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Aimo A, Fabiani I, Vergaro G, Arzilli C, Chubuchny V, Pasanisi EM, Petersen C, Poggianti E, Taddei C, Pugliese NR, Bayes-Genis A, Lupón J, Giannoni A, Ripoli A, Georgiopoulos G, Passino C, Emdin M. Prognostic value of reverse remodelling criteria in heart failure with reduced or mid-range ejection fraction. ESC Heart Fail 2021; 8:3014-3025. [PMID: 34002938 PMCID: PMC8318429 DOI: 10.1002/ehf2.13396] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 04/14/2021] [Accepted: 04/19/2021] [Indexed: 12/20/2022] Open
Abstract
Aims Reverse remodelling (RR) is the recovery from left ventricular (LV) dilatation and dysfunction. Many arbitrary criteria for RR have been proposed. We searched the criteria with the strongest prognostic yield for the hard endpoint of cardiovascular death. Methods and results We performed a systematic literature search of diagnostic criteria for RR. We evaluated their prognostic significance in a cohort of 927 patients with LV ejection fraction (LVEF) < 50% undergoing two echocardiograms within 12 ± 2 months. These patients were followed for a median of 2.8 years (interquartile interval 1.3–4.9) after the second echocardiogram, recording 123 cardiovascular deaths. Two prognostic models were defined. Model 1 included age, LVEF, N‐terminal pro‐B‐type natriuretic peptide, ischaemic aetiology, cardiac resynchronization therapy, estimated glomerular filtration rate, New York Heart Association, and LV end‐systolic volume (LVESV) index, and Model 2 the validated Cardiac and Comorbid Conditions Heart Failure score. We identified 25 criteria for RR, the most used being LVESV reduction ≥15% (12 studies out of 42). In the whole cohort, two criteria proved particularly effective in risk reclassification over Model 1 and Model 2. These criteria were (i) LVEF increase >10 U and (ii) LVEF increase ≥1 category [severe (LVEF ≤ 30%), moderate (LVEF 31–40%), mild LV dysfunction (LVEF 41–55%), and normal LV function (LVEF ≥ 56%)]. The same two criteria yielded independent prognostic significance and improved risk reclassification even in patients with more severe systolic dysfunction, namely, those with LVEF < 40% or LVEF ≤ 35%. Furthermore, LVEF increase >10 U and LVEF increase ≥1 category displayed a greater prognostic value than LVESV reduction ≥15%, both in the whole cohort and in the subgroups with LVEF < 40% or LVEF ≤ 35%. For example, LVEF increase >10 U independently predicted cardiovascular death over Model 1 and LVESV reduction ≥15% (hazard ratio 0.40, 95% confidence interval 0.18–0.90, P = 0.026), while LVESV reduction ≥15% did not independently predict cardiovascular death (P = 0.112). Conclusions Left ventricular ejection fraction increase >10 U and LVEF increase ≥1 category are stronger predictors of cardiovascular death than the most commonly used criterion for RR, namely, LVESV reduction ≥15%.
