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Yu J, Taskén AA, Berg EAR, Tannvik TD, Slagsvold KH, Kirkeby-Garstad I, Grenne B, Kiss G, Aakhus S. Continuous monitoring of left ventricular function in postoperative intensive care patients using artificial intelligence and transesophageal echocardiography. Intensive Care Med Exp 2024; 12:54. [PMID: 38856861 PMCID: PMC11164841 DOI: 10.1186/s40635-024-00640-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Accepted: 06/04/2024] [Indexed: 06/11/2024] Open
Abstract
BACKGROUND Continuous monitoring of mitral annular plane systolic excursion (MAPSE) using transesophageal echocardiography (TEE) may improve the evaluation of left ventricular (LV) function in postoperative intensive care patients. We aimed to assess the utility of continuous monitoring of LV function using TEE and artificial intelligence (autoMAPSE) in postoperative intensive care patients. METHODS In this prospective observational study, we monitored 50 postoperative intensive care patients for 120 min immediately after cardiac surgery. We recorded a set of two-chamber and four-chamber TEE images every five minutes. We defined monitoring feasibility as how often the same wall from the same patient could be reassessed, and categorized monitoring feasibility as excellent if the same LV wall could be reassessed in ≥ 90% of the total recordings. To compare autoMAPSE with manual measurements, we rapidly recorded three sets of repeated images to assess precision (least significant change), bias, and limits of agreement (LOA). To assess the ability to identify changes (trending ability), we compared changes in autoMAPSE with the changes in manual measurements in images obtained during the initiation of cardiopulmonary bypass as well as before and after surgery. RESULTS Monitoring feasibility was excellent in most patients (88%). Compared with manual measurements, autoMAPSE was more precise (least significant change 2.2 vs 3.1 mm, P < 0.001), had low bias (0.4 mm), and acceptable agreement (LOA - 2.7 to 3.5 mm). AutoMAPSE had excellent trending ability, as its measurements changed in the same direction as manual measurements (concordance rate 96%). CONCLUSION Continuous monitoring of LV function was feasible using autoMAPSE. Compared with manual measurements, autoMAPSE had excellent trending ability, low bias, acceptable agreement, and was more precise.
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Affiliation(s)
- Jinyang Yu
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Postboks 8905, 7491, Trondheim, Norway.
- Clinic of Cardiology St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway.
| | - Anders Austlid Taskén
- Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Erik Andreas Rye Berg
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Postboks 8905, 7491, Trondheim, Norway
- Clinic of Cardiology St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Tomas Dybos Tannvik
- Department of Anesthesia and Intensive Care, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Katrine Hordnes Slagsvold
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Postboks 8905, 7491, Trondheim, Norway
- Clinic of Cardiothoracic Surgery, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Idar Kirkeby-Garstad
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Postboks 8905, 7491, Trondheim, Norway
| | - Bjørnar Grenne
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Postboks 8905, 7491, Trondheim, Norway
- Clinic of Cardiology St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway
- Centre of Innovative Ultrasound Solutions, Trondheim, Norway
| | - Gabriel Kiss
- Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Svend Aakhus
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology, Postboks 8905, 7491, Trondheim, Norway
- Clinic of Cardiology St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway
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Yu J, Taskén AA, Flade HM, Skogvoll E, Berg EAR, Grenne B, Rimehaug A, Kirkeby-Garstad I, Kiss G, Aakhus S. Automatic assessment of left ventricular function for hemodynamic monitoring using artificial intelligence and transesophageal echocardiography. J Clin Monit Comput 2024; 38:281-291. [PMID: 38280975 DOI: 10.1007/s10877-023-01118-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 12/03/2023] [Indexed: 01/29/2024]
Abstract
We have developed a method to automatically assess LV function by measuring mitral annular plane systolic excursion (MAPSE) using artificial intelligence and transesophageal echocardiography (autoMAPSE). Our aim was to evaluate autoMAPSE as an automatic tool for rapid and quantitative assessment of LV function in critical care patients. In this retrospective study, we studied 40 critical care patients immediately after cardiac surgery. First, we recorded a set of echocardiographic data, consisting of three consecutive beats of midesophageal two- and four-chamber views. We then altered the patient's hemodynamics by positioning them in anti-Trendelenburg and repeated the recordings. We measured MAPSE manually and used autoMAPSE in all available heartbeats and in four LV walls. To assess the agreement with manual measurements, we used a modified Bland-Altman analysis. To assess the precision of each method, we calculated the least significant change (LSC). Finally, to assess trending ability, we calculated the concordance rates using a four-quadrant plot. We found that autoMAPSE measured MAPSE in almost every set of two- and four-chamber views (feasibility 95%). It took less than a second to measure and average MAPSE over three heartbeats. AutoMAPSE had a low bias (0.4 mm) and acceptable limits of agreement (- 3.7 to 4.5 mm). AutoMAPSE was more precise than manual measurements if it averaged more heartbeats. AutoMAPSE had acceptable trending ability (concordance rate 81%) during hemodynamic alterations. In conclusion, autoMAPSE is feasible as an automatic tool for rapid and quantitative assessment of LV function, indicating its potential for hemodynamic monitoring.
