Delayed medical care due to transportation barriers among adults with atherosclerotic cardiovascular disease.

BACKGROUND: In patients with atherosclerotic cardiovascular disease (ASCVD), barriers related to transportation may impair access to care, with potential implications for prognosis. Although few studies have explored transportation barriers among patients with ASCVD, the correlates of delayed care due to transportation barriers have not been examined in this population. We aimed to examine this in U.S. patients with ASCVD using nationally representative data. METHODS: Using data from the 2009-2018 National Health Interview Survey, we estimated the self-reported prevalence of delayed medical care due to transportation barriers among adults with ASCVD, overall and by sociodemographic characteristics. Logistic regression was used to examine the association between various sociodemographic characteristics and delayed care due to transportation barriers. RESULTS: Among adults with ASCVD, 4.5% (95% CI; 4.2, 4.8) or ∼876,000 annually reported delayed care due to transportation barriers. Income (low-income: odds ratio [OR] 4.43, 95% CI [3.04, 6.46]; lowest-income: OR 6.35, 95% CI [4.36, 9.23]) and Medicaid insurance (OR 4.53; 95% CI [3.27, 6.29]) were strongly associated with delayed care due to transportation barriers. Additionally, younger individuals, women, non-Hispanic Black adults, and those from the U.S. South or Midwest, had higher odds of reporting delayed care due to transportation barriers. CONCLUSIONS: Approximately 5% of adults with ASCVD experience delayed care due to transportation barriers. Vulnerable groups include young adults, women, low-income people, and those with public/no insurance. Future studies should analyze the feasibility and potential benefits of interventions such as use of telehealth, mobile clinics, and provision of transportation among patients with ASCVD in the U.S.

Engagement With COVID-19 Public Health Measures in the United States: A Cross-sectional Social Media Analysis from June to November 2020.

BACKGROUND: COVID-19 has continued to spread in the United States and globally. Closely monitoring public engagement and perceptions of COVID-19 and preventive measures using social media data could provide important information for understanding the progress of current interventions and planning future programs. OBJECTIVE: The aim of this study is to measure the public's behaviors and perceptions regarding COVID-19 and its effects on daily life during 5 months of the pandemic. METHODS: Natural language processing (NLP) algorithms were used to identify COVID-19-related and unrelated topics in over 300 million online data sources from June 15 to November 15, 2020. Posts in the sample were geotagged by NetBase, a third-party data provider, and sensitivity and positive predictive value were both calculated to validate the classification of posts. Each post may have included discussion of multiple topics. The prevalence of discussion regarding these topics was measured over this time period and compared to daily case rates in the United States. RESULTS: The final sample size included 9,065,733 posts, 70% of which were sourced from the United States. In October and November, discussion including mentions of COVID-19 and related health behaviors did not increase as it had from June to September, despite an increase in COVID-19 daily cases in the United States beginning in October. Additionally, discussion was more focused on daily life topics (n=6,210,255, 69%), compared with COVID-19 in general (n=3,390,139, 37%) and COVID-19 public health measures (n=1,836,200, 20%). CONCLUSIONS: There was a decline in COVID-19-related social media discussion sourced mainly from the United States, even as COVID-19 cases in the United States increased to the highest rate since the beginning of the pandemic. Targeted public health messaging may be needed to ensure engagement in public health prevention measures as global vaccination efforts continue.

Trends in Differences in Health Status and Health Care Access and Affordability by Race and Ethnicity in the United States, 1999-2018.

