ultrasonography. METHODS AND RESULTS: In a training set of 5257 studies (17 570 videos) from 2016 to 2020 [Yale-New Haven Hospital (YNHH), Connecticut], an ensemble of three-dimensional convolutional neural networks was developed to detect severe AS, leveraging self-supervised contrastive pretraining for label-efficient model development. This deep learning model was validated in a temporally distinct set of 2040 consecutive studies from 2021 from YNHH as well as two geographically distinct cohorts of 4226 and 3072 studies, from California and other hospitals in New England, respectively. The deep learning model achieved an area under the receiver operating characteristic curve (AUROC) of 0.978 (95% CI: 0.966, 0.988) for detecting severe AS in the temporally distinct test set, maintaining its diagnostic performance in geographically distinct cohorts [0.952 AUROC (95% CI: 0.941, 0.963) in California and 0.942 AUROC (95% CI: 0.909, 0.966) in New England]. The model was interpretable with saliency maps identifying the aortic valve, mitral annulus, and left atrium as the predictive regions. Among non-severe AS cases, predicted probabilities were associated with worse quantitative metrics of AS suggesting an association with various stages of AS severity. CONCLUSION: This study developed and externally validated an automated approach for severe AS detection using single-view 2D echocardiography, with potential utility for point-of-care screening.

Physician responses to apple watch-detected irregular rhythm alerts.

BACKGROUND: While the US Food and Drug Administration (FDA) has cleared smartwatch software for detecting atrial fibrillation (AF), there is lack of guidance on management by physicians. We sought to evaluate the approach to management of Apple Watch alerts for AF by physicians and assess whether respondent and case characteristics were associated with their approach. METHODS: We conducted a case-based survey of physicians practicing primary care, emergency medicine, and cardiology at 2 large academic centers (Yale and University of California San Francisco) between September and December 2021. Cases described asymptomatic patients receiving Apple Watch AF alerts; cases varied in sex, race, medical history, and notification frequency. We evaluated physician responses among prespecified diagnostic testing, referral, and treatment options. RESULTS: We emailed 636 physicians, of whom 95 (14.9%) completed the survey, including 39 primary care, 25 emergency medicine, and 31 cardiology physicians. Among a total of 192 cases (16 unique scenarios), physicians selected at least one diagnostic test in 191 (99.5%) cases and medications in 48 (25.0%). Physicians in primary care, emergency medicine, and cardiology reported varying preference for patient referral (14%, 30%, and 16%, respectively; P=.048), rhythm monitoring (84%, 46%, and 94%, respectively; P<.001), measurement of BNP (8%, 20%, and 2%; P=.003), and use of antiarrhythmics (16%, 4%, and 23%; P=.023). There were few physician differences in reported practices across patient demographics (sex and race), clinical complexity, and alert frequency of the clinical case. CONCLUSIONS: In hypothetical cases of patients presenting without clinical symptoms, physicians opted for further diagnostic testing and often to medical intervention based on Apple Watch irregular rhythm notifications. There was also considerable variation across physician specialties, suggesting a need for uniform clinical practice guidelines. Additional study is required before irregular rhythm notifications should be used in clinical settings.

Machine learning in precision diabetes care and cardiovascular risk prediction.

Artificial intelligence and machine learning are driving a paradigm shift in medicine, promising data-driven, personalized solutions for managing diabetes and the excess cardiovascular risk it poses. In this comprehensive review of machine learning applications in the care of patients with diabetes at increased cardiovascular risk, we offer a broad overview of various data-driven methods and how they may be leveraged in developing predictive models for personalized care. We review existing as well as expected artificial intelligence solutions in the context of diagnosis, prognostication, phenotyping, and treatment of diabetes and its cardiovascular complications. In addition to discussing the key properties of such models that enable their successful application in complex risk prediction, we define challenges that arise from their misuse and the role of methodological standards in overcoming these limitations. We also identify key issues in equity and bias mitigation in healthcare and discuss how the current regulatory framework should ensure the efficacy and safety of medical artificial intelligence products in transforming cardiovascular care and outcomes in diabetes.

