LOGAN-CV: A Prospective Study of a Multifaceted Intervention Targeting United States Clinicians to Improve Guideline-Based Management of Lipid-Lowering Therapy.

INTRODUCTION: The 2018 American Heart Association (AHA)/American College of Cardiology (ACC)/Multisociety blood cholesterol guidelines recommend clinicians consider adding non-statin therapy for patients with very high-risk (VHR) atherosclerotic cardiovascular disease (ASCVD) and low-density lipoprotein cholesterol (LDL-C) ≥ 70 mg/dl while receiving maximally tolerated statins. However, according to a recent study, only 17.1% of patients with established ASCVD received appropriate lipid-lowering therapy (LLT) intensification. Here, we describe the design of a prospective, 12-month study (LOGAN-CV) evaluating a multifaceted site-level intervention to enhance clinicians' adherence to guidelines to improve LDL-C levels for patients with VHR ASCVD. METHODS: Clinicians from up to ten research sites are eligible if they care for adult patients with ASCVD. Interventions include educational modules, a cloud-based performance platform providing clinicians a tailored summary of their LDL-C management performance, newsletters, periodic peer-to-peer calls, and pre- and post-intervention surveys evaluating knowledge, attitudes, and beliefs around LDL-C management, with additional interventions for clinicians demonstrating a lower readiness to make treatment decisions based on guideline recommendations. Patients with VHR ASCVD, defined as having recent myocardial infarction and LDL-C ≥ 70 mg/dl despite statin treatment, will be included in the study. Patient data will be collected from electronic medical records from baseline (clinician enrollment) through the 12-month intervention. The study started in October 2022, with anticipated completion in March 2024. PLANNED OUTCOMES: The change in proportion of patients with LDL-C < 70 mg/dl achieved at any time during the 12-month intervention (primary); LLT intensification, changes in guideline-aligned LDL-C testing and LLT titration over 12 months, and change in overall clinicians' knowledge, attitudes, and beliefs are key outcomes of interest. The LOGAN-CV study addresses a critical unmet need in LDL-C control in patients with VHR ASCVD and evaluates the effect of a multifaceted intervention targeting clinicians to improve their adherence to guidelines and consequently improve clinical outcomes for patients.

US Surveillance of Acute Ischemic Stroke Patient Characteristics, Care Quality, and Outcomes for 2019.

BACKGROUND: The United States lacks a timely and accurate nationwide surveillance system for acute ischemic stroke (AIS). We use the Get With The Guidelines-Stroke registry to apply poststratification survey weights to generate national assessment of AIS epidemiology, hospital care quality, and in-hospital outcomes. METHODS: Clinical data from the Get With The Guidelines-Stroke registry were weighted using a Bayesian interpolation method anchored to observations from the national inpatient sample. To generate a US stroke forecast for 2019, we linearized time trend estimates from the national inpatient sample to project anticipated AIS hospital volume, distribution, and race/ethnicity characteristics for the year 2019. Primary measures of AIS epidemiology and clinical care included patient and hospital characteristics, stroke severity, vital and laboratory measures, treatment interventions, performance measures, disposition, and clinical outcomes at discharge. RESULTS: We estimate 552 476 patients with AIS were admitted in 2019 to US hospitals. Median age was 71 (interquartile range, 60-81), 48.8% female. Atrial fibrillation was diagnosed in 22.6%, 30.2% had prior stroke/transient ischemic attack, and 36.4% had diabetes. At baseline, 46.4% of patients with AIS were taking antiplatelet agents, 19.2% anticoagulants, and 46.3% cholesterol-reducers. Mortality was 4.4%, and only 52.3% were able to ambulate independently at discharge. Performance nationally on AIS achievement measures were generally higher than 95% for all measures but the use of thrombolytics within 3 hours of early stroke presentations (81.9%). Additional quality measures had lower rates of receipt: dysphagia screening (84.9%), early thrombolytics by 4.5 hours (79.7%), and statin therapy (80.6%). CONCLUSIONS: We provide timely, reliable, and actionable US national AIS surveillance using Bayesian interpolation poststratification weights. These data may facilitate more targeted quality improvement efforts, resource allocation, and national policies to improve AIS care and outcomes.

Smoking is associated with increased risk of cardiovascular events, disease severity, and mortality among patients hospitalized for SARS-CoV-2 infections.