IMPORTANCE: The elimination of racial and ethnic differences in health status and health care access is a US goal, but it is unclear whether the country has made progress over the last 2 decades. OBJECTIVE: To determine 20-year trends in the racial and ethnic differences in self-reported measures of health status and health care access and affordability among adults in the US. DESIGN, SETTING, AND PARTICIPANTS: Serial cross-sectional study of National Health Interview Survey data, 1999-2018, that included 596 355 adults. EXPOSURES: Self-reported race, ethnicity, and income level. MAIN OUTCOMES AND MEASURES: Rates and racial and ethnic differences in self-reported health status and health care access and affordability. RESULTS: The study included 596 355 adults (mean [SE] age, 46.2 [0.07] years, 51.8% [SE, 0.10] women), of whom 4.7% were Asian, 11.8% were Black, 13.8% were Latino/Hispanic, and 69.7% were White. The estimated percentages of people with low income were 28.2%, 46.1%, 51.5%, and 23.9% among Asian, Black, Latino/Hispanic, and White individuals, respectively. Black individuals with low income had the highest estimated prevalence of poor or fair health status (29.1% [95% CI, 26.5%-31.7%] in 1999 and 24.9% [95% CI, 21.8%-28.3%] in 2018), while White individuals with middle and high income had the lowest (6.4% [95% CI, 5.9%-6.8%] in 1999 and 6.3% [95% CI, 5.8%-6.7%] in 2018). Black individuals had a significantly higher estimated prevalence of poor or fair health status than White individuals in 1999, regardless of income strata (P < .001 for the overall and low-income groups; P = .03 for middle and high-income group). From 1999 to 2018, racial and ethnic gaps in poor or fair health status did not change significantly, with or without income stratification, except for a significant decrease in the difference between White and Black individuals with low income (-6.7 percentage points [95% CI, -11.3 to -2.0]; P = .005); the difference in 2018 was no longer statistically significant (P = .13). Black and White individuals had the highest levels of self-reported functional limitations, which increased significantly among all groups over time. There were significant reductions in the racial and ethnic differences in some self-reported measures of health care access, but not affordability, with and without income stratification. CONCLUSIONS AND RELEVANCE: In a serial cross-sectional survey study of US adults from 1999 to 2018, racial and ethnic differences in self-reported health status, access, and affordability improved in some subgroups, but largely persisted.

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.

Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study.

BACKGROUND: The current acute kidney injury (AKI) risk prediction model for patients undergoing percutaneous coronary intervention (PCI) from the American College of Cardiology (ACC) National Cardiovascular Data Registry (NCDR) employed regression techniques. This study aimed to evaluate whether models using machine learning techniques could significantly improve AKI risk prediction after PCI. METHODS AND FINDINGS: We used the same cohort and candidate variables used to develop the current NCDR CathPCI Registry AKI model, including 947,091 patients who underwent PCI procedures between June 1, 2009, and June 30, 2011. The mean age of these patients was 64.8 years, and 32.8% were women, with a total of 69,826 (7.4%) AKI events. We replicated the current AKI model as the baseline model and compared it with a series of new models. Temporal validation was performed using data from 970,869 patients undergoing PCIs between July 1, 2016, and March 31, 2017, with a mean age of 65.7 years; 31.9% were women, and 72,954 (7.5%) had AKI events. Each model was derived by implementing one of two strategies for preprocessing candidate variables (preselecting and transforming candidate variables or using all candidate variables in their original forms), one of three variable-selection methods (stepwise backward selection, lasso regularization, or permutation-based selection), and one of two methods to model the relationship between variables and outcome (logistic regression or gradient descent boosting). The cohort was divided into different training (70%) and test (30%) sets using 100 different random splits, and the performance of the models was evaluated internally in the test sets. The best model, according to the internal evaluation, was derived by using all available candidate variables in their original form, permutation-based variable selection, and gradient descent boosting. Compared with the baseline model that uses 11 variables, the best model used 13 variables and achieved a significantly better area under the receiver operating characteristic curve (AUC) of 0.752 (95% confidence interval [CI] 0.749-0.754) versus 0.711 (95% CI 0.708-0.714), a significantly better Brier score of 0.0617 (95% CI 0.0615-0.0618) versus 0.0636 (95% CI 0.0634-0.0638), and a better calibration slope of observed versus predicted rate of 1.008 (95% CI 0.988-1.028) versus 1.036 (95% CI 1.015-1.056). The best model also had a significantly wider predictive range (25.3% versus 21.6%, p < 0.001) and was more accurate in stratifying AKI risk for patients. Evaluated on a more contemporary CathPCI cohort (July 1, 2015-March 31, 2017), the best model consistently achieved significantly better performance than the baseline model in AUC (0.785 versus 0.753), Brier score (0.0610 versus 0.0627), calibration slope (1.003 versus 1.062), and predictive range (29.4% versus 26.2%). The current study does not address implementation for risk calculation at the point of care, and potential challenges include the availability and accessibility of the predictors. CONCLUSIONS: Machine learning techniques and data-driven approaches resulted in improved prediction of AKI risk after PCI. The results support the potential of these techniques for improving risk prediction models and identification of patients who may benefit from risk-mitigation strategies.