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Affiliation(s)
- Jinyang Yu
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway.
- Clinic of Cardiology St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.
| | - Anders Austlid Taskén
- Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Hans Martin Flade
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Anesthesia and Intensive Care, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Eirik Skogvoll
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Anesthesia and Intensive Care, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Erik Andreas Rye Berg
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Cardiology St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Bjørnar Grenne
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Cardiology St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Audun Rimehaug
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Anesthesia and Intensive Care, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Idar Kirkeby-Garstad
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
| | - Gabriel Kiss
- Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Svend Aakhus
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Cardiology St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
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3
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Berg EAR, Taskén AA, Nordal T, Grenne B, Espeland T, Kirkeby-Garstad I, Dalen H, Holte E, Stølen S, Aakhus S, Kiss G. Fully automatic estimation of global left ventricular systolic function using deep learning in transoesophageal echocardiography. EUROPEAN HEART JOURNAL. IMAGING METHODS AND PRACTICE 2023; 1:qyad007. [PMID: 39044786 PMCID: PMC11195714 DOI: 10.1093/ehjimp/qyad007] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 06/19/2023] [Indexed: 07/25/2024]
Abstract
Aims To improve monitoring of cardiac function during major surgery and intensive care, we have developed a method for fully automatic estimation of mitral annular plane systolic excursion (auto-MAPSE) using deep learning in transoesophageal echocardiography (TOE). The aim of this study was a clinical validation of auto-MAPSE in patients with heart disease. Methods and results TOE recordings were collected from 185 consecutive patients without selection on image quality. Deep-learning-based auto-MAPSE was trained and optimized from 105 patient recordings. We assessed auto-MAPSE feasibility, and agreement and inter-rater reliability with manual reference in 80 patients with and without electrocardiogram (ECG) tracings. Mean processing time for auto-MAPSE was 0.3 s per cardiac cycle/view. Overall feasibility was >90% for manual MAPSE and ECG-enabled auto-MAPSE and 82% for ECG-disabled auto-MAPSE. Feasibility in at least two walls was ≥95% for all methods. Compared with manual reference, bias [95% limits of agreement (LoA)] was -0.5 [-4.0, 3.1] mm for ECG-enabled auto-MAPSE and -0.2 [-4.2, 3.6] mm for ECG-disabled auto-MAPSE. Intra-class correlation coefficient (ICC) for consistency was 0.90 and 0.88, respectively. Manual inter-observer bias [95% LoA] was -0.9 [-4.7, 3.0] mm, and ICC was 0.86. Conclusion Auto-MAPSE was fast and highly feasible. Inter-rater reliability between auto-MAPSE and manual reference was good. Agreement between auto-MAPSE and manual reference did not differ from manual inter-observer agreement. As the principal advantages of deep-learning-based assessment are speed and reproducibility, auto-MAPSE has the potential to improve real-time monitoring of left ventricular function. This should be investigated in relevant clinical settings.