The clinical sequalae of SARS-CoV-2 infection are in part dependent upon age and pre-existing health conditions. Although the use of tobacco products decreases cardiorespiratory fitness while increasing susceptibility to microbial infections, limited information is available on how smoking affects COVID-19 severity. Therefore, we examined whether smokers hospitalized for COVID-19 are at a greater risk for developing severe complications than non-smokers. Data were from all hospitalized adults with SARS-CoV-2 infection from the American Heart Association's Get-With-The-Guidelines COVID-19 Registry, from January 2020 to March 2021, which is a hospital-based voluntary national registry initiated in 2019 with 122 participating hospitals across the United States. Patients who reported smoking at the time of admission were classified as smokers. Severe outcome was defined as either death or the use of mechanical ventilation. Of the 31,545 patients in the cohort, 6,717 patients were 1:2 propensity matched (for age, sex, race, medical history, medications, and time-frame of hospital admission) and classified as current smokers or non-smokers according to admission data. In multivariable analyses, after adjusting for sociodemographic characteristics, medical history, medication use, and the time of hospital admission, patients self-identified as current smokers had higher adjusted odds of death (adjusted odds ratio [aOR], 1.41; 95% CI, 1.21-1.64), the use of mechanical ventilation (aOR 1.15; 95% CI 1.01-1.32), and increased risk of major adverse cardiovascular events (aOR, 1.27; 95% CI 1.05-1.52). Independent of sociodemographic characteristics and medical history, smoking was associated with a higher risk of severe COVID-19, including death.

Functional status at 30 and 90 days after mild ischaemic stroke.

BACKGROUND/OBJECTIVE: This study compares the global disability status of patients who had a mild ischaemic stroke at 30 and 90 days poststroke, as measured by the modified Rankin Scale (mRS), and identifies predictors of change in disability status between 30 and 90 days. METHODS: The study population included 1339 patients who had a ischaemic stroke enrolled in the Mild and Rapidly Improving Stroke Study with National Institutes of Health (NIH) stroke score 0-5 and mRS measurements at 30 and 90 days. Outcomes were (1) Improvement defined as having mRS >1 at 30 days and mRS 0-1 at 90 days OR mRS >2 at 30 days and mRS 0-2 at 90 days and (2) Worsening defined as an increase of ≥2 points or a worsening from mRS of 1 at 30 days to 2 at 90 days. Demographic and clinical characteristics at hospital arrival were abstracted from medical records, and regression models were used to identify predictors of functional improvement and decline from 30 to 90 days post-stroke. Significant predictors were mutually adjusted in multivariable models that also included age and stroke severity. RESULTS: Fifty-seven per cent of study participants had no change in mRS value from 30 to 90 days. Overall, there was moderate agreement in mRS between the two time points (weighted kappa=0.59 (95% CI 0.56 to 0.62)). However, worsening on the mRS was observed in 7.54% of the study population from 30 to 90 days, and 17.33% improved. Participants of older age (per year OR 1.02, 95% CI 1.00 to 1.03), greater stroke severity (per NIH Stroke Scale (NIHSS) point at admission OR 1.17, 95% CI 1.03 to 1.34), and those with no alteplase treatment (OR 1.72, 95% CI 1.11 to 2.69) were more likely to show functional decline after mutual adjustment. DISCUSSION: A quarter of all mild ischaemic stroke participants exhibited functional changes between 30 and 90 days, suggesting that the 30-day outcome may insufficiently represent long-term recovery in mild stroke and longer follow-up may be clinically necessary. TRIAL REGISTRATION NUMBER: NCT02072681.

Troponin is unrelated to outcomes in heart failure patients discharged from the emergency department.

