Left ventricular myocardial constructive work predicts reduction of ejection fraction in patients with heart failure with preserved ejection fraction

Left ventricular myocardial constructive work predicts reduction of ejection fraction in patients with heart failure with preserved ejection fraction | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Left ventricular myocardial constructive work predicts reduction of ejection fraction in patients with heart failure with preserved ejection fraction Aram Chilingaryan, Lusine Tunyan, Milena Arzumanyan, Tsiala Ustyan, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5268112/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract We aimed to found predictors of EF deterioration in HFpEF patients toprevent their further deterioration. Methods. We studied 215 patients(63% women) 73±8 years with HFpEF and with records of Charlson index(CI), glomerular filtration rate (GFR). Myocardial work (MW), globallongitudinal (LS), radial (RS), circumferential (SS) and area strain(AS).GW index , global constructive work (GCW), wasted work, GWefficiency were obtained by echocardiography. Patients followed up for 3years. Results. 5 patients developed myocardial infarction and wereexcluded from the study.Baseline EF was higher in women (61,2 ± 3,1 vs56,4 ± 2,7; P70 years (62,4 ± 2,1 vs 57,1 ± 2,3;p<0.005), and with end-diastolic volume index <60 ml/m2 (56,1 ± 3,2vs 63,4 ± 2,3; p<0.001). EF decline compared to baseline was -7.3 ±1.6%, p70 years, inpatients with coronary artery disease and did not relate to sex, LV size,CI, and GFR. During follow up 58(27%) patients had EF<50%.,worsening in AS (-27.9±8.5% vs -24.7±5.3%, p<0.003), LS (-19.7±2.4% vs -17.1±1.6%, p<0.005), and GCW (2378±117 vs2102±10, p<0.002). Patients with EF 50% (22.4±7.2% vs -27.6±8.1%,p<0.002; 2081±92 vs 2489±127, p<0.001). GCW was thepredictor of EF deterioration(area under curve 0,8853). Conclusion. GCW predicts EF decline in HFpEF patients which may help earlieridentify this subset of patients and prevent their furtherdeterioration. Figures Figure 1 Introduction Heart failure (HF) is a worldwide health problem with high morbidity and mortality. Its prevalence has been increased over time, mainly due to increase in share of heart failure with preserved ejection fraction (HFpEF) in overall HF syndrome, because of increased life expectancy and the emergence of age-related comorbidities which in turn predispose to HFpEF [1]. HFpEF remained an unresolved issue for years regarding its management. Proven therapies for heart failure with reduced EF (HFrEF) failed to show benefit in that category. Recently SGLT2 inhibitors have been proven to reduce hospitalization in patients with HFpEF [2]. However, despite the advances in the treatment of HFpEF, its management remains challenging. SGLT2 inhibitors benefits across the full range of ejection fraction [3], and sacubitril/valsartan benefits up to the lower end of preserved EF <57% [4] imply that in some patients with HFpEF some pathophysiological mechanisms of HFrEF might co-exist, and some subset of HFpEF patients might benefit from proven therapies of HFrEF, particularly those with EF deterioration over time. EF changes are not infrequent in patients with HF and many patients move from one HF category to another [5]. We aimed to find out predictors of EF deterioration in HFpEF patients assuming that we might start treating these patients subset earlier with proven therapies of HFrEF, preventing further deterioration . Methods Study population All patients with dyspnea admitted to our hospital between 2019 and 2020 were examined for HFpEF. Diagnosis of HFpEF was made based on the HFA-PEFF algorithm [6]. Exclusion criteria were poor acoustic window, age > 80 years old, acute coronary syndrome at the time of admission, significant valvular heart disease (moderate to severe regurgitations or stenosis), atrial fibrillation, constrictive pericarditis or hypertrophic cardiomyopathy. 