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Affiliation(s)
- Erik Andreas Rye Berg
- Centre for Innovative Ultrasound Solutions, Department of Circulation and Medical Imaging, Faculty of Medicine and Health Science, Norwegian University of Science and Technology, Prinsesse Kristinas gate 3, Trondheim 7030, Norway
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Science, Norwegian University of Science and Technology, Prinsesse Kristinas gate 3, Trondheim 7030, Norway
- Clinic of Cardiology, St Olavs Hospital, Trondheim University Hospital, Prinsesse Kristinas gate 3, Trondheim 7030, Norway
| | - Anders Austlid Taskén
- Department of Computer Science, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology, Trondheim 7034, Norway
| | - Trym Nordal
- Department of Engineering Cybernetics, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology, Trondheim 7034, Norway
| | - Bjørnar Grenne
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Science, Norwegian University of Science and Technology, Prinsesse Kristinas gate 3, Trondheim 7030, Norway
- Clinic of Cardiology, St Olavs Hospital, Trondheim University Hospital, Prinsesse Kristinas gate 3, Trondheim 7030, Norway
| | - Torvald Espeland
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Science, Norwegian University of Science and Technology, Prinsesse Kristinas gate 3, Trondheim 7030, Norway
- Clinic of Cardiology, St Olavs Hospital, Trondheim University Hospital, Prinsesse Kristinas gate 3, Trondheim 7030, Norway
| | - Idar Kirkeby-Garstad
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Science, Norwegian University of Science and Technology, Prinsesse Kristinas gate 3, Trondheim 7030, Norway
- Department of Anaesthesiology and Intensive Care Medicine, St Olavs Hospital, Trondheim University Hospital, Trondheim 7030, Norway
| | - Håvard Dalen
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Science, Norwegian University of Science and Technology, Prinsesse Kristinas gate 3, Trondheim 7030, Norway
- Clinic of Cardiology, St Olavs Hospital, Trondheim University Hospital, Prinsesse Kristinas gate 3, Trondheim 7030, Norway
| | - Espen Holte
- Clinic of Cardiology, St Olavs Hospital, Trondheim University Hospital, Prinsesse Kristinas gate 3, Trondheim 7030, Norway
| | - Stian Stølen
- Clinic of Cardiology, St Olavs Hospital, Trondheim University Hospital, Prinsesse Kristinas gate 3, Trondheim 7030, Norway
| | - Svend Aakhus
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Science, Norwegian University of Science and Technology, Prinsesse Kristinas gate 3, Trondheim 7030, Norway
- Clinic of Cardiology, St Olavs Hospital, Trondheim University Hospital, Prinsesse Kristinas gate 3, Trondheim 7030, Norway
| | - Gabriel Kiss
- Department of Computer Science, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology, Trondheim 7034, Norway
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Arvidsson PM, Nelsson A, Edlund J, Smith JG, Magnusson M, Jin N, Heiberg E, Carlsson M, Steding-Ehrenborg K, Arheden H. Kinetic energy of left ventricular blood flow across heart failure phenotypes and in subclinical diastolic dysfunction. J Appl Physiol (1985) 2022; 133:697-709. [PMID: 36037442 DOI: 10.1152/japplphysiol.00257.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Kinetic energy (KE) of intracardiac blood flow reflects myocardial work spent on accelerating blood and provides a mechanistic window into diastolic filling dynamics. Diastolic dysfunction may represent an early stage in the development of heart failure (HF). Here we evaluated the hemodynamic effects of impaired diastolic function in subjects with and without HF, testing the hypothesis that left ventricular KE differs between controls, subjects with subclinical diastolic dysfunction (SDD), and HF patients. METHODS We studied 77 subjects (16 controls, 20 subjects with SDD, 16 HFpEF, 9 HFmrEF, and 16 HFrEF patients, age- and sex-matched at the group level). Cardiac magnetic resonance at 1.5T included intracardiac 4D flow and cine imaging. Left ventricular KE was calculated as 0.5*m*v2. RESULTS Systolic KE was similar between groups (p>0.4), also after indexing to stroke volume (p=0.25), and was primarily driven by ventricular emptying rate (p<0.0001, R2=0.52). Diastolic KE was higher in heart failure patients than controls (p<0.05) but similar between SDD and HFpEF (p>0.18), correlating with inflow conditions (E-wave velocity, p<0.0001, R2=0.24) and end-diastolic volume (p=0.0003, R2=0.17) but not with average e' (p=0.07). CONCLUSIONS Diastolic KE differs between controls and heart failure, suggesting more work is spent filling the failing ventricle, while systolic KE does not differentiate between well-matched groups with normal ejection fraction even in the presence of relaxation abnormalities and heart failure. Mechanistically, KE reflects the acceleration imparted on the blood and is driven by variations in ventricular emptying and filling rates, volumes, and heart rate, regardless of underlying pathology.