Timing of Blood Draws Among Patients Hospitalized in a Large Academic Medical Center.

This study describes the degree to which blood draws occurred among hospitalized patients during traditional sleep hours and investigates trends over time.

Association of marital/partner status with hospital readmission among young adults with acute myocardial infarction.

INTRODUCTION: Despite evidence supporting the benefits of marriage on cardiovascular health, the impact of marital/partner status on the long-term readmission of young acute myocardial infarction (AMI) survivors is less clear. We examined the association between marital/partner status and 1-year all-cause readmission and explored sex differences among young AMI survivors. METHODS: Data were from the VIRGO study (Variation in Recovery: Role of Gender on Outcomes of Young AMI Patients), which enrolled young adults aged 18-55 years with AMI (2008-2012). The primary end point was all-cause readmission within 1 year of hospital discharge, obtained from medical records and patient interviews and adjudicated by a physician panel. We performed Cox proportional hazards models with sequential adjustment for demographic, socioeconomic, clinical, and psychosocial factors. Sex-marital/partner status interaction was also tested. RESULTS: Of the 2,979 adults with AMI (2002 women [67.2%]; mean age 48 [interquartile range, 44-52] years), unpartnered individuals were more likely to experience all-cause readmissions compared with married/partnered individuals within the first year after hospital discharge (34.6% versus 27.2%, hazard ratio [HR] = 1.31; 95% confidence interval [CI], 1.15-1.49). The association attenuated but remained significant after adjustment for demographic and socioeconomic factors (adjusted HR, 1.16; 95% CI, 1.01-1.34), and it was not significant after further adjusting for clinical factors and psychosocial factors (adjusted HR, 1.10; 95%CI, 0.94-1.28). A sex-marital/partner status interaction was not significant (p = 0.69). Sensitivity analysis using data with multiple imputation and restricting outcomes to cardiac readmission yielded comparable results. CONCLUSIONS: In a cohort of young adults aged 18-55 years, unpartnered status was associated with 1.3-fold increased risk of all-cause readmission within 1 year of AMI discharge. Further adjustment for demographic, socioeconomic, clinical, and psychosocial factors attenuated the association, suggesting that these factors may explain disparities in readmission between married/partnered versus unpartnered young adults. Whereas young women experienced more readmission compared to similar-aged men, the association between marital/partner status and 1-year readmission did not vary by sex.

Developing an Actionable Taxonomy of Persistent Hypertension Using Electronic Health Records.

BACKGROUND: The digital transformation of medical data presents opportunities for novel approaches to manage patients with persistent hypertension. We sought to develop an actionable taxonomy of patients with persistent hypertension (defined as 5 or more consecutive measurements of blood pressure ≥160/100 mmHg over time) based on data from the electronic health records. METHODS: This qualitative study was a content analysis of clinician notes in the electronic health records of patients in the Yale New Haven Health System. Eligible patients were 18 to 85 years and had blood pressure ≥160/100 mmHg at 5 or more consecutive outpatient visits between January 1, 2013 and October 31, 2018. A total of 1664 patients met criteria, of which 200 records were randomly selected for chart review. Through a systematic, inductive approach, we developed a rubric to abstract data from the electronic health records and then analyzed the abstracted data qualitatively using conventional content analysis until saturation was reached. RESULTS: We reached saturation with 115 patients, who had a mean age of 66.0 (SD, 11.6) years; 54.8% were female; 52.2%, 30.4%, and 13.9% were White, Black, and Hispanic patients. We identified 3 content domains related to persistence of hypertension: (1) non-intensification of pharmacological treatment, defined as absence of antihypertensive treatment intensification in response to persistent severely elevated blood pressure; (2) non-implementation of prescribed treatment, defined as a documentation of provider recommending a specified treatment plan to address hypertension but treatment plan not being implemented; and (3) non-response to prescribed treatment, defined as clinician-acknowledged persistent hypertension despite documented effort to escalate existing pharmacologic agents and addition of additional pharmacologic agents with presumption of adherence. CONCLUSIONS: This study presents a novel actionable taxonomy for classifying patients with persistent hypertension by their contributing causes based on electronic health record data. These categories can be automated and linked to specific types of actions to address them.