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Affiliation(s)
- Alberto Aimo
- Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy.,Cardiology Division, Fondazione Toscana Gabriele Monasterio, Piazza Martiri della Libertà 33, Pisa, 56124, Italy
| | - Iacopo Fabiani
- Cardiology Division, Fondazione Toscana Gabriele Monasterio, Piazza Martiri della Libertà 33, Pisa, 56124, Italy
| | - Giuseppe Vergaro
- Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy.,Cardiology Division, Fondazione Toscana Gabriele Monasterio, Piazza Martiri della Libertà 33, Pisa, 56124, Italy
| | | | - Vladyslav Chubuchny
- Cardiology Division, Fondazione Toscana Gabriele Monasterio, Piazza Martiri della Libertà 33, Pisa, 56124, Italy
| | - Emilio Maria Pasanisi
- Cardiology Division, Fondazione Toscana Gabriele Monasterio, Piazza Martiri della Libertà 33, Pisa, 56124, Italy
| | - Christina Petersen
- Cardiology Division, Fondazione Toscana Gabriele Monasterio, Piazza Martiri della Libertà 33, Pisa, 56124, Italy
| | - Elisa Poggianti
- Cardiology Division, Fondazione Toscana Gabriele Monasterio, Piazza Martiri della Libertà 33, Pisa, 56124, Italy
| | - Claudia Taddei
- Cardiology Division, Fondazione Toscana Gabriele Monasterio, Piazza Martiri della Libertà 33, Pisa, 56124, Italy
| | | | - Antoni Bayes-Genis
- CIBER Cardiovascular, Instituto de Salud Carlos III, Madrid, Spain.,Hospital Universitari Germans Trias i Pujol, Badalona, Barcelona, Spain
| | - Josep Lupón
- CIBER Cardiovascular, Instituto de Salud Carlos III, Madrid, Spain.,Hospital Universitari Germans Trias i Pujol, Badalona, Barcelona, Spain
| | - Alberto Giannoni
- Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy.,Cardiology Division, Fondazione Toscana Gabriele Monasterio, Piazza Martiri della Libertà 33, Pisa, 56124, Italy
| | - Andrea Ripoli
- Cardiology Division, Fondazione Toscana Gabriele Monasterio, Piazza Martiri della Libertà 33, Pisa, 56124, Italy
| | - Georgios Georgiopoulos
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Claudio Passino
- Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy.,Cardiology Division, Fondazione Toscana Gabriele Monasterio, Piazza Martiri della Libertà 33, Pisa, 56124, Italy
| | - Michele Emdin
- Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy.,Cardiology Division, Fondazione Toscana Gabriele Monasterio, Piazza Martiri della Libertà 33, Pisa, 56124, Italy
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Dong Y, Wang D, Lv J, Pan Z, Xu R, Ding J, Cui X, Xie X, Guo X. MAGGIC Risk Model Predicts Adverse Events and Left Ventricular Remodeling in Non-Ischemic Dilated Cardiomyopathy. Int J Gen Med 2020; 13:1477-1486. [PMID: 33335419 PMCID: PMC7736706 DOI: 10.2147/ijgm.s288732] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 11/18/2020] [Indexed: 11/23/2022] Open
Abstract
Purpose We aimed to study the Meta-analysis Global Group in Chronic Heart Failure (MAGGIC) risk model’s prognostic value and relationship with left ventricular remodeling in dilated cardiomyopathy. Patients and Methods Dilated cardiomyopathy patients were prospectively recruited and underwent clinical assessments. MAGGIC risk score was calculated. Patients were followed up for adverse events and echocardiography. Primary endpoints were all-cause mortality and first rehospitalization due to heart failure. Secondary endpoint was left ventricular remodeling defined as a decline in left ventricular ejection fraction >10% or an increase in left ventricular end-diastolic diameter >10%. Survival status was examined using Cox regression analysis. The model’s ability to discriminate adverse events and left ventricular remodeling was calculated using a receiver operating characteristics curve. Results In total, 114 patients were included (median follow-up time = 31 months). The risk score was independently related to adverse events (2-year all-cause mortality: hazard ratio [HR] = 1.122; 95% confidence interval [CI], 1.043–1.208; 1-year first rehospitalization due to heart failure: HR = 1.094; 95% CI, 1.032–1.158; 2-year first rehospitalization due to heart failure: HR = 1.088; 95% CI, 1.033–1.147, all P < 0.05). One-year change in left ventricular end-diastolic diameter was correlated with the risk score (r = 0.305, P = 0.002). The model demonstrated modest ability in discriminating adverse events and left ventricular remodeling (all areas under the curve were 0.6–0.7). Conclusion The MAGGIC risk score was related to adverse events and left ventricular remodeling in dilated cardiomyopathy.
