Optimizing Care Delivery in Patients with Chronic Kidney Disease in the United States: Proceedings of a Multidisciplinary Roundtable Discussion and Literature Review.

BACKGROUND: Approximately 37 million individuals in the United States (US) have chronic kidney disease (CKD). Patients with CKD have a substantial morbidity and mortality, which contributes to a huge economic burden to the healthcare system. A limited number of clinical pathways or defined workflows exist for CKD care delivery in the US, primarily due to a lower prioritization of CKD care within health systems compared with other areas (e.g., cardiovascular disease [CVD], cancer screening). CKD is a public health crisis and by the year 2040, CKD will become the fifth leading cause of years of life lost. It is therefore critical to address these challenges to improve outcomes in patients with CKD. METHODS: The CKD Leaders Network conducted a virtual, 3 h, multidisciplinary roundtable discussion with eight subject-matter experts to better understand key factors impacting CKD care delivery and barriers across the US. A premeeting survey identified topics for discussion covering the screening, diagnosis, risk stratification, and management of CKD across the care continuum. Findings from this roundtable are summarized and presented herein. RESULTS: Universal challenges exist across health systems, including a lack of awareness amongst providers and patients, constrained care team bandwidth, inadequate financial incentives for early CKD identification, non-standardized diagnostic classification and triage processes, and non-centralized patient information. Proposed solutions include highlighting immediate and long-term financial implications linked with failure to identify and address at-risk individuals, identifying and managing early-stage CKD, enhancing efforts to support guideline-based education for providers and patients, and capitalizing on next-generation solutions. CONCLUSIONS: Payers and other industry stakeholders have opportunities to contribute to optimal CKD care delivery. Beyond addressing the inadequacies that currently exist, actionable tactics can be implemented into clinical practice to improve clinical outcomes in patients at risk for or diagnosed with CKD in the US.

Retrospective comparison of traditional and artificial intelligence-based heart failure phenotyping in a US health system to enable real-world evidence.

OBJECTIVE: Quantitatively evaluate the quality of data underlying real-world evidence (RWE) in heart failure (HF). DESIGN: Retrospective comparison of accuracy in identifying patients with HF and phenotypic information was made using traditional (ie, structured query language applied to structured electronic health record (EHR) data) and advanced (ie, artificial intelligence (AI) applied to unstructured EHR data) RWE approaches. The performance of each approach was measured by the harmonic mean of precision and recall (F1 score) using manual annotation of medical records as a reference standard. SETTING: EHR data from a large academic healthcare system in North America between 2015 and 2019, with an expected catchment of approximately 5 00 000 patients. POPULATION: 4288 encounters for 1155 patients aged 18-85 years, with 472 patients identified as having HF. OUTCOME MEASURES: HF and associated concepts, such as comorbidities, left ventricular ejection fraction, and selected medications. RESULTS: The average F1 scores across 19 HF-specific concepts were 49.0% and 94.1% for the traditional and advanced approaches, respectively (p<0.001 for all concepts with available data). The absolute difference in F1 score between approaches was 45.1% (98.1% relative increase in F1 score using the advanced approach). The advanced approach achieved superior F1 scores for HF presence, phenotype and associated comorbidities. Some phenotypes, such as HF with preserved ejection fraction, revealed dramatic differences in extraction accuracy based on technology applied, with a 4.9% F1 score when using natural language processing (NLP) alone and a 91.0% F1 score when using NLP plus AI-based inference. CONCLUSIONS: A traditional RWE generation approach resulted in low data quality in patients with HF. While an advanced approach demonstrated high accuracy, the results varied dramatically based on extraction techniques. For future studies, advanced approaches and accuracy measurement may be required to ensure data are fit-for-purpose.

Characterization of Individuals With Apparent Resistant Hypertension Using Contemporary Guidelines: Insights From CV-QUIC.