Background: Prior data has demonstrated increased mortality in hospitalized patients with acute heart failure (AHF) and troponin elevation. No data has specifically examined the prognostic significance of troponin elevation in patients with AHF discharged after emergency department (ED) management. Objective: Evaluate the relationship between troponin elevation and outcomes in patients with AHF who are treated and released from the ED. Methods: This was a secondary analysis of the Get with the Guidelines to Reduce Disparities in AHF Patients Discharged from the ED (GUIDED-HF) trial, a randomized, controlled trial of ED patients with AHF who were discharged. Patients with elevated conventional troponin not due to acute coronary syndrome (ACS) were included. Our primary outcome was a composite endpoint: time to 30-day cardiovascular death and/or heart failure-related events. Results: Of the 491 subjects included in the GUIDED-HF trial, 418 had troponin measured during the ED evaluation and 66 (16%) had troponin values above the 99th percentile. Median age was 63 years (interquartile range, 54-70), 62% (n = 261) were male, 63% (n = 265) were Black, and 16% (n = 67) experienced our primary outcome. There were no differences in our primary outcome between those with and without troponin elevation (12/66, 18.1% vs 55/352, 15.6%; P = 0.60). This effect was maintained regardless of assignment to usual care or the intervention arm. In multivariable regression analysis, there was no association between our primary outcome and elevated troponin (hazard ratio, 1.00; 95% confidence interval,  0.49-2.01, P = 0.994). Conclusion: If confirmed in a larger cohort, these findings may facilitate safe ED discharge for a group of patients with AHF without ACS when an elevated troponin is the primary reason for admission.

Association of Recent Use of Non-Vitamin K Antagonist Oral Anticoagulants With Intracranial Hemorrhage Among Patients With Acute Ischemic Stroke Treated With Alteplase.

Importance: Current guidelines recommend against use of intravenous alteplase in patients with acute ischemic stroke who are taking non-vitamin K antagonist oral anticoagulants (NOACs). Objective: To evaluate the safety and functional outcomes of intravenous alteplase among patients who were taking NOACs prior to stroke and compare outcomes with patients who were not taking long-term anticoagulants. Design, Setting, and Participants: A retrospective cohort study of 163 038 patients with acute ischemic stroke either taking NOACs or not taking anticoagulants prior to stroke and treated with intravenous alteplase within 4.5 hours of symptom onset at 1752 US hospitals participating in the Get With The Guidelines-Stroke program between April 2015 and March 2020, with complementary data from the Addressing Real-world Anticoagulant Management Issues in Stroke registry. Exposures: Prestroke treatment with NOACs within 7 days prior to alteplase treatment. Main Outcomes and Measures: The primary outcome was symptomatic intracranial hemorrhage occurring within 36 hours after intravenous alteplase administration. There were 4 secondary safety outcomes, including inpatient mortality, and 7 secondary functional outcomes assessed at hospital discharge, including the proportion of patients discharged home. Results: Of 163 038 patients treated with intravenous alteplase (median age, 70 [IQR, 59 to 81] years; 49.1% women), 2207 (1.4%) were taking NOACs and 160 831 (98.6%) were not taking anticoagulants prior to their stroke. Patients taking NOACs were older (median age, 75 [IQR, 64 to 82] years vs 70 [IQR, 58 to 81] years for those not taking anticoagulants), had a higher prevalence of cardiovascular comorbidities, and experienced more severe strokes (median National Institutes of Health Stroke Scale score, 10 [IQR, 5 to 17] vs 7 [IQR, 4 to 14]) (all standardized differences >10). The unadjusted rate of symptomatic intracranial hemorrhage was 3.7% (95% CI, 2.9% to 4.5%) for patients taking NOACs vs 3.2% (95% CI, 3.1% to 3.3%) for patients not taking anticoagulants. After adjusting for baseline clinical factors, the risk of symptomatic intracranial hemorrhage was not significantly different between groups (adjusted odds ratio [OR], 0.88 [95% CI, 0.70 to 1.10]; adjusted risk difference [RD], -0.51% [95% CI, -1.36% to 0.34%]). There were no significant differences in the secondary safety outcomes, including inpatient mortality (6.3% for patients taking NOACs vs 4.9% for patients not taking anticoagulants; adjusted OR, 0.84 [95% CI, 0.69 to 1.01]; adjusted RD, -1.20% [95% CI, -2.39% to -0%]). Of the secondary functional outcomes, 4 of 7 showed significant differences in favor of the NOAC group after adjustment, including the proportion of patients discharged home (45.9% vs 53.6% for patients not taking anticoagulants; adjusted OR, 1.17 [95% CI, 1.06 to 1.29]; adjusted RD, 3.84% [95% CI, 1.46% to 6.22%]). Conclusions and Relevance: Among patients with acute ischemic stroke treated with intravenous alteplase, use of NOACs within the preceding 7 days, compared with no use of anticoagulants, was not associated with a significantly increased risk of intracranial hemorrhage.