Association of Body Mass Index and Age With Morbidity and Mortality in Patients Hospitalized With COVID-19: Results From the American Heart Association COVID-19 Cardiovascular Disease Registry.

BACKGROUND: Obesity may contribute to adverse outcomes in coronavirus disease 2019 (COVID-19). However, studies of large, broadly generalizable patient populations are lacking, and the effect of body mass index (BMI) on COVID-19 outcomes- particularly in younger adults-remains uncertain. METHODS: We analyzed data from patients hospitalized with COVID-19 at 88 US hospitals enrolled in the American Heart Association's COVID-19 Cardiovascular Disease Registry with data collection through July 22, 2020. BMI was stratified by World Health Organization obesity class, with normal weight prespecified as the reference group. RESULTS: Obesity, and, in particular, class III obesity, was overrepresented in the registry in comparison with the US population, with the largest differences among adults ≤50 years. Among 7606 patients, in-hospital death or mechanical ventilation occurred in 2109 (27.7%), in-hospital death in 1302 (17.1%), and mechanical ventilation in 1602 (21.1%). After multivariable adjustment, classes I to III obesity were associated with higher risks of in-hospital death or mechanical ventilation (odds ratio, 1.28 [95% CI, 1.09-1.51], 1.57 [1.29-1.91], 1.80 [1.47-2.20], respectively), and class III obesity was associated with a higher risk of in-hospital death (hazard ratio, 1.26 [95% CI, 1.00-1.58]). Overweight and class I to III obese individuals were at higher risk for mechanical ventilation (odds ratio, 1.28 [95% CI, 1.09-1.51], 1.54 [1.29-1.84], 1.88 [1.52-2.32], and 2.08 [1.68-2.58], respectively). Significant BMI by age interactions were seen for all primary end points (P-interaction<0.05 for each), such that the association of BMI with death or mechanical ventilation was strongest in adults ≤50 years, intermediate in adults 51 to 70 years, and weakest in adults >70 years. Severe obesity (BMI ≥40 kg/m2) was associated with an increased risk of in-hospital death only in those ≤50 years (hazard ratio, 1.36 [1.01-1.84]). In adjusted analyses, higher BMI was associated with dialysis initiation and with venous thromboembolism but not with major adverse cardiac events. CONCLUSIONS: Obese patients are more likely to be hospitalized with COVID-19, and are at higher risk of in-hospital death or mechanical ventilation, in particular, if young (age ≤50 years). Obese patients are also at higher risk for venous thromboembolism and dialysis. These observations support clear public health messaging and rigorous adherence to COVID-19 prevention strategies in all obese individuals regardless of age.

Identifying quality of life outcome patterns to inform treatment choices in ischemic cardiomyopathy.

BACKGROUND: The Surgical Treatment for Ischemic Heart Failure (STICH) trial found that routine use of coronary artery bypass surgery (CABG) improved mean quality of life (QoL) scores relative to guideline-directed medical therapy (GDMT) in patients with ischemic cardiomyopathy. However, mean differences in QoL scores do not provide what patients want to know when facing a high-risk/high-benefit treatment choice. METHODS: We analyzed Kansas City Cardiomyopathy Questionnaire (KCCQ) Overall Summary scores in CABG and GDMT patients over 36 months using a combination of statistical methods to group QoL data into clinically relevant outcome patterns (phenotype trajectories) and to then identify the main baseline predictors of each phenotype. QoL outcome phenotypes were developed using mixture models to define the dominant phenotype trajectories present in STICH QoL data. Logistic regression models were used to predict each patient's probability of achieving each outcome pattern with each treatment. RESULTS: In STICH, 592 patients underwent CABG and 607 were managed with GDMT. Our analyses identified 3 phenotype trajectory patterns in both treatment groups. Two of the 3 trajectories showed improving patterns, and were classified as "good QoL trajectories," seen in 498 (84.1%) CABG and 449 (73.9%) GDMT patients. Defining a consequential CABG-GDMT treatment difference as a >10% higher absolute predicted probability of belonging to good QoL trajectories, 277 (23.5%) patients were more likely to have good outcome with CABG while 45 (3.8%) patients were more likely to have a good outcome with GDMT. For 644 (54.7%) patients, CABG and GDMT probabilities of a good outcome were within 5% of each other. CONCLUSIONS: The pattern of QoL outcomes after CABG compared with GDMT in STICH followed 3 main phenotypic trajectories, which could be predicted based on individual baseline features. Patient-specific predictions about expected QoL outcomes with different treatment choices provide an intuitive framework for personalizing patient decision making.

