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Background: Medical record review by a physician clinical events committee is the gold standard for identifying cardiovascular outcomes in clinical trials, but is labor-intensive and poorly reproducible. Automated outcome adjudication by artificial intelligence (AI) could enable larger and less expensive clinical trials, but has not been validated in global studies. Methods: We developed a novel model for automated AI-based heart failure adjudication ("HF-NLP") using hospitalizations from three international clinical outcomes trials. This model was tested on potential heart failure hospitalizations from the DELIVER trial, a cardiovascular outcomes trial comparing dapagliflozin with placebo in 6063 patients with heart failure with mildly reduced or preserved ejection fraction. AI-based adjudications were compared with adjudications from a clinical events committee that followed FDA-based criteria. Results: AI-based adjudication agreed with the clinical events committee in 83% of events. A strategy of human review for events that the AI model deemed uncertain (16%) would have achieved 91% agreement with the clinical events committee while reducing adjudication workload by 84%. The estimated effect of dapagliflozin on heart failure hospitalization was nearly identical with AI-based adjudication (hazard ratio 0.76 [95% CI 0.66-0.88]) compared to clinical events committee adjudication (hazard ratio 0.77 [95% CI 0.67-0.89]). The AI model extracted symptoms, signs, and treatments of heart failure from each medical record in tabular format and quoted sentences documenting them. Conclusions: AI-based adjudication of clinical outcomes has the potential to improve the efficiency of global clinical trials while preserving accuracy and interpretability.

Randomized clinical trials are the gold standard for establishing the efficacy and safety of cardiovascular therapies. However, current pivotal trials are expensive, lengthy, and insufficiently diverse. Emerging artificial intelligence (AI) technologies can potentially automate and streamline clinical trial operations. This review describes opportunities to integrate AI throughout a trial's life cycle, including designing the trial, identifying eligible patients, obtaining informed consent, ascertaining physiological and clinical event outcomes, interpreting imaging, and analyzing or disseminating the results. Nevertheless, AI poses risks, including generating inaccurate results, amplifying biases against underrepresented groups, and violating patient privacy. Medical journals and regulators are developing new frameworks to evaluate AI research tools and the data they generate. Given the high-stakes role of randomized trials in medical decision making, AI must be integrated carefully and transparently to protect the validity of trial results., Competing Interests: Funding Support and Author Disclosures Dr Cunningham has received support from the KL2/Harvard Catalyst Medical Research Investigator Training program and the American Heart Association (23CDA1052151); and has received consulting fees from Roche Diagnosis, Edgewise Therapeutics, KCK, and Occlutech. Dr Abraham has served as a consultant to Boehringer Ingelheim, CVRx, Impulse Dynamics, Sensible Medical, Vectorious, V-Wave, and Zoll Respicardia. Dr Bhatt has received research grant support to his institution from the National Institutes of Health (NIH) National Heart, Lung, and Blood Institute (NHLBI) and National Institute on Aging, the American College of Cardiology Foundation, and the Centers for Disease Control and Prevention (CDC); and has received consulting fees from the Kinetix Group, Merck, Sanofi Pasteur, and Novo Nordisk. Dr Dunn has served as a scientific advisor to Veri. Dr Felker has received research grants from NIH, Bayer, Bristol Myers Squibb, Novartis, Daxor, Merck, Cytokinetics, and CSL-Behring; has acted as a consultant to Novartis, Bristol Myers Squibb, Cytokinetics, Innolife, Boehringer Ingelheim, Abbott, Sanofi, Regeneron, Myovant, Sequana, Windtree Therapeutics, and Whiteswell; and has served on clinical endpoint committees or data safety monitoring boards for Merck, Medtronic, EBR Systems, Rocket Pharma, V-Wave, and LivaNova. Dr Jain has received consulting fees from Bristol Myers Squibb, ARTIS Ventures, and Broadview Ventures outside of the submitted work. Dr Lindsell has received grants and contracts from the NIH, the U.S. Department of Defense, CDC, Biomeme, Novartis, bioMérieux, AstraZeneca, AbbVie, Entegrion, and Endpoint Health, all outside of the submitted work; has obtained patents for risk stratification in sepsis and septic shock issued to Cincinnati Children’s Hospital Medical Center; has served on data safety monitoring boards unrelated to the current work; has held stock options in Bioscape Digital unrelated to the current work; and has served as Editor-in-Chief of the Journal of Clinical and Translational Science. Mr Mace is an employee of Acorai AB; and has held stock interest in Abbott Laboratories. Dr Martyn has served as an advisor to or has received consulting fees from Fire1, Cleveland Clinic/American Well Joint Venture, Boehringer Ingelheim/Eli Lilly, NIRSense, Novo Nordisk, AstraZeneca, and Apricity Robotics; and has received grant support from Ionis Therapeutics, AstraZeneca, and the Heart Failure Society of America. Dr Shah is an employee of Meta, which had no role in this work or providing financial support. Dr Tison has received research grants from MyoKardia, a wholly owned subsidiary of Bristol Myers Squibb, and Janssen Pharmaceuticals; and is an advisor to Viz.ai and Prolaio. Dr Fakhouri is an employee of the Office of Medical Policy, Center for Drug Evaluation and Research, U.S. Food and Drug Administration; the views expressed in this article are those of the authors and do not necessarily represent the views or policies of the U.S. Food and Drug Administration. Dr Krumholz has received options from Element Science and Identifeye; has received payments from F-Prime for advisory roles; has co-founded and held equity in Hugo Health, Refactor Health, and ENSIGHT-AI; and has been associated with research contracts through Yale University from Janssen, Kenvue, and Pfizer. Dr O’Connor has received consulting fees from Merck, Abiomed, and Zealcare. Dr Solomon has received research grants from Alexion, Alnylam, AstraZeneca, Bellerophon, Bayer, Bristol Myers Squibb, Boston Scientific, Cytokinetics, Edgewise, Eidos, Gossamer, GSK, Ionis, Lilly, MyoKardia, NIH NHLBI, Novartis, Novo Nordisk, Respicardia, Sanofi Pasteur, Theracos, and US2.AI; and has consulted for Abbott, Action, Akros, Alexion, Alnylam, Amgen, Arena, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, Cardior, Cardurion, Corvia, Cytokinetics, Daiichi-Sankyo, GSK, Lilly, Merck, MyoKardia, Novartis, Roche, Theracos, Quantum Genomics, Janssen, Cardiac Dimensions, Tenaya, Sanofi-Pasteur, Dinaqor, Tremeau, CellProThera, Moderna, American Regent, Sarepta, Lexicon, AnaCardio, Akros, and Valo. Drs Psotka and Fiuzat have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Cognitive impairment is common in patients with heart failure and preserved ejection fraction but its clinical correlates and prognostic associations are poorly understood., Methods: We analyzed cognitive function, using the Mini-Mental State Examination (MMSE), in patients with heart failure and preserved ejection fraction enrolled in a prespecified substudy of the PARAGON-HF trial (Prospective Comparison of Angiotensin Receptor Neprilysin Inhibitor With Angiotensin Receptor Blocker Global Outcomes in Heart Failure With Preserved Ejection Fraction). Logistic regression analyses were performed to determine the variables associated with lower MMSE scores at baseline and postbaseline decline in MMSE scores at 48 weeks. Cox proportional hazards regression and semiparametric proportional rates models were used to examine the risk of clinical outcomes related to baseline MMSE scores, and decline in MMSE scores during follow-up, adjusted for prognostic variables including NT-proBNP (N-terminal pro-B-type natriuretic peptide)., Results: At baseline, cognitive function was normal (MMSE score 28-30) in 1809 of 2895 patients (62.5%), borderline (score 24-27) in 794 (27.4%), and impaired (score <24) in 292 (10.1%). Variables associated with both a lower MMSE score at baseline and a decline in score from baseline included older age, a history of stroke or transient ischemia attack, and lower serum albumin. Compared with those with baseline MMSE scores of 28 to 30, patients in the lower MMSE score categories had a stepwise increase in the risk of the composite of time to first HF hospitalization or cardiovascular death, with an adjusted hazard ratio of 1.27 (95% CI, 1.06-1.53) for those with scores of 24 to 27 and 1.58 (95% CI, 1.21-2.06) for those with scores <24, respectively. These associations were also found for the individual components of the composite and all-cause death. Likewise, cognitive impairment was associated with a 50% higher risk of total (first and repeat) heart failure hospitalizations and cardiovascular deaths. Examining the change in MMSE score from baseline, a decrease in MMSE score during follow-up was associated with a higher risk of death., Conclusions: In patients with heart failure and preserved ejection fraction, even modest baseline impairment of cognitive function was associated with worse outcomes, including death. A decline in MMSE score during follow-up was a strong predictor of mortality, independent of other prognostic variables.

A common missense variant in ICAM1 among African American individuals (rs5491; pK56M) has been associated with risk of heart failure with preserved ejection fraction (HFpEF), but the pathways that lead to HFpEF among those with this variant are not clear. In this analysis of 92 circulating proteins and their associated networks, we identified 7 circulating inflammatory proteins associated with rs5491 among >600 African American individuals. Using weighted coexpression network analysis, 3 protein networks were identified, one of which was associated with rs5491. This protein network was most highly represented by members of the tumor necrosis receptor superfamily. The rs5491 variant demonstrated an inflammatory proteomic profile in a separate cohort of African American individuals. This analysis identifies inflammatory pathways that may drive HFpEF among African American individuals with the ICAM1 pK56M (rs5491) variant., Competing Interests: Dr Patel is supported by grant R01HL167986 from the NIH. MESA and the MESA SHARe project are conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts 75N92020D00001, HHSN268201500003I, N01-HC-95159, 75N92020D00005, N01-HC-95160, 75N92020D00002, N01-HC-95161, 75N92020D00003, N01-HC-95162, 75N92020D00006, N01-HC-95163, 75N92020D00004, N01-HC-95164, 75N92020D00007, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC95169, UL1-TR-000040, UL1-TR-001079, UL1-TR-001420, UL1-TR-001881, and DK063491. Funding for SHARe genotyping was provided by NHLBI Contract N02-HL-64278. Genotyping was performed at Affymetrix (Santa Clara, California, USA) and the Broad Institute of Harvard and MIT (Boston, Massachusetts, USA) using the Affymetrix Genome-Wide Human SNP Array 6.0. The MESA CARe data used for the analyses described in this manuscript were obtained through Genetics (accession numbers). Funding for CARe genotyping was provided by NHLBI Contract N01-HC-65226. The Atherosclerosis Risk in Communities study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, under Contract nos. (75N92022D00001, 75N92022D00002, 75N92022D00003, 75N92022D00004, 75N92022D00005). Dr Cunningham has received consulting fees from Occlutech, KCK, Roche Diagnostics, and Edgewise Therapeutics and grant support from the American Heart Association (23CDA1052151) and Harvard Catalyst. Dr Sanjiv Shah has received research grants from AstraZeneca, Corvia, and Pfizer, and consulting fees from Abbott, Alleviant, AstraZeneca, Amgen, Aria CV, Axon Therapies, Bayer, Boehringer-Ingelheim, Boston Scientific, Bristol Myers Squibb, Cyclerion, Cytokinetics, Edwards Lifesciences, Eidos, Imara, Impulse Dynamics, Intellia, Ionis, Lilly, Merck, MyoKardia, Novartis, Novo Nordisk, Pfizer, Prothena, Regeneron, Rivus, Sardocor, Shifamed, Tenax, Tenaya, and Ultromics. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© 2024 The Authors.)