Frequency and Prognostic Significance of Clinical Fluctuations Before Hospital Arrival in Stroke.

BACKGROUND AND PURPOSE: Clinical fluctuations in ischemic stroke symptoms are common, but fluctuations before hospital arrival have not been previously characterized. METHODS: A standardized qualitative assessment of fluctuations before hospital arrival was obtained in an observational study that enrolled patients with mild ischemic stroke symptoms (National Institutes of Health Stroke Scale [NIHSS] score of 0-5) present on arrival to hospital within 4.5 hours of onset, in a subset of 100 hospitals participating in the Get With The Guidelines-Stroke quality improvement program. The number of fluctuations, direction, and the overall improvement or worsening was recorded based on reports from the patient, family, or paramedics. Baseline NIHSS on arrival and at 72 hours (or discharge if before) and final diagnosis and stroke subtype were collected. Outcomes at 90 days included the modified Rankin Scale, Barthel Index, Stroke Impact Scale 16, and European Quality of Life. Prehospital fluctuations were examined in relation to hospital NIHSS change (admission to 72 hours or discharge) and 90-day outcomes. RESULTS: Among 1588 participants, prehospital fluctuations, consisting of improvement, worsening, or both were observed in 35.5%: 25.1% improved once, 5.3% worsened once, and 5.1% had more than 1 fluctuation. Those who improved were less likely and those who worsened were more likely to receive alteplase. Those who improved before hospital arrival had lower change in the hospital NIHSS than those who did not fluctuate. Better adjusted 90-day outcomes were noted in those with prehospital improvement compared to those without any fluctuations. CONCLUSIONS: Fluctuations in neurological symptoms and signs are common in the prehospital setting. Prehospital improvement was associated with better 90-day outcomes, controlling for admission NIHSS and alteplase treatment. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02072681.

Women and ethnoracial minorities with poor cardiovascular health measures associated with a higher risk of developing mood disorder.

BACKGROUND: Mood disorders (MDS) are a type of mental health illness that effects millions of people in the United States. Early prediction of MDS can give providers greater opportunity to treat these disorders. We hypothesized that longitudinal cardiovascular health (CVH) measurements would be informative for MDS prediction. METHODS: To test this hypothesis, the American Heart Association's Guideline Advantage (TGA) dataset was used, which contained longitudinal EHR from 70 outpatient clinics. The statistical analysis and machine learning models were employed to identify the associations of the MDS and the longitudinal CVH metrics and other confounding factors. RESULTS: Patients diagnosed with MDS consistently had a higher proportion of poor CVH compared to patients without MDS, with the largest difference between groups for Body mass index (BMI) and Smoking. Race and gender were associated with status of CVH metrics. Approximate 46% female patients with MDS had a poor hemoglobin A1C compared to 44% of those without MDS; 62% of those with MDS had poor BMI compared to 47% of those without MDS; 59% of those with MDS had poor blood pressure (BP) compared to 43% of those without MDS; and 43% of those with MDS were current smokers compared to 17% of those without MDS. CONCLUSIONS: Women and ethnoracial minorities with poor cardiovascular health measures were associated with a higher risk of development of MDS, which indicated the high utility for using routine medical records data collected in care to improve detection and treatment for MDS among patients with poor CVH.

Discovering disease-disease associations using electronic health records in The Guideline Advantage (TGA) dataset.

Certain diseases have strong comorbidity and co-occurrence with others. Understanding disease-disease associations can potentially increase awareness among healthcare providers of co-occurring conditions and facilitate earlier diagnosis, prevention and treatment of patients. In this study, we utilized the valuable and large The Guideline Advantage (TGA) longitudinal electronic health record dataset from 70 outpatient clinics across the United States to investigate potential disease-disease associations. Specifically, the most prevalent 50 disease diagnoses were manually identified from 165,732 unique patients. To investigate the co-occurrence or dependency associations among the 50 diseases, the categorical disease terms were first mapped into numerical vectors based on disease co-occurrence frequency in individual patients using the Word2Vec approach. Then the novel and interesting disease association clusters were identified using correlation and clustering analyses in the numerical space. Moreover, the distribution of time delay (Δt) between pair-wise strongly associated diseases (correlation coefficients ≥ 0.5) were calculated to show the dependency among the diseases. The results can indicate the risk of disease comorbidity and complications, and facilitate disease prevention and optimal treatment decision-making.

