Using large language models to assess public perceptions around glucagon-like peptide-1 receptor agonists on social media.

BACKGROUND: The prevalence of obesity has been increasing worldwide, with substantial implications for public health. Obesity is independently associated with cardiovascular morbidity and mortality and is estimated to cost the health system over $200 billion dollars annually. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have emerged as a practice-changing therapy for weight loss and cardiovascular risk reduction independent of diabetes. METHODS: We used large language models to augment our previously reported artificial intelligence-enabled topic modeling pipeline to analyze over 390,000 unique GLP-1 RA-related Reddit discussions. RESULTS: We find high interest around GLP-1 RAs, with a total of 168 topics and 33 groups focused on the GLP-1 RA experience with weight loss, comparison of side effects between differing GLP-1 RAs and alternate therapies, issues with GLP-1 RA access and supply, and the positive psychological benefits of GLP-1 RAs and associated weight loss. Notably, public sentiment in these discussions was mostly neutral-to-positive. CONCLUSIONS: These findings have important implications for monitoring new side effects not captured in randomized control trials and understanding the public health challenge of drug shortages.

Obesity is a global public health burden that increases heart disease risk. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are a class of medications originally developed for diabetes but are now used to improve lifespans in those with heart disease and increase weight loss. To better understand how the public views this type of drug, over 390,000 discussions from the social media platform Reddit were analyzed using computer software. Topics of discussion included experiences with weight loss, side effects of different GLP-1 RAs, and concerns about drug access and supply. The results showed a mainly neutral-to-positive view of these medications. The findings may help identify new side effects not previously seen in clinical trials and highlight future directions for research and public health efforts.

How adoption of new pharmaceuticals can impact US health system reimbursement under alternative payment models: An economic model measuring the impact of sotagliflozin among patients with heart failure and diabetes.

BACKGROUND: Heart failure (HF) is among the leading causes of death in the United States. Further, patients hospitalized because of HF with comorbid diabetes mellitus (DM) are at a significantly increased risk of death and rehospitalization. Results from the SOLOIST-WHF trial show that sotagliflozin lowered rates of readmission among hospitalized patients with HF and comorbid DM. However, it is unclear what the economic impact of the use of sotagliflozin would be on hospitals and health systems, particularly in an age where provider reimbursement is increasingly tied to value. OBJECTIVE: To quantify the 1-year financial impact on US provider health systems of adopting sotagliflozin relative to standard of care (SoC) across different alternative payment models. METHODS: This study created a 3-part decision tree model to quantify the financial impact of using sotagliflozin to treat patients hospitalized with HF in a US hospital setting. The model first estimated the clinical and economic outcomes of health systems with current SoC (no sotagliflozin) to treat US patients hospitalized for HF with comorbid DM. Then, using the results from the SOLOIST trial, the changes in clinical and economic outcomes with sotagliflozin adoption were modeled. Finally, the differences in health care utilization between sotagliflozin and SoC arms were translated to differences in health system reimbursement in the context of 3 common alternative payment models (APMs) in addition to the baseline fee-for-service (FFS) model: FFS with the Hospital Readmissions Reduction Program, the Bundled Payments for Care Improvement-Advanced program, and Accountable Care Organizations. RESULTS: A typical community hospital would have 83.4 patients per year on average with an index HF hospitalization with comorbid DM. The model predicted that sotagliflozin would reduce the probability of hospitalization, emergency department visits, and deaths by 29.3%, 38.5%, and 17.8%, respectively, compared with SoC. For hospitals not participating in APM programs, sotagliflozin resulted in a net loss of $92.94 per person ($7,754 per health system). Conversely, when accounting for provider health system participation in APMs, sotagliflozin adoption increased financial returns by $4,720 per person ($305,604 per health system) under the Hospital Readmissions Reduction Program, $1,200 per person ($100,106 per health system) for the Bundled Payments for Care Improvement-Advanced program, and $1,078 per person ($31,029 per health system) for Accountable Care Organizations. Based on the national average composition of APM reimbursement, sotagliflozin adoption resulted in a $1,576 increase in margin per patient with HF ($105,454 per health system). CONCLUSIONS: Although sotagliflozin adoption reduced health system revenue in an FFS payment model, it led to a net positive financial impact after accounting for APM bonus payments.