Financial Hardship From Medical Bills Among Adults With Chronic Liver Diseases: National Estimates From the United States.

BACKGROUND AND AIMS: Chronic liver diseases (CLD) affect approximately 2% of the U.S. population and are associated with substantial burden of hospitalization and costs. We estimated the national burden and consequences of financial hardship from medical bills in individuals with CLD. APPROACH AND RESULTS: Using the National Health Interview Survey from 2014 to 2018, we identified individuals with self-reported CLD. We used complex weighted survey analysis to obtain national estimates of financial hardship from medical bills and other financial toxicity measures (eg, cost-related medication nonadherence, personal and/or health care-related financial distress, food insecurity). We evaluated the association of financial hardship from medical bills with unplanned health care use and work productivity, accounting for differences in age, sex, race/ethnicity, insurance, income, education, and comorbidities. Of the 3,666 (representing 5.3 million) U.S. adults with CLD, 1,377 (representing 2 million [37%, 95% CI: 35%-39%]) reported financial hardship from medical bills, including 549 (representing 740,000 [14%, 95% CI: 13%-16%]) who were unable to pay medical bills at all. Adults who were unable to pay medical bills had 8.4-times higher odds of cost-related medication nonadherence (adjusted OR [aOR], 8.39 [95% CI, 5.72-12.32]), 6.3-times higher odds of financial distress (aOR, 6.33 [4.44-9.03]), and 5.6-times higher odds of food insecurity (aOR, 5.59 [3.74-8.37]), as compared to patients without financial hardship from medical bills. Patients unable to pay medical bills had 1.9-times higher odds of emergency department visits (aOR, 1.85 [1.33-2.57]) and 1.8-times higher odds of missing work due to disease (aOR, 1.83 [1.26-2.67]). CONCLUSIONS: One in 3 adults with CLD experience financial hardship from medical bills, and frequently experience financial toxicity and unplanned healthcare use. These financial determinates of health have important implications in the context of value-based care.

Subjective Financial Hardship due to Medical Bills Among Patients With Heart Failure in the United States: The 2014-2018 Medical Expenditure Panel Survey.

BACKGROUND: Heart failure (HF) poses a substantial economic burden on the United States (US) health care system. In contrast, little is known about the financial challenges faced by patients with HF. In this study, we examined the scope and sociodemographic predictors of subjective financial hardship due to medical bills incurred by patients with HF. METHODS: In the Medical Expenditure Panel Survey (MEPS; years 2014--2018), a US nationally representative database, we identified all patients who reported having HF. Any subjective financial hardship due to medical bills was assessed based on patients' reporting either themselves or their families (1) having difficulties paying medical bills in the past 12 months, (2) paying bills late or (3) being unable to pay bills at all. Logistic regression was used to evaluate independent predictors of financial hardship among patients with HF. All analyses took into consideration the survey's complex design. RESULTS: A total of 116,563 MEPS participants were included in the analysis, of whom 858 (0.7%) had diagnoses of HF, representing 1.8 million (95% CI 1.6-2.0) patients annually. Overall, 33% (95% CI 29%-38%) reported any financial hardship due to medical bills, and 13.2% were not able to pay bills at all. Age ≤ 65 years and lower educational attainment were independently associated with higher odds of subjective financial hardship due to medical bills. CONCLUSION: Subjective financial hardship is a prevalent issue for patients with HF in the US, particularly those who are younger and have lower educational attainment. There is a need for policies that reduce out-of-pocket costs for the care of HF, an enhanced identification of this phenomenon in the clinical setting, and approaches to help minimize financial toxicity in patients with HF while ensuring optimal quality of care.

A phenomapping-derived tool to personalize the selection of anatomical vs. functional testing in evaluating chest pain (ASSIST).