BACKGROUND: Apparent resistant hypertension (aRH) carries excess cardiovascular risk beyond nonresistant forms of hypertension; however, our understanding of this at-risk population, as defined by current US practice guidelines, is limited. Accordingly, we sought to evaluate the prevalence, clinical characteristics, and pharmacotherapeutic patterns of patients with aRH using contemporary blood pressure guidance. METHODS: We classified patients at 3 large healthcare systems by hypertensive status using contemporary hypertension guidelines. We subsequently described the demographic and clinical characteristics of patients with aRH and compared these factors among hypertensive patients without aRH and between those with controlled and uncontrolled aRH. RESULTS: A total of 2 420 468 patients were analyzed, of whom 1 343 489 (55.6%) were hypertensive according to contemporary guidelines. Among hypertensive patients, 11 992 (8.5%) met criteria for aRH, with nearly all assessed comorbid conditions, particularly diabetes and heart failure, being more common in those with aRH. When compared with patients with uncontrolled aRH, those with controlled aRH were more frequently prescribed a beta-blocker, diuretic, and nitrate, with the largest standardized difference observed for a mineralocorticoid receptor antagonist (35.4% versus 10.4%, Cohen D 0.62). Consistent findings were noted in sensitivity analyses using the blood pressure threshold of 140/90 mm Hg. CONCLUSIONS: In an analysis of over 2.4 million individuals, a lower prevalence of aRH was observed than previously reported (12%-15%), but with a high burden of comorbidities. Identification of differences in pharmacotherapy between patients with controlled and uncontrolled aRH, particularly lower rates of mineralocorticoid receptor antagonist use, help define potential opportunities to improve care and lower cardiovascular risk.

Sociodemographic determinants of oral anticoagulant prescription in patients with atrial fibrillations: findings from the PINNACLE registry using machine learning.

Background: Current risk scores that are solely based on clinical factors have shown modest predictive ability for understanding of factors associated with gaps in real-world prescription of oral anticoagulation (OAC) in patients with atrial fibrillation (AF). Objective: In this study, we sought to identify the role of social and geographic determinants, beyond clinical factors associated with variation in OAC prescriptions using a large national registry of ambulatory patients with AF. Methods: Between January 2017 and June 2018, we identified patients with AF from the American College of Cardiology PINNACLE (Practice Innovation and Clinical Excellence) Registry. We examined associations between patient and site-of-care factors and prescription of OAC across U.S. counties. Several machine learning (ML) methods were used to identify factors associated with OAC prescription. Results: Among 864,339 patients with AF, 586,560 (68%) were prescribed OAC. County OAC prescription rates ranged from 26.8% to 93%, with higher OAC use in the Western United States. Supervised ML analysis in predicting likelihood of OAC prescriptions and identified a rank order of patient features associated with OAC prescription. In the ML models, in addition to clinical factors, medication use (aspirin, antihypertensives, antiarrhythmic agents, lipid modifying agents), and age, household income, clinic size, and U.S. region were among the most important predictors of an OAC prescription. Conclusion: In a contemporary, national cohort of patients with AF underuse of OAC remains high, with notable geographic variation. Our results demonstrated the role of several important demographic and socioeconomic factors in underutilization of OAC in patients with AF.

Clinical Trial Participation and COVID-19: a Descriptive Analysis from the American Heart Association's Get With The Guidelines Registry.

As COVID-19 cases begin to decrease in the USA, learning from the pandemic experience will provide insights regarding disparities of care delivery. We sought to determine if specific populations hospitalized with COVID-19 are equally likely to be enrolled in clinical trials. We examined patients hospitalized with COVID-19 at centers participating in the American Heart Association's COVID-19 CVD Registry. The primary outcome was odds of enrollment in a clinical trial, according to sex, race, and ethnicity. Among 14,397 adults hospitalized with COVID-19, 9.5% (n = 1,377) were enrolled in a clinical trial. The proportion of enrolled patients was the lowest for Black patients (8%); in multivariable analysis, female and Black patients were less likely to be enrolled in a clinical trial related to COVID-19 compared to men and other racial groups, respectively. Determination of specific reasons for the disparities in trial participation related to COVID-19 in these populations should be further investigated.

Leveraging Healthcare System Data to Identify High-Risk Dyslipidemia Patients.

PURPOSE OF REVIEW: While randomized controlled trials have historically served as the gold standard for shaping guideline recommendations, real-world data are increasingly being used to inform clinical decision-making. We describe ways in which healthcare systems are generating real-world data related to dyslipidemia and how these data are being leveraged to improve patient care. RECENT FINDINGS: The electronic medical record has emerged as a major source of clinical data, which alongside claims and pharmacy dispending data is enabling healthcare systems the ability to identify care gaps (underdiagnosis and undertreatment) in patients with dyslipidemia. Availability of this data also allows healthcare systems the ability to test and deliver interventions at the point-of-care. Real-world data possess great potential as a complement to randomized controlled trials. Healthcare systems are uniquely positioned to not only define care gaps and areas of opportunity, but to also to leverage tools (e.g., clinical decision support, case identification) aimed at closing them.