215 patients (63% women) 71±8 years with HFpEF and excellent echo acoustic windows were enrolled. Patients were followed up for 3 years. Patients baseline characteristics Hyperlipidemia was defined by the patient’s serum lipid spectrum. Diabetes mellitus (DM) was defined by fasting blood glucose levels, A1C Hb or previous records. Chronic obstructive lung disease was identified from previous medical records. Hypertension was identified by the patient’s history or if office triple measurements of systolic blood pressure or diastolic blood pressure are >140 mm Hg and/or >90 mm Hg respectively. Coronary artery disease (CAD) was diagnosed from previous medical records as a history of myocardial infarction (MI), coronary intervention, or coronary artery bypass grafting. Anemia was diagnosed if hemoglobin <13.5 mg/dL in men and <12 mg/dL in women. Glomerular filtration rate was calculated from creatinine levels by the estimation fromula [7]. Patients’ height and weight were taken at the time of enrolment for body mass index calculation. The level of comorbidity was evaluated by Comorbidity Index [8]. The use of β blockers, angiotensin-converting enzyme inhibitors (ACE-I), angiotensin receptor blockers (ARB), and mineralocorticoid receptor antagonists (MRA) prior to the study enrollment was documented. Echocardiography Echocardiography (EchoCG) was performed by two experienced echocardiographers using GE vivid 7 ultrasound system. All linear, volumetric measurements and assessment of left ventricular filling pressures were done according to joint ASE and EACVI recommendations [9,10]. 3D images were obtained by full volume acquisition from four cycles with the patient holding breath at the best visualization. All images were stored and analyzed offline using software EchoPac v.203. Speckle tracking were performed offline using Q analysis by manually tracing endocardium in 3 apical and 3 parasternal short axis views, after which the program automatically delineated left ventricular walls, manual correction were performed if needed, and then the program automatically obtained longitudinal (LS), circumferential (CS), radial strain (RS), area strain (AS) and LV twist values. Global work index (GWI) was obtained from pressure-strain loops derived from 2D speckle tracking analysis multiplied by brachial blood pressure measured right before the echocardiography exam with patient in the left lateral decubitus position. Global constructive work (GCW) as the sum of positive work due to myocardial shortening during systole and negative work due to lengthening during isovolumic relaxation, global wasted work (GWW) as energy loss by myocardial lengthening in systole and shortening in isovolumic relaxation, and global work efficiency (GWE) as the percentage ratio of constructive work to the sum of constructive work and wasted work were obtained. Ejection fraction and area strain (AS) were calculated in 3D using LVQ analysis on EchoPac. Statistical analysis Statistical analysis was conducted using SAS Version 9.2.1 with a significance level set at P < 0.05. Baseline clinical variables were summarized as means with standard deviations, medians with interquartile ranges for variables with skewed distributions, or as frequencies. Differences between groups were analyzed using t-tests for continuous variables and chi-square tests for categorical variables. To evaluate the longitudinal change in ejection fraction (EF), linear mixed effects regression models were employed, allowing for the fitting of a linear regression line for everyone. The cohort results were aggregated to assess overtime changes in EF. Only age and left ventricular end-diastolic diameter (LVEDD) were analyzed as continuous variables within the model, the other results were expressed categorically for simplicity in interpretation. In order to assess the prognostic importance