AIMS: Coronary artery disease is frequently diagnosed following evaluation of stable chest pain with anatomical or functional testing. A more granular understanding of patient phenotypes that benefit from either strategy may enable personalized testing. METHODS AND RESULTS: Using participant-level data from 9572 patients undergoing anatomical (n = 4734) vs. functional (n = 4838) testing in the PROMISE (PROspective Multicenter Imaging Study for Evaluation of Chest Pain) trial, we created a topological representation of the study population based on 57 pre-randomization variables. Within each patient's 5% topological neighbourhood, Cox regression models provided individual patient-centred hazard ratios for major adverse cardiovascular events and revealed marked heterogeneity across the phenomap [median 1.11 (10th to 90th percentile: 0.52-2.61]), suggestive of distinct phenotypic neighbourhoods favouring anatomical or functional testing. Based on this risk phenomap, we employed an extreme gradient boosting algorithm in 80% of the PROMISE population to predict the personalized benefit of anatomical vs. functional testing using 12 model-derived, routinely collected variables and created a decision support tool named ASSIST (Anatomical vs. Stress teSting decIsion Support Tool). In both the remaining 20% of PROMISE and an external validation set consisting of patients from SCOT-HEART (Scottish COmputed Tomography of the HEART Trial) undergoing anatomical-first vs. functional-first assessment, the testing strategy recommended by ASSIST was associated with a significantly lower incidence of each study's primary endpoint (P = 0.0024 and P = 0.0321 for interaction, respectively), as well as a harmonized endpoint of all-cause mortality or non-fatal myocardial infarction (P = 0.0309 and P < 0.0001 for interaction, respectively). CONCLUSION: We propose a novel phenomapping-derived decision support tool to standardize the selection of anatomical vs. functional testing in the evaluation of stable chest pain, validated in two large and geographically diverse clinical trial populations.

Prevalence and Effects of Food Insecurity and Social Support on Financial Toxicity in and Healthcare Use by Patients With Inflammatory Bowel Diseases.

BACKGROUND & AIMS: We estimated the prevalence of social determinants of health (SDH, food insecurity and social support) in adults with inflammatory bowel diseases (IBD) in the United States and evaluated associations with financial toxicity and healthcare use. METHODS: In the National Health Interview Survey 2015, we identified adults with IBD and estimated the prevalence of food insecurity and/or lack of social support. We evaluated associations with financial toxicity (financial hardship due to medical bills, personal and health-related financial distress, cost-related medication nonadherence, healthcare affordability) and emergency department use. RESULTS: Of estimated 3.1 million adults with IBD in the US, 42% or estimated 1,277,215 patients with IBD reported at least one negative SDH, with 12% reporting both food insecurity and lack of social support. On multivariable analysis adjusting for age, sex, race, family income and comorbidities, patients with food insecurity were significantly more likely to experience financial hardship due to medical bills (odds ratio [OR], 3.31; 95% CI, 1.48-7.39), financial distress (OR, 6.92; 95% CI, 2.28-21.0) and cost-related medication non-adherence (OR, 8.07; 95% CI, 3.16-20.6). Similarly, patients with inadequate social support were significantly more likely to experience financial hardship due to medical bills (OR, 2.98; 95% CI, 1.56-5.67), financial distress (OR, 3.05; 95% CI, 1.64-5.67) and cost-related medication non-adherence (OR, 2.71; 95% CI, 1.10-6.66). Food insecurity and/or lack of social support was not associated with increased risk of emergency department use. CONCLUSIONS: In an analysis of data from the National Health Interview Survey 2015, we found that 1 in 8 patients with IBD have food insecurity and lack social support, which is associated with higher financial toxicity. Patients with IBD should be assessed for SDH to tailor healthcare delivery and improve population health.

Financial burden, distress, and toxicity in cardiovascular disease.

Cardiovascular disease (CVD) is a major source of financial burden and distress, which has 3 main domains: (1) psychological distress; (2) cost-related care non-adherence or medical care deferral, and (3) tradeoffs with basic non-medical needs. We propose 4 ways to reduce financial distress in CVD: (1) policymakers can expand insurance coverage and curtail underinsurance; (2) health systems can limit expenditure on low-benefit, high-cost treatments while developing services for high-risk individuals; (3) physicians can engage in shared-decision-making for high-cost interventions, and (4) community-based initiatives can support patients with system navigation and financial coping. Avenues for research include (1) analysis of how healthcare policies affect financial burden; (2) comparative effectiveness studies examining high and low-cost strategies for CVD management; and (3) studying interventions to reduce financial burden, financial coaching, and community health worker integration.