Quantifying Blood Pressure Visit-to-Visit Variability in the Real-World Setting: A Retrospective Cohort Study.

BACKGROUND: Visit-to-visit variability (VVV) in blood pressure values has been reported in clinical studies. However, little is known about VVV in clinical practice and whether it is associated with patient characteristics in real-world setting. METHODS: We conducted a retrospective cohort study to quantify VVV in systolic blood pressure (SBP) values in a real-world setting. We included adults (age ≥18 years) with at least 2 outpatient visits between January 1, 2014 and October 31, 2018 from Yale New Haven Health System. Patient-level measures of VVV included SD and coefficient of variation of a given patient's SBP across visits. We calculated patient-level VVV overall and by patient subgroups. We further developed a multilevel regression model to assess the extent to which VVV in SBP was explained by patient characteristics. RESULTS: The study population included 537 218 adults, with a total of 7 721 864 SBP measurements. The mean age was 53.4 (SD 19.0) years, 60.4% were women, 69.4% were non-Hispanic White, and 18.1% were on antihypertensive medications. Patients had a mean body mass index of 28.4 (5.9) kg/m2 and 22.6%, 8.0%, 9.7%, and 5.6% had a history of hypertension, diabetes, hyperlipidemia, and coronary artery disease, respectively. The mean number of visits per patient was 13.3, over an average period of 2.4 years. The mean (SD) intraindividual SD and coefficient of variation of SBP across visits were 10.6 (5.1) mm Hg and 0.08 (0.04). These measures of blood pressure variation were consistent across patient subgroups defined by demographic characteristics and medical history. In the multivariable linear regression model, only 4% of the variance in absolute standardized difference was attributable to patient characteristics. CONCLUSIONS: The VVV in real-world practice poses challenges for management of patients with hypertension based on blood pressure readings in outpatient settings and suggest the need to go beyond episodic clinic evaluation.

Sex-Specific Associations of Obstructive Sleep Apnea Risk With Patient Characteristics and Functional Outcomes After Acute Myocardial Infarction: Evidence From the VIRGO Study.

Background Though associations between obstructive sleep apnea (OSA) and cardiovascular outcomes are well described, limited data exist regarding the impact of OSA on sex-specific outcomes after acute myocardial infarction (AMI). Methods and Results The VIRGO (Variation in Recovery: Role of Gender on Outcomes of Young AMI Patients) study enrolled 3572 adults aged 18 to 55 years with AMI from the United States and Spain during 2008 to 2012. We included patients for whom the Berlin Questionnaire for OSA was scored at the time of AMI admission (3141; 2105 women, 1036 men). We examined the sex-specific association between baseline OSA risk with functional outcomes including health status and depressive symptoms at 1 and 12 months after AMI. Among both groups, 49% of patients were at high risk for OSA (1040 women; 509 men), but only 4.7% (148) of patients had a diagnosed history of OSA. Though patients with a high OSA risk reported worse physical and mental health status and depression than low-risk patients in both sexes, the difference in these functional outcomes was wider in women than men. Moreover, women with a high OSA risk had worse health status, depression, and quality of life than high-risk men, both at baseline and at 1 and 12 months after AMI. Conclusions Young women with a high OSA risk have poorer health status and more depressive symptoms than men at the time of AMI, which may place them at higher risk of poorer health outcomes over the year following the AMI. Further, the majority of patients at high risk of OSA are undiagnosed at the time of presentation of AMI.

Patterns of Digoxin Prescribing for Medicare Beneficiaries in the United States 2013-2019.