Potential Impact of 2017 American College of Cardiology/American Heart Association Hypertension Guideline on Contemporary Practice: A Cross-Sectional Analysis From NCDR PINNACLE Registry.

Background Clinical implications of change in the 2017 American College of Cardiology (ACC)/American Heart Association (AHA) guideline on the diagnosis and management of hypertension, compared with recommendations by 2014 expert panel and Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC7), are not known. Methods and Results Using data from the NCDR (National Cardiovascular Data Registry) PINNACLE (Practice Innovation and Clinical Excellence) Registry (January 2013-Decemver 2016), we compared the proportion and clinical characteristics of patients seen in cardiology practices diagnosed with hypertension, recommended antihypertensive treatment, and achieving blood pressure (BP) goals per each guideline document. In addition, we evaluated the proportion of patients at the level of practices meeting BP targets defined by each guideline. Of 6 042 630 patients evaluated, 5 027 961 (83.2%) were diagnosed with hypertension per the 2017 ACC/AHA guideline, compared with 4 521 272 (74.8%) per the 2014 panel and 4 545 976 (75.2%) per JNC7. The largest increase in hypertension prevalence was seen in younger ages, women, and those with lower cardiovascular risk. Antihypertensive medication was recommended to 70.6% of patients per the ACC/AHA guideline compared with 61.8% and 65.9% per the 2014 panel and JNC7, respectively. Among those on antihypertensive agents, 41.2% achieved BP targets per the ACC/AHA guideline, compared with 79.4% per the 2014 panel and 64.3% per JNC7. Lower proportions of women, non-White (Black and "other") races, and those at higher cardiovascular risk achieved BP goals. Median practice-level proportion of patients meeting BP targets per the 2014 panel but not the ACC/AHA guideline was 37.8% (interquartile range, 34.8%-40.7%) and per JNC7 but not the ACC/AHA guideline was 22.9% (interquartile range, 19.8%-25.9%). Conclusions Following publication of the 2017 guideline, significantly more people, particularly younger people and those with lower cardiovascular risk, will be diagnosed with hypertension and need antihypertensive treatment compared with previous recommendations. Significant practice-level variation in BP control also exists. Efforts are needed to improve guideline-concordant hypertension management in an effort to improve outcomes.

Fulminant Myocarditis Following SARS-CoV-2 Infection: JACC Patient Care Pathways.

A 60-year-old woman with a past medical history of asthma presented with fulminant myocarditis 9 days after testing positive for SARS-CoV-2 and 16 days after developing symptoms consistent with COVID-19. Her hospital course was complicated by the need for veno-arterial extracorporeal membrane oxygenation, ventricular arrhythmias, and pseudomonas bacteremia. She ultimately recovered and was discharged to home with normal left ventricular systolic function. Thereafter, she developed symptomatic ventricular tachycardia, for which she received an implantable cardioverter-defibrillator and antiarrhythmic drug therapy.

Fulminant Myocarditis Following SARS-CoV-2 Infection: JACC Patient Care Pathways.

A 60-year-old woman with a past medical history of asthma presented with fulminant myocarditis 9 days after testing positive for SARS-CoV-2 and 16 days after developing symptoms consistent with COVID-19. Her hospital course was complicated by the need for veno-arterial extracorporeal membrane oxygenation, ventricular arrhythmias, and pseudomonas bacteremia. She ultimately recovered and was discharged to home with normal left ventricular systolic function. Thereafter, she developed symptomatic ventricular tachycardia, for which she received an implantable cardioverter-defibrillator and antiarrhythmic drug therapy.

Temporal trends and predictors of surgical ablation for atrial fibrillation across a multistate healthcare system.

