Objective: The objective of this study was to describe the prevalence of obesity, obesity-related conditions (ORCs), and antiobesity medication (AOM) eligibility and prescribing practice among eligible patients in a large health care system.
Methods: In this cross-sectional analysis of the multicenter Mass General Brigham health care system (Boston, Massachusetts) spanning 2018 to 2022, adults eligible for AOMs (BMI ≥ 30 kg/m or BMI 27-29.9 kg/m with ≥1 ORC) were identified.
A majority of patients with heart failure (HF) do not receive adequate medical therapy as recommended by clinical guidelines. One major obstacle encountered by population health management (PHM) programs to improve medication usage is the substantial burden placed on clinical staff who must manually sift through electronic health records (EHRs) to ascertain patients' eligibility for the guidelines. As a potential solution, the study team developed a rule-based system (RBS) that automatically parses the EHR for identifying patients with HF who may be eligible for guideline-directed therapy.
View Article and Find Full Text PDFBackground And Aims: Individuals with heart failure (HF), other forms of cardiovascular disease, or kidney disease are at increased risk for the development and adverse health effects of diabetes. As such, prevention or delay of diabetes is an important treatment priority in these groups. The aim of this meta-analysis was to determine the effect of sodium-glucose co-transporter 2 inhibitors (SGLT2i) on incident diabetes in HF across the spectrum of left ventricular ejection fraction (LVEF) and across the broader spectrum of cardiovascular or kidney disease.
View Article and Find Full Text PDFImportance: Kidney health has received increasing focus as part of comprehensive heart failure (HF) treatment efforts. However, the occurrence of clinically relevant kidney outcomes in contemporary populations with HF has not been well studied.
Objective: To examine rates of incident dialysis and acute kidney injury (AKI) among Medicare beneficiaries after HF hospitalization.
Aims: Type 2 diabetes (T2D) and heart failure (HF) frequently coexist, but whether clinical outcomes and treatment effects of sodium-glucose cotransporter 2 inhibitors (SGLT2i) vary in relation to background glucose-lowering therapy (GLT) in this population is uncertain.
Methods And Results: DELIVER randomized patients with HF and left ventricular ejection fraction (LVEF) >40% to dapagliflozin or placebo. The primary outcome was a composite of worsening HF (HF hospitalization or urgent HF visit) or cardiovascular death.
Aims: To describe the baseline characteristics of participants in the FINEARTS-HF trial, contextualized with prior trials including patients with heart failure (HF) with mildly reduced and preserved ejection fraction (HFmrEF/HFpEF). The FINEARTS-HF trial is comparing the effects of the non-steroidal mineralocorticoid receptor antagonist finerenone with placebo in reducing cardiovascular death and total worsening HF events in patients with HFmrEF/HFpEF.
Methods And Results: Patients with symptomatic HF, left ventricular ejection fraction (LVEF) ≥40%, estimated glomerular filtration rate ≥ 25 ml/min/1.
This review serves to compare contemporary clinical practice recommendations for the management of heart failure (HF), as codified in the 2021 European Society of Cardiology (ESC) guideline, the 2022 American College of Cardiology (ACC)/American Heart Association (AHA)/Heart Failure Society of America (HFSA) guideline, and the 2023 focused update of the 2021 ESC document. Overall, these guidelines aim to solidify significant advances throughout the HF continuum since the publication of previous full guideline iterations (2013 and 2016 for the ACC/AHA and ESC, respectively). All guidelines provide new recommendations for an increasingly complex landscape of HF care, with focus on primary HF prevention, HF stages, rapid initiation and optimization of evidence-based pharmacotherapies, overlapping cardiac and noncardiac comorbidities, device-based therapies, and management pathways for special groups of patients, including those with cardiac amyloidosis.
View Article and Find Full Text PDFImportance: The transformative potential of artificial intelligence (AI), particularly via large language models, is increasingly being manifested in healthcare. Dietary interventions are foundational to weight management efforts, but whether AI techniques are presently capable of generating clinically applicable diet plans has not been evaluated.
Objective: Our study sought to evaluate the potential of personalized AI-generated weight-loss diet plans for clinical applications by employing a survey-based assessment conducted by experts in the fields of obesity medicine and clinical nutrition.