Background: Prognostic markers and biological pathways linked to detrimental clinical outcomes in heart failure with preserved ejection fraction (HFpEF) remain incompletely defined., Methods and Results: We measured serum levels of 4123 unique proteins in 1117 patients with HFpEF enrolled in the PARAGON-HF (Efficacy and Safety of LCZ696 Compared to Valsartan, on Morbidity and Mortality in Heart Failure Patients With Preserved Ejection Fraction) trial using a modified aptamer proteomic assay. Baseline circulating protein concentrations significantly associated with the primary end point and the timing and occurrence of total heart failure hospitalization and cardiovascular death were identified by recurrent events regression, accounting for multiple testing, adjusted for age, sex, treatment, and anticoagulant use, and compared with published analyses in 2515 patients with heart failure with reduced ejection fraction from the PARADIGM-HF (Prospective Comparison of ARNI With ACEI to Determine Impact on Global Mortality and Morbidity in Heart Failure) and ATMOSPHERE (Efficacy and Safety of Aliskiren and Aliskiren/Enalapril Combination on Morbidity-Mortality in Patients With Chronic Heart Failure) clinical trials. We identified 288 proteins that were robustly associated with the risk of heart failure hospitalization and cardiovascular death in patients with HFpEF. The baseline proteins most strongly related to outcomes included B2M (β-2 microglobulin), TIMP1 (tissue inhibitor of matrix metalloproteinase 1), SERPINA4 (serpin family A member 4), and SVEP1 (sushi, von Willebrand factor type A, EGF, and pentraxin domain containing 1). Overall, the protein-outcome associations in patients with HFpEF did not markedly differ as compared with patients with heart failure with reduced ejection fraction. A proteomic risk score derived in patients with HFpEF was not superior to a previous proteomic score derived in heart failure with reduced ejection fraction nor to clinical risk factors, NT-proBNP (N-terminal pro-B-type natriuretic peptide), or high-sensitivity cardiac troponin., Conclusions: Numerous serum proteins linked to metabolic, coagulation, and extracellular matrix regulatory pathways were associated with worse HFpEF prognosis in the PARAGON-HF proteomic substudy. Our results demonstrate substantial similarities among serum proteomic risk markers for heart failure hospitalization and cardiovascular death when comparing clinical trial participants with heart failure across the ejection fraction spectrum., Registration: URL: https://www.clinicaltrials.gov; Unique Identifiers: NCT01920711, NCT01035255, NCT00853658.

Importance: The gold standard for outcome adjudication in clinical trials is medical record review by a physician clinical events committee (CEC), which requires substantial time and expertise. Automated adjudication of medical records by natural language processing (NLP) may offer a more resource-efficient alternative but this approach has not been validated in a multicenter setting., Objective: To externally validate the Community Care Cohort Project (C3PO) NLP model for heart failure (HF) hospitalization adjudication, which was previously developed and tested within one health care system, compared to gold-standard CEC adjudication in a multicenter clinical trial., Design, Setting, and Participants: This was a retrospective analysis of the Influenza Vaccine to Effectively Stop Cardio Thoracic Events and Decompensated Heart Failure (INVESTED) trial, which compared 2 influenza vaccines in 5260 participants with cardiovascular disease at 157 sites in the US and Canada between September 2016 and January 2019. Analysis was performed from November 2022 to October 2023., Exposures: Individual sites submitted medical records for each hospitalization. The central INVESTED CEC and the C3PO NLP model independently adjudicated whether the cause of hospitalization was HF using the prepared hospitalization dossier. The C3PO NLP model was fine-tuned (C3PO + INVESTED) and a de novo NLP model was trained using half the INVESTED hospitalizations., Main Outcomes and Measures: Concordance between the C3PO NLP model HF adjudication and the gold-standard INVESTED CEC adjudication was measured by raw agreement, κ, sensitivity, and specificity. The fine-tuned and de novo INVESTED NLP models were evaluated in an internal validation cohort not used for training., Results: Among 4060 hospitalizations in 1973 patients (mean [SD] age, 66.4 [13.2] years; 514 [27.4%] female and 1432 [72.6%] male]), 1074 hospitalizations (26%) were adjudicated as HF by the CEC. There was good agreement between the C3PO NLP and CEC HF adjudications (raw agreement, 87% [95% CI, 86-88]; κ, 0.69 [95% CI, 0.66-0.72]). C3PO NLP model sensitivity was 94% (95% CI, 92-95) and specificity was 84% (95% CI, 83-85). The fine-tuned C3PO and de novo NLP models demonstrated agreement of 93% (95% CI, 92-94) and κ of 0.82 (95% CI, 0.77-0.86) and 0.83 (95% CI, 0.79-0.87), respectively, vs the CEC. CEC reviewer interrater reproducibility was 94% (95% CI, 93-95; κ, 0.85 [95% CI, 0.80-0.89])., Conclusions and Relevance: The C3PO NLP model developed within 1 health care system identified HF events with good agreement relative to the gold-standard CEC in an external multicenter clinical trial. Fine-tuning the model improved agreement and approximated human reproducibility. Further study is needed to determine whether NLP will improve the efficiency of future multicenter clinical trials by identifying clinical events at scale.

Background: Hospitalization is recognized as a sentinel event in the disease trajectory of patients with heart failure (HF), but not all patients experiencing clinical decompensation are ultimately hospitalized. Outpatient intensification of diuretics is common in response to symptoms of worsening HF, yet its prognostic and clinical relevance, specifically for patients with HF with mildly reduced or preserved ejection fraction, is uncertain., Methods: In this prespecified analysis of the DELIVER trial (Dapagliflozin Evaluation to Improve the Lives of Patients With Preserved Ejection Fraction Heart Failure), we assessed the association between various nonfatal worsening HF events (those requiring hospitalization, urgent outpatient visits requiring intravenous HF therapies, and outpatient oral diuretic intensification) and rates of subsequent mortality. We further examined the treatment effect of dapagliflozin on an expanded composite end point of cardiovascular death, HF hospitalization, urgent HF visit, or outpatient oral diuretic intensification., Results: In DELIVER, 4532 (72%) patients experienced no worsening HF event, whereas 789 (13%) had outpatient oral diuretic intensification, 86 (1%) required an urgent HF visit, 585 (9%) had an HF hospitalization, and 271 (4%) died of cardiovascular causes as a first presentation. Patients with a first presentation manifesting as outpatient oral diuretic intensification experienced rates of subsequent mortality that were higher (10 [8-12] per 100 patient-years) than those without a worsening HF event (4 [3-4] per 100 patient-years) but similar to rates of subsequent death after an urgent HF visit (10 [6-18] per 100 patient-years). Patients with an HF hospitalization as a first presentation of worsening HF had the highest rates of subsequent death (35 [31-40] per 100 patient-years). The addition of outpatient diuretic intensification to the adjudicated DELIVER primary end point (cardiovascular death, HF hospitalization, or urgent HF visit) increased the overall number of patients experiencing an event from 1122 to 1731 (a 54% increase). Dapagliflozin reduced the need for outpatient diuretic intensification alone (hazard ratio, 0.72 [95% CI, 0.64-0.82]) and when analyzed as a part of an expanded composite end point of worsening HF or cardiovascular death (hazard ratio, 0.76 [95% CI, 0.69-0.84])., Conclusions: In patients with HF with mildly reduced or preserved ejection fraction, worsening HF requiring oral diuretic intensification in ambulatory care was frequent, adversely prognostic, and significantly reduced by dapagliflozin., Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03619213., Competing Interests: Disclosures Dr Chatur is supported by the Canadian Arthur J.E. Child’s Cardiology Fellowship. Dr Vaduganathan has received research grant support, has served on advisory boards, or has had speaker engagements with American Regent, Amgen, AstraZeneca, Bayer AG, Baxter Healthcare, Boehringer Ingelheim, Chiesi, Cytokinetics, Lexicon Pharmaceuticals, Merck, Novartis, Novo Nordisk, Pharmacosmos, Relypsa, Roche Diagnostics, Sanofi, and Tricog Health; and has participated on clinical trial committees for studies sponsored by AstraZeneca, Galmed, Novartis, Bayer AG, Occlutech, and Impulse Dynamics. Dr Claggett has been a consultant for Amgen, AO Biome, Biogen, Boehringer Ingelheim, Corvia, Gilead, Myokardia, Cardurion, and Novartis. Dr Cunningham has been a consultant for Roche Diagnostics, Occlutech, and KCK. Dr Docherty reports receiving grant support from Novartis and lecture fees from Eli Lilly. Dr Desai has received research grant support from AstraZeneca, Alnylam, and Novartis; and has received consulting fees and honoraria from Abbott, AstraZeneca, Alnylam, Boehringer-Ingelheim, Boston Scientific, Biofourmis, Corvidia, DalCor Pharma, Novartis, Relypsa, and Regeneron. Dr Jhund has received consulting fees, advisory board fees, and lecture fees from Novartis, advisory board fees from Cytokinetics, and grant support from Boehringer Ingelheim. Dr de Boer’s institution, the University Medical Centre Groningen, has received research grants and fees (outside the submitted work) from AstraZeneca, Abbott, Boehringer Ingelheim, Cardio Pharmaceuticals Gmbh, Ionis Pharmaceuticals, Inc, Novo Nordisk, and Roche. Dr de Boer has received speaker fees from Abbott, AstraZeneca, Bayer, Novartis, and Roche (outside the submitted work). Dr Hernandez has received research grant support from American Regent, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Boston Scientific, Bristol Myers Suib, Cytokinetics, Eidos, Intercept, Merck, and Novartis. Dr Lam is supported by a clinician scientist award from the National Medical Research Council of Singapore; has received research support from AstraZeneca, Bayer, Boston Scientific, and Roche Diagnostics, has served as a consultant or was on the advisory board/steering committee/executive committee for Actelion, Amgen, Applied Therapeutics, AstraZeneca, Bayer, Boehringer Ingelheim, Boston Scientific, Cytokinetics, Darma Inc, Us2.ai, Janssen Research & Development LLC, Medscape, Merck, Novartis, Novo Nordisk, Radcliffe Group Ltd, Roche Diagnostics, Sanofi, and WebMD Global LLC; and serves as the cofounder and nonexecutive director of Us2.ai. Dr Inzucchi has served on clinical trial committees or as a consultant to AstraZeneca, Boehringer Ingelheim/Lilly, Novo Nordisk, Merck, Pfizer and Bayer; and has given lectures sponsored by AstraZeneca and Boehringer Ingelheim. Dr Kosiborod has received research grant support from AstraZeneca, and Boehringer Ingelheim; has served as a consultant or on an advisory board for Amgen, Applied Therapeutics, AstraZeneca, Bayer, Boehringer Ingelheim, Eli Lilly, Esperion Therapeutics, Janssen, Merck (Diabetes and Cardiovascular), Novo Nordisk, Sanofi, and Vifor Pharma; has received other research support from AstraZeneca; and has received honoraria from AstraZeneca, Boehringer Ingelheim, and Novo Nordisk. Dr Martinez has received personal fees from AstraZeneca. Dr Shah has received either personal or institutional research support for DELIVER from AstraZeneca. Dr Solomon has received either personal or institutional research support for DELIVER from AstraZeneca. Drs Petersson and Langkilde are employees and shareholders of AstraZeneca. Dr McMurray has received grants from, and his employer was paid by, AstraZeneca, Theracos, and GlaxoSmithKline during the conduct of the study. His employer was paid by Novartis, Amgen, Bristol-Myers Squibb, Bayer, Abb-vie, Dal-Cor, Kidney Research UK, and Cardurion, and he received grants from the British Heart Foundation. Dr Solomon has received research grants from Actelion, Alnylam, Amgen, AstraZeneca, Bellerophon, Bayer, BMS, Celladon, Cytokinetics, Eidos, Gilead, GSK, Ionis, Lilly, Mesoblast, MyoKardia, National Institutes of Health/National Heart, Lung, and Blood Institute, Neurotronik, Novartis, NovoNordisk, Respicardia, Sanofi Pasteur, Theracos, and US2.AI, and has consulted for Abbott, Action, Akros, Alnylam, Amgen, Arena, AstraZeneca, Bayer, Boeringer-Ingelheim, BMS, Cardior, Cardurion, Corvia, Cytokinetics, Daiichi-Sankyo, GSK, Lilly, Merck, Myokardia, Novartis, Roche, Theracos, Quantum Genomics, Cardurion, Janssen, Cardiac Dimensions, Tenaya, Sanofi-Pasteur, Dinaqor, Tremeau, CellProThera, Moderna, American Regent, Sarepta, Lexicon, Anacardio, Akros, and Puretech Health.