Improvement in Kansas City Cardiomyopathy Questionnaire Scores After a Self-Care Intervention in Patients With Acute Heart Failure Discharged From the Emergency Department.

BACKGROUND: We conducted a secondary analysis of changes in the Kansas City Cardiomyopathy Questionnaire (KCCQ)-12 over 30 days in a randomized trial of self-care coaching versus structured usual care in patients with acute heart failure who were discharged from the emergency department. METHODS: Patients in 15 emergency departments completed the KCCQ-12 at emergency department discharge and at 30 days. We compared change in KCCQ-12 scores between the intervention and usual care arms, adjusted for enrollment KCCQ-12 and demographic characteristics. We used linear regression to describe changes in KCCQ-12 summary scores and logistic regression to characterize clinically meaningful KCCQ-12 subdomain changes at 30 days. RESULTS: There were 350 patients with both enrollment and 30-day KCCQ summary scores available; 166 allocated to usual care and 184 to the intervention arm. Median age was 64 years (interquartile range, 55-70), 37% were female participants, 63% were Black, median KCCQ-12 summary score at enrollment was 47 (interquartile range, 33-64). Self-care coaching resulted in significantly greater improvement in health status compared with structured usual care (5.4-point greater improvement, 95% CI, 1.12-9.68; P=0.01). Improvements in health status in the intervention arm were driven by improvements within the symptom frequency (adjusted odds ratio, 1.62 [95% CI, 1.01-2.59]) and quality of life (adjusted odds ratio, 2.39 [95% CI, 1.46-3.90]) subdomains. CONCLUSIONS: In this secondary analysis, patients with acute heart failure who received a tailored, self-care intervention after emergency department discharge had clinically significant improvements in health status at 30 days compared with structured usual care largely due to improvements within the symptom frequency and quality of life subdomains of the KCCQ-12. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02519283.

Thrombolysis in Mild Stroke: A Comparative Analysis of the PRISMS and MaRISS Studies.

Background and Purpose: Mild ischemic stroke patients enrolled in randomized controlled trials of thrombolysis may have a different symptom severity distribution than those treated in routine clinical practice. Methods: We compared the distribution of the National Institutes of Health Stroke Scale (NIHSS) scores, neurological symptoms/severity among patients enrolled in the PRISMS (Potential of r-tPA for Ischemic Strokes With Mild Symptoms) randomized controlled trial to those with NIHSS score ≤5 enrolled in the prospective MaRISS (Mild and Rapidly Improving Stroke Study) registry using global P values from χ2 analyses. Results: Among 1736 participants in MaRISS, 972 (56%) were treated with alteplase and 764 (44%) were not. These participants were compared with 313 patients randomized in PRISMS. The median NIHSS scores were 3 (2­4) in MaRISS alteplase-treated, 1 (1­3) in MaRISS non­alteplase-treated, and 2 (1­3) in PRISMS. The percentage with an NIHSS score of 0 to 2 was 36.3%, 73.3%, and 65.2% in the 3 groups, respectively (P<0.0001). The proportion of patients with a dominant neurological syndrome (≥1 NIHSS item score of ≥2) was higher in MaRISS alteplase-treated (32%) compared with MaRISS nonalteplase-treated (13.8%) and PRISMS (8.6%; P<0.0001). Conclusions: Patients randomized in PRISMS had comparable deficit and syndromic severity to patients not treated with alteplase in the MaRISS registry and lesser severity than patients treated with alteplase in MaRISS. The PRISMS trial cohort is representative of mild patients who do not receive alteplase in current broad clinical practice.

Application of a time-series deep learning model to predict cardiac dysrhythmias in electronic health records.