Equity in the Setting of Heart Failure Diagnosis: An Analysis of Differences Between and Within Clinician Practices.

BACKGROUND: Timely heart failure (HF) diagnosis can lead to earlier intervention and reduced morbidity. Among historically marginalized patients, new-onset HF diagnosis is more likely to occur in acute care settings (emergency department or inpatient hospitalization) than outpatient settings. Whether inequity within outpatient clinician practices affects diagnosis settings is unknown. METHODS: We determined the setting of incident HF diagnosis among Medicare fee-for-service beneficiaries between 2013 and 2017. We identified sociodemographic and medical characteristics associated with HF diagnosis in the acute care setting. Within each outpatient clinician practice, we compared acute care diagnosis rates across sociodemographic characteristics: female versus male sex, non-Hispanic White versus other racial and ethnic groups, and dual Medicare-Medicaid eligible (a surrogate for low income) versus nondual-eligible patients. Based on within-practice differences in acute diagnosis rates, we stratified clinician practices by equity (high, intermediate, and low) and compared clinician practice characteristics. RESULTS: Among 315 439 Medicare patients with incident HF, 173 121 (54.9%) were first diagnosed in acute care settings. Higher adjusted acute care diagnosis rates were associated with female sex (6.4% [95% CI, 6.1%-6.8%]), American Indian (3.6% [95% CI, 1.1%-6.1%]) race, and dual eligibility (4.1% [95% CI, 3.7%-4.5%]). These differences persisted within clinician practices. With clinician practice adjustment, dual-eligible patients had a 4.9% (95% CI, 4.5%-5.4%) greater acute care diagnosis rate than nondual-eligible patients. Clinician practices with greater equity across dual eligibility also had greater equity across sex and race and ethnicity and were more likely to be composed of predominantly primary care clinicians. CONCLUSIONS: Differences in HF diagnosis rates in the acute care setting between and within clinician practices highlight an opportunity to improve equity in diagnosing historically marginalized patients.

Applying natural language processing to identify emergency department and observation encounters for worsening heart failure.

AIMS: Worsening heart failure (WHF) events occurring in non-inpatient settings are becoming increasingly recognized, with implications for prognostication. We evaluate the performance of a natural language processing (NLP)-based approach compared with traditional diagnostic coding for non-inpatient clinical encounters and left ventricular ejection fraction (LVEF). METHODS AND RESULTS: We compared characteristics for encounters that did vs. did not meet WHF criteria, stratified by care setting [i.e. emergency department (ED) and observation stay]. Overall, 8407 (22%) encounters met NLP-based criteria for WHF (3909 ED visits and 4498 observation stays). The use of an NLP-derived definition adjudicated 3983 (12%) of non-primary HF diagnoses as meeting consensus definitions for WHF. The most common diagnosis indicated in these encounters was dyspnoea. Results were primarily driven by observation stays, in which 2205 (23%) encounters with a secondary HF diagnosis met the WHF definition by NLP. CONCLUSIONS: The use of standard claims-based adjudication for primary diagnosis in the non-inpatient setting may lead to misclassification of WHF events in the ED and overestimate observation stays. Primary diagnoses alone may underestimate the burden of WHF in non-hospitalized settings.

Sex-Based Differences in the Epidemiology, Clinical Characteristics, and Outcomes Associated with Worsening Heart Failure Events in a Learning Health System.

BACKGROUND: Differences in demographics, risk factors, and clinical characteristics may contribute to variations in men and women in terms of the prevalence, clinical setting, and outcomes associated with worsening heart failure (WHF) events. We sought to describe sex-based differences in the epidemiology, clinical characteristics, and outcomes associated with WHF events across clinical settings. METHODS AND RESULTS: We examined adults diagnosed with HF from 2010 to 2019 within a large, integrated health care delivery system. Electronic health record data were accessed for hospitalizations, emergency department (ED) visits and observation stays, and outpatient encounters. WHF was identified using validated natural language processing algorithms and defined as ≥1 symptom, ≥2 objective findings (including ≥1 sign), and ≥1 change in HF-related therapy. Incidence rates and associated outcomes for WHF were compared across care setting by sex. We identified 1,122,368 unique clinical encounters with a diagnosis code for HF, with 124,479 meeting WHF criteria. These WHF encounters existed among 102,116 patients, of whom 48,543 (47.5%) were women and 53,573 (52.5%) were men. Women experiencing WHF were older and more likely to have HF with preserved ejection fraction compared with men. The clinical settings of WHF were similar among women and men: hospitalizations (36.8% vs 37.7%), ED visits or observation stays (11.8% vs 13.4%), and outpatient encounters (4.4% vs 4.9%). Women had lower odds of 30-day mortality after an index hospitalization (adjusted odds ratio 0.88, 95% confidence interval 0.83-0.93) or ED visit or observation stay (adjusted odds ratio 0.86, 95% confidence interval 0.75-0.98) for WHF. CONCLUSIONS: Women and men contribute similarly to WHF events across diverse clinical settings despite marked differences in age and left ventricular ejection fraction.