Aims: It is uncertain how much candidate biomarkers improve risk prediction when added to comprehensive models including routinely collected clinical and laboratory variables in heart failure., Methods and Results: Aldosterone, cystatin C, high-sensitivity troponin T (hs-TnT), galectin-3, growth differentiation factor-15 (GDF-15), kidney injury molecule-1, matrix metalloproteinase-2 and -9, soluble suppression of tumourigenicity-2, tissue inhibitor of metalloproteinase-1 (TIMP-1) and urinary albumin to creatinine ratio were measured in 1559 of PARADIGM-HF participants. We tested whether these biomarkers, individually or collectively, improved the performance of the PREDICT-HF prognostic model, which includes clinical, routine laboratory, and natriuretic peptide data, for the primary endpoint and cardiovascular and all-cause mortality. The mean age of participants was 67.3 ± 9.9 years, 1254 (80.4%) were men and 1103 (71%) were in New York Heart Association class II. During a mean follow-up of 30.7 months, 300 patients experienced the primary outcome and 197 died. Added individually, only four biomarkers were independently associated with all outcomes: hs-TnT, GDF-15, cystatin C and TIMP-1. When all biomarkers were added simultaneously to the PREDICT-HF models, only hs-TnT remained an independent predictor of all three endpoints. GDF-15 also remained predictive of the primary endpoint; TIMP-1 was the only other predictor of both cardiovascular and all-cause mortality. Individually or in combination, these biomarkers did not lead to significant improvements in discrimination or reclassification., Conclusions: None of the biomarkers studied individually or collectively led to a meaningful improvement in the prediction of outcomes over what is provided by clinical, routine laboratory, and natriuretic peptide variables., (© 2023 The Authors. European Journal of Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Background: Intercellular adhesion molecule-1 (ICAM-1) is a cell surface protein that participates in endothelial activation and is hypothesized to play a central role in heart failure (HF). We evaluated associations of ICAM1 missense genetic variants with circulating ICAM-1 levels and with incident HF., Methods and Results: We identified 3 missense variants within ICAM1 (rs5491, rs5498 and rs1799969) and evaluated their associations with ICAM-1 levels in the Coronary Artery Risk Development in Young Adults Study and the Multi-Ethnic Study of Atherosclerosis (MESA). We determined the association among these 3 variants and incident HF in MESA. We separately evaluated significant associations in the Atherosclerosis Risk in Communities (ARIC) study. Of the 3 missense variants, rs5491 was common in Black participants (minor allele frequency [MAF] > 20%) and rare in other race/ethnic groups (MAF < 5%). In Black participants, the presence of rs5491 was associated with higher levels of circulating ICAM-1 at 2 timepoints separated by 8 years. Among Black participants in MESA (n = 1600), the presence of rs5491 was associated with an increased risk of incident HF with preserved ejection fraction (HFpEF; HR = 2.30; [95% CI 1.25-4.21; P = 0.007]). The other ICAM1 missense variants (rs5498 and rs1799969) were associated with ICAM-1 levels, but there were no associations with HF. In ARIC, rs5491 was significantly associated with incident HF (HR = 1.24 [95% CI 1.02 - 1.51]; P = 0.03), with a similar direction of effect for HFpEF that was not statistically significant., Conclusions: A common ICAM1 missense variant among Black individuals may be associated with increased risk of HF, which may be HFpEF-specific., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Aims: Patients recently hospitalized for heart failure (HF) often have unstable haemodynamics and experience worsening renal failure, and are at elevated risk for recurrent HF events. In DELIVER, dapagliflozin reduced HF events or cardiovascular death including among patients who were hospitalized or recently hospitalized., Methods and Results: We examined the effects of dapagliflozin versus placebo on estimated glomerular filtration rate (eGFR) slope (acute and chronic), 1-month change in systolic blood pressure, and the occurrence of serious hypovolaemic or renal adverse events in patients with and without HF hospitalization within 30 days of randomization. The 654 (90 randomized during hospitalization, 147 1-7 days post-discharge and 417 8-30 days post-discharge) recently hospitalized patients had lower baseline eGFR compared with those without recent HF hospitalization (median [interquartile range] 55 [43, 71] vs. 60 [47, 75] ml/min/1.73 m 2 ). Dapagliflozin consistently reduced the risk of all-cause (p interaction  = 0.20), cardiac-related (p interaction  = 0.75), and HF-specific (p interaction  = 0.90) hospitalizations, irrespective of recent HF hospitalization. In those recently hospitalized, acute placebo-corrected eGFR reductions with dapagliflozin were modest and similar to patients without recent hospitalization (-2.0 [-4.1, +0.1] vs. -3.4 [-3.9, -2.9] ml/min/1.73 m 2 , p interaction  = 0.12). Dapagliflozin's effect to slow chronic eGFR decline was similar regardless of recent hospitalization (p interaction  = 0.57). Dapagliflozin had a minimal effect on 1-month systolic blood pressure and to a similar degree in patients with and without recent hospitalization (-1.3 vs.-1.8 mmHg, p interaction  = 0.64). There was no treatment-related excess in renal or hypovolaemic serious adverse events, irrespective of recent HF hospitalization., Conclusion: In patients recently hospitalized with HF, initiation of dapagliflozin had minimal effects on blood pressure and did not increase renal or hypovolaemic serious adverse events, yet afforded long-term cardiovascular and kidney protective effects. These data suggest that the benefit to risk ratio favours initiation of dapagliflozin among stabilized patients hospitalized or recently hospitalized for HF., Clinical Trial Registration: ClinicalTrials.gov NCT03619213., (© 2023 The Authors. European Journal of Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Background: Scalable and safe approaches for heart failure guideline-directed medical therapy (GDMT) optimization are needed., Objectives: The authors assessed the safety and effectiveness of a virtual care team guided strategy on GDMT optimization in hospitalized patients with heart failure with reduced ejection fraction (HFrEF)., Methods: In a multicenter implementation trial, we allocated 252 hospital encounters in patients with left ventricular ejection fraction ≤40% to a virtual care team guided strategy (107 encounters among 83 patients) or usual care (145 encounters among 115 patients) across 3 centers in an integrated health system. In the virtual care team group, clinicians received up to 1 daily GDMT optimization suggestion from a physician-pharmacist team. The primary effectiveness outcome was in-hospital change in GDMT optimization score (+2 initiations, +1 dose up-titrations, -1 dose down-titrations, -2 discontinuations summed across classes). In-hospital safety outcomes were adjudicated by an independent clinical events committee., Results: Among 252 encounters, the mean age was 69 ± 14 years, 85 (34%) were women, 35 (14%) were Black, and 43 (17%) were Hispanic. The virtual care team strategy significantly improved GDMT optimization scores vs usual care (adjusted difference: +1.2; 95% CI: 0.7-1.8; P < 0.001). New initiations (44% vs 23%; absolute difference: +21%; P = 0.001) and net intensifications (44% vs 24%; absolute difference: +20%; P = 0.002) during hospitalization were higher in the virtual care team group, translating to a number needed to intervene of 5 encounters. Overall, 23 (21%) in the virtual care team group and 40 (28%) in usual care experienced 1 or more adverse events (P = 0.30). Acute kidney injury, bradycardia, hypotension, hyperkalemia, and hospital length of stay were similar between groups., Conclusions: Among patients hospitalized with HFrEF, a virtual care team guided strategy for GDMT optimization was safe and improved GDMT across multiple hospitals in an integrated health system. Virtual teams represent a centralized and scalable approach to optimize GDMT., Competing Interests: Funding Support and Author Disclosures Funding was provided by the Brigham Health Care Redesign Incubator and Startup Program, Brigham and Women’s Hospital, Mass General Brigham, Boston, Massachusetts. Dr Varshney has received consulting fees from Broadview Ventures. Dr Claggett has received consulting fees from Cardurion, Corvia, Cytokinetics, Intellia, and Novartis. Dr Eaton is employed at Brigham and Women’s hospital, but is also employed by Janssen Pharmaceuticals. Dr Cunningham has received consulting fees from Roche Diagnostics and Occlutech. Dr Choudhry has received research grant support to Brigham and Women‘s Hospital from Merck, Sanofi, AstraZeneca, CVS Health, and Medisafe. Dr Solomon has received research grants from Actelion, Alnylam, Amgen, AstraZeneca, Bellerophon, Bayer, Bristol Myers Squibb, Celladon, Cytokinetics, Eidos, Gilead, GlaxoSmithKline, Ionis, Lilly, Mesoblast, MyoKardia, National Institutes of Health/National Heart, Lung, and Blood Institute, Neurotronik, Novartis, NovoNordisk, Respicardia, Sanofi Pasteur, Theracos, and US2.AI; and has consulted for Abbott, Action, Akros, Alnylam, Amgen, Arena, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, Cardior, Cardurion, Corvia, Cytokinetics, Daiichi Sankyo, GlaxoSmithKline, Lilly, Merck, Myokardia, Novartis, Roche, Theracos, Quantum Genomics, Cardurion, Janssen, Cardiac Dimensions, Tenaya, Sanofi-Pasteur, Dinaqor, Tremeau, CellProThera, Moderna, American Regent, and Sarepta. Dr Vaduganathan has received research grant support from, served on advisory boards for, or had speaker engagements with American Regent, Amgen, AstraZeneca, Bayer, Baxter Healthcare, Boehringer Ingelheim, Chiesi, Cytokinetics, Lexicon Pharmaceuticals, Novartis, Novo Nordisk, Pharmacosmos, Relypsa, Roche Diagnostics, Sanofi, and Tricog Health; and participates on clinical trial committees for studies sponsored by AstraZeneca, Galmed, Novartis, Bayer, Occlutech, and Impulse Dynamics. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Myocardial interstitial fibrosis is associated with cardiovascular disease and adverse prognosis. Here, to investigate the biological pathways that underlie fibrosis in the human heart, we developed a machine learning model to measure native myocardial T1 time, a marker of myocardial fibrosis, in 41,505 UK Biobank participants who underwent cardiac magnetic resonance imaging. Greater T1 time was associated with diabetes mellitus, renal disease, aortic stenosis, cardiomyopathy, heart failure, atrial fibrillation, conduction disease and rheumatoid arthritis. Genome-wide association analysis identified 11 independent loci associated with T1 time. The identified loci implicated genes involved in glucose transport (SLC2A12), iron homeostasis (HFE, TMPRSS6), tissue repair (ADAMTSL1, VEGFC), oxidative stress (SOD2), cardiac hypertrophy (MYH7B) and calcium signaling (CAMK2D). Using a transforming growth factor β1-mediated cardiac fibroblast activation assay, we found that 9 of the 11 loci consisted of genes that exhibited temporal changes in expression or open chromatin conformation supporting their biological relevance to myofibroblast cell state acquisition. By harnessing machine learning to perform large-scale quantification of myocardial interstitial fibrosis using cardiac imaging, we validate associations between cardiac fibrosis and disease, and identify new biologically relevant pathways underlying fibrosis., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Background: Absence of a dicrotic notch on finger photoplethysmography is an easily ascertainable and inexpensive trait that has been associated with age and prevalent cardiovascular disease. However, the trait exists along a continuum, and little is known about its genetic underpinnings or prognostic value for incident cardiovascular disease., Methods: In 169 787 participants in the UK Biobank, we identified absent dicrotic notch on photoplethysmography and created a novel continuous trait reflecting notch smoothness using machine learning. Next, we determined the heritability, genetic basis, polygenic risk, and clinical relations for the binary absent notch trait and the newly derived continuous notch smoothness trait., Results: Heritability of the continuous notch smoothness trait was 7.5%, compared with 5.6% for the binary absent notch trait. A genome-wide association study of notch smoothness identified 15 significant loci, implicating genes including NT5C2 ( P =1.2×10 -26 ), IGFBP3 ( P =4.8×10 -18 ), and PHACTR1 ( P =1.4×10 -13 ), compared with 6 loci for the binary absent notch trait. Notch smoothness stratified risk of incident myocardial infarction or coronary artery disease, stroke, heart failure, and aortic stenosis. A polygenic risk score for notch smoothness was associated with incident cardiovascular disease and all-cause death in UK Biobank participants without available photoplethysmography data., Conclusions: We found that a machine learning derived continuous trait reflecting dicrotic notch smoothness on photoplethysmography was heritable and associated with genes involved in vascular stiffness. Greater notch smoothness was associated with greater risk of incident cardiovascular disease. Raw digital phenotyping may identify individuals at risk for disease via specific genetic pathways.