Background: Studies show that digoxin use is declining but is still prevalent. Recent data on digoxin prescription and characteristics of digoxin prescribers are unknown, which can help understand its contemporary use. Methods: Using Medicare Part D data from 2013 to 2019, we studied the change in number and proportion of digoxin prescriptions and digoxin prescribers, overall and by specialty. Using logistic regression, we identified prescriber characteristics associated with digoxin prescription. Results: From 2013 to 2019, total digoxin prescriptions (4.6 to 1.8 million) and proportion of digoxin prescribers decreased (9.1% to 4.3% overall; 26.6% to 11.8% among General Medicine prescribers and 65.4% to 48.9% among Cardiology). Of digoxin prescribers from 2013 practicing in 2019 (91.2% remained active), 59.1% did not prescribe digoxin at all, 31.7% reduced, and 9.2% maintained or increased prescriptions. The proportion of all digoxin prescriptions that were prescribed by General Medicine prescribers declined from 59.7% to 48.2% and increased for Cardiology (29% to 38.5%). Among new prescribers in 2019 (N = 85,508), only 1.9% prescribed digoxin. Digoxin prescribers when compared to non-digoxin prescribers were more likely male, graduated from medical school earlier, were located in the Midwest or South, and belonged to Cardiology (all P < .001). Conclusions: Digoxin prescriptions continue to decline with over half of 2013 prescribers no longer prescribing digoxin in 2019. This may be a result of the increasing availability of newer heart failure therapies. The decline in digoxin prescription was greater among general medicine physicians than cardiologists, suggesting a change in digoxin use to a medication prescribed increasingly by specialists.

Association of Marital/Partner Status with Hospital Readmission Among Young Adults With Acute Myocardial Infarction.

Introduction: Despite evidence supporting the benefits of marriage on cardiovascular health, the impact of marital/partner status on the long-term readmission of young acute myocardial infarction (AMI) survivors is less clear. We aimed to examine the association between marital/partner status and 1-year all-cause readmission, and explore sex differences, among young AMI survivors. Methods: Data were from the VIRGO study (Variation in Recovery: Role of Gender on Outcomes of Young AMI Patients), which enrolled young adults aged 18-55 years with AMI (2008-2012). The primary end point was all-cause readmission within 1 year of hospital discharge, obtained from medical record, patient interviews, and adjudicated by a physician panel. We performed Cox proportional hazards models with sequential adjustment for demographic, socioeconomic, clinical and psychosocial factors. Sex-marital/partner status interaction was also tested. Results: Of the 2,979 adults with AMI (2002 women [67.2%]; mean age 48 [interquartile range, 44-52] years), unpartnered individuals were more likely to experience all-cause readmissions compared with married/partnered individuals within the first year after hospital discharge (34.6% versus 27.2%, hazard ratio [HR]=1.31; 95% confidence interval [CI], 1.15-1.49). The association attenuated but remained significant after adjustment for demographic and socioeconomic factors (adjusted HR, 1.16; 95%CI, 1.01-1.34), and was not significant after further adjusting for clinical factors and psychosocial factors (adjusted HR, 1.10; 95%CI, 0.94-1.28). Sex-marital/partner status interaction was not significant (p=0.69). Sensitivity analysis using data with multiple imputation, and restricting outcomes to cardiac readmission yielded comparable results. Conclusions: In a cohort of young adults aged 18-55 years, unpartnered status was associated with 1.3-fold increased risk of all-cause readmission within 1 year of AMI discharge. Further adjustment for demographic, socioeconomic, clinical and psychosocial factors attenuated the association, suggesting that these factors may explain disparities in readmission between married/partnered versus unpartnered young adults. Whereas young women experienced more readmission compared to similar-aged men, the association between marital/partner status and 1-year readmission did not vary by sex.

Impact of Marital Stress on 1-Year Health Outcomes Among Young Adults With Acute Myocardial Infarction.