of EF changes, EF was considered a time-varying variable in the Cox proportional hazards regression models. Results Patients with HFpEF have high prevalence of hypertension, CAD and DM, anemia, the prevalence of smokers was relatively low (table 1). Table 1. Baseline patient characteristics Age, y 71±8 Gender (Women), n (%) 144 (67.0) Current smoking n (%) 39 (18.1) Diabetes mellitus n (%) 69 (32.0) Hyperlipidemia n (%) 90 (41.9) CAD n (%) 82 (38.1) Anemia n (%) 71 (33.0) COPD n (%) 60 (27.9) Cerebrovascular disease n (%) 88 (40.9) EDVi (ml/m 2 ) 60.0 ± 12 eGFR, ml/min 56.9 ± 21.7 Charlson index ≥3 81 (37.7) ACE/ARB n (%) 161 (75) n (%) 137 (64) MRA n (%) 146 (68) The mean baseline value of EF was 58.7%. Baseline EF was higher in women, in patients >70 years, with anemia, and with end-diastolic volume index 70 years, and in patients with CAD and did not relate to sex, LV size, CI, and GFR (table 2). 5 patients who developed myocardial infarction were excluded from the study. Table 2. Ejection fraction values at baseline relative to patients’ characteristics Baseline parameters EF values P value EF mean (%) 58.7 ± 3.1 Women, n=144 61,2 ± 3,1 70 years, n=112 62,4 ± 2,1 <0.005 <70 years, n=103 56,7 ± 2,3 CAD yes, n=82 58,9 ± 2,9 0.12 CAD no, n=133 57,6 ± 3,3 EDVi (ml/m 2 ) <median (60), n=87 63.4 ± 2.3 <0.001 EDVi (ml/m 2 ) ≥median, n=128 56.1 ± 3.2 Comorbidity Index ≥3, n=90 59.2 ± 3.8 0.23 Comorbidity Index ≤3, n=125 58.1 ± 3.5 eGFR (ml/min) <median (56.9), n=76 58.2 ± 3.1 0.28 eGFR <median, n=139 57.8 ± 3.5 Anemia yes, n=71 62.1 ± 3.8 70 years, and in patients with CAD and did not relate to sex, LV size, CI, and GFR. (table 3). Table 3. Changes in EF for 3 years follow up Parameters Change in EF over 3 years FU P value Overall change in EF (%) -7.3 ± 1.6 70 years, n=109 -7.9 ± 1.8 <0.01 <70 years, n=101 -5.7 ± 1.7 CAD yes, n=80 -7,8 ± 1,9 <0.001 CAD no, n=130 -5,3 ± 1,6 EDVi (ml/m 2 ) <median (60), n=85 -6.8 ± 1.5 0.53 EDVi (ml/m 2 ) ≥median, n=125 -7.1 ± 1.8 Comorbidity Index ≥3, n=87 -7.2 ± 1.9 0.76 Comorbidity Index ≤3, n=123 -7.1 ± 1.7 eGFR (ml/min) <median (56.9), n=73 -6.9 ± 1.4 0.47 eGFR <median, n=137 -7.2 ± 2.1 Anemia yes, n=68 -7.3 ± 1.4 0.72 Anemia no, n=142 -7.2 ± 1.5 We observed significant reduction in AS, LS, GCW. (table 4) Table 4 . Changes in global strain values and myocardial work Parameters Baseline 3 years FU P value Longitudinal strain -19.7±2.4% -17.1±1.6% <0.005 Circumferential strain (%) 14.3±3.5% 13.9±3.1% 0.18 Radial strain (%) 31.7±10.8% 29.8±10.1% 0.06 LV twist (%) 1.9±0.8 1.8±0.9 0.150 Area strain (%) -27.9±8.5% -24.7±5.3% <0.003 GWI (mg%) 2470±161 2210±147 <0.005 GCW (mg%) 2378±117 2102±101 <0.002 GWW (mg%) 112±9 116±7 0.07 GWE (%) 95±2 94±3 0.21 There was a correlation of EF with LS, AS, GWI, and GCW (table 5) Table 5 . Correlation of deformation and myocardial work parameter with EF LS AS GWI GCW EF 0.43 0.52 0.51 0.59 P value 0.01 0.001 0.003 <0.001 58(27%) patients had EF<50%. Patients with EF 50%. (table 6). Table 6 . Baseline parameters of patients who consequently had EF 50% at the end of the study Parameters EF 50% P value Longitudinal strain (%) -18.1 ± 2.2 20.2 ± 2.4 <0.01 Circumferential strain (%) -13.4 ± 3.8 -14.5 ± 4.1 <0.04 Radial strain (%) 31.4 ± 11.2 31.8 ± 10.6 0.12 LV twist (%) 1.9 ± 0.9 1.9 ± 1.2 0.17 Area strain (%) 23.9±7.2 -28.8±8.1 <0.002 GWI (mmHg%) 2451±142 2493±158 0.06 GCW (mmHg%) 2081±92 2489±127 <0.001 GWW (mmHg%) 118±9 111±8 0.06 GWE (%) 94.6 ± 2.1 95.7 ± 1,8 0.05 GCW was the only predictor of EF deterioration (area under curve 0.8853) Fig. 1, Table 7 Table 7. Predictive values of deformation and myocardial work parameters for EF Parameters AUC Longitudinal strain 0.6348 Circumferential strain(%) 0.5839 Radial strain (%) 0.6184 LV twist (%) 0.5841 Area strain (%) 0.6972 GWI (mg%) 0.6483 GCW (mg%) 0.8853 GWW (mg%) 0.6235 GWE (%) 0.6872 Discussion We conducted this study to assess the dynamics of systolic