Atherosclerosis evaluation and cardiovascular risk estimation using coronary computed tomography angiography.

Clinical risk scores based on traditional risk factors of atherosclerosis correlate imprecisely to an individual's complex pathophysiological predisposition to atherosclerosis and provide limited accuracy for predicting major adverse cardiovascular events (MACE). Over the past two decades, computed tomography scanners and techniques for coronary computed tomography angiography (CCTA) analysis have substantially improved, enabling more precise atherosclerotic plaque quantification and characterization. The accuracy of CCTA for quantifying stenosis and atherosclerosis has been validated in numerous multicentre studies and has shown consistent incremental prognostic value for MACE over the clinical risk spectrum in different populations. Serial CCTA studies have advanced our understanding of vascular biology and atherosclerotic disease progression. The direct disease visualization of CCTA has the potential to be used synergistically with indirect markers of risk to significantly improve prevention of MACE, pending large-scale randomized evaluation.

Contemporary Decongestion Strategies in Patients Hospitalized for Heart Failure: A National Community-Based Cohort Study.

BACKGROUND: Heart failure (HF) is a leading cause of hospitalization in the United States. Decongestion remains a central goal of inpatient management, but contemporary decongestion practices and associated weight loss have not been well characterized nationally. OBJECTIVES: This study aimed to describe contemporary inpatient diuretic practices and clinical predictors of weight loss in patients hospitalized for HF. METHODS: The authors identified HF hospitalizations from 2015 to 2022 in a U.S. national database aggregating deidentified patient-level electronic health record data across 31 geographically diverse community-based health systems. The authors report patient characteristics and inpatient weight change as a primary indicator of decongestion. Predictors of weight loss were evaluated using multivariable models. Temporal trends in inpatient diuretic practices, including augmented diuresis strategies such as adjunctive thiazides and continuous diuretic infusions, were assessed. RESULTS: The study cohort included 262,673 HF admissions across 165,482 unique patients. The median inpatient weight loss was 5.3 pounds (Q1-Q3: 0.0-12.8 pounds) or 2.4 kg (Q1-Q3: 0.0-5.8 kg). Discharge weight was higher than admission weight in 20% of encounters. An increase of ≥0.3 mg/dL in serum creatinine from admission to inpatient peak occurred in >30% of hospitalizations and was associated with less weight loss. Adjunctive diuretic agents were utilized in <20% of encounters but were associated with greater weight loss. CONCLUSIONS: In a large-scale U.S. community-based cohort study of HF hospitalizations, estimated weight loss from inpatient decongestion remains highly variable, with weight gain observed across many admissions. Augmented diuresis strategies were infrequently used. Comparative effectiveness trials are needed to establish optimal strategies for inpatient decongestion for acute HF.

Clinical Impact of Routine Assessment of Patient-Reported Health Status in Heart Failure Clinic: The PRO-HF Trial.