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Affiliation(s)
- Per Martin Arvidsson
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden
| | - Anders Nelsson
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden
| | - Jonathan Edlund
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden
| | - J Gustav Smith
- Department of Cardiology, Clinical Sciences, Lund University, Skåne University Hospital, Lund, Sweden.,Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Martin Magnusson
- Department of Cardiology, Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden.,Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden.,Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Ning Jin
- Cardiovascular MR R&D, Siemens Medical Solutions USA, Inc., Cleveland, Ohio, United States
| | - Einar Heiberg
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden.,Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Marcus Carlsson
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden
| | - Katarina Steding-Ehrenborg
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden
| | - Håkan Arheden
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden
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5
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Systolic and diastolic function during cycling at the respiratory threshold between elderly and young healthy individuals. Sci Rep 2022; 12:3825. [PMID: 35264702 PMCID: PMC8907329 DOI: 10.1038/s41598-022-07933-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Accepted: 02/28/2022] [Indexed: 11/20/2022] Open
Abstract
The hemodynamic consequences of aging have been extensively investigated during maximal incremental exercise. However, less is known about the effects of aging on hemodynamics during submaximal steady-state exercise. The aim of the present investigation was to compare the hemodynamics of healthy elderly and young subjects during an exercise bout conducted at the gas threshold (GET) intensity. Two groups of healthy, physically active subjects were studied: the elderly group—EG (n = 11; > 60 years old) and the young group—YG (n = 13; < 35 years old). Both groups performed a 5-min rectangular exercise test at the GET intensity. Hemodynamics were measured using echocardiography. The main finding was that stroke volume responses were higher in the YG than the EG (72.5 ± 16.7 vs. 52.4 ± 8.4 ml, respectively). The increased stroke volume capacity in the YG was the consequence of a greater capacity to increase cardiac preload and contractility and, to a lesser extent, to reduce systemic vascular resistance. Importantly, the atrial contribution to ventricular diastolic filling was substantially higher in the YG when compared to the EG.
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6
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Arvidsson PM, Nelsson A, Magnusson M, Smith JG, Carlsson M, Arheden H. Hemodynamic force analysis is not ready for clinical trials on HFpEF. Sci Rep 2022; 12:4017. [PMID: 35256713 PMCID: PMC8901629 DOI: 10.1038/s41598-022-08023-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 02/22/2022] [Indexed: 01/11/2023] Open
Abstract
Hemodynamic force analysis has been proposed as a novel tool for early detection of subclinical systolic dysfunction in heart failure with preserved ejection fraction (HFpEF). Here we investigated the ability of hemodynamic forces to discriminate between healthy subjects and heart failure patients with varying degrees of systolic dysfunction. We studied 34 controls, 16 HFpEF patients, and 25 heart failure patients with mid-range (HFmrEF) or reduced ejection fraction (HFrEF) using cardiac magnetic resonance with acquisition of cine images and 4D flow at 1.5 T. The Navier-Stokes equation was used to compute global left ventricular hemodynamic forces over the entire cardiac cycle. Forces were analyzed for systole, diastole, and the entire heartbeat, with and without normalization to left ventricular volume. Volume-normalized hemodynamic forces demonstrated significant positive correlation with EF (r2 = 0.47, p < 0.0001) and were found significantly lower in heart failure with reduced ejection fraction compared to controls (p < 0.0001 for systole and diastole). No difference was seen between controls and HFpEF (p > 0.34). Non-normalized forces displayed no differences between controls and HFpEF (p > 0.24 for all analyses) and did not correlate with EF (p = 0.36). Left ventricular hemodynamic force analysis, whether indexed to LV volumes or not, is not ready for clinical trials on HFpEF assessment.
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Affiliation(s)
- Per M Arvidsson
- Clinical Physiology, Department of Clinical Sciences Lund, Skåne University Hospital, Lund University, 22185, Lund, Sweden
| | - Anders Nelsson
- Clinical Physiology, Department of Clinical Sciences Lund, Skåne University Hospital, Lund University, 22185, Lund, Sweden
| | - Martin Magnusson
- Department of Cardiology, Clinical Sciences, Skåne University Hospital, Lund University, Malmö, Sweden.,Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden.,Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - J Gustav Smith
- Department of Cardiology, Clinical Sciences, Skåne University Hospital, Lund University, Lund, Sweden
| | - Marcus Carlsson
- Clinical Physiology, Department of Clinical Sciences Lund, Skåne University Hospital, Lund University, 22185, Lund, Sweden
| | - Håkan Arheden
- Clinical Physiology, Department of Clinical Sciences Lund, Skåne University Hospital, Lund University, 22185, Lund, Sweden.
