Nancy Muriel Herrera Leano

All Publications

• Impact of the 2025 ASE Guidelines on the Classification of LV Diastolic Dysfunction in the Community: A Project Baseline Health Study. Circulation. Cardiovascular imaging Herrera-Leaño, N., Celestin, B., Santana, E., Sandoval, R., Fahed, G., Khoury, P., O'Sullivan, J. W., Kuznetsova, T., Cauwenberghs, N., Mahaffey, K. W., Douglas, P. S., Daubert, M., Haddad, F. 2026: e019402

  Abstract

  The 2016 American Society of Echocardiography (ASE) guidelines for left ventricular diastolic dysfunction (LVDD) classification resulted in a significant proportion of indeterminate classifications and grades. To address these limitations and incorporate new evidence, the ASE updated its recommendations in 2025. The impact of these revisions in community cohorts remains unclear.We studied 1953 Project Baseline Health Study participants who underwent comprehensive transthoracic echocardiography. LVDD was classified using the 2016 and 2025 ASE recommendations. For the 2025 recommendations, fixed and age-specific thresholds were evaluated separately. We compared LVDD prevalence, reclassification patterns, associations with cardiovascular risk factors, and prognostic value for major adverse cardiovascular events over a median follow-up of 4.3 years.Median age was 50.6 years (Q1-Q3: 36.3-64.2); 56.3% were female, 35.3% had hypertension, and 14.2% had diabetes. The prevalence of LVDD was higher with the 2025 recommendations than with the 2016 algorithm: fixed criteria 308 (15.8%), age-specific criteria 220 (11.3%) versus ASE 2016 154 (8.0%). Among 119 (6.1%) participants classified as indeterminate by the 2016 algorithm, the 2025 recommendations reclassified 51.2% as no LVDD and 31.8% as Grade 2 LVDD. Participants reclassified as no LVDD had event-free survival that was not statistically different from those without LVDD (P=0.26), whereas those reclassified as Grade 2 had higher event rates (12.5% versus 3.8%; P=0.02). Major adverse cardiovascular events occurred in 98 (5.0%) participants over the follow-up period. LVDD by all classification approaches was independently associated with major adverse cardiovascular events after adjustment for baseline risk factors.The 2025 ASE recommendations identified more participants with LVDD than the 2016 algorithm without indeterminate classification or grading. LVDD by the 2025 classification was significantly associated with major adverse cardiovascular events, supporting the clinical relevance of the revised framework.

  View details for DOI 10.1161/CIRCIMAGING.125.019402

  View details for PubMedID 42131912

• A Case of Heart Failure With Reduced Ejection Fraction Secondary to Dilated Cardiomyopathy due to Long-Standing Untreated Acromegaly: A Case Report and Focused Literature Review CLINICAL CASE REPORTS Porras Bueno, C., Herrera Leano, N., Soto Chavez, M., Parra Prieto, D., Marino Correa, A. 2026; 14 (4)

  View details for DOI 10.1002/ccr3.72420

  View details for Web of Science ID 001727235000001

• Old Criteria, New Intelligence: The Evolution of ECG in Pulmonary Hypertension Diagnosis. Respiratory medicine Herrera-Leaño, N., Sahay, S., Benza, R. L., Barahona-Correa, J., Haddad, F. 2026: 108646

  Abstract

  Pulmonary hypertension (PH) carries a significant mortality risk, highlighting the need for improved early detection strategies. This review examines the evolution of electrocardiographic assessment in PH diagnosis, from traditional criteria to artificial intelligence (AI) algorithms.We conducted a literature review analyzing 24 studies published between 1986 and 2025, including 18 traditional ECG validation studies and 6 AI-based investigations. Methodological quality was assessed using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) and QUADAS-AI frameworks. Studies were categorized by approach and diagnostic performance metrics were systematically evaluated.Traditional ECG criteria demonstrated consistently high specificity (71-100%) but low sensitivity (0-66%) for detection of PH, limiting screening utility while maintaining confirmatory value. AI-based algorithms achieved superior balanced diagnostic performance with sensitivity of 74-85% and specificity of 85%. AI algorithms also demonstrated early detection capability, identifying PH up to 2-5 years before conventional clinical diagnosis.Traditional criteria retain value for diagnosis and response to therapy, while AI can be leveraged for early detection of PH. Implementation requires addressing computational infrastructure, healthcare provider training, and regulatory approval.

  View details for DOI 10.1016/j.rmed.2026.108646

  View details for PubMedID 41544985