BACKGROUND: The impact of routine clinic use of patient-reported outcome (PRO) measures on clinical outcomes in patients with heart failure (HF) has not been well-characterized. We tested if clinic-based use of a disease-specific PRO improves patient-reported quality of life at 1 year. METHODS: The PRO-HF trial (Patient-Reported Outcome Measurement in Heart Failure Clinic) was an open-label, parallel, patient-level randomized clinical trial of routine PRO assessment or usual care at an academic HF clinic between August 30, 2021, and June 30, 2022, with 1 year of follow-up. In the PRO assessment arm, participants completed the Kansas City Cardiomyopathy Questionnaire-12 (KCCQ-12) at each HF clinic visit, and results were shared with their treating clinician. The usual care arm completed the KCCQ-12 at randomization and 1 year later, which was not shared with the treating clinician. The primary outcome was the KCCQ-12 overall summary score (OSS) between 12 and 15 months after randomization. Secondary outcomes included domains of the KCCQ-12, hospitalization and emergency department visit rates, HF medication therapy, clinic visit frequency, and testing rates. RESULTS: Across 17 clinicians, 1248 participants were enrolled and randomized to PRO assessment (n=624) or usual care (n=624). The median age was 63.9 years (interquartile range [IQR], 51.8-72.8), 38.9% were women, and the median baseline KCCQ-12 OSS was 82.3 (IQR, 58.3-94.8). Final KCCQ-12 (available in 87.9% of the PRO arm and 85.1% in usual care; P=0.16) median OSS were 87.5 (IQR, 68.8-96.9) in the PRO arm and 87.6 (IQR, 69.7-96.9) in the usual care arm with a baseline-adjusted mean difference of 0.2 ([95% CI, -1.7 to 2.0]; P=0.85). The results were consistent across prespecified subgroups. A post hoc analysis demonstrated a significant interaction with greater benefit among participants with a baseline KCCQ-12 OSS of 60 to 80 but not in less or more symptomatic participants. No significant differences were found in 1-year mortality, hospitalizations, emergency department visits, medication therapy, clinic follow-up, or testing rates between arms. CONCLUSIONS: Routine PRO assessment in HF clinic visits did not impact patient-reported quality of life or other clinical outcomes. Alternate strategies and settings for embedding PROs into routine clinical care should be tested. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04164004.

Uptake of Sodium-Glucose Cotransporter-2 Inhibitors in Hospitalized Patients With Heart Failure: Insights From the Veterans Affairs Healthcare System.

BACKGROUND: The use of sodium-glucose cotransporter-2 inhibitors (SGLT2is) in Veterans Affairs (VA) patients hospitalized with heart failure (HF) has not been reported previously. METHODS: VA electronic health record data were used to identify patients hospitalized for HF (primary or secondary diagnosis) from 01/2019-11/2022. Patients with SGLT2i allergy, advanced/end-stage chronic kidney disease (CKD) or advanced HF therapies were excluded. We identified factors associated with discharge SGLT2i prescriptions for patients hospitalized due to HF in 2022. We also compared SGLT2i and angiotensin receptor-neprilysin inhibitor (ARNI) prescription rates. Hospital-level variations in SGLT2i prescriptions were assessed via the median odds ratio. RESULTS: A total of 69,680 patients were hospitalized due to HF; 10.3% were prescribed SGLT2i at discharge (4.4% newly prescribed, 5.9% continued preadmission therapy). SGLT2i prescription increased over time and was higher in patients with HFrEF and primary HF. Among 15,762 patients hospitalized in 2022, SGLT2i prescription was more likely in patients with diabetes (adjusted odds ratio [aOR] 2.27; 95% confidence interval [CI]: 2.09-2.47) and ischemic heart disease (aOR 1.14; 95% CI: 1.03-1.26). Patients with increased age (aOR 0.77 per 10 years; 95% CI: 0.73-0.80) and lower systolic blood pressure (aOR 0.94 per 10 mmHg; 95% CI: 0.92-0.96) were less likely to be prescribed SGLT2i, and SGLT2i prescription was not more likely in patients with CKD (aOR 1.07; 95% CI 0.98-1.16). The adjusted median odds ratio suggested a 1.8-fold variation in the likelihood that similar patients at 2 random VA sites were prescribed SGLT2i (range 0-21.0%). In patients with EF ≤ 40%, 30.9% were prescribed SGLT2i while 26.9% were prescribed ARNI (P < 0.01). CONCLUSION: One-tenth of VA patients hospitalized for HF were prescribed SGLT2i at discharge. Opportunities exist to reduce variation in SGLT2i prescription rates across hospitals and to promote its use in patients with CKD and older age.

The economics of heart failure care.