Background Stress experienced in a marriage or committed relationship may be associated with worse patient-reported outcomes after acute myocardial infarction (AMI), but little is known about this association in young adults (≤55 years) with AMI. Methods and Results We used data from VIRGO (Variation in Recovery: Role of Gender on Outcomes of Young AMI Patients), an observational cohort study that enrolled individuals aged 18 to 55 years with AMI (2008-2012). Marital stress was self-reported 1 month after AMI using the Stockholm Marital Stress Scale (categorized as absent/mild, moderate, and severe). Outcomes were physical/mental health (Short Form-12), generic health status (EuroQol-5 Dimensions), cardiac-specific quality of life and angina (Seattle Angina Questionnaire), depressive symptoms (Patient Health Questionnaire-9), and all-cause readmission 1 year after AMI. Regression models were sequentially adjusted for baseline health, demographics (sex, age, race or ethnicity), and socioeconomic factors (education, income, employment, and insurance). Sex and marital stress interaction was also tested. Among 1593 married/partnered participants, 576 (36.2%) reported severe marital stress, which was more common in female than male participants (39.4% versus 30.4%, P=0.001). Severe marital stress was significantly associated with worse mental health (beta=-2.13, SE=0.75, P=0.004), generic health status (beta=-3.87, SE=1.46, P=0.008), cardiac-specific quality of life (beta=-6.41, SE=1.65, P<0.001), and greater odds of angina (odds ratio [OR], 1.49 [95% CI, 1.06-2.10], P=0.023) and all-cause readmissions (OR, 1.45 [95% CI, 1.04-2.00], P=0.006), after adjusting for baseline health, demographics, and socioeconomic factors. These associations were similar across sexes (P-interaction all >0.05). Conclusions The association between marital stress and worse 1-year health outcomes was statistically significant in young patients with AMI, suggesting a need for routine screening and the creation of interventions to support patients with stress recovering from an AMI.

Sex Difference in Outcomes of Acute Myocardial Infarction in Young Patients.

BACKGROUND: Younger women experience worse health status than men after their index episode of acute myocardial infarction (AMI). However, whether women have a higher risk for cardiovascular and noncardiovascular hospitalizations in the year after discharge is unknown. OBJECTIVES: The aim of this study was to determine sex differences in causes and timing of 1-year outcomes after AMI in people aged 18 to 55 years. METHODS: Data from the VIRGO (Variation in Recovery: Role of Gender on Outcomes of Young AMI Patients) study, which enrolled young patients with AMI across 103 U.S. hospitals, were used. Sex differences in all-cause and cause-specific hospitalizations were compared by calculating incidence rates ([IRs] per 1,000 person-years) and IR ratios with 95% CIs. We then performed sequential modeling to evaluate the sex difference by calculating subdistribution HRs (SHRs) accounting for deaths. RESULTS: Among 2,979 patients, at least 1 hospitalization occurred among 905 patients (30.4%) in the year after discharge. The leading causes of hospitalization were coronary related (IR: 171.8 [95% CI: 153.6-192.2] among women vs 117.8 [95% CI: 97.3-142.6] among men), followed by noncardiac hospitalization (IR: 145.8 [95% CI: 129.2-164.5] among women vs 69.6 [95% CI: 54.5-88.9] among men). Furthermore, a sex difference was present for coronary-related hospitalizations (SHR: 1.33; 95% CI: 1.04-1.70; P = 0.02) and noncardiac hospitalizations (SHR: 1.51; 95% CI: 1.13-2.07; P = 0.01). CONCLUSIONS: Young women with AMI experience more adverse outcomes than men in the year after discharge. Coronary-related hospitalizations were most common, but noncardiac hospitalizations showed the most significant sex disparity.

National Trends in Racial and Ethnic Disparities in Use of Recommended Therapies in Adults with Atherosclerotic Cardiovascular Disease, 1999-2020.