Electronic health record risk score provides earlier prognostication of clinical outcomes in patients admitted to the cardiac intensive care unit.

In this observational study, we compared the prognostic ability of an electronic health record (EHR)-derived risk score, the Rothman Index (RI), automatically derived on admission, to the first 24-hour Sequential Organ Failure Assessment (SOFA) score for outcome prediction in the modern cardiac intensive care unit (CICU). We found that while the 24-hour SOFA score provided modestly superior discrimination for both in-hospital and CICU mortality, the RI upon CICU admission had better calibration for both outcomes. Given the ubiquitous nature of EHR utilization in the United States, the RI may become an important tool to rapidly risk stratify CICU patients within the ICU and improve resource allocation.

Financial Hardship Among Nonelderly Adults With CKD in the United States.

RATIONALE & OBJECTIVE: The burden of financial hardship among individuals with chronic kidney disease (CKD) has not been extensively studied. Therefore, we describe the scope and determinants of financial hardship among a nationally representative sample of adults with CKD. STUDY DESIGN: Cross-sectional. SETTING & PARTICIPANTS: Nonelderly adults with CKD from the 2014-2018 National Health Interview Survey. EXPOSURE: Sociodemographic and clinical characteristics. OUTCOME: Financial hardship based on medical bills and consequences of financial hardship (high financial distress, food insecurity, cost-related medication nonadherence, delayed/forgone care due to cost). Financial hardship was categorized into 3 levels: no financial hardship, financial hardship but able to pay bills, and unable to pay bills at all. Financial hardship was then modeled in 2 different ways: (1) any financial hardship (regardless of ability to pay) versus no financial hardship and (2) inability to pay bills versus no financial hardship and financial hardship but able to pay bills. ANALYTICAL APPROACH: Nationally representative estimates of financial hardship from medical bills were computed. Multivariable logistic regression models were used to examine the associations of sociodemographic and clinical factors with the outcomes of financial hardship based on medical bills. RESULTS: A total 1,425 individuals, representing approximately 2.1 million Americans, reported a diagnosis of CKD within the past year, of whom 46.9% (95% CI, 43.7%-50.2%) reported experiencing financial hardship from medical bills; 20.9% (95% CI, 18.5%-23.6%) reported inability to pay medical bills at all. Lack of insurance was the strongest determinant of financial hardship in this population (odds ratio, 4.06 [95% CI, 2.18-7.56]). LIMITATIONS: Self-reported nature of CKD diagnosis. CONCLUSIONS: Approximately half the nonelderly US population with CKD experiences financial hardship from medical bills that is associated strongly with lack of insurance. Evidence-based clinical and policy interventions are needed to address these hardships.

Characteristics of cardiac catheterization laboratory directors at the 2017 U.S. News & World Report top 100 U.S. cardiovascular hospitals.

INTRODUCTION: The cardiac catheterization laboratory (CCL) is a focal point for cardiovascular programs and the CCL director represents the key personnel. We outline profiles of CCL directors at the 2017 U.S. News & World Report top 100 U.S. cardiovascular hospitals. METHODS: Using hospital websites, LinkedIn, Healthgrades, Medicare Provider Utilization and Payment Data 2017, and Scopus, we described CCL directors (in 2017) by age, gender, years since medical graduation, international medical school graduate (IMG) status, academic rank, provider clinical focus, and Hirsch (h)-index. RESULTS: Nearly all CCL directors were male (97%). The median age (interquartile range [IQR]) was 53 (49-61) years and median (IQR) years since medical school graduation was 28 (23-35) years. Over a third of CCL directors (39.4%) were IMGs and 38.4% had completed fellowship training at the same facility where they were CCL director. The median (IQR) h-index was 11 (6-22). Of the 69.7% CCL directors who held faculty positions, 60.9% were professors and 30.4% were associate professors. From Medicare data, 45.5% performed only percutaneous coronary interventions, 41.4% performed structural interventions, 3.0% peripheral interventions, and 2.0% performed both structural and peripheral. CCL directors at the top 25 hospitals had higher h-indexes, and more likely to have completed fellowship training at their own institution. CONCLUSIONS: There are very few women CCL directors at the top U.S. cardiovascular hospitals. A third of the CCL directors were IMGs. A significant proportion of CCL directors primarily performed structural interventions and trained at the same institution, more so at the top 25 hospitals.