Background: Patients recently hospitalized for heart failure (HF) are at high risk for rehospitalization and death., Objectives: The purpose of this study was to investigate clinical outcomes and response to dapagliflozin in patients with HF with mildly reduced or preserved left ventricular ejection fraction (LVEF) who were enrolled during or following hospitalization., Methods: The DELIVER (Dapagliflozin Evaluation to Improve the LIVES of Patients With PReserved Ejection Fraction Heart Failure) trial randomized patients with HF and LVEF >40% to dapagliflozin or placebo. DELIVER permitted randomization during or shortly after hospitalization for HF in clinically stable patients off intravenous HF therapies. This prespecified analysis investigated whether recent HF hospitalization modified risk of clinical events or response to dapagliflozin. The primary outcome was worsening HF event or cardiovascular death., Results: Of 6,263 patients in DELIVER, 654 (10.4%) were randomized during HF hospitalization or within 30 days of discharge. Recent HF hospitalization was associated with greater risk of the primary outcome after multivariable adjustment (HR: 1.88; 95% CI: 1.60-2.21; P < 0.001). Dapagliflozin reduced the primary outcome by 22% in recently hospitalized patients (HR: 0.78; 95% CI: 0.60-1.03) and 18% in patients without recent hospitalization (HR: 0.82; 95% CI: 0.72-0.94; P interaction = 0.71). Rates of adverse events, including volume depletion, diabetic ketoacidosis, or renal events, were similar with dapagliflozin and placebo in recently hospitalized patients., Conclusions: Dapagliflozin safely reduced risk of worsening HF or cardiovascular death similarly in patients with and without history of recent HF hospitalization. Starting dapagliflozin during or shortly after HF hospitalization in patients with mildly reduced or preserved LVEF appears safe and effective. (Dapagliflozin Evaluation to Improve the LIVEs of Patients With PReserved Ejection Fraction Heart Failure [DELIVER]; NCT03619213)., Competing Interests: Funding Support and Author Disclosures DELIVER was sponsored by AstraZeneca. Dr Cunningham has received grant support from the American College of Cardiology/Association of Black Cardiologists Bristol Myers Squibb Research Award. Dr Claggett has received consulting fees from Amgen, Cardurion, Corvia, and Novartis. Dr Vaduganathan has received research grant support or served on advisory boards for American Regent, Amgen, AstraZeneca, Bayer AG, Baxter Healthcare, Boehringer Ingelheim, Cytokinetics, Lexicon Pharmaceuticals, Novartis, Pharmacosmos, Relypsa, Roche Diagnostics, Sanofi, and Tricog Health; has speaker engagements with AstraZeneca, Novartis, and Roche Diagnostics; and participates on clinical trial committees for studies sponsored by Galmed, Novartis, Bayer AG, Occlutech, and Impulse Dynamics. Dr Desai has received grant support from Abbott, Alnylam, AstraZeneca, Bayer, and Novartis; and has received consulting fees from Abbott, Alnylam, AstraZeneca, Avidity, Axon Therapeutics, Bayer, Biofourmis, Boston Scientific, Cytokinetics, GlaxoSmithKline, Merck, Novartis, Parxel, Regeneron, Roche, and Verily. Dr Jhund's employer has been remunerated for his work on the DELIVER and DAPA-HF trials by AstraZeneca; has received consulting and speaker fees from Novartis, AstraZeneca, and Boehringer Ingelheim; has received research funding from Boehringer Ingelheim; and has received remuneration for clinical trial work from Novo Nordisk and Bayer. Dr de Boer has received research grants and/or fees from AstraZeneca, Abbott, Boehringer Ingelheim, Cardior Pharmaceuticals GmbH, Ionis Pharmaceuticals, Novo Nordisk, and Roche; and has had speaker engagements with Abbott, AstraZeneca, Bayer, Bristol Myers Squibb, Novartis, and Roche. Dr DeMets has received consulting fees from Frontier Science, Actelion, Bristol Myers Squibb, Medtronic, Boston Scientific, GlaxoSmithKline, and Merck; and has received consulting fees and is the owner of DL DeMets Consulting. Dr Hernandez has received research grant support from American Regent, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Merck, Novartis, Somologic, and Verily; and has served as a consultant or on the Advisory Board for Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Boston Scientific, Bristol Myers Squibb, Cytokinetics, Eidos, Intercept, Merck, and Novartis. Dr Inzucchi has served on clinical trial committees and/or as a consultant to AstraZeneca, Boehringer Ingelheim, Novo Nordisk, Lexicon, Merck, Pfizer, vTv Therapeutics, Abbott, and Esperion; and has delivered lectures sponsored by AstraZeneca and Boehringer Ingelheim. Dr Kosiborod has received research grant support from AstraZeneca and Boehringer Ingelheim; has served as a consultant or on an advisory board for Alnylam, Amgen, Applied Therapeutics, AstraZeneca, Bayer, Boehringer Ingelheim, Esperion Therapeutics, Eli Lilly, Janssen, Lexicon, Merck (Diabetes and Cardiovascular), Pharmacosmos, Novo Nordisk, Sanofi, and Vifor; has received other research support from AstraZeneca; and has received honoraria from AstraZeneca, Boehringer Ingelheim, and Novo Nordisk. Dr Lam is supported by a Clinician Scientist Award from the National Medical Research Council of Singapore; has received research support from Bayer and Roche Diagnostics; has served as a consultant or has been on the Advisory Board/Steering Committee/Executive Committee for AstraZeneca, Abbott, Actelion, Alleviant Medical, Allysta Pharma, Amgen, AnaCardio AB, Applied Therapeutics, Bayer, Boehringer Ingelheim, Boston Scientific, Cytokinetics, Darma Inc, EchoNous Inc, Eli Lilly, Impulse Dynamics, Ionis Pharmaceutical, Janssen Research & Development LLC, Medscape/WebMD Global LLC, Merck, Novartis, Novo Nordisk, Prosciento Inc, Radcliffe Group Ltd, Roche Diagnostics, Sanofi, Siemens Healthcare Diagnostics, and Us2.ai; and serves as cofounder and nonexecutive director of Us2.ai. Dr Martinez has received personal fees from AstraZeneca. Dr Shah has received research grants from the National Institutes of Health (U54 HL160273, R01 HL107577, R01 HL127028, R01 HL140731, R01 HL149423), Actelion, AstraZeneca, Corvia, Novartis, and Pfizer; and has received consulting fees from Abbott, Actelion, AstraZeneca, Amgen, Aria CV, Axon Therapies, Bayer, Boehringer Ingelheim, Boston Scientific, Bristol Myers Squibb, Cardiora, Coridea, CVRx, Cyclerion, Cytokinetics, Edwards Lifesciences, Eidos, Eisai, Imara, Impulse Dynamics, GSK, Intellia, Ionis, Ironwood, Lilly, Merck, MyoKardia, Novartis, Novo Nordisk, Pfizer, Prothena, Regeneron, Rivus, Sanofi, Sardocor, Shifamed, Tenax, Tenaya, and United Therapeutics. Dr O’Meara has received research funds (paid to her institution) for clinical trials from American Regent, Amgen, AstraZeneca, Bayer, Cardurion, Cytokinetics, Novartis, and Pfizer; has received consulting fees paid to her or her institutions from AstraZeneca, Bayer, Boehringer Ingelheim, Cytokinetics, Eli Lilly, and Janssen; and has received speaker fees from AstraZeneca, Bayer, and Boehringer Ingelheim. Drs Wilderäng, Lindholm, Petersson, and Langkilde are employees and shareholders of AstraZeneca. Dr McMurray has received funding to his institution, Glasgow University, for his work on clinical trials, consulting, and other research activities from Alnylam, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, Cardurion, Cytokinetics, Dal-Cor, GlaxoSmithKline, Ionis, KBP Biosciences, Novartis, Pfizer, and Theracos; and has received personal lecture fees from the Corpus, Abbott, Hickma, Sun Pharmaceuticals, Medscape/Heart.Org, Radcliffe Cardiology, Servier Director, and Global Clinical Trial Partners (GCTP). Dr Solomon has received research grants from Actelion, Alnylam, Amgen, AstraZeneca, Bellerophon, Bayer, Bristol Myers Squibb, Celladon, Cytokinetics, Eidos, Gilead, GlaxoSmithKline, Ionis, Lilly, Mesoblast, MyoKardia, National Institutes of Health/National Heart, Lung, and Blood Institute, Neurotronik, Novartis, NovoNordisk, Respicardia, Sanofi Pasteur, Theracos, and US2.AI; and has consulted for Abbott, Action, Akros, Alnylam, Amgen, Arena, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, Cardior, Cardurion, Corvia, Cytokinetics, Daiichi-Sankyo, GlaxoSmithKline, Lilly, Merck, Myokardia, Novartis, Roche, Theracos, Quantum Genomics, Cardurion, Janssen, Cardiac Dimensions, Tenaya, Sanofi-Pasteur, Dinaqor, Tremeau, CellProThera, Moderna, American Regent, Sarepta, Lexicon, Anacardio, and Akros. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Aims: The Candesartan in Heart failure Assessment of Reduction in Mortality and morbidity (CHARM) programme consisted of three parallel, randomized, double-blind clinical trials comparing candesartan with placebo in patients with heart failure (HF) categorized according to left ventricular ejection fraction and tolerability to an angiotensin-converting enzyme inhibitor. We conducted a pharmacogenomic study of the CHARM trials with the objective of identifying genetic predictors of HF progression and of the efficacy and safety of treatment with candesartan., Methods: We performed genome-wide association studies in 2727 patients of European ancestry from CHARM-Overall and stratified by CHARM study according to preserved and reduced ejection fraction and according to assignment to the interventional treatment with candesartan. We tested genetic association with the composite endpoint of cardiovascular death or hospitalization for heart failure for drug efficacy in candesartan-treated patients and for HF progression using patients from both candesartan and placebo arms. The safety endpoints for response to candesartan were hyperkalaemia, renal dysfunction, hypotension, and change in systolic blood pressure between baseline and 6 weeks of treatment. To support our observations, we conducted a genome-wide gene-level collapsing analysis from whole-exome sequencing data with the composite cardiovascular endpoint., Results: We found that the A allele (14% allele frequency) of the genetic variant rs66886237 at 8p21.3 near the gene GFRA2 was associated with the composite cardiovascular endpoint in 1029 HF patients with preserved ejection fraction from the CHARM-Preserved study (hazard ratio: 1.91, 95% confidence interval: 1.55-2.35; P = 1.7 × 10 -9 ). The association was independent of candesartan treatment, and the genetic variant was not associated with the cardiovascular endpoint in patients with reduced ejection fraction. None of the genome-wide association studies for candesartan safety or efficacy conducted in patients treated with candesartan passed the significance threshold. We found no significant association from the gene-level collapsing analysis., Conclusions: We have identified a candidate genetic variant potentially predictive of the progression of heart failure in patients with preserved ejection fraction. The findings require further replication, and we cannot exclude the possibility that the results may be chance findings., (© 2022 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Aims: In patients with atrial fibrillation (AF), peripheral artery disease (PAD) is associated with higher rates of stroke and bleeding. Both higher dose edoxaban (60/30 mg) and lower dose edoxaban (30/15 mg) were non-inferior to warfarin for stroke and systemic embolism (SSE) and significantly reduced major bleeding in AF patients in the global study to assess the safety and effectiveness of edoxaban vs standard practice of dosing with warfarin in patients with atrial fibrillation (ENGAGE AF-TIMI 48) trial. Whether the efficacy and safety of these dosing strategies vs. warfarin are consistent in patients with AF and PAD has not been described., Methods and Results: Of 21 105 patients with AF randomized to warfarin, edoxaban 60/30 mg, or edoxaban 30/15 mg, 841 were identified with PAD. Endpoints included major adverse cardiovascular events (MACEs), SSE, and major bleeding. Patients with PAD had higher risk of MACEs [adjusted hazard ratio (HRadj) 1.33, 95% confidence interval (CI) 1.12-1.57, P = 0.001] and cardiovascular (CV) death (HRadj 1.49, 95% CI 1.21-1.83, P &lt; 0.001) than those without PAD, but not major bleeding. The efficacy of edoxaban 60/30 mg vs. warfarin was consistent regardless of PAD (SSE HR; PAD 1.16, 95% CI 0.42-3.20; no-PAD 0.86, 95% CI 0.74-1.02, P-interaction 0.57) as was major bleeding (PAD 0.96, 95% CI 0.54-1.70; no-PAD 0.80, 95% CI 0.70-0.91, P-interaction 0.54). Edoxaban 30/15 mg was inferior for SSE, with significant heterogeneity when stratified by PAD status (P-interaction 0.039)., Conclusion: Patients with AF and PAD are at heightened risk of MACEs and CV death vs. those without PAD. The efficacy and safety of edoxaban 60/30 mg vs. warfarin in AF are consistent regardless of PAD; however, edoxaban 30/15 mg is inferior for stroke prevention in AF patients with PAD. Clinical Trial Registration: ClinicalTrials.gov identifier: NCT00781391., (© The Author(s) 2021. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Background: Cardiac magnetic resonance imaging (CMR) is a powerful diagnostic modality that provides detailed quantitative assessment of cardiac anatomy and function. Automated extraction of CMR measurements from clinical reports that are typically stored as unstructured text in electronic health record systems would facilitate their use in research. Existing machine learning approaches either rely on large quantities of expert annotation or require the development of engineered rules that are time-consuming and are specific to the setting in which they were developed., Objective: We hypothesize that the use of pretrained transformer-based language models may enable label-efficient numerical extraction from clinical text without the need for heuristics or large quantities of expert annotations. Here, we fine-tuned pretrained transformer-based language models on a small quantity of CMR annotations to extract 21 CMR measurements. We assessed the effect of clinical pretraining to reduce labeling needs and explored alternative representations of numerical inputs to improve performance., Methods: Our study sample comprised 99,252 patients that received longitudinal cardiology care in a multi-institutional health care system. There were 12,720 available CMR reports from 9280 patients. We adapted PRAnCER (Platform Enabling Rapid Annotation for Clinical Entity Recognition), an annotation tool for clinical text, to collect annotations from a study clinician on 370 reports. We experimented with 5 different representations of numerical quantities and several model weight initializations. We evaluated extraction performance using macroaveraged F 1 -scores across the measurements of interest. We applied the best-performing model to extract measurements from the remaining CMR reports in the study sample and evaluated established associations between selected extracted measures with clinical outcomes to demonstrate validity., Results: All combinations of weight initializations and numerical representations obtained excellent performance on the gold-standard test set, suggesting that transformer models fine-tuned on a small set of annotations can effectively extract numerical quantities. Our results further indicate that custom numerical representations did not appear to have a significant impact on extraction performance. The best-performing model achieved a macroaveraged F 1 -score of 0.957 across the evaluated CMR measurements (range 0.92 for the lowest-performing measure of left atrial anterior-posterior dimension to 1.0 for the highest-performing measures of left ventricular end systolic volume index and left ventricular end systolic diameter). Application of the best-performing model to the study cohort yielded 136,407 measurements from all available reports in the study sample. We observed expected associations between extracted left ventricular mass index, left ventricular ejection fraction, and right ventricular ejection fraction with clinical outcomes like atrial fibrillation, heart failure, and mortality., Conclusions: This study demonstrated that a domain-agnostic pretrained transformer model is able to effectively extract quantitative clinical measurements from diagnostic reports with a relatively small number of gold-standard annotations. The proposed workflow may serve as a roadmap for other quantitative entity extraction., (©Pulkit Singh, Julian Haimovich, Christopher Reeder, Shaan Khurshid, Emily S Lau, Jonathan W Cunningham, Anthony Philippakis, Christopher D Anderson, Jennifer E Ho, Steven A Lubitz, Puneet Batra. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 16.09.2022.)