Importance: Despite efforts to improve the quality of care for patients with atherosclerotic cardiovascular disease (ASCVD), it is unclear whether the US has made progress in reducing racial and ethnic differences in utilization of guideline-recommended therapies for secondary prevention. Objective: To evaluate 21-year trends in racial and ethnic differences in utilization of guideline-recommended pharmacological medications and lifestyle modifications among US adults with ASCVD. Design, Setting, and Participants: This cross-sectional study includes data from the National Health and Nutrition Examination Survey between 1999 and 2020. Eligible participants were adults aged 18 years or older with a history of ASCVD. Data were analyzed between March 2022 and May 2023. Exposure: Self-reported race and ethnicity. Main Outcome and Measures: Rates and racial and ethnic differences in the use of guideline-recommended pharmacological medications and lifestyle modifications. Results: The study included 5218 adults with a history of ASCVD (mean [SD] age, 65.5 [13.2] years, 2148 women [weighted average, 44.2%]), among whom 1170 (11.6%) were Black, 930 (7.7%) were Hispanic or Latino, and 3118 (80.7%) were White in the weighted sample. Between 1999 and 2020, there was a significant increase in total cholesterol control and statin use in all racial and ethnic subgroups, and in angiotensin-converting enzyme inhibitor (ACEI) and angiotensin receptor blocker (ARB) utilization in non-Hispanic White individuals and Hispanic and Latino individuals (Hispanic and Latino individuals: 17.12 percentage points; 95% CI, 0.37-37.88 percentage points; P = .046; non-Hispanic White individuals: 12.14 percentage points; 95% CI, 6.08-18.20 percentage points; P < .001), as well as smoking cessation within the Hispanic and Latino population (-27.13 percentage points; 95% CI, -43.14 to -11.12 percentage points; P = .002). During the same period, the difference in smoking cessation between Hispanic and Latino individuals and White individuals was reduced (-24.85 percentage points; 95% CI, -38.19 to -11.51 percentage points; P < .001), but racial and ethnic differences for other metrics did not change significantly. Notably, substantial gaps persisted between current care and optimal care throughout the 2 decades of data analyzed. In the period of 2017 to 2020, optimal regimens were observed in 47.4% (95% CI, 39.3%-55.4%), 48.7% (95% CI, 36.7%-60.6%), and 53.0% (95% CI, 45.6%-60.4%) of Black, Hispanic and Latino, and White individuals, respectively. Conclusions and Relevance: In this cross-sectional study of US adults with ASCVD, significant disparities persisted between current care and optimal care, surpassing any differences observed among demographic groups. These findings highlight the critical need for sustained efforts to bridge these gaps and achieve better outcomes for all patients, regardless of their racial and ethnic backgrounds.

Developing Validated Tools to Identify Pulmonary Embolism in Electronic Databases: Rationale and Design of the PE-EHR+ Study.

BACKGROUND: Contemporary pulmonary embolism (PE) research, in many cases, relies on data from electronic health records (EHRs) and administrative databases that use International Classification of Diseases (ICD) codes. Natural language processing (NLP) tools can be used for automated chart review and patient identification. However, there remains uncertainty with the validity of ICD-10 codes or NLP algorithms for patient identification. METHODS: The PE-EHR+ study has been designed to validate ICD-10 codes as Principal Discharge Diagnosis, or Secondary Discharge Diagnoses, as well as NLP tools set out in prior studies to identify patients with PE within EHRs. Manual chart review by two independent abstractors by predefined criteria will be the reference standard. Sensitivity, specificity, and positive and negative predictive values will be determined. We will assess the discriminatory function of code subgroups for intermediate- and high-risk PE. In addition, accuracy of NLP algorithms to identify PE from radiology reports will be assessed. RESULTS: A total of 1,734 patients from the Mass General Brigham health system have been identified. These include 578 with ICD-10 Principal Discharge Diagnosis codes for PE, 578 with codes in the secondary position, and 578 without PE codes during the index hospitalization. Patients within each group were selected randomly from the entire pool of patients at the Mass General Brigham health system. A smaller subset of patients will also be identified from the Yale-New Haven Health System. Data validation and analyses will be forthcoming. CONCLUSIONS: The PE-EHR+ study will help validate efficient tools for identification of patients with PE in EHRs, improving the reliability of efficient observational studies or randomized trials of patients with PE using electronic databases.

Temporal Trends in Racial and Ethnic Disparities in Multimorbidity Prevalence in the United States, 1999-2018.

BACKGROUND: Disparities in multimorbidity prevalence indicate health inequalities, as the risk of morbidity does not intrinsically differ by race/ethnicity. This study aimed to determine if multimorbidity differences by race/ethnicity are decreasing over time. METHODS: Serial cross-sectional analysis of the National Health Interview Survey, 1999-2018. Included individuals were ≥18 years old and categorized by self-reported race, ethnicity, age, and income. The main outcomes were temporal trends in multimorbidity prevalence based on the self-reported presence of ≥2 of 9 common chronic conditions. FINDINGS: The study sample included 596,355 individuals (4.7% Asian, 11.8% Black, 13.8% Latino/Hispanic, and 69.7% White). In 1999, the estimated prevalence of multimorbidity was 5.9% among Asian, 17.4% among Black, 10.7% among Latino/Hispanic, and 13.5% among White individuals. Prevalence increased for all racial/ethnic groups during the study period (P ≤ .001 for each), with no significant change in the differences between them. In 2018, compared with White individuals, multimorbidity was more prevalent among Black individuals (+2.5 percentage points) and less prevalent among Asian and Latino/Hispanic individuals (-6.6 and -2.1 percentage points, respectively). Among those aged ≥30 years, Black individuals had multimorbidity prevalence equivalent to that of Latino/Hispanic and White individuals aged 5 years older, and Asian individuals aged 10 years older. CONCLUSIONS: From 1999 to 2018, a period of increasing multimorbidity prevalence for all the groups studied, there was no significant progress in eliminating disparities between Black individuals and White individuals. Public health interventions that prevent the onset of chronic conditions in early life may be needed to eliminate these disparities.