Pulselessness After Initiation of Cardiopulmonary Resuscitation for Bradycardia in Hospitalized Children.

BACKGROUND: Cardiopulmonary resuscitation (CPR) is initiated in hospitalized children with bradycardia and poor perfusion. However, their rate of progression to pulseless cardiac arrest despite CPR and the differences in survival compared with initially pulseless arrest are unknown. We examined the prevalence and predictors of survival of children who progress from bradycardia to pulseless in-hospital cardiac arrest despite CPR. METHODS: Pediatric patients >30 days and <18 years of age who received CPR at hospitals participating in Get With The Guidelines-Resuscitation during 2000 to 2016 were included. Each CPR event was classified as bradycardia with pulse, bradycardia with subsequent pulselessness, and initial pulseless cardiac arrest. We assessed risk-adjusted rates of survival to hospital discharge using multilevel Poisson regression models. RESULTS: Overall, 5592 pediatric patients were treated with CPR, of whom 2799 (50.1%) received CPR for bradycardia with poor perfusion and 2793 (49.9%) for initial pulseless cardiac arrest. Among those with bradycardia, 869 (31.0%, or 15.5% of cohort) became pulseless after a median of 3 minutes of CPR (interquartile range, 1-9 minutes). Rates of survival to discharge were 70.0% (1351 of 1930) for bradycardia with pulse, 30.1% (262 of 869) for bradycardia progressing to pulselessness, and 37.5% (1046 of 2793) for initial pulseless cardiac arrest (P for difference across groups <0.001). Children who became pulseless despite CPR for bradycardia had a 19% lower likelihood (risk ratio, 0.81 [95% CI, 0.70, 0.93]; P=0.004) of surviving to hospital discharge than those who were initially pulseless. Among children who progressed to pulselessness despite CPR for bradycardia, a longer interval between CPR and pulselessness was a predictor of lower survival (reference, <2 minutes; for 2-5 minutes, risk ratio, 0.54 [95% CI, 0.41-0.70]; for >5 minutes, risk ratio, 0.41 [95% CI, 0.32-0.53]). CONCLUSIONS: Among hospitalized children in whom CPR is initiated, half have bradycardia with poor perfusion at the initiation of chest compressions, and nearly one-third of these progress to pulseless in-hospital cardiac arrest despite CPR. Survival was significantly lower for children who progress to pulselessness despite CPR compared with those who were initially pulseless. These findings suggest that pediatric patients who lose their pulse despite resuscitation attempts are at particularly high risk and require a renewed focus on postresuscitation care.

Cost-Related Medication Nonadherence in Adults With Atherosclerotic Cardiovascular Disease in the United States, 2013 to 2017.

BACKGROUND: Medication nonadherence is associated with worse outcomes in patients with atherosclerotic cardiovascular disease (ASCVD), a group who requires long-term therapy for secondary prevention. It is important to understand to what extent drug costs, which are potentially actionable factors, contribute to medication nonadherence. METHODS: In a nationally representative survey of US adults in the National Health Interview Survey (2013-2017), we identified individuals ≥18 years with a reported history of ASCVD. Participants were considered to have experienced cost-related nonadherence (CRN) if in the preceding 12 months they reported skipping doses to save money, taking less medication to save money, or delaying filling a prescription to save money. We used survey analysis to obtain national estimates. RESULTS: Of the 14 279 surveyed individuals with ASCVD, a weighted 12.6% (or 2.2 million [95% CI, 2.1-2.4]) experienced CRN, including 8.6% or 1.5 million missing doses, 8.8% or 1.6 million taking lower than prescribed doses, and 10.5% or 1.9 million intentionally delaying a medication fill to save costs. Age <65 years, female sex, low family income, lack of health insurance, and high comorbidity burden were independently associated with CRN, with >1 in 5 reporting CRN in these subgroups. Survey respondents with CRN compared with those without CRN had 10.8-fold higher odds of requesting low-cost medications and 8.9-fold higher odds of using alternative, nonprescription, therapies. CONCLUSIONS: One in 8 patients with ASCVD reports nonadherence to medications because of cost. The removal of financial barriers to accessing medications, particularly among vulnerable patient groups, may help improve adherence to essential therapy to reduce ASCVD morbidity and mortality.

