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- Cameli, Matteo, et al.
(författare)
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The analysis of left atrial function predicts the severity of functional impairment in chronic heart failure : The FLASH multicenter study
- 2019
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Ingår i: International Journal of Cardiology. - : ELSEVIER IRELAND LTD. - 0167-5273 .- 1874-1754. ; 286, s. 87-91
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Tidskriftsartikel (refereegranskat)abstract
- Background: Heart failure (HF) patients presentwith a variety of symptoms at different stages of the disease, but the underlying pathophysiology still is unclear. Left atrial (LA) function might be tightly related to changes in patients' symptoms, more than morphological and anatomic heart features, measurable by ultrasound imaging technique. This study sought to investigate the correlation between LA function, assessed by Speckle Tracking Echocardiography (STE) and Quality of Life (QoL), assessed by theMinnesota Livingwith Heart Failure Questionnaire (MLHFQ), in patients with chronic HF. Methods: Clinically stable HF outpatients (n = 369) were enrolled from 7 different international centres and underwent echocardiographic studies. Patients >75 years old and with atrial fibrillation were excluded. LA strain during reservoir phase (LASr) by STE was measured in all subjects by averaging the 6 atrial segments. LA size was assessed using biplane volume and 4-chamber area acquisition. Results: LASr strongly correlated with both MLHFQ total score (r = -0.87; p < 0.0001). Less significant correlations between MLHFQ and either LA volume or left ventricular global longitudinal strain (LV-GLS) were found (r = 0.28; p = 0.05 and r = 0.30; p = 0.01, respectively). No significant correlation was found between MLHFQ score, LVEF (r = -0.15; p = ns), E/E' ratio (r = 0.19; p = ns), and E/A ratio (r = 0.20; p = ns). Among all echocardiographic parameters analyzed, LASr presented the highest diagnostic accuracy (AUC = 0.74) in predicting a poor QoL (>45), when compared with LV-GLS (AUC = 0.61), LA volume (AUC = 0.54) and E/e' ratio (AUC = 0.51). Conclusions: In patients with HF, irrespective of etiology, LA function strongly correlates with patients' QoL. (C) 2019 Elsevier B.V. All rights reserved.
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| 2. |
- Henein, Michael Y., et al.
(författare)
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Biomarkers predict in-hospital major adverse cardiac events in covid-19 patients : A multicenter international study
- 2021
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Ingår i: Journal of Clinical Medicine. - : MDPI. - 2077-0383. ; 10:24
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Tidskriftsartikel (refereegranskat)abstract
- Background: The COVID-19 pandemic carries a high burden of morbidity and mortality worldwide. We aimed to identify possible predictors of in-hospital major cardiovascular (CV) events in COVID-19.Methods: We retrospectively included patients hospitalized for COVID-19 from 10 centers. Clinical, biochemical, electrocardiographic, and imaging data at admission and medications were collected. Primary endpoint was a composite of in-hospital CV death, acute heart failure (AHF), acute myocarditis, arrhythmias, acute coronary syndromes (ACS), cardiocirculatory arrest, and pulmonary embolism (PE).Results: Of the 748 patients included, 141(19%) reached the set endpoint: 49 (7%) CV death, 15 (2%) acute myocarditis, 32 (4%) sustained-supraventricular or ventricular arrhythmias, 14 (2%) cardiocirculatory arrest, 8 (1%) ACS, 41 (5%) AHF, and 39 (5%) PE. Patients with CV events had higher age, body temperature, creatinine, high-sensitivity troponin, white blood cells, and platelet counts at admission and were more likely to have systemic hypertension, renal failure (creatinine ≥ 1.25 mg/dL), chronic obstructive pulmonary disease, atrial fibrillation, and cardiomyopathy. On univariate and multivariate analysis, troponin and renal failure were associated with the composite endpoint. Kaplan–Meier analysis showed a clear divergence of in-hospital composite event-free survival stratified according to median troponin value and the presence of renal failure (Log rank p < 0.001).Conclusions: Our findings, derived from a multicenter data collection study, suggest the routine use of biomarkers, such as cardiac troponin and serum creatinine, for in-hospital prediction of CV events in patients with COVID-19.
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