Heart failure (HF) poses a significant economic burden in the US, with costs projected to reach $70 billion by 2030. Cost-effectiveness analyses play a pivotal role in assessing the economic value of HF therapies. In this review, we overview the cost-effectiveness of HF therapies and discuss ways to improve patient access. Based on current costs, guideline directed medical therapies for HF with reduced ejection fraction provide high economic value except for sodium-glucose cotransporter-2 inhibitors, which provide intermediate economic value. Combining therapy with the four pillars of medical therapy also has intermediate economic value, with incremental cost-effectiveness ratios ranging from $73,000 to $98,500/ quality adjusted life-years. High economic value procedures include cardiac resynchronization devices, implantable cardioverter-defibrillators, and coronary artery bypass surgery. In contrast, advanced HF therapies have previously demonstrated intermediate to low economic value, but newer data appear more favorable. Given the affordability challenges of HF therapies, additional efforts are needed to ensure optimal care for patients. The recent Inflation Reduction Act contains provisions to reform policy pertaining to drug price negotiation and out-of-pocket spending, as well as measures to increase access to existing programs, including the Medicare low-income subsidy. On a patient level, it is also important to encourage patient and physician awareness and discussions surrounding medical costs. Overall, a broad approach to improving available therapies and access to care is needed to reduce the growing clinical and economic morbidity of HF.

Design and Implementation of an Electronic Health Record-Integrated Hypertension Management Application.

BACKGROUND: High blood pressure affects approximately 116 million adults in the United States. It is the leading risk factor for death and disability across the world. Unfortunately, over the past decade, hypertension control rates have decreased across the United States. Prediction models and clinical studies have shown that reducing clinician inertia alone is sufficient to reach the target of ≥80% blood pressure control. Digital health tools containing evidence-based algorithms that are able to reduce clinician inertia are a good fit for turning the tide in blood pressure control, but careful consideration should be taken in the design process to integrate digital health interventions into the clinical workflow. METHODS: We describe the development of a provider-facing hypertension management platform. We enumerate key steps of the development process, including needs finding, clinical workflow analysis, treatment algorithm creation, platform design and electronic health record integration. We interviewed and surveyed 5 Stanford clinicians from primary care, cardiology, and their clinical care team members (including nurses, advanced practice providers, medical assistants) to identify needs and break down the steps of clinician workflow analysis. The application design and development stage were aided by a team of approximately 15 specialists in the fields of primary care, hypertension, bioinformatics, and software development. CONCLUSIONS: Digital monitoring holds immense potential for revolutionizing chronic disease management. Our team developed a hypertension management platform at an academic medical center to address some of the top barriers to adoption and achieving clinical outcomes. The frameworks and processes described in this article may be used for the development of a diverse range of digital health tools in the cardiovascular space.

Opportunistic assessment of ischemic heart disease risk using abdominopelvic computed tomography and medical record data: a multimodal explainable artificial intelligence approach.

Current risk scores using clinical risk factors for predicting ischemic heart disease (IHD) events-the leading cause of global mortality-have known limitations and may be improved by imaging biomarkers. While body composition (BC) imaging biomarkers derived from abdominopelvic computed tomography (CT) correlate with IHD risk, they are impractical to measure manually. Here, in a retrospective cohort of 8139 contrast-enhanced abdominopelvic CT examinations undergoing up to 5 years of follow-up, we developed multimodal opportunistic risk assessment models for IHD by automatically extracting BC features from abdominal CT images and integrating these with features from each patient's electronic medical record (EMR). Our predictive methods match and, in some cases, outperform clinical risk scores currently used in IHD risk assessment. We provide clinical interpretability of our model using a new method of determining tissue-level contributions from CT along with weightings of EMR features contributing to IHD risk. We conclude that such a multimodal approach, which automatically integrates BC biomarkers and EMR data, can enhance IHD risk assessment and aid primary prevention efforts for IHD. To further promote research, we release the Opportunistic L3 Ischemic heart disease (OL3I) dataset, the first public multimodal dataset for opportunistic CT prediction of IHD.

ACC/AHA/ASE/ASNC/ASPC/HFSA/HRS/SCAI/SCCT/SCMR/STS 2023 Multimodality Appropriate Use Criteria for the Detection and Risk Assessment of Chronic Coronary Disease.