Association Between Sociodemographic Determinants and Disparities in Stroke Symptom Awareness Among US Young Adults.

BACKGROUND AND PURPOSE: Despite declining stroke rates in the general population, stroke incidence and hospitalizations are rising among younger individuals. Awareness of and prompt response to stroke symptoms are crucial components of a timely diagnosis and disease management. We assessed awareness of stroke symptoms and response to a perceived stroke among young adults in the United States. METHODS: Using data from the 2017 National Health Interview Survey, we assessed awareness of 5 common stroke symptoms and the knowledge of planned response (ie, calling emergency medical services) among young adults (<45 years) across diverse sociodemographic groups. Common stroke symptoms included: (1) numbness of face/arm/leg, (2) confusion/trouble speaking, (3) difficulty walking/dizziness/loss of balance, (4) trouble seeing in one/both eyes, and (5) severe headache. RESULTS: Our study population included 24 769 adults, of which 9844 (39.7%) were young adults who were included in our primary analysis, and represented 107.2 million US young adults (mean age 31.3 [±7.5] years, 50.6% women, and 62.2% non-Hispanic White). Overall, 2718 young adults (28.9%) were not aware of all 5 stroke symptoms, whereas 242 individuals (2.7%; representing 2.9 million young adults in the United States) were not aware of a single symptom. After adjusting for confounders, Hispanic ethnicity (odds ratio, 1.96 [95% CI, 1.17-3.28]), non-US born immigration status (odds ratio, 2.02 [95% CI, 1.31-3.11]), and lower education level (odds ratio, 2.77 [95% CI, 1.76-4.35]), were significantly associated with lack of symptom awareness. Individuals with 5 high-risk characteristics (non-White, non-US born, low income, uninsured, and high school educated or lower) had nearly a 4-fold higher odds of not being aware of all symptoms (odds ratio, 3.70 [95% CI, 2.43-5.62]). CONCLUSIONS: Based on data from the National Health Interview Survey, a large proportion of young adults may not be aware of stroke symptoms. Certain sociodemographic subgroups with decreased awareness may benefit from focused public health interventions.

Cost-minimization study of the percutaneous approach to endovascular aortic aneurysm repair.

OBJECTIVE: Percutaneous access for endovascular aortic aneurysm repair (P-EVAR) is less invasive compared with surgical access for endovascular aortic aneurysm repair (S-EVAR). P-EVAR has been associated with shorter recovery and fewer wound complications. However, vascular closure devices (VCDs) are costly, and the economic effects of P-EVAR have important implications for resource allocation. The objective of our study was to estimate the differences in the costs between P-EVAR and S-EVAR. METHODS: We used a decision tree to analyze the costs from a payer perspective throughout the course of the index hospitalization. The probabilities, relative risks, and mean difference summary measures were obtained from a systematic review and meta-analysis. We modelled differences in surgical site infection, lymphocele, and the length of hospitalization. Cost parameters were derived from the 2014 National Inpatient Sample using "International Classification of Diseases, 9th Revision, Clinical Modification" codes. Attributable costs were estimated using generalized linear models adjusted by age, sex, and comorbidities. A sensitivity analysis was performed to determine the robustness of the results. RESULTS: A total of 6876 abdominal and thoracic EVARs were identified. P-EVAR resulted in a mean cost savings of $751 per procedure. The mean costs for P-EVAR were $1287 (95% confidence interval [CI], $884-$1835) and for S-EVAR were $2038 (95% CI, $757-$4280). P-EVAR procedures were converted to open procedures in 4.3% of the cases. The P-EVAR patients had a difference of -1.4 days (95% CI, -0.12 to -2.68) in the length of hospitalization at a cost of $1190/d (standard error, $298). The cost savings of P-EVAR was primarily driven by the cost differences in the length of hospitalization. In the base case, four VCDs were used per P-EVAR at $200/device. In the two-way sensitivity analysis, P-EVAR resulted in cost savings, even when 1.5 times more VCDs had been used per procedure and the cost of each VCD was 1.5 times greater. In our probabilistic sensitivity analysis, P-EVAR was the cost savings strategy for 82.6% of 10,000 Monte Carlo simulations when simultaneously varying parameters across their uncertainty ranges. CONCLUSIONS: P-EVAR had lower costs compared with S-EVAR and could result in dramatic cost savings if extrapolated to the number of aortic aneurysms repaired. Our analysis was a conservative estimate that did not account for the improved quality of life after P-EVAR.