BACKGROUND: Multiple class I and class IIa recommendations exist related to surgical ablation (SA) of atrial fibrillation (AF) in patients undergoing cardiac surgery. OBJECTIVE: Examine temporal trends and predictors of SA for AF in a large US healthcare system. METHODS: We retrospectively analyzed data from the Society for Thoracic Surgery (STS) Adult Cardiac Surgery Database for 21 hospitals in the Providence St. Joseph Health system. All patients with preoperative AF who underwent isolated coronary artery bypass graft (CABG) surgery, isolated aortic valve replacement (AVR), AVR with CABG surgery (AVR+CABG), isolated mitral valve repair or replacement (MVRr), and MVRr with CABG surgery (MVRr+CABG) from July 1, 2014, to March 31, 2020 were included. Temporal trends in SA were evaluated using the Cochran-Armitage trends test. A multilevel logistic regression model was used to examine patient-, hospital-, and surgeon-level predictors of SA. RESULTS: Among 3124 patients with preoperative AF, 910 (29.1%) underwent SA. This was performed most often in those undergoing isolated MVRr (n = 324, 44.8%) or MVRr+CABG (n = 75, 35.2%). Rates of SA increased over time and were highly variable between hospitals. Years since graduation from medical school for the primary operator was one of the few predictors of SA: odds ratio (95% confidence interval) = 0.71 (0.56-0.90) for every 10-year increase. Annual surgical (both hospital and operator) and AF catheter ablation volumes were not predictive of SA. CONCLUSION: Wide variability in rates of SA for AF exist, underscoring the need for greater preoperative collaboration between cardiologists, electrophysiologists, and cardiac surgeons.

Discordance Between Standard Equations for Determination of LDL Cholesterol in Patients With Atherosclerosis.

BACKGROUND: Accurate estimation of low-density lipoprotein cholesterol (LDL-C) is important for guiding cholesterol-lowering therapy. Different methods currently exist to estimate LDL-C. OBJECTIVES: This study sought to assess discordance of estimated LDL-C using the Friedewald, Sampson, and Martin/Hopkins equations. METHODS: Electronic health record data from patients with atherosclerotic cardiovascular disease and triglyceride (TG) levels of <400 mg/dL between October 1, 2015, and June 30, 2019, were retrospectively analyzed. LDL-C was estimated using the Friedewald, Sampson, and Martin/Hopkins equations. Patients were categorized as concordant if LDL-C was <70 mg/dL with each pairwise comparison of equations and as discordant if LDL-C was <70 mg/dL for the index equation and ≥70 mg/dL for the comparator. RESULTS: The study included 146,106 patients with atherosclerotic cardiovascular disease (mean age: 68 years; 56% male; 91% White). The Martin/Hopkins equation consistently estimated higher LDL-C values than the Friedewald and Sampson equations. Discordance rates were 15% for the Friedewald vs Martin/Hopkins comparison, 9% for the Friedewald vs Sampson comparison, and 7% for the Sampson vs Martin/Hopkins comparison. Discordance increased at lower LDL-C cutpoints and in those with elevated TG levels. Among patients with TG levels of ≥150 mg/dL, a >10 mg/dL difference in LDL-C was present in 67%, 27%, and 23% of patients when comparing the Friedewald vs Martin/Hopkins, Friedewald vs Sampson, and Sampson vs Martin/Hopkins equations, respectively. CONCLUSIONS: Clinically meaningful differences in estimated LDL-C exist among equations, particularly at TG levels of ≥150 mg/dL and/or lower LDL-C levels. Reliance on the Friedewald and Sampson equations may result in the underestimation and undertreatment of LDL-C in those at increased risk.

A simplified approach to identification of risk status in patients with atherosclerotic cardiovascular disease.

OBJECTIVE: The 2018 American Heart Association/American College of Cardiology (AHA/ACC) Blood Cholesterol Guideline recommendation to classify patients with atherosclerotic cardiovascular disease (ASCVD) as very high-risk (VHR) vs not-VHR (NVHR) has important implications for escalation of medical therapy. We aimed to define the prevalence and clinical characteristics of these two groups within a large multi-state healthcare system and develop a simpler means to assist clinicians in identifying VHR patients using classification and regression tree (CART) analysis. METHODS: We performed a retrospective analysis of all patients in a 28-hospital US healthcare system in 2018. ICD-10 codes were used to define the ASCVD population. Per the AHA/ACC Guideline, VHR status was defined by ≥2 major ASCVD events or 1 major ASCVD event and ≥2 high-risk conditions. CART analysis was performed on training and validation datasets. A random forest model was used to verify results. RESULTS: Of 180,669 ASCVD patients identified, 58% were VHR. Among patients with a history of myocardial infarction (MI) or recent acute coronary syndrome (ACS), 99% and 96% were classified as VHR, respectively. Both CART and random forest models identified recent ACS, ischemic stroke, hypertension, peripheral artery disease, history of MI, and age as the most important predictors of VHR status. Using five rules identified by CART analysis, fewer than 50% of risk factors were required to assign VHR status. CONCLUSION: CART analysis helped to streamline the identification of VHR patients based on a limited number of rules and risk factors. This approach may help improve clinical decision making by simplifying ASCVD risk assessment at the point of care. Further validation is needed, however, in more diverse populations.