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7
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Berg J, Jablonowski R, Mohammad M, Solem K, Borgquist R, Ostenfeld E, Arheden H, Carlsson M. Ventricular longitudinal shortening is an independent predictor of death in heart failure patients with reduced ejection fraction. Sci Rep 2021; 11:20280. [PMID: 34645886 PMCID: PMC8514526 DOI: 10.1038/s41598-021-99613-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 09/14/2021] [Indexed: 01/07/2023] Open
Abstract
Reduced ventricular longitudinal shortening measured by atrioventricular plane displacement (AVPD) and global longitudinal strain (GLS) are prognostic markers in heart disease. This study aims to determine if AVPD and GLS with cardiovascular magnetic resonance (CMR) are independent predictors of cardiovascular (CV) and all-cause death also in heart failure with reduced ejection fraction (HFrEF). Patients (n = 287) were examined with CMR and AVPD, GLS, ventricular volumes, myocardial fibrosis/scar were measured. Follow-up was 5 years with cause of death retrieved from a national registry. Forty CV and 60 all-cause deaths occurred and CV non-survivors had a lower AVPD (6.4 ± 2.0 vs 8.0 ± 2.4 mm, p < 0.001) and worse GLS (− 6.1 ± 2.2 vs − 7.7 ± 3.1%, p = 0.001). Kaplan–Meier analyses displayed increased survival for patients in the highest AVPD- and GLS-tertiles vs. the lowest tertiles (AVPD: p = 0.001, GLS: p = 0.013). AVPD and GLS showed in univariate analysis a hazard ratio (HR) of 1.30 (per-mm-decrease) and 1.19 (per-%-decrease) for CV death. Mean AVPD and GLS were independent predictors of all-cause death (HR = 1.24 per-mm-decrease and 1.15 per-%-decrease), but only AVPD showed incremental value over age, sex, body-mass-index, EF, etiology and fibrosis/scar for CV death (HR = 1.33 per-mm-decrease, p < 0.001). Ventricular longitudinal shortening remains independently prognostic for death in HFrEF even after adjusting for well-known clinical risk factors.
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Affiliation(s)
- J Berg
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden.,Syntach AB, Lund, Sweden
| | - R Jablonowski
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden
| | - M Mohammad
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden
| | | | - R Borgquist
- Cardiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden
| | - E Ostenfeld
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden
| | - H Arheden
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden
| | - M Carlsson
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden.
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8
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Magnani S, Mulliri G, Roberto S, Sechi F, Ghiani G, Sainas G, Nughedu G, Vargiu R, Bassareo PP, Crisafulli A. Systolic and Diastolic Functions After a Brief Acute Bout of Mild Exercise in Normobaric Hypoxia. Front Physiol 2021; 12:650696. [PMID: 33967823 PMCID: PMC8103167 DOI: 10.3389/fphys.2021.650696] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 03/31/2021] [Indexed: 11/13/2022] Open
Abstract
Acute hypoxia (AH) is a challenge to the homeostasis of the cardiovascular system, especially during exercise. Research in this area is scarce. We aimed to ascertain whether echocardiographic, Doppler, and tissue Doppler measures were able to detect changes in systolic and diastolic functions during the recovery after mild exercise in AH. Twelve healthy males (age 33.5 ± 4.8 years) completed a cardiopulmonary test on an electromagnetically braked cycle-ergometer to determine their maximum workload (Wmax). On separate days, participants performed randomly assigned two exercise sessions consisting in 3 min pedalling at 30% of Wmax: (1) one test was conducted in normoxia (NORMO) and (2) one in normobaric hypoxia with FiO2 set to 13.5% (HYPO). Hemodynamics were assessed with an echocardiographic system. The main result was that the HYPO session increased parameters related to myocardial contractility such as pre-ejection period and systolic myocardial velocity with respect to the NORMO test. Moreover, the HYPO test enhanced early transmitral filling peak velocities. No effects were detected for left ventricular volumes, as end-diastolic, end-systolic, and stroke volume were similar between the NORMO and the HYPO test. Results of the present investigation support the hypothesis that a brief, mild exercise bout in acute normobaric hypoxia does not impair systolic or diastolic functions. Rather, it appears that stroke volume is well preserved and that systolic and early diastolic functions are enhanced by exercise in hypoxia.
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Affiliation(s)
- Sara Magnani
- Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.,International PhD in Innovation Sciences and Technologies, University of Cagliari, Cagliari, Italy
| | - Gabriele Mulliri
- Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.,International PhD in Innovation Sciences and Technologies, University of Cagliari, Cagliari, Italy
| | - Silvana Roberto
- Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Fabio Sechi
- Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Giovanna Ghiani
- Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Gianmarco Sainas
- Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Giorgio Nughedu
- Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Romina Vargiu
- Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - Pier Paolo Bassareo
- University College of Dublin, Mater Misericordiae University Teaching Hospital, Dublin, Ireland
| | - Antonio Crisafulli
- Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.,International PhD in Innovation Sciences and Technologies, University of Cagliari, Cagliari, Italy
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