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- Axelsson, Jimmy, et al.
(author)
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Ejection fraction in left bundle branch block is disproportionately reduced in relation to amount of myocardial scar
- 2018
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In: Journal of Electrocardiology. - : Elsevier BV. - 0022-0736 .- 1532-8430. ; 51:6, s. 1071-1076
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Journal article (peer-reviewed)abstract
- Introduction: The relationship between left ventricular (LV) ejection fraction (EF) and LV myocardial scar can identify potentially reversible causes of LV dysfunction. Left bundle branch block (LBBB) alters the electrical and mechanical activation of the LV. We hypothesized that the relationship between LVEF and scar extent is different in LBBB compared to controls. Methods: We compared the relationship between LVEF and scar burden between patients with LBBB and scar (n = 83), and patients with chronic ischemic heart disease and scar but no electrocardiographic conduction abnormality (controls, n = 90), who had undergone cardiovascular magnetic resonance (CMR) imaging at one of three centers. LVEF (%) was measured in CMR cine images. Scar burden was quantified by CMR late gadolinium enhancement (LGE) and expressed as % of LV mass (%LVM). Maximum possible LVEF (LVEFmax) was defined as the function describing the hypotenuse in the LVEF versus myocardial scar extent scatter plot. Dysfunction index was defined as LVEFmax derived from the control cohort minus the measured LVEF. Results: Compared to controls with scar, LBBB with scar had a lower LVEF (median [interquartile range] 27 [19–38] vs 36 [25–50] %, p < 0.001), smaller scar (4 [1–9] vs 11 [6–20] %LVM, p < 0.001), and greater dysfunction index (39 [30–52] vs 21 [12–35] % points, p < 0.001). Conclusions: Among LBBB patients referred for CMR, LVEF is disproportionately reduced in relation to the amount of scar. Dyssynchrony in LBBB may thus impair compensation for loss of contractile myocardium.
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| 2. |
- Lindow, Thomas, et al.
(author)
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Heart age gap estimated by explainable advanced electrocardiography is associated with cardiovascular risk factors and survival
- 2023
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In: The European Heart Journal - Digital Health. - : Oxford University Press. - 2634-3916. ; 4:5, s. 384-392
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Journal article (peer-reviewed)abstract
- AimsDeep neural network artificial intelligence (DNN-AI)-based Heart Age estimations have been presented and used to show that the difference between an electrocardiogram (ECG)-estimated Heart Age and chronological age is associated with prognosis. An accurate ECG Heart Age, without DNNs, has been developed using explainable advanced ECG (A-ECG) methods. We aimed to evaluate the prognostic value of the explainable A-ECG Heart Age and compare its performance to a DNN-AI Heart Age.Methods and resultsBoth A-ECG and DNN-AI Heart Age were applied to patients who had undergone clinical cardiovascular magnetic resonance imaging. The association between A-ECG or DNN-AI Heart Age Gap and cardiovascular risk factors was evaluated using logistic regression. The association between Heart Age Gaps and death or heart failure (HF) hospitalization was evaluated using Cox regression adjusted for clinical covariates/comorbidities. Among patients [n = 731, 103 (14.1%) deaths, 52 (7.1%) HF hospitalizations, median (interquartile range) follow-up 5.7 (4.7-6.7) years], A-ECG Heart Age Gap was associated with risk factors and outcomes [unadjusted hazard ratio (HR) (95% confidence interval) (5 year increments): 1.23 (1.13-1.34) and adjusted HR 1.11 (1.01-1.22)]. DNN-AI Heart Age Gap was associated with risk factors and outcomes after adjustments [HR (5 year increments): 1.11 (1.01-1.21)], but not in unadjusted analyses [HR 1.00 (0.93-1.08)], making it less easily applicable in clinical practice.ConclusionA-ECG Heart Age Gap is associated with cardiovascular risk factors and HF hospitalization or death. Explainable A-ECG Heart Age Gap has the potential for improving clinical adoption and prognostic performance compared with existing DNN-AI-type methods. Graphical Abstract
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| 3. |
- Lundin, Magnus, et al.