function in patients with HFpEF. We observed significant reduction in systolic function parameters, with average EF reduction of 7.3% over 3 years follow up. About a third of our patients with HFpEF had EF < 50% during follow up of which 12% had EF < 40% at the end of the study. Though HFpEF is considered as predominantly diastolic deterioration entity there are many pathophysiologic factors that determine concomitant systolic dysfunction [ 11 ]. Though some mechanisms of systolic disfunction has been proposed, including development of myocardial infarction, neurohormonal activation, infiltrative and inflammatory processes, the mechanism remains unclear. We excluded patients with new MI from the study, so it cannot explain EF decline in our study. Also, the Dunlay et al showed that neurohormonal modulator medication did not change the course of EF decline in patients with HFpEF [ 12 ]. In our study changes in EF were not affected by baseline LV dimensions, baseline EF and comorbidity index which suggests that other mechanisms than initial systolic functional status, neurohormonal activation and inflammation might be involved in the development of systolic dysfunction. We observed a decline in longitudinal, circumferential and area strain in patients with EF reduction. These parameters positively correlated with EF, but GCW was the only predictor of EF decline. The results of the study allow to predict patients with later decline in EF so start treating them more aggressively. Though Dunlay et al study did not show benefit of ACE/ARB and \(\:\beta\:\:\) blockers [ 12 ] it is unclear how these patients would respond to the newer heart failure medications such as sacubitril/valsartan and probably gain more benefits from SGLT2 inhibitors when they are still in the normal EF range compared with their counterparts with lower risk of EF deterioration. We speculate that the patients with HFpEF with increased risk of systolic function deterioration might get more benefits from HFrEF evidence-based treatment, and it can be started before EF goes down. Though data from PARAGON-HF showed that ARNI are effective in patients with HFpEF with EF up to 57% [ 4 ], in our study EF decline did not relate to baseline EF values, and patients even with higher EF and lower GCW are at risk of EF decline and probably they might benefit from ARNI. Further studies are needed to answer this question. Abbreviations HF Heart Failure HFpEF Heart failure with preserves ejection fraction HFrEF Heart failure with reduced ejection fraction EF Ejection fraction DM Diabetes Mellitus MI Myocardial infarction CAD Coronary artery disease EchoCG Echocardiography ASE American Society of Echocardiography EACVI European Association of Cardiovascular Imaging LS Longitudinal strain CS Circumferential strain RS Radial strain AS Area strain GWI Global work index GCW Global constructive work GWE Global work efficiency LVEDD Left ventricular end-diastolic diameter COPD Chronic obstructive lung disease EDVi End-diastolic volume index eGFR Estimated glomerular filtration rate Declarations Ethics approval and consent to participate Study conduction has been approved by Yerevan MC Ethical Committee. All participants signed the consent. Consent for publication All participants signed the consent for publication at the time of signing the consent to participate Competing interest Authors have nothing to declare as a conflict of interests Funding The study was funded by The RA Ministry of Education, Science, Culture and Sports Higher Education and Science Committee Authors contributions Aram Chilingaryan Contribute to collecting patient's data, making and interpreting exams, writing papers. Hovik Balyan Contribute to writing papers. Milena Arzumanyan Contribute to collecting patient's data, making and interpreting exams, writing papers. Tsiala Ustyan and Anush Barkhudaryan Contribute to making exams. Nadezhda Iskandaryan-Contribute