Nicolas Thellier1, Alexandre Altes2, Ludovic Appert2, Camille Binda2, Blandine Leman3, Wassima Marsou2, Nicolas Debry2, Camille Joly4, Pierre-Vladimir Ennezat5, Christophe Tribouilloy6, Sylvestre Maréchaux7. 1. Université Lille Nord de France, GCS-Groupement des Hôpitaux de l'Institut Catholique de Lille, Laboratoire d'échocardiographie, services de cardiologies, Centre des Valvulopathies, Faculté de Médecine et de Maïeutique, Université Catholique de Lille, Lille, France; Centre Universitaire de Recherche en Santé, Laboratoire MP3CV-EA 7517, Université de Picardie, Amiens, France. 2. Université Lille Nord de France, GCS-Groupement des Hôpitaux de l'Institut Catholique de Lille, Laboratoire d'échocardiographie, services de cardiologies, Centre des Valvulopathies, Faculté de Médecine et de Maïeutique, Université Catholique de Lille, Lille, France. 3. Université Lille Nord de France, GCS-Groupement des Hôpitaux de l'Institut Catholique de Lille, Laboratoire d'échocardiographie, services de cardiologies, Centre des Valvulopathies, Faculté de Médecine et de Maïeutique, Université Catholique de Lille, Lille, France; Centre Hospitalier de Valenciennes, Service de cardiologie, Valenciennes, France. 4. Université Lille Nord de France, GCS-Groupement des Hôpitaux de l'Institut Catholique de Lille, Délégation à la recherche clinique et l'innovation, Lille, France. 5. Centre Hospitalier Universitaire de Grenoble, Grenoble, France. 6. Centre Universitaire de Recherche en Santé, Laboratoire MP3CV-EA 7517, Université de Picardie, Amiens, France; Centre Hospitalier Universitaire d'Amiens, Amiens, France. 7. Université Lille Nord de France, GCS-Groupement des Hôpitaux de l'Institut Catholique de Lille, Laboratoire d'échocardiographie, services de cardiologies, Centre des Valvulopathies, Faculté de Médecine et de Maïeutique, Université Catholique de Lille, Lille, France; Centre Universitaire de Recherche en Santé, Laboratoire MP3CV-EA 7517, Université de Picardie, Amiens, France. Electronic address: Sylvestre.marechaux@yahoo.fr.
Abstract
BACKGROUND: Impaired left ventricular (LV) speckle-tracking-derived global longitudinal strain (GLS) magnitude (GLS worse than 14.7%) has been associated with poor outcome in patients with severe aortic stenosis (AS) and preserved LV ejection fraction (EF). OBJECTIVES: To test the hypothesis that GLS magnitude ≤ 15% obtained with vendor-independent speckle-tracking strain software may be able to identify patients with severe AS who are at higher risk of death, despite preserved LVEF and no or mild symptoms. METHODS: GLS was retrospectively obtained in 332 patients with severe AS (aortic valve area indexed [AVAi] < 0.6 cm2/m2), no or mild symptoms, and LVEF ≥ 50%. Absolute values of GLS were collected. Survival analyses were carried out to study the impact of GLS magnitude on all-cause mortality. RESULTS: During a median follow-up period of 42 (37-46) months, 105 patients died. On multivariate analysis, and after adjustment of known clinical and/or echocardiographic predictors of outcome and aortic valve replacement as a time-dependent covariate, GLS magnitude ≤ 15% was independently associated with mortality during follow-up (all P < .01). Adding GLS magnitude ≤ 15% (adjusted hazard ratio = 1.99 [1.17-3.38], P = .011) to a multivariate model including clinical and echocardiographic variables of prognostic importance (aortic valve replacement, aortic valve area, LV stroke volume index < 30 mL/m2, and LVEF<60%) improved the predictive performance with improved global model fit, reclassification, and better discrimination. After propensity score matching (n = 196), increased risk of mortality persisted among patients with GLS magnitude ≤ 15% compared with those with GLS > 15% (hazard ratio = 2.10; 95% confidence interval, 1.20-3.68; P = .009). CONCLUSIONS: In this series of patients with severe AS, no or mild symptoms, and LVEF ≥ 50%, GLS obtained with vendor-independent speckle-tracking strain software was an effective tool to identify patients with a poor outcome. Detection of myocardial dysfunction by identifying GLS magnitude < 15% in patients with severe AS, no or mild symptoms, and LVEF ≥ 50%, can aid in risk assessment.
BACKGROUND: Impaired left ventricular (LV) speckle-tracking-derived global longitudinal strain (GLS) magnitude (GLS worse than 14.7%) has been associated with poor outcome in patients with severe aortic stenosis (AS) and preserved LV ejection fraction (EF). OBJECTIVES: To test the hypothesis that GLS magnitude ≤ 15% obtained with vendor-independent speckle-tracking strain software may be able to identify patients with severe AS who are at higher risk of death, despite preserved LVEF and no or mild symptoms. METHODS: GLS was retrospectively obtained in 332 patients with severe AS (aortic valve area indexed [AVAi] < 0.6 cm2/m2), no or mild symptoms, and LVEF ≥ 50%. Absolute values of GLS were collected. Survival analyses were carried out to study the impact of GLS magnitude on all-cause mortality. RESULTS: During a median follow-up period of 42 (37-46) months, 105 patientsdied. On multivariate analysis, and after adjustment of known clinical and/or echocardiographic predictors of outcome and aortic valve replacement as a time-dependent covariate, GLS magnitude ≤ 15% was independently associated with mortality during follow-up (all P < .01). Adding GLS magnitude ≤ 15% (adjusted hazard ratio = 1.99 [1.17-3.38], P = .011) to a multivariate model including clinical and echocardiographic variables of prognostic importance (aortic valve replacement, aortic valve area, LV stroke volume index < 30 mL/m2, and LVEF<60%) improved the predictive performance with improved global model fit, reclassification, and better discrimination. After propensity score matching (n = 196), increased risk of mortality persisted among patients with GLS magnitude ≤ 15% compared with those with GLS > 15% (hazard ratio = 2.10; 95% confidence interval, 1.20-3.68; P = .009). CONCLUSIONS: In this series of patients with severe AS, no or mild symptoms, and LVEF ≥ 50%, GLS obtained with vendor-independent speckle-tracking strain software was an effective tool to identify patients with a poor outcome. Detection of myocardial dysfunction by identifying GLS magnitude < 15% in patients with severe AS, no or mild symptoms, and LVEF ≥ 50%, can aid in risk assessment.
Authors: Tetsuji Kitano; Attila Kovács; Yosuke Nabeshima; Márton Tokodi; Alexandra Fábián; Bálint Károly Lakatos; Masaaki Takeuchi Journal: Front Cardiovasc Med Date: 2022-02-25