Financial Hardship After Traumatic Injury: Risk Factors and Drivers of Out-of-Pocket Health Expenses.

BACKGROUND: Trauma-related disorders rank among the top five most costly medical conditions to the health care system. However, the impact of out-of-pocket (OOP) health expenses for traumatic conditions is not known. In this cross-sectional study, we use nationally representative data to investigate whether patients with a traumatic injury experienced financial hardship from OOP health expenses. METHODS: Using data from the Medical Expenditure Panel Survey from 2010 to 2015, we analyzed the financial burden associated with a traumatic injury. Primary outcomes were excess financial burden (OOP>20% of annual income) and catastrophic medical expenses (OOP>40% of annual income). A multivariable logistic regression analysis evaluated whether these outcomes were associated with traumatic injury, adjusting for demographic, socioeconomic, and health care factors. We then completed a descriptive analysis to elucidate drivers of total OOP expenses. RESULTS: Of the 90,964 families in the cohort, 6434 families had a traumatic injury requiring a visit to the emergency room and 668 families had a traumatic injury requiring hospitalization. Overall 1 in 8 households with an injured family member requiring hospitalization experienced financial hardship. These families were more likely to experience excess financial burden (OR: 2.04, 95% CI: 1.13-3.64) and catastrophic medical expenses (OR: 3.08, 95% CI: 1.37-6.9). The largest burden of OOP expenses was due to prescription drug costs, with inpatient costs as a major driver of OOP expenses for those requiring hospitalization. CONCLUSIONS: Households with an injured family member requiring hospitalization are significantly more vulnerable to financial hardship from OOP health expenses than the noninjured population. Prescription drug and inpatient costs were the most significant drivers of OOP health expenses.

Increasing Sepsis Rates in the United States: Results From National Inpatient Sample, 2005 to 2014.

OBJECTIVES: To examine the trends in hospitalization rates, mortality, and costs for sepsis during the years 2005 to 2014. METHODS: This was a retrospective serial cross-sectional analysis of patients ≥18 years admitted for sepsis in National Inpatient Sample. Trends in sepsis hospitalizations were estimated, and age- and sex-adjusted rates were calculated for the years 2005 to 2014. RESULTS: There were 541 694 sepsis admissions in 2005 and increased to 1 338 905 in 2014. Sepsis rates increased significantly from 1.2% to 2.7% during the years 2005 to 2014 (relative increase: 123.8%; P trend < .001). However, the relative increase changed by 105.8% (P trend < .001) after adjusting for age and sex and maintained significance. Although total cost of hospitalization due to sepsis increased significantly from US$22.2 to US$38.1 billion (P trend < .001), the mean hospitalization cost decreased significantly from US$46,470 to US$29,290 (P trend < .001). CONCLUSIONS: Hospitalizations for sepsis increased during the years 2005 to 2014. Our study paradoxically found declining rates of in-hospital mortality, length of stay, and mean hospitalization cost for sepsis. These findings could be due to biases introduced by International Classification of Diseases, Ninth Revision, Clinical Modification coding rules and increased readmission rates or alternatively due to increased awareness and surveillance and changing disposition status. Standardized epidemiologic registries should be developed to overcome these biases.