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Affiliation(s)
- Yang Dong
- Department of Cardiology, The First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Dongfei Wang
- Department of Cardiology, The First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Jialan Lv
- Department of Cardiology, The First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Zhicheng Pan
- Department of Cardiology, The First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Rui Xu
- Department of Cardiology, The First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Jie Ding
- Department of Cardiology, The First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Xiao Cui
- Department of Cardiology, The First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Xudong Xie
- Department of Cardiology, The First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Xiaogang Guo
- Department of Cardiology, The First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, People's Republic of China
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Wang M, Guo S, He M, Shao X, Feng L, Yu Y, Gong W, Liu Q, Melnikov V, Wang X, He Z, Jiang L, Chen M, Sun J, Cai J, Zhao Y, Li Y, Tritos NA, Hu Z, Zhang Z. High-Performance Liquid Chromatography-Mass Spectrometry-Based Lipid Metabolite Profiling of Acromegaly. J Clin Endocrinol Metab 2020; 105:5701424. [PMID: 31930294 DOI: 10.1210/clinem/dgaa014] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 01/10/2020] [Indexed: 11/19/2022]
Abstract
CONTEXT Metabolic disorders, especially dysregulated lipid metabolism, increase the risk of cardiovascular mortality in acromegaly. Previous studies measuring plasma macromolecular lipids have yielded conflicting results. PURPOSE To explore the plasma lipid metabolite profiles by metabolomics analysis and identify potential metabolites associated with cardiac function in acromegaly. METHODS Plasma was obtained from 80 newly diagnosed, untreated patients with acromegaly and 80 healthy controls. Echocardiography was performed. Based on the results of an oral glucose tolerance test (OGTT), patients were categorized into 2 groups: normal glucose tolerance (NGT, n = 28) and impaired glucose tolerance or diabetes mellitus (IGT/DM, n = 52). High-performance liquid chromatography-mass spectrometry (HPLC-MS)-based metabolomics analysis was conducted. Data were processed by principal components analysis (PCA), orthogonal partial least square-discriminant analysis (OPLS-DA), and MetaboAnalyst 4.0. Associations between metabolic substances and cardiovascular parameters were also explored. RESULTS Metabolomics uncovered a distinct metabolic pattern between acromegaly and healthy controls, and perturbed pathways mainly include glycerophospholipid metabolism, sphingolipid metabolism, as well as linoleic acid metabolism. Collective analysis showed that phosphatidylethanolamine (PE) (22:6/16:0) was positively correlated with LV mass, while lysophosphatidylcholine (LysoPC) (16:0) was positively correlated with fractional shortening (FS) and left ventricle ejection fraction (LVEF). CONCLUSION Patients with acromegaly have distinct lipid metabolite profiling, while PE (22:6/16:0) and LysoPC (16:0) are correlated with cardiac structure and function, which may contribute to the risk of cardiovascular complications.
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Affiliation(s)
- Meng Wang
- Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Shizhe Guo
- Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Min He
- Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xiaoqing Shao
- Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Lei Feng
- Instrumental Analysis Center of Jiaotong University, Shanghai, China
| | - Yifei Yu
- Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wei Gong
- Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Qingfeng Liu
- Department of Pharmacy, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | | | - Xiaoxue Wang
- Instrumental Analysis Center of Jiaotong University, Shanghai, China
| | - Zhian He
- Instrumental Analysis Center of Jiaotong University, Shanghai, China
| | - Lin Jiang
- Healthcare Center of Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Maohua Chen
- Department of Neurosurgery, The Central Hospital of Wenzhou, Affiliated Dingli Clinical Institute of Wenzhou Medical University, Wenzhou, China
| | - Jun Sun
- Department of Neurosurgery, The Central Hospital of Wenzhou, Affiliated Dingli Clinical Institute of Wenzhou Medical University, Wenzhou, China
| | - Jianyong Cai
- Department of Neurosurgery, The Central Hospital of Wenzhou, Affiliated Dingli Clinical Institute of Wenzhou Medical University, Wenzhou, China
| | - Yao Zhao
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yiming Li
- Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Nicholas A Tritos
- Neuroendocrine Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Zhiyu Hu
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Shanghai Jiao Tong University, Shanghai, China
- Institute of Nano/Micro Energy, Shanghai Jiao Tong University, Shanghai, China
| | - Zhaoyun Zhang
- Department of Endocrinology and Metabolism, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
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