The American College of Cardiology (ACC) Foundation, along with key specialty and subspecialty societies, conducted an appropriate use review of stress testing and anatomic diagnostic procedures for risk assessment and evaluation of known or suspected chronic coronary disease (CCD), formerly referred to as stable ischemic heart disease (SIHD). This document reflects an updating of the prior Appropriate Use Criteria (AUC) published for radionuclide imaging, stress echocardiography (echo), calcium scoring, coronary computed tomography angiography (CCTA), stress cardiac magnetic resonance (CMR), and invasive coronary angiography for SIHD. This is in keeping with the commitment to revise and refine the AUC on a frequent basis. As with the prior version of this document, rating of test modalities is provided side-by-side for a given clinical scenario. These ratings are explicitly not considered competitive rankings due to the limited availability of comparative evidence, patient variability, and the range of capabilities available in any given local setting1-4.This version of the AUC for CCD is a focused update of the prior version of the AUC for SIHD4. Key changes beyond the updated ratings based on new evidence include the following: 1. Clinical scenarios related to preoperative testing were removed and will be incorporated into another AUC document under development. 2. Some clinical scenarios and tables were removed in an effort to simplify the selection of clinical scenarios. Additionally, the flowchart of tables has been reorganized, and all clinical scenario tables can now be reached by answering a limited number of clinical questions about the patient, starting with the patient's symptom status. 3. Several clinical scenarios have been revised to incorporate changes in other documents such as pretest probability assessment, atherosclerotic cardiovascular disease (ASCVD) risk assessment, syncope, and others. ASCVD risk factors that are not accounted for in contemporary risk calculators have been added as modifiers to certain clinical scenarios. The 64 clinical scenarios rated in this document are limited to the detection and risk assessment of CCD and were drawn from common applications or anticipated uses, as well as from current clinical practice guidelines.5 These clinical scenarios do not specifically address patients having acute chest pain episodes. They may, however, be applicable in the inpatient setting if the patient is not having an acute coronary syndrome and warrants evaluation for CCD.Using standardized methodology, clinical scenarios were developed to describe common patient encounters in clinical practice focused on common applications and anticipated uses of testing for CCD. Where appropriate, the scenarios were developed on the basis of the most current ACC/American Heart Association guidelines. A separate, independent rating panel scored the clinical scenarios in this document on a scale of 1 to 9, following a modified Delphi process consistent with the recently updated AUC development methodology. Scores of 7 to 9 indicate that a modality is considered appropriate for the clinical scenario presented, midrange scores of 4 to 6 indicate that a modality may be appropriate for the clinical scenario, and scores of 1 to 3 indicate that a modality is rarely appropriate.

Association of Coronary Artery Calcium Detected by Routine Ungated CT Imaging With Cardiovascular Outcomes.

BACKGROUND: Coronary artery calcium (CAC) is a strong predictor of cardiovascular events across all racial and ethnic groups. CAC can be quantified on nonelectrocardiography (ECG)-gated computed tomography (CT) performed for other reasons, allowing for opportunistic screening for subclinical atherosclerosis. OBJECTIVES: The authors investigated whether incidental CAC quantified on routine non-ECG-gated CTs using a deep-learning (DL) algorithm provided cardiovascular risk stratification beyond traditional risk prediction methods. METHODS: Incidental CAC was quantified using a DL algorithm (DL-CAC) on non-ECG-gated chest CTs performed for routine care in all settings at a large academic medical center from 2014 to 2019. We measured the association between DL-CAC (0, 1-99, or ≥100) with all-cause death (primary outcome), and the secondary composite outcomes of death/myocardial infarction (MI)/stroke and death/MI/stroke/revascularization using Cox regression. We adjusted for age, sex, race, ethnicity, comorbidities, systolic blood pressure, lipid levels, smoking status, and antihypertensive use. Ten-year atherosclerotic cardiovascular disease risk was calculated using the pooled cohort equations. RESULTS: Of 5,678 adults without ASCVD (51% women, 18% Asian, 13% Hispanic/Latinx), 52% had DL-CAC >0. Those with DL-CAC ≥100 had an average 10-year ASCVD risk of 24%; yet, only 26% were on statins. After adjustment, patients with DL-CAC ≥100 had increased risk of death (HR: 1.51; 95% CI: 1.28-1.79), death/MI/stroke (HR: 1.57; 95% CI: 1.33-1.84), and death/MI/stroke/revascularization (HR: 1.69; 95% CI: 1.45-1.98) compared with DL-CAC = 0. CONCLUSIONS: Incidental CAC ≥100 was associated with an increased risk of all-cause death and adverse cardiovascular outcomes, beyond traditional risk factors. DL-CAC from routine non-ECG-gated CTs identifies patients at increased cardiovascular risk and holds promise as a tool for opportunistic screening to facilitate earlier intervention.