Excess Mortality Among Patients Hospitalized During the COVID-19 Pandemic.

BACKGROUND: The extent to which the COVID-19 pandemic has affected outcomes for patients with unplanned hospitalizations is unclear. OBJECTIVE: To examine changes in in-hospital mortality for patients without COVID-19 during the first 10 months of the pandemic (March 4, 2020 to December 31, 2020). DESIGN, SETTING, AND PARTICIPANTS: Observational study of adults with unplanned hospitalizations at 51 hospitals across 6 Western states. EXPOSURES: Unplanned hospitalizations occurring during the spring COVID-19 surge (March 4 to May 13, 2020; Period 1), an intervening period (May 14 to October 19, 2020; Period 2), and the fall COVID-19 surge (October 20 to December 31, 2020; Period 3) were compared with a pre-COVID-19 baseline period from January 1, 2019, to March 3, 2020. MAIN OUTCOMES AND MEASURES: We examined daily hospital admissions and in-hospital mortality overall and in 30 conditions. RESULTS: Unplanned hospitalizations declined steeply during Periods 1 and 3 (by 47.5% and 25% compared with baseline, respectively). Although volumes declined, adjusted in-hospital mortality rose from 2.9% in the pre-pandemic period to 3.5% in Period 1 (20.7% relative increase), returning to baseline in Period 2, and rose again to 3.4% in Period 3. Elevated mortality was seen for nearly all conditions studied during the pandemic surge periods. CONCLUSION: Pandemic COVID-19 surges were associated with higher rates of in-hospital mortality among patients without COVID-19, suggesting disruptions in care patterns for patients with many common acute and chronic illnesses.

Transradial Access for High-Risk Percutaneous Coronary Intervention: Implications of the Risk-Treatment Paradox.

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Repeated cross-sectional analysis of hydroxychloroquine deimplementation in the AHA COVID-19 CVD Registry.

There is little data describing trends in the use of hydroxychloroquine for COVID-19 following publication of randomized trials that failed to demonstrate a benefit of this therapy. We identified 13,957 patients admitted for active COVID-19 at 85 U.S. hospitals participating in a national registry between March 1 and August 31, 2020. The overall proportion of patients receiving hydroxychloroquine peaked at 55.2% in March and April and decreased to 4.8% in May and June and 0.8% in July and August. At the hospital-level, median use was 59.4% in March and April (IQR 48.5-71.5%, range 0-100%) and decreased to 0.3% (IQR 0-5.4%, range 0-100%) by May and June and 0% (IQR 0-1.3%, range 0-36.4%) by July and August. The rate and hospital-level uniformity in deimplementation of this ineffective therapy for COVID-19 reflects a rapid response to evolving clinical information and further study may offer strategies to inform deimplementation of ineffective clinical care.

Cardiovascular procedural deferral and outcomes over COVID-19 pandemic phases: A multi-center study.

BACKGROUND: The COVID-19 pandemic has disrupted routine cardiovascular care, with unclear impact on procedural deferrals and associated outcomes across diverse patient populations. METHODS: Cardiovascular procedures performed at 30 hospitals across 6 Western states in 2 large, non-profit healthcare systems (Providence St. Joseph Health and Stanford Healthcare) from December 2018-June 2020 were analyzed for changes over time. Risk-adjusted in-hospital mortality was compared across pandemic phases with multivariate logistic regression. RESULTS: Among 36,125 procedures (69% percutaneous coronary intervention, 13% coronary artery bypass graft surgery, 10% transcatheter aortic valve replacement, and 8% surgical aortic valve replacement), weekly volumes changed in 2 distinct phases after the initial inflection point on February 23, 2020: an initial period of significant deferral (COVID I: March 15-April 11) followed by recovery (COVID II: April 12 onwards). Compared to pre-COVID, COVID I patients were less likely to be female (P = .0003), older (P < .0001), Asian or Black (P = .02), or Medicare insured (P < .0001), and COVID I procedures were higher acuity (P < .0001), but not higher complexity. In COVID II, there was a trend toward more procedural deferral in regions with a higher COVID-19 burden (P = .05). Compared to pre-COVID, there were no differences in risk-adjusted in-hospital mortality during both COVID phases. CONCLUSIONS: Significant decreases in cardiovascular procedural volumes occurred early in the COVID-19 pandemic, with disproportionate impacts by race, gender, and age. These findings should inform our approach to future healthcare disruptions.