BACKGROUND: Cardiac dysrhythmias (CD) affect millions of Americans in the United States (US), and are associated with considerable morbidity and mortality. New strategies to combat this growing problem are urgently needed. OBJECTIVES: Predicting CD using electronic health record (EHR) data would allow for earlier diagnosis and treatment of the condition, thus improving overall cardiovascular outcomes. The Guideline Advantage (TGA) is an American Heart Association ambulatory quality clinical data registry of EHR data representing 70 clinics distributed throughout the US, and has been used to monitor outpatient prevention and disease management outcome measures across populations and for longitudinal research on the impact of preventative care. METHODS: For this study, we represented all time-series cardiovascular health (CVH) measures and the corresponding data collection time points for each patient by numerical embedding vectors. We then employed a deep learning technique-long-short term memory (LSTM) model-to predict CD from the vector of time-series CVH measures by 5-fold cross validation and compared the performance of this model to the results of deep neural networks, logistic regression, random forest, and Naïve Bayes models. RESULTS: We demonstrated that the LSTM model outperformed other traditional machine learning models and achieved the best prediction performance as measured by the average area under the receiver operator curve (AUROC): 0.76 for LSTM, 0.71 for deep neural networks, 0.66 for logistic regression, 0.67 for random forest, and 0.59 for Naïve Bayes. The most influential feature from the LSTM model were blood pressure. CONCLUSIONS: These findings may be used to prevent CD in the outpatient setting by encouraging appropriate surveillance and management of CVH.

Intracerebral Hemorrhage in Patients With COVID-19: An Analysis From the COVID-19 Cardiovascular Disease Registry.

[Figure: see text].

Predictors of Outcomes in Patients With Mild Ischemic Stroke Symptoms: MaRISS.

Background and Purpose: Although most strokes present with mild symptoms, these have been poorly represented in clinical trials. The objective of this study is to describe multidimensional outcomes, identify predictors of worse outcomes, and explore the effect of thrombolysis in this population. Methods: This prospective observational study included patients with ischemic stroke or transient ischemic attack, a baseline National Institutes of Health Stroke Scale (NIHSS) score 0 to 5, presenting within 4.5 hours from symptom onset. The primary outcome was a 90-day modified Rankin Scale score of 0 to 1; secondary outcomes included good outcomes in the Barthel Index, Stroke Impact Scale-16, and European Quality of Life. Multivariable models were created to determine predictors of outcomes and the effect of alteplase. Results: A total of 1765 participants were included from 100 Get With The Guidelines-Stroke participating hospitals (age, 65±14; 42% women; final diagnosis of ischemic stroke, 90%; transient ischemic attack, 10%; 57% received alteplase). At 90 days, 37% were disabled and 25% not independent. Worse outcomes were noted for older individuals, women, non-Hispanic Blacks and Hispanics, Medicaid recipients, smokers, those with diabetes, atrial fibrillation, prior stroke, higher baseline NIHSS, visual field defects, and extremity weakness. Similar outcomes were noted for the alteplase-treated and untreated groups. Alteplase-treated patients were younger (64±13 versus 67±1.4) with higher NIHSS (2.9±1.4 versus 1.7±1.4). After adjusting for age, sex, race/ethnicity, and baseline NIHSS, we did not identify an effect of alteplase on the primary outcome but did find an association with Stroke Impact Scale-16 in the restricted sample of baseline NIHSS score 3­5. Few symptomatic intracerebral hemorrhages were recorded (<1%). Conclusions: A large proportion of stroke patients presenting with low NIHSS have a disabled outcome. Baseline predictors of worse outcomes are described. An effect of alteplase on outcomes was not identified in the overall cohort, but a suggestion of efficacy was noted in the NIHSS 3­5 subgroup. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02072681.

National surveillance of stroke quality of care and outcomes by applying post-stratification survey weights on the Get With The Guidelines-Stroke patient registry.

BACKGROUND: The U.S. lacks a stroke surveillance system. This study develops a method to transform an existing registry into a nationally representative database to evaluate acute ischemic stroke care quality. METHODS: Two statistical approaches are used to develop post-stratification weights for the Get With The Guidelines-Stroke registry by anchoring population estimates to the National Inpatient Sample. Post-stratification survey weights are estimated using a raking procedure and Bayesian interpolation methods. Weighting methods are adjusted to limit the dispersion of weights and make reasonable epidemiologic estimates of patient characteristics, quality of hospital care, and clinical outcomes. Standardized differences in national estimates are reported between the two post-stratification methods for anchored and non-anchored patient characteristics to evaluate estimation quality. Primary measures evaluated are patient and hospital characteristics, stroke severity, vital and laboratory measures, disposition, and clinical outcomes at discharge. RESULTS: A total of 1,388,296 acute ischemic strokes occurred between 2012 and 2014. Raking and Bayesian estimates of clinical data not available in administrative data are estimated within 5 to 10% of margin for expected values. Median weight for the raking method is 1.386 and the weights at the 99th percentile is 6.881 with a maximum weight of 30.775. Median Bayesian weight is 1.329 and the 99th percentile weights is 11.201 with a maximum weight of 515.689. CONCLUSIONS: Leveraging existing databases with patient registries to develop post-stratification weights is a reliable approach to estimate acute ischemic stroke epidemiology and monitoring for stroke quality of care nationally. These methods may be applied to other diseases or settings to better monitor population health.