Background Whether coronary artery disease (CAD) is a significant risk factor for heart failure (HF) with preserved ejection fraction (HFpEF) is unclear. Methods and Results Among 9902 participants in the ARIC (Atherosclerosis Risk in Communities) study, we assessed the association of incident CAD with subsequent incident HFpEF (left ventricular ejection fraction [≥50%]) and HF with reduced ejection fraction (HFrEF; left ventricular ejection fraction <50%) using survival models with time-updated variables. We also assessed the extent to which echocardiographic correlates of prevalent CAD account for the relationship between CAD and incident HFpEF. Over 13-year follow-up, incident CAD developed in 892 participants and 178 subsequently developed HF (86 HFrEF, 71 HFpEF). Incident HFrEF and HFpEF risk were both greatest early after the CAD event. At >1 year post-CAD event, adjusted incidence of HFrEF and HFpEF were similar (7.2 [95% CI, 5.2-10.0] and 6.7 [4.8-9.2] per 1000 person-years, respectively) and CAD remained predictive of both (HFrEF: hazard ratio, 2.76 [95% CI, 1.99-3.84]; HFpEF: 1.85 [1.35-2.54]) after adjusting for demographics and common comorbidities. Among 4779 HF-free participants at Visit 5 (2011-2013), the 490 with prevalent CAD had lower left ventricular ejection fraction and higher left ventricular mass index, E/e', and left atrial volume index (all P <0.01). The association of prevalent CAD with incident HFpEF post-Visit 5 was not significant after adjusting for echocardiographic measures, with the greatest attenuation observed for left ventricular diastolic function. Conclusions CAD is a significant risk factor for incident HFpEF after adjustment for demographics and common comorbidities. This relationship is partially accounted for by echocardiographic alterations, particularly left ventricular diastolic function.