(author)
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Left ventricular global wall thickness is easily calculated, detects and characterizes hypertrophy, and has prognostic utility
- 2019
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Conference paper (other academic/artistic)abstract
- BACKGROUND: Cardiovascular magnetic resonance (CMR) can be used to measure left ventricular end-diastolic volume (LVEDV) and left ventricular mass (LVM). However, there is currently no good way to measure the normality of LVM in relation to a given LVEDV. We hypothesized that a simple measure of left ventricular global wall thickness (GWT) would be accurate, beneficial for detecting and characterizing hypertrophy, and have prognostic significance.METHODS: Subjects underwent CMR at 1.5T, including healthy volunteers (n=99) and patients assessed for heart disease (n=2828).RESULTS: GWT calculated from LVEDV and LVM had excellent agreement with measured mean end-diastolic wall thickness of the entire left ventricle (bias 0.01±0.23mm). GWT was most predictive of death or hospitalization for heart failure in patients with normal findings by CMR (n=326, log-rank 26.8, p<0.001, median [interquartile range] follow-up 5.8 [5.0–6.7] years). GWT indexed to body surface area (GWTi) was most predictive of outcomes in patients with normal LVEDV index (n=1352, log-rank 36.4, p<0.001, follow-up 5.5 [4.1–6.5] years). Patients with concentric remodeling had worse prognosis than the normal patients (p=0.02), and the patients with hypertrophy had worse prognosis than both normal patients (p<0.001) and patients with concentric remodeling (p=0.045), see Figure 1. Of patients with suspected heart disease but normal CMR findings regarding left ventricular volumes, function, mass, and scar, 22% were found to have increased mean GWTi corresponding to concentric remodeling, see Figure 2.CONCLUSIONS: Left ventricular GWT is an intuitive measure that can be easily calculated from mass and volume with high accuracy, and has prognostic utility in patients with normal CMR findings. Also, GWTi classifies hypertrophy as concentric or eccentric, and detects concentric remodeling in a substantial portion of patients with otherwise normal findings.
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| 5. |
- Lundin, Magnus, et al.
(author)
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Prognostic utility and characterization of left ventricular hypertrophy using global thickness
- 2023
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In: Scientific Reports. - 2045-2322. ; 13:1
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Journal article (peer-reviewed)abstract
- Cardiovascular magnetic resonance (CMR) can accurately measure left ventricular (LV) mass, and several measures related to LV wall thickness exist. We hypothesized that prognosis can be used to select an optimal measure of wall thickness for characterizing LV hypertrophy. Subjects having undergone CMR were studied (cardiac patients, n = 2543; healthy volunteers, n = 100). A new measure, global wall thickness (GT, GTI if indexed to body surface area) was accurately calculated from LV mass and end-diastolic volume. Among patients with follow-up (n = 1575, median follow-up 5.4 years), the most predictive measure of death or hospitalization for heart failure was LV mass index (LVMI) (hazard ratio (HR)[95% confidence interval] 1.16[1.12-1.20], p < 0.001), followed by GTI (HR 1.14[1.09-1.19], p < 0.001). Among patients with normal findings (n = 326, median follow-up 5.8 years), the most predictive measure was GT (HR 1.62[1.35-1.94], p < 0.001). GT and LVMI could characterize patients as having a normal LV mass and wall thickness, concentric remodeling, concentric hypertrophy, or eccentric hypertrophy, and the three abnormal groups had worse prognosis than the normal group (p < 0.05 for all). LV mass is highly prognostic when mass is elevated, but GT is easily and accurately calculated, and adds value and discrimination amongst those with normal LV mass (early disease).
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| 6. |
- Wieslander, Björn, et al.
(author)
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The ability of the electrocardiogram in left bundle branch block to detect myocardial scar determined by cardiovascular magnetic resonance
- 2018
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In: Journal of Electrocardiology. - : Elsevier BV. - 0022-0736 .- 1532-8430. ; 51:5, s. 779-786
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Journal article (peer-reviewed)abstract
- Aims: We aimed to improve the electrocardiographic 2009 left bundle branch block (LBBB) Selvester QRS score (2009 LBSS) for scar assessment. Methods: We retrospectively identified 325 LBBB patients with available ECG and cardiovascular magnetic resonance imaging (CMR) with late gadolinium enhancement from four centers (142 [44%] with CMR scar). Forty-four semi-automatically measured ECG variables pre-selected based on the 2009 LBSS yielded one multivariable model for scar detection and another for scar quantification. Results: The 2009 LBSS achieved an area under the curve (AUC) of 0.60 (95% confidence interval 0.54–0.66) for scar detection, and R2 = 0.04, p < 0.001, for scar quantification. Multivariable modeling improved scar detection to AUC 0.72 (0.66–0.77) and scar quantification to R2 = 0.21, p < 0.001. Conclusions: The 2009 LBSS detects and quantifies myocardial scar with poor accuracy. Improved models with extensive comparison of ECG and CMR had modest performance, indicating limited room for improvement of the 2009 LBSS.
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