Predicting cardiovascular health trajectories in time-series electronic health records with LSTM models.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death in the United States (US). Better cardiovascular health (CVH) is associated with CVD prevention. Predicting future CVH levels may help providers better manage patients' CVH. We hypothesized that CVH measures can be predicted based on previous measurements from longitudinal electronic health record (EHR) data. METHODS: The Guideline Advantage (TGA) dataset was used and contained EHR data from 70 outpatient clinics across the United States (US). We studied predictions of 5 CVH submetrics: smoking status (SMK), body mass index (BMI), blood pressure (BP), hemoglobin A1c (A1C), and low-density lipoprotein (LDL). We applied embedding techniques and long short-term memory (LSTM) networks - to predict future CVH category levels from all the previous CVH measurements of 216,445 unique patients for each CVH submetric. RESULTS: The LSTM model performance was evaluated by the area under the receiver operator curve (AUROC): the micro-average AUROC was 0.99 for SMK prediction; 0.97 for BMI; 0.84 for BP; 0.91 for A1C; and 0.93 for LDL prediction. Model performance was not improved by using all 5 submetric measures compared with using single submetric measures. CONCLUSIONS: We suggest that future CVH levels can be predicted using previous CVH measurements for each submetric, which has implications for population cardiovascular health management. Predicting patients' future CVH levels might directly increase patient CVH health and thus quality of life, while also indirectly decreasing the burden and cost for clinical health system caused by CVD and cancers.

Achieving Optimal Population Cardiovascular Health Requires an Interdisciplinary Team and a Learning Healthcare System: A Scientific Statement From the American Heart Association.

Population cardiovascular health, or improving cardiovascular health among patients and the population at large, requires a redoubling of primordial and primary prevention efforts as declines in cardiovascular disease mortality have decelerated over the past decade. Great potential exists for healthcare systems-based approaches to aid in reversing these trends. A learning healthcare system, in which population cardiovascular health metrics are measured, evaluated, intervened on, and re-evaluated, can serve as a model for developing the evidence base for developing, deploying, and disseminating interventions. This scientific statement on optimizing population cardiovascular health summarizes the current evidence for such an approach; reviews contemporary sources for relevant performance and clinical metrics; highlights the role of implementation science strategies; and advocates for an interdisciplinary team approach to enhance the impact of this work.

Effect of a Self-care Intervention on 90-Day Outcomes in Patients With Acute Heart Failure Discharged From the Emergency Department: A Randomized Clinical Trial.