Background: β-Amyloid has recently been discovered in the myocardium of patients with Alzheimer's disease (AD). Whether genetic variation in apolipoprotein E (APOE) ɛ4, a common variant associated with Alzheimer's disease, is associated with incident heart failure (HF), N-terminal pro-B-type natriuretic peptide (NT-proBNP), and cardiac structure and function is unknown., Methods and Results: We studied 15,064 White and Black participants in the Atherosclerosis Risk in Communities, relating genotype status at visit 1 (1987-1989) to incident HF hospitalization using Cox regression. At visits 2, 4, and 5, we assessed NT-proBNP levels by genotype. At visits 3 and 5, we related Aβ peptides to incident HF. At visit 5 (2011-2013, n = 6251), we assessed the relationship of genotype with prevalent HF and echocardiographic parameters. The mean participant age was 54.7 ± 5.8 years, 45% were men, and 73% were White. At visit 5, there was no difference in prevalent HF by genotype. The APOE ε4 carriers did not have increased risk for HF hospitalization. The APOE ε4 genotype was not associated with cardiac structure and function or NT-proBNP levels. The Aβ peptides were not associated with incident HF after multivariable adjustment., Conclusions: A genetic predisposition to Alzheimer's disease through APOE ε4 is not associated with an increased prevalence of HF, HF hospitalization, myocardial remodeling, or biochemical evidence of HF., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: Compared with enalapril, sacubitril/valsartan lowered HbA1c and reduced new insulin therapy in patients with heart failure with reduced ejection fraction (HFrEF) and diabetes in the PARADIGM-HF trial. We sought to assess the glycemic effects of sacubitril/valsartan in heart failure with preserved ejection fraction (HFpEF) and diabetes, and across the spectrum of left ventricular ejection fraction (LVEF) in heart failure and diabetes., Methods: We compared the effect of sacubitril/valsartan, relative to valsartan, on HbA1c, new insulin therapy and hypoglycemia in the randomized controlled trial PARAGON-HF, and performed pooled analyses of PARAGON-HF and PARADIGM-HF., Results: Among 2395 patients with HFpEF and diabetes in PARAGON-HF, sacubitril/valsartan compared with valsartan reduced HbA1c (baseline-adjusted between-group difference in HbA1c change at 48 weeks: - 0.24%, 95% CI - 0.33 to - 0.16%, P < 0.001). Numerically, new insulin treatment was initiated less often in the sacubitril/valsartan group than in the valsartan group, but the difference was not statistically significant (12.8% vs. 16.1%; HR: 0.80, 95% CI 0.62-1.02, P = 0.07). Hypoglycemia adverse event reports were low, but more frequent in those receiving sacubitril/valsartan than in the valsartan group (4.2% vs. 2.6%; HR: 1.64, 95% CI 1.05-2.56, P = 0.030). In a pooled analysis of PARAGON-HF and PARADIGM-HF, the effect of sacubitril/valsartan on change in HbA1c was not significantly modified by LVEF (P interaction  = 0.56). Across the spectrum of LVEF, sacubitril/valsartan reduced new insulin therapy (HR: 0.75, 95% CI 0.63-0.89, P = 0.001), compared with enalapril or valsartan., Conclusions: Sacubitril/valsartan reduced HbA1c and new insulin therapy in patients with heart failure and diabetes across the spectrum of LVEF but may be associated with a slightly higher risk for hypoglycemia. Trial registration ClinicalTrials.gov NCT01920711., (© 2022. The Author(s).)

The increased need for heart transplantation in patients with advanced heart failure has introduced demand for a greater supply of donor hearts. Progress in cross-species experimental models has led to promise for ushering in the clinical use of xenotransplantation (XTx) as a potential solution to the organ shortage worldwide. In this review, the authors first highlight the historical advances that led to the first pig-to-human heart transplantation, a landmark moment in the field of advanced heart failure. The authors discuss immunologic, infectious, and physiological challenges for implementation of XTx, as well as innovations in the science of genetic manipulation that allowed clinical translation of this therapy. The authors consider ongoing barriers that affect ongoing translation of this technology into clinical care in the current era. Finally, the authors propose a framework for advancing clinical application of XTx., Competing Interests: Dr Mehra has received payments to his institution from Abbott for consulting; has received consulting fees from Janssen, Mesoblast, Broadview Ventures, Natera, Paragonix, Moderna, and the Baim Institute for Clinical Research; and is a scientific advisory board member for NuPulseCV, Leviticus, and FineHeart. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© 2022 The Authors.)

Congenital heart diseases often involve maldevelopment of the evolutionarily recent right heart chamber. To gain insight into right heart structure and function, we fine-tuned deep learning models to recognize the right atrium, right ventricle and pulmonary artery, measuring right heart structures in 40,000 individuals from the UK Biobank with magnetic resonance imaging. Genome-wide association studies identified 130 distinct loci associated with at least one right heart measurement, of which 72 were not associated with left heart structures. Loci were found near genes previously linked with congenital heart disease, including NKX2-5, TBX5/TBX3, WNT9B and GATA4. A genome-wide polygenic predictor of right ventricular ejection fraction was associated with incident dilated cardiomyopathy (hazard ratio, 1.33 per standard deviation; P = 7.1 × 10 -13 ) and remained significant after accounting for a left ventricular polygenic score. Harnessing deep learning to perform large-scale cardiac phenotyping, our results yield insights into the genetic determinants of right heart structure and function., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Background: Of the more than 550,000 patients receiving maintenance hemodialysis (HD) in the United States, each has an average of 1.6 admissions annually (>880,000 inpatient HD sessions). Little is known about the temporal changes in laboratory values, ECGs, and intravascular and extravascular volume during inpatient HD sessions., Methods: In this prospective cohort study of hospitalized HD patients, we assessed intradialytic laboratory values (metabolic panels, blood gases, ionized calcium levels), ECGs, and sonographic measures of volume status., Results: Among 30 participants undergoing HD (mean age 62 years; 53% men, 43% Black) laboratory values had the largest changes in the first hour of HD. There was no significant change in ionized calcium levels pre- to post-HD (change: -0.01±0.07, P =0.24); 12 of 30 and 17 of 30 patients had levels below the lower reference limit at the beginning and end of HD, respectively. The mean pH increased pre- to post-HD (change: 0.06±0.04, P <0.001); 21 of 30 had a pH above the upper reference limit post-HD. There was a trend toward longer median QTc duration from pre- to post-HD (change: 7.5 msec [-5 msec, 19 msec], P =0.07). The sum of B lines on lung ultrasound decreased from pre- to post-HD (median decrease: 3 [1, 7], P <0.01). The collapsibility index of the inferior vena cava increased pre- to post-HD (median increase: 4.8% [1.5%, 13.4%], P =0.01), whereas internal jugular vein diameter did not change ( P =0.24)., Conclusions: Among hospitalized patients undergoing HD, we found dynamic changes in laboratory values, QTc duration, and volume status. Further research is required to assess whether HD prescriptions can be tailored to alter these variations to potentially improve patient outcomes., Competing Interests: F.R. Mc Causland reports consultancy for GlaxoSmithKline, and research funding paid to institution from Advanced Medical and Fifth Eye. E. Platz reports consultancy for Novartis and ScPharmaceuticals; research funding from the National Institutes of Health; and other interests or relationships with Women as One. All remaining authors have nothing to disclose., (Copyright © 2022 by the American Society of Nephrology.)

Electronic health record (EHR) datasets are statistically powerful but are subject to ascertainment bias and missingness. Using the Mass General Brigham multi-institutional EHR, we approximated a community-based cohort by sampling patients receiving longitudinal primary care between 2001-2018 (Community Care Cohort Project [C3PO], n = 520,868). We utilized natural language processing (NLP) to recover vital signs from unstructured notes. We assessed the validity of C3PO by deploying established risk models for myocardial infarction/stroke and atrial fibrillation. We then compared C3PO to Convenience Samples including all individuals from the same EHR with complete data, but without a longitudinal primary care requirement. NLP reduced the missingness of vital signs by 31%. NLP-recovered vital signs were highly correlated with values derived from structured fields (Pearson r range 0.95-0.99). Atrial fibrillation and myocardial infarction/stroke incidence were lower and risk models were better calibrated in C3PO as opposed to the Convenience Samples (calibration error range for myocardial infarction/stroke: 0.012-0.030 in C3PO vs. 0.028-0.046 in Convenience Samples; calibration error for atrial fibrillation 0.028 in C3PO vs. 0.036 in Convenience Samples). Sampling patients receiving regular primary care and using NLP to recover missing data may reduce bias and maximize generalizability of EHR research., (© 2022. The Author(s).)