Developing Clinical Risk Prediction Models for Worsening Heart Failure Events and Death by Left Ventricular Ejection Fraction.

Background There is a need to develop electronic health record-based predictive models for worsening heart failure (WHF) events across clinical settings and across the spectrum of left ventricular ejection fraction (LVEF). Methods and Results We studied adults with heart failure (HF) from 2011 to 2019 within an integrated health care delivery system. WHF encounters were ascertained using natural language processing and structured data. We conducted boosted decision tree ensemble models to predict 1-year hospitalizations, emergency department visits/observation stays, and outpatient encounters for WHF and all-cause death within each LVEF category: HF with reduced ejection fraction (EF) (LVEF <40%), HF with mildly reduced EF (LVEF 40%-49%), and HF with preserved EF (LVEF ≥50%). Model discrimination was evaluated using area under the curve and calibration using mean squared error. We identified 338 426 adults with HF: 61 045 (18.0%) had HF with reduced EF, 49 618 (14.7%) had HF with mildly reduced EF, and 227 763 (67.3%) had HF with preserved EF. The 1-year risks of any WHF event and death were, respectively, 22.3% and 13.0% for HF with reduced EF, 17.0% and 10.1% for HF with mildly reduced EF, and 16.3% and 10.3% for HF with preserved EF. The WHF model displayed an area under the curve of 0.76 and mean squared error of 0.13, whereas the model for death displayed an area under the curve of 0.83 and mean squared error of 0.076. Performance and predictors were similar across WHF encounter types and LVEF categories. Conclusions We developed risk prediction models for 1-year WHF events and death across the LVEF spectrum using structured and unstructured electronic health record data and observed no substantial differences in model performance or predictors except for death, despite differences in underlying HF cause.

Heart failure medical therapy prior to mitral transcatheter edge-to-edge repair: the STS/ACC Transcatheter Valve Therapy Registry.

BACKGROUND AND AIMS: Guideline-directed medical therapy (GDMT) is recommended before mitral valve transcatheter edge-to-edge repair (MTEER) in patients with heart failure (HF) and severe functional mitral regurgitation (FMR). Whether MTEER is being performed on the background of optimal GDMT in clinical practice is unknown. METHODS: Patients with left ventricular ejection fraction (LVEF) < 50% who underwent MTEER for FMR from 23 July 2019 to 31 March 2022 in the Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy Registry were identified. Pre-procedure GDMT utilization was assessed. Cox proportional hazards models were constructed to evaluate associations between pre-MTEER therapy (no/single, double, or triple therapy) and risk of 1-year mortality or HF hospitalization (HFH). RESULTS: Among 4199 patients across 449 sites, beta-blockers, angiotensin-converting enzyme inhibitors/angiotensin receptor blockers, mineralocorticoid receptor antagonists, and angiotensin receptor-neprilysin inhibitors were used in 85.1%, 44.4%, 28.6%, and 19.9% before MTEER, respectively. Triple therapy was prescribed for 19.2%, double therapy for 38.2%, single therapy for 36.0%, and 6.5% were on no GDMT. Significant centre-level variation in the proportion of patients on pre-intervention triple therapy was observed (0%-61%; adjusted median odds ratio 1.48 [95% confidence interval (CI) 1.25-3.88]; P < .001). In patients eligible for 1-year follow-up (n = 2014; 341 sites), the composite rate of 1-year mortality or HFH was lowest in patients prescribed triple therapy (23.0%) compared with double (24.8%), single (35.7%), and no (41.1%) therapy (P < .01 comparing across groups). Associations persisted after accounting for relevant clinical characteristics, with lower risk in patients prescribed triple therapy [adjusted hazard ratio (aHR) 0.73, 95% CI .55-.97] and double therapy (aHR 0.69, 95% CI .56-.86) before MTEER compared with no/single therapy. CONCLUSIONS: Under one-fifth of patients with LVEF <50% who underwent MTEER for FMR in this US nationwide registry were prescribed comprehensive GDMT, with substantial variation across sites. Compared with no/single therapy, triple and double therapy before MTEER were independently associated with reduced risk of mortality or HFH 1 year after intervention.