Importance: Up to 20% of patients who present to the emergency department (ED) with acute heart failure (AHF) are discharged without hospitalization. Compared with rates in hospitalized patients, readmission and mortality are worse for ED patients. Objective: To assess the impact of a self-care intervention on 90-day outcomes in patients with AHF who are discharged from the ED. Design, Setting, and Participants: Get With the Guidelines in Emergency Department Patients With Heart Failure was an unblinded, parallel-group, multicenter randomized trial. Patients were randomized 1:1 to usual care vs a tailored self-care intervention. Patients with AHF discharged after ED-based management at 15 geographically diverse EDs were included. The trial was conducted from October 28, 2015, to September 5, 2019. Interventions: Home visit within 7 days of discharge and twice-monthly telephone-based self-care coaching for 3 months. Main Outcomes and Measures: The primary outcome was a global rank of cardiovascular death, HF-related events (unscheduled clinic visit due to HF, ED revisit, or hospitalization), and changes in the Kansas City Cardiomyopathy Questionnaire-12 (KCCQ-12) summary score (SS) at 90 days. Key secondary outcomes included the global rank outcome at 30 days and changes in the KCCQ-12 SS score at 30 and 90 days. Intention-to-treat analysis was performed for the primary, secondary, and safety outcomes. Per-protocol analysis was conducted including patients who completed a home visit and had scheduled outpatient follow-up in the intervention arm. Results: Owing to slow enrollment, 479 of a planned 700 patients were randomized: 235 to the intervention arm and 244 to the usual care arm. The median age was 63.0 years (interquartile range, 54.7-70.2), 302 patients (63%) were African American, 305 patients (64%) were men, and 178 patients (37%) had a previous ejection fraction greater than 50%. There was no significant difference in the primary outcome between patients in the intervention vs usual care arm (hazard ratio [HR], 0.89; 95% CI, 0.73-1.10; P = .28). At day 30, patients in the intervention arm had significantly better global rank (HR, 0.80; 95% CI, 0.64-0.99; P = .04) and a 5.5-point higher KCCQ-12 SS (95% CI, 1.3-9.7; P = .01), while at day 90, the KCCQ-12 SS was 2.7 points higher (95% CI, -1.9 to 7.2; P = .25). Conclusions and Relevance: The self-care intervention did not improve the primary global rank outcome at 90 days in this trial. However, benefit was observed in the global rank and KCCQ-12 SS at 30 days, suggesting that an early benefit of a tailored self-care program initiated at an ED visit for AHF was not sustained through 90 days. Trial Registration: ClinicalTrials.gov Identifier: NCT02519283.

Time-series cardiovascular risk factors and receipt of screening for breast, cervical, and colon cancer: The Guideline Advantage.

BACKGROUND: Cancer is the second leading cause of death in the United States. Cancer screenings can detect precancerous cells and allow for earlier diagnosis and treatment. Our purpose was to better understand risk factors for cancer screenings and assess the effect of cancer screenings on changes of Cardiovascular health (CVH) measures before and after cancer screenings among patients. METHODS: We used The Guideline Advantage (TGA)-American Heart Association ambulatory quality clinical data registry of electronic health record data (n = 362,533 patients) to investigate associations between time-series CVH measures and receipt of breast, cervical, and colon cancer screenings. Long short-term memory (LSTM) neural networks was employed to predict receipt of cancer screenings. We also compared the distributions of CVH factors between patients who received cancer screenings and those who did not. Finally, we examined and quantified changes in CVH measures among the screened and non-screened groups. RESULTS: Model performance was evaluated by the area under the receiver operator curve (AUROC): the average AUROC of 10 curves was 0.63 for breast, 0.70 for cervical, and 0.61 for colon cancer screening. Distribution comparison found that screened patients had a higher prevalence of poor CVH categories. CVH submetrics were improved for patients after cancer screenings. CONCLUSION: Deep learning algorithm could be used to investigate the associations between time-series CVH measures and cancer screenings in an ambulatory population. Patients with more adverse CVH profiles tend to be screened for cancers, and cancer screening may also prompt favorable changes in CVH. Cancer screenings may increase patient CVH health, thus potentially decreasing burden of disease and costs for the health system (e.g., cardiovascular diseases and cancers).

The American Heart Association 2030 Impact Goal: A Presidential Advisory From the American Heart Association.

Each decade, the American Heart Association (AHA) develops an Impact Goal to guide its overall strategic direction and investments in its research, quality improvement, advocacy, and public health programs. Guided by the AHA's new Mission Statement, to be a relentless force for a world of longer, healthier lives, the 2030 Impact Goal is anchored in an understanding that to achieve cardiovascular health for all, the AHA must include a broader vision of health and well-being and emphasize health equity. In the next decade, by 2030, the AHA will strive to equitably increase healthy life expectancy beyond current projections, with global and local collaborators, from 66 years of age to at least 68 years of age across the United States and from 64 years of age to at least 67 years of age worldwide. The AHA commits to developing additional targets for equity and well-being to accompany this overarching Impact Goal. To attain the 2030 Impact Goal, we recommend a thoughtful evaluation of interventions available to the public, patients, providers, healthcare delivery systems, communities, policy makers, and legislators. This presidential advisory summarizes the task force's main considerations in determining the 2030 Impact Goal and the metrics to monitor progress. It describes the aspiration that these goals will be achieved by working with a diverse community of volunteers, patients, scientists, healthcare professionals, and partner organizations needed to ensure success.