Aim: Natriuretic peptides (NPs) are now routinely incorporated as key inclusion criteria in clinical trials of heart failure with preserved ejection fraction (HFpEF) as objective measures of risk. An early amendment in PARAGON-HF required all participants to have elevated NP concentrations, but some were enrolled pre-amendment, providing a unique opportunity to understand the influence of enrolment pathway in HFpEF clinical trials., Methods and Results: Among 4796 participants in PARAGON-HF, 193 (4.0%) did not meet the final NP-based enrolment criteria (N-terminal pro-B-type natriuretic peptide >300 pg/ml for patients in sinus rhythm or >900 pg/ml for patients in atrial fibrillation/flutter). These patients had lower rates of the primary endpoint of total heart failure hospitalizations and cardiovascular death as compared with patients meeting final enrolment criteria (8.6 [6.7-11.2] events per 100 patient-years vs. 14.0 [13.4-14.7] events per 100 patient-years; p = 0.01). The rate ratio for the treatment effect comparing sacubitril/valsartan with valsartan was 0.85 (95% confidence interval 0.74-0.99; p = 0.04) in those who met final criteria., Conclusions: Natriuretic peptides are an important tool in HFpEF clinical trials to objectively affirm diagnoses and enrich clinical event rates., (© 2022 The Authors. European Journal of Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Background: Solid-organ transplant (SOT) recipients with coronavirus disease 2019 (COVID-19) have higher risk of adverse outcomes compared to the general population. Whether hospitalized SOT recipients with COVID-19 are at higher risk of mortality than SOT recipients hospitalized for other causes, including non-COVID-19 pneumonia, remains unclear., Methods: We used logistic regression to compare outcomes of SOT recipients hospitalized with COVID-19 to non-COVID-19 related admissions and with non-COVID-19 pneumonia., Results: Of 17,012 hospitalized SOT recipients, 1682 had COVID-19. Those with COVID-19 had higher odds of ICU admission (adjusted odds ratio [aOR] 2.12 [95%CI: 1.88-2.39]) and mechanical ventilation (aOR 3.75 [95%CI: 3.24-4.33]). COVID-19 was associated with higher odds of in-hospital death, which was more pronounced earlier in the pandemic (aOR 9.74 [95%CI: 7.08-13.39] for April/May vs. aOR 7.08 [95%CI: 5.62-8.93] for June through November 2020; P-interaction = .03). Compared to SOT recipients hospitalized with non-COVID-19 pneumonia, odds of in-hospital death were higher in SOT recipients with COVID-19 (aOR 2.44 [95% CI: 1.90-3.13]), regardless of time of hospitalization (P-interaction > .40)., Conclusions: In this large cohort of SOT recipients, hospitalization with COVID-19 was associated with higher odds of complications and in-hospital mortality than non-COVID-19 related admissions, and 2.5-fold higher odds of in-hospital mortality, compared to SOT recipients with non-COVID-19 pneumonia., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Aims: Implementation of guideline-directed medical therapy (GDMT) for heart failure with reduced ejection fraction (HFrEF) remains incomplete. Non-cardiovascular hospitalization may present opportunities for GDMT optimization. We assessed the efficacy and durability of a virtual, multidisciplinary 'GDMT Team' on medical therapy prescription for HFrEF., Methods and Results: Consecutive hospitalizations in patients with HFrEF (ejection fraction ≤40%) were prospectively identified from 3 February to 1 March 2020 (usual care group) and 2 March to 28 August 2020 (intervention group). Patients with critical illness, de novo heart failure, and systolic blood pressure <90 mmHg in the preceeding 24 hs prior to enrollment were excluded. In the intervention group, a pharmacist-physician GDMT Team provided optimization suggestions to treating teams based on an evidence-based algorithm. The primary outcome was a GDMT optimization score, the sum of positive (+1 for new initiations or up-titrations) and negative therapeutic changes (-1 for discontinuations or down-titrations) at hospital discharge. Serious in-hospital safety events were assessed. Among 278 consecutive encounters with HFrEF, 118 met eligibility criteria; 29 (25%) received usual care and 89 (75%) received the GDMT Team intervention. Among usual care encounters, there were no changes in GDMT prescription during hospitalization. In the intervention group, β-blocker (72% to 88%; P = 0.01), angiotensin receptor-neprilysin inhibitor (6% to 17%; P = 0.03), mineralocorticoid receptor antagonist (16% to 29%; P = 0.05), and triple therapy (9% to 26%; P < 0.01) prescriptions increased during hospitalization. After adjustment for clinically relevant covariates, the GDMT Team was associated with an increase in GDMT optimization score (+0.58; 95% confidence interval +0.09 to +1.07; P = 0.02). There were no serious in-hospital adverse events., Conclusions: Non-cardiovascular hospitalizations are a potentially safe and effective setting for GDMT optimization. A virtual GDMT Team was associated with improved heart failure therapeutic optimization. This implementation strategy warrants testing in a prospective randomized controlled trial., (© 2021 European Society of Cardiology.)

Objectives: This study sought to evaluate the frequency and prognostic implications of urgent heart failure (HF) visits in a large global clinical trial of HF with preserved ejection fraction (HFpEF)., Background: Episodes of worsening HF managed without hospitalization are common and prognostically important in HF with reduced ejection fraction (EF). The significance of these ambulatory worsening HF events in HFpEF is uncertain., Methods: PARAGON-HF (Prospective Comparison of ARNI with ARB Global Outcomes in HF with Preserved Ejection Fraction) randomly assigned 4,796 patients with HFpEF (≥45%) to treatment with sacubitril/valsartan vs. valsartan with a primary composite endpoint of total HF hospitalizations and cardiovascular death. Urgent ambulatory HF visits requiring intravenous diuretic treatment were prospectively collected and adjudicated by a blinded committee. We examined the effect of study treatment on a prespecified expanded composite of cardiovascular death and worsening HF events (including HF hospitalizations and urgent HF visits) and the effect of each type of HF event on subsequent mortality., Results: Of 884 first worsening HF events, 66 (7.5%) were urgent HF visits. Patients whose first episode of worsening HF event was an urgent visit had similar age, comorbidities, baseline N-terminal prohormone of B-type natriuretic peptide, and Meta-Analysis Global Group in Chronic Heart Failure risk scores to those in whom the first HF event was a hospitalization (all comparisons p > 0.05). Regardless of the treatment setting, patients with a first episode of worsening HF had higher rates of subsequent death (19.2 per 100 patient-years; 95% confidence interval [CI]: 16.9 to 21.8 for HF hospitalization and 10.1 per 100 patients-years; 95% CI: 5.4 to 18.7 for urgent HF visit) compared with those who did not experience worsening HF (death rate 4.0 per 100 patient-years; 95% CI: 3.6 to 4.4). Including total urgent HF visits in the composite study endpoint added 95 total events and would have shortened the trial duration needed for event accrual. The addition of urgent HF visits in a prespecified composite endpoint reinforced the treatment efficacy of sacubitril/valsartan compared with valsartan (rate ratio 0.86; 95% CI: 0.75 to 0.99; p = 0.040)., Conclusions: Like HF hospitalizations, worsening HF events treated in the ambulatory setting are prognostically important in HFpEF. Inclusion of these events in the composite primary endpoint underscores the benefit of sacubitril/valsartan compared with valsartan in PARAGON-HF. (Prospective Comparison of ARNI with ARB Global Outcomes in HF with Preserved Ejection Fraction [PARAGON-HF]; NCT01920711)., Competing Interests: Funding Support and Author Disclosures The PARAGON-HF trial was sponsored by Novartis. Dr. Vaduganathan has been supported by the KL2/Catalyst Medical Research Investigator Training award from Harvard Catalyst (National Institutes of Health (NIH)/National Center for Advancing Translational Sciences Award UL 1TR002541); has received research grant support and/or serves on advisory boards for American Regent, Amgen, AstraZeneca, Baxter Healthcare, Bayer AG, Boehringer Ingelheim, Cytokinetics, and Relypsa; and has participated on clinical endpoint committees for studies sponsored by Galmed, Novartis (including the PARAGON-HF trial), and NIH. Dr. Cunningham has been supported by National Heart, Lung, and Blood Institute (NHLBI) T32 postdoctoral training grant (T32HL094301). Dr. Claggett has received consultancy fees from Amgen, Boehringer Ingelheim, Gilead, Novartis, AOBiome, and Corvia. Dr. Barkoudah has received research support from Bristol-Myers Squibb, Janssen, NIH, and payments made to Brigham and Women's Hospital for performing clinical endpoints adjudication and Advisory Board fees from Bristol-Myers Squibb, Janssen, Novartis, Pfizer, and Portola, and travel expenses from Alexion. Dr. Zannad has been supported by French National Research Agency Fighting Heart Failure grant ANR-15-RHU-0004, by the French PIA project “Lorraine Université d’Excellence” Functional Genomic, Epigenomic and ENvironment interplay to IMPACT the Understanding, diagnosis and management of healthy and pathological AGEing grant ANR-15-IDEX-04-LUE programmes, the Contrat de Plan Etat Région Lorraine, and the FEDER IT2MP; has received steering committee personal fees from Applied Therapeutics, Amgen, Bayer, Boehringer, Novartis, Janssen, Cellprothera and CVRx; advisory board personal fees from AstraZeneca, Vifor Fresenius, Cardior, Cereno pharmaceutical, Corvidia, Merck, Myokardia, NovoNordisk and Owkin; stock options at Cereno and G3Pharmaceutical; and is the founder of the Global Cardiovascular Clinical Trialist Forum. Dr. Pfeffer has received consulting fees from Amgen, AstraZeneca, Bayer, DalCor Pharma UK, Genzyme, Lilly, the Medicines Company, MedImmune, Medtronic, Merck, Novartis, Novo Nordisk, Relypsa, Salix, Sanderling, Sanofi, Takeda, Teva, Thrasos, and Vericel; and has received research grant support from Amgen, Celladon, Novartis, and Sanofi. The Brigham and Women’s Hospital has patents for the use of inhibitors of the renin–angiotensin system in selected survivors of myocardial infarction with Novartis Pharmaceuticals on which Dr. Pfeffer is a co-inventor. His share of the licensing agreement is irrevocably transferred to charity. Drs. Rizkala and Sabarwal have been employees of Novartis. Dr. Rizkala owns shares in Novartis. Dr. McMurray has received payments from his employer, Glasgow University, for work on clinical trials, consulting and other activities from Alnylam, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, Cardurion, Cytokinetics, Dal-Cor, GlaxoSmithKline, KBP Biosciences, Novartis, Pfizer, and Theracos; and personal payments from Abbott, Hikma, Ionis, Sun Pharmaceuticals, and Servier. Dr. Solomon has received research grants from Actelion, Alnylam, Amgen, AstraZeneca, Bellerophon, Bayer, Bristol Myers Squibb, Celladon, Cytokinetics, Eidos, Gilead, GlaxoSmithKline, Ionis, Lilly, Mesoblast, MyoKardia, NIH/NHLBI, Neurotronik, Novartis, NovoNordisk, Respicardia, Sanofi Pasteur, Theracos; and has consulted for Abbott, Action Akros, Alnylam, Amgen, Arena, AstraZeneca, Bayer, Boehringer-Ingelheim, Bristol Myers Squibb, Cardior, Cardurion, Corvia, Cytokinetics, GlaxoSmithKline, Ironwood, Lilly, Merck, Myokardia, Novartis, Roche, Takeda, Theracos, Quantum Genetics, Janssen, Cardiac Dimensions, Tenaya, Sanofi-Pasteur, Dinaqor, Tremeau, CellProThera, Moderna, and American Regent. Dr. Desai has received research grant support from AstraZeneca, Alnylam, Bayer, and Novartis; and consulting fees and honoraria from Abbott, AstraZeneca, Alnylam, Boehringer Ingelheim, Boston Scientific, Biofourmis, Cytokinetics, DalCor Pharma, Merck, Novartis, Relypsa, and Regeneron. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Membrane-bound angiotensin-converting enzyme 2 is important in regulation of the renin-angiotensin-aldosterone system, but the association of cleaved soluble ACE2 (sACE2) with cardiovascular disease (CVD) is unclear. We evaluated the association of sACE2 with cardiac biomarkers, structure, and function and cardiovascular events in the Atherosclerosis Risk in Communities Study. sACE2 was measured in a subset of 497 participants (mean age 78±5.4 years, 53% men, 27% black); Cox regression analyses assessed prospective associations of sACE2 with time to first CVD event at median 6.1-year follow-up. sACE2 was higher in men, blacks, and participants with prevalent CVD, diabetes, or hypertension. Higher sACE2 levels were associated with significantly higher biomarkers of cardiac injury (high-sensitivity cardiac troponin I and T, N-terminal pro-B-type natriuretic peptide), greater left ventricular mass index, and impaired diastolic function in linear regression analyses, and with increased risk for heart failure hospitalization (adjusted hazard ratio per natural log unit increase [HR] 1.32, 95% confidence interval [CI] 1.10 to 1.58), CVD events (HR 1.34, 95% CI 1.13 to 1.60), and all-cause death (HR 1.26, 95% CI 1.01 to 1.57). In an elderly biracial cohort, sACE2 was positively associated with biomarkers reflecting myocardial injury and neurohormonal activation, left ventricular mass index, impaired diastolic function, CVD, events and all-cause death., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Olive Tang, Elizabeth Selvin, Vijay Nambi, Faiez Zannad, Salim S. Virani, Bing Yu, Jonathan W. Cunningham, Amil M. Shah, Christie M. Ballantyne report financial support was provided by National Institutes of Health, US Department of Veterans Affairs, European Union 7th Framework Programme for Research and Technological Development, World Heart Federation, American Heart Association. Dr. Selvin reports a relationship with Novo Nordisk. that includes:. Dr. Nambi reports a relationship with Merck. that includes:. Ballantyne reports a relationship with Abbott Diagnostic, Denka Seiken, Roche Diagnostic. that includes:. Zannad reports a relationship with Janssen, Bayer, Boston Scientific, Amgen, CVRx, Boehringer, AstraZeneca, Vifor Fresenius, Cardior, Cereno Pharmacuetical, Applied Therapeutics, Merck, and Novartis, CVCT. that includes:. Virani reports a relationship with American College of Cardiology, PALM registry at Duke Clinical Research Institute that includes:. Shah reports a relationship with Novartis, Philips Ultrasound that includes:. De Lemos reports a relationship with Roche Diagnostics, Abbott Diagnostics, Ortho Clinical Diagnostics, Quidel Cardiovascular, Inc. that includes:. Dr. Hoogeveen reports a relationship with Denka Seiken that includes:. Declaration of competing interests: Dr. Selvin: honoraria from Novo Nordisk. Dr. Nambi: site PI study sponsored by Merck. Dr. Zannad: personal fees from Janssen, Bayer, Boston Scientific, Amgen, CVRx, Boehringer, AstraZeneca, Vifor Fresenius, Cardior, Cereno Pharmacuetical, Applied Therapeutics, Merck, and Novartis; founder of CVCT. Dr. Virani: honorarium: American College of Cardiology (Associate editor for Innovations acc.org); Steering Committee member: PALM registry at Duke Clinical Research Institute (no financial remuneration). Dr Shah: research support (significant; paid to institution, not patient) from Novartis, and consultant (modest) for Philips Ultrasound. Dr. de Lemos: grant support and consulting income from Roche Diagnostics and Abbott Diagnostics, consulting income from Ortho Clinical Diagnostics and Quidel Cardiovascular, Inc. Dr. Hoogeveen: grant support and consulting fees from Denka Seiken outside the submitted work. Dr. Ballantyne: grants/research support (significant; paid to institution, not patient): Abbott Diagnostic, Roche Diagnostic; consultant (modest): Abbott Diagnostic, Denka Seiken, Roche Diagnostic. Dr. Hussain, Ms. Tang, Ms. Sun, Dr. Jia, Dr. Folsom, Dr. Heiss, Dr. Mosley, Dr. Coresh, Dr. Boerwinkle, Dr. Yu, Dr. Cunningham, Dr. Solomon: none. Grant support: The Atherosclerosis Risk in Communities study has been funded in whole or in part with federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services (contract numbers HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700005I, HHSN268201700004I). This work was supported by NIH grants F30-DK120160 (O.T.), K24-DK106414 (E.S.), R01-DK089174 (E.S.), R01-HL134320 (E.S. and C.M.B.), R01-HL141824 (B.Y.), R01-HL142003 (B.Y.), T32-HL094301 (J.W.C.), R01-HL135008 (A.M.S.), R01-HL143224 (A.M.S.), R01-HL150342 (A.M.S.), and K24-HL152008 (A.M.S.)]; US Department of Veterans Affairs grants 1I01CX001112-01 (V.N.), IIR 16-072 (S.V.), and IIR 19-069 (S.V.); European Union 7th Framework Programme for Research and Technological Development grant HEALTH-F7-305507 (F.Z., as part of Heart OMics in AGEing); World Heart Federation (S.V.); and American Heart Association grant 17SDG33661228 (B.Y.)., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Abstract: Third-trimester bleeding is an obstetric emergency and is associated with significant maternal and fetal morbidity and mortality. The two most common causes for third-trimester bleeding are placental abruption and placenta previa, which account for about half of all cases. Clinicians should have a thorough understanding of the risk factors, clinical presentation, and appropriate management of these conditions. Timely management is necessary for the survival of mother and fetus and to reduce the incidence of neonatal complications., (Copyright © 2021 American Academy of Physician Assistants.)