National Trends in Racial and Ethnic Disparities in Antihypertensive Medication Use and Blood Pressure Control Among Adults With Hypertension, 2011-2018.

Poor hypertension awareness and underuse of guideline-recommended medications are critical factors contributing to poor hypertension control. Using data from 8095 hypertensive people aged ≥18 years from the National Health and Nutrition Examination Survey (2011-2018), we examined recent trends in racial and ethnic differences in awareness and antihypertensive medication use, and their association with racial and ethnic differences in hypertension control. Between 2011 and 2018, age-adjusted hypertension awareness declined for Black, Hispanic, and White individuals, but the 3 outcomes increased or did not change for Asian individuals. Compared with White individuals, Black individuals had a similar awareness (odds ratio, 1.20 [0.96-1.45]) and overall treatment rates (1.04 [0.84-1.25]), and received more intensive antihypertensive medication if treated (1.41 [1.27-1.56]), but had a lower control rate (0.72 [0.61-0.83]). Asian and Hispanic individuals had significantly lower awareness rates (0.69 [0.52-0.85] and 0.74 [0.59-0.89]), overall treatment rates (0.72 [0.57-0.88] and 0.69 [0.55-0.82]), received less intensive medication if treated (0.60 [0.50-0.72] and 0.86 [0.75-0.96]), and had lower control rates (0.66 [0.54-0.79] and 0.69 [0.57-0.81]). The racial and ethnic differences in awareness, treatment, and control persisted over the study period and were consistent across age, sex, and income strata. Lower awareness and treatment were significantly associated with lower control in Asian and Hispanic individuals (P<0.01 for all) but not in Black individuals. These findings highlight the need for interventions to improve awareness and treatment among Asian and Hispanic individuals, and more investigation into the downstream factors that may contribute to the poor hypertension control among Black individuals.

Hemodynamic differences between women and men with elevated blood pressure in China: A non-invasive assessment of 45,082 adults using impedance cardiography.

BACKGROUND: Whether there are sex differences in hemodynamic profiles among people with elevated blood pressure is not well understood and could guide personalization of treatment. METHODS AND RESULTS: We described the clinical and hemodynamic characteristics of adults with elevated blood pressure in China using impedance cardiography. We included 45,082 individuals with elevated blood pressure (defined as systolic blood pressure of ≥130 mmHg or a diastolic blood pressure of ≥80 mmHg), of which 35.2% were women. Overall, women had a higher mean systolic blood pressure than men (139.0 [±15.7] mmHg vs 136.8 [±13.8] mmHg, P<0.001), but a lower mean diastolic blood pressure (82.6 [±9.0] mmHg vs 85.6 [±8.9] mmHg, P<0.001). After adjusting for age, region, and body mass index, women <50 years old had lower systemic vascular resistance index (beta-coefficient [ß] -31.7; 95% CI: -51.2, -12.2) and higher cardiac index (ß 0.07; 95% CI: 0.04, 0.09) than men of their same age group, whereas among those ≥50 years old women had higher systemic vascular resistance index (ß 120.4; 95% CI: 102.4, 138.5) but lower cardiac index (ß -0.15; 95% CI: -0.16, -0.13). Results were consistent with a propensity score matching sensitivity analysis, although the magnitude of the SVRI difference was lower and non-significant. However, there was substantial overlap between women and men in the distribution plots of these variables, with overlapping areas ranging from 78% to 88%. CONCLUSIONS: Our findings indicate that there are sex differences in hypertension phenotype, but that sex alone is insufficient to infer an individual's profile.