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AI-Based Fully Automated Left Atrioventricular Coupling Index as a Prognostic Marker in Patients Undergoing Stress CMR.
Pezel, Théo; Garot, Philippe; Toupin, Solenn; Sanguineti, Francesca; Hovasse, Thomas; Unterseeh, Thierry; Champagne, Stéphane; Morisset, Stéphane; Chitiboi, Teodora; Jacob, Athira J; Sharma, Puneet; Venkatesh, Bharath Ambale; Lima, João A C; Garot, Jérôme.
Afiliación
  • Pezel T; Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques Cartier, Ramsay Santé, Massy, France; Inserm UMRS 942, Service de Cardiologie, Hôpital Lariboisière, Assistance Publique-Hôpitaux de Paris, Université Paris Cité, Paris, France.
  • Garot P; Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques Cartier, Ramsay Santé, Massy, France.
  • Toupin S; Scientific Partnerships, Siemens Healthcare France, Saint-Denis, France.
  • Sanguineti F; Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques Cartier, Ramsay Santé, Massy, France.
  • Hovasse T; Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques Cartier, Ramsay Santé, Massy, France.
  • Unterseeh T; Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques Cartier, Ramsay Santé, Massy, France.
  • Champagne S; Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques Cartier, Ramsay Santé, Massy, France.
  • Morisset S; Independent Biostatistician, Assistance Publique-Hôpitaux de Paris, Université Paris Cité, Paris, France.
  • Chitiboi T; Siemens Healthcare GmbH, Hamburg, Germany.
  • Jacob AJ; Digital Technologies and Innovation, Siemens Healthineers, Princeton, New Jersey, USA.
  • Sharma P; Digital Technologies and Innovation, Siemens Healthineers, Princeton, New Jersey, USA.
  • Venkatesh BA; Division of Cardiology, Department of Medicine, Johns Hopkins Hospital, Johns Hopkins University School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA; Department of Radiology, Johns Hopkins Hospital, Johns Hopkins University School of Medicine, Johns Hopkins University, Baltimore,
  • Lima JAC; Division of Cardiology, Department of Medicine, Johns Hopkins Hospital, Johns Hopkins University School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA; Department of Radiology, Johns Hopkins Hospital, Johns Hopkins University School of Medicine, Johns Hopkins University, Baltimore,
  • Garot J; Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques Cartier, Ramsay Santé, Massy, France. Electronic address: jgarot@angio-icps.com.
JACC Cardiovasc Imaging ; 16(10): 1288-1302, 2023 10.
Article en En | MEDLINE | ID: mdl-37052568
ABSTRACT

BACKGROUND:

The left atrioventricular coupling index (LACI) is a strong and independent predictor of heart failure (HF) in individuals without clinical cardiovascular disease. Its prognostic value is not established in patients with cardiovascular disease.

OBJECTIVES:

This study sought to determine in patients undergoing stress cardiac magnetic resonance (CMR) whether fully automated artificial intelligence-based LACI can provide incremental prognostic value to predict HF.

METHODS:

Between 2016 and 2018, the authors conducted a longitudinal study including all consecutive patients with abnormal (inducible ischemia or late gadolinium enhancement) vasodilator stress CMR. Control subjects with normal stress CMR were selected using propensity score matching. LACI was defined as the ratio of left atrial to left ventricular end-diastolic volumes. The primary outcome included hospitalization for acute HF or cardiovascular death. Cox regression was used to evaluate the association of LACI with the primary outcome after adjustment for traditional risk factors.

RESULTS:

In 2,134 patients (65 ± 12 years, 77% men, 11 matched patients [1,067 with normal and 1,067 with abnormal CMR]), LACI was positively associated with the primary outcome (median follow-up 5.2 years [IQR 4.8-5.5 years]) before and after adjustment for risk factors in the overall propensity-matched population (adjusted HR 1.18 [95% CI 1.13-1.24]), in patients with abnormal CMR (adjusted HR per 0.1% increment 1.22 [95% CI 1.14-1.30]), and in patients with normal CMR (adjusted HR per 0.1% increment 1.12 [95% CI 1.05-1.20]) (all P < 0.001). After adjustment, a higher LACI of ≥25% showed the greatest improvement in model discrimination and reclassification over and above traditional risk factors and stress CMR findings (C-index improvement 0.16; net reclassification improvement = 0.388; integrative discrimination index = 0.153, all P < 0.001; likelihood ratio test P < 0.001).

CONCLUSIONS:

LACI is independently associated with hospitalization for HF and cardiovascular death in patients undergoing stress CMR, with an incremental prognostic value over traditional risk factors including inducible ischemia and late gadolinium enhancement.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Enfermedades Cardiovasculares / Insuficiencia Cardíaca Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Male Idioma: En Año: 2023 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Enfermedades Cardiovasculares / Insuficiencia Cardíaca Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Male Idioma: En Año: 2023 Tipo del documento: Article