Objectives: The purpose of this study was to evaluate in-hospital outcomes among patients with a history of heart failure (HF) hospitalized with coronavirus disease-2019 (COVID-19)., Background: Cardiometabolic comorbidities are common in patients with severe COVID-19. Patients with HF may be particularly susceptible to COVID-19 complications., Methods: The Premier Healthcare Database was used to identify patients with at least 1 HF hospitalization or 2 HF outpatient visits between January 1, 2019, and March 31, 2020, who were subsequently hospitalized between April and September 2020. Baseline characteristics, health care resource utilization, and mortality rates were compared between those hospitalized with COVID-19 and those hospitalized with other causes. Predictors of in-hospital mortality were identified in HF patients hospitalized with COVID-19 by using multivariate logistic regression., Results: Among 1,212,153 patients with history of HF, 132,312 patients were hospitalized from April 1, 2020, to September 30, 2020. A total of 23,843 patients (18.0%) were hospitalized with acute HF, 8,383 patients (6.4%) were hospitalized with COVID-19, and 100,068 patients (75.6%) were hospitalized with alternative reasons. Hospitalization with COVID-19 was associated with greater odds of in-hospital mortality as compared with hospitalization with acute HF; 24.2% of patients hospitalized with COVID-19 died in-hospital compared to 2.6% of those hospitalized with acute HF. This association was strongest in April (adjusted odds ratio [OR]: 14.48; 95% confidence interval [CI]:12.25 to 17.12) than in subsequent months (adjusted OR: 10.11; 95% CI: 8.95 to 11.42; p interaction  <0.001). Among patients with HF hospitalized with COVID-19, male sex (adjusted OR: 1.26; 95% CI: 1.13 to 1.40) and morbid obesity (adjusted OR: 1.25; 95% CI: 1.07 to 1.46) were associated with greater odds of in-hospital mortality, along with age (adjusted OR: 1.35; 95% CI: 1.29 to 1.42 per 10 years) and admission earlier in the pandemic., Conclusions: Patients with HF hospitalized with COVID-19 are at high risk for complications, with nearly 1 in 4 dying during hospitalization., Competing Interests: Author Disclosures Dr. Bhatt has received speaker fees from Sanofi Pasteur; and is supported by National Heart, Lung, and Blood Institute T32 post-doctoral training grant T32HL007604. Dr. Jering is supported by National Heart, Lung, and Blood Institute T32 post-doctoral training grant T32HL007604. Dr. Vaduganathan has received grants from Harvard Catalyst, grants and personal fees from Amgen, and personal fees from AstraZeneca, Baxter HealthCare, Bayer AG, Boehringer Ingelheim, Cytokinetics, and Relypsa outside the submitted work. Dr. Claggett has received personal fees from Amgen, Boehringer Ingelheim, Corvia, MyoKardia, and Novartis outside the submitted work. Dr. Cunningham is supported by National Heart, Lung, and Blood Institute T32 post-doctoral training grant T32HL007604. Dr. Rosenthal is an employee of Premier Inc., which curates the Premier Healthcare Database. Dr. Signorovitch is an employee of Analysis Group, Inc. Dr. Thune has received lecture fees from Bristol-Myers Squibb; and has received personal fees and travel support from Novartis. Dr. Vardeny has received research support from U.S. National Institutes of Health; and is a consultant for Sanofi-Pasteur. Dr. Solomon has received grants from Alnylam, Amgen, AstraZeneca, Bellerophon, Bayer, Bristol-Myers Squibb, Celladon, Cytokinetics, Eidos, Gilead, GlaxoSmithKline, Ionis, Lone Star Heart, Mesoblast, MyoKardia, Neurotronik, National Institutes of Health/National Heart, Lung, and Blood Institute, Novartis, Respicardia, Sanofi Pasteur, and Theracos; and has received personal fees from Akros, Alnylam, Amgen, Arena, AstraZeneca, Bayer, Bristol-Meyers Squibb, Cardior, Cardurion, Corvia, Cytokinetics, Daiichi-Sankyo, Gilead, GlaxoSmithKline, Ironwood, Merck, Myokardia, Novartis, Roche, Takeda, Theracos, Quantum Genetics, Cardurion, AoBiome, Janssen, Cardiac Dimensions, Sanofi-Pasteur, Tenaya, Dinaqor, Tremeau, CellProThera, and Moderna outside the submitted work., (Copyright © 2021 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)