to collecting patient's data. Armenuhi Asatryan Contribute to interpreting exams. Harutyun Ghrmajyan Contribute to collecting patient's data. Lusine Tunyan Contribute to collecting patient's data, making and interpreting exams, writing papers. Acknowledgements Aslanyan Levon for co-participating and providing programs for statistical analysis Arzumanyan Ashot for revising the document References Bozkurt B, Ahmad T, Alexander KM, Baker WL, Bosak K, Breathett K, Fonarow GC, Heidenreich P, Ho JE, Hsich E, Ibrahim NE, Jones LM, Khan SS, Khazanie P, Koelling T, Krumholz HM, Khush KK, Lee C, Morris AA, Page RL 2nd, Pandey A, Piano MR, Stehlik J, Stevenson LW, Teerlink JR, Vaduganathan M, Ziaeian B (2023) Writing Committee Members. Heart Failure Epidemiology and Outcomes Statistics: A Report of the Heart Failure Society of America. J Card Fail 29(10):1412–1451. 10.1016/j.cardfail.2023.07.006 Epub 2023 Sep 26. PMID: 37797885 Jaiswal A, Jaiswal V, Ang SP, Hanif M, Vadhera A, Agrawal V et al (2023) SGLT2 inhibitors among patients with heart failure with preserved ejection fraction: a meta-analysis of randomised controlled trials. Royal College of Surgeons in Ireland. J contribution. https://hdl.handle.net/10779/rcsi.24271234.v1 Vaduganathan M, Docherty KF, Claggett BL, Jhund PS, de Boer RA, Hernandez AF, Inzucchi SE, Kosiborod MN, Lam CSP, Martinez F, Shah SJ, Desai AS, McMurray JJV, Solomon SD (2022) SGLT-2 inhibitors in patients with heart failure: a comprehensive meta-analysis of five randomised controlled trials. Lancet. ;400(10354):757–767. 10.1016/S0140-6736(22)01429-5 . Epub 2022 Aug 27. Erratum in: Lancet. 2023;401(10371):104. PMID: 36041474 Vaduganathan M, Claggett BL, Greene SJ et al (2021) Potential Implications of Expanded US Food and Drug Administration Labeling for Sacubitril/Valsartan in the US. JAMA Cardiol 6(12):1415–1423. 10.1001/jamacardio.2021.3651 Savarese G, Vedin O, D'Amario D, Uijl A, Dahlström U, Rosano G, Lam CSP, Lund LH (2019) Prevalence and Prognostic Implications of Longitudinal Ejection Fraction Change in Heart Failure. JACC Heart Fail. ;7(4):306–317. 10.1016/j.jchf.2018.11.019 . Epub 2019 Mar 6. Erratum in: JACC Heart Fail. 2019;7(8):735–736. Abstract corrected. PMID: 30852236 Pieske B, Tschöpe C, de Boer RA, Fraser AG, Anker SD, Donal E, Edelmann F, Fu M, Guazzi M, Lam CSP, Lancellotti P, Melenovsky V, Morris DA, Nagel E, Pieske-Kraigher E, Ponikowski P, Solomon SD, Vasan RS, Rutten FH, Voors AA, Ruschitzka F, Paulus WJ, Seferovic P, Filippatos G (2019) How to diagnose heart failure with preserved ejection fraction: the HFA-PEFF diagnostic algorithm: a consensus recommendation from the Heart Failure Association (HFA) of the European Society of Cardiology (ESC). Eur Heart J. ;40(40):3297–3317. 10.1093/eurheartj/ehz641 . Erratum in: Eur Heart J. 2021;42(13):1274. PMID: 31504452 Levey AS, Coresh J, Greene T, Stevens LA, Zhang YL, Hendriksen S, Kusek JW, Van Lente F (2006) Chronic Kidney Disease Epidemiology Collaboration. Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med. ;145(4):247 – 54. 10.7326/0003-4819-145-4-200608150-00004 . Erratum in: Ann Intern Med. 2008;149(7):519. Erratum in: Ann Intern Med. 2021;174(4):584. PMID: 16908915 Charlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. ;40(5):373 – 83. 10.1016/0021-9681(87)90171-8 . PMID: 3558716 Lang RM, Badano LP, Mor-Avi V, Afilalo J, Armstrong A, Ernande L, Flachskampf FA, Foster E, Goldstein SA, Kuznetsova T, Lancellotti P, Muraru D, Picard MH, Rietzschel ER, Rudski L, Spencer KT, Tsang W, Voigt JU (2015) Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. J Am Soc Echocardiogr. ;28(1):1–39.e14. 10.1016/j.echo.2014.10.003 . PMID: 25559473 Nagueh SF, Smiseth OA, Appleton CP et al (2016) Recommendations for the evaluation of left ventricular diastolic function by echocardiography: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. J Am Soc Echocardiogr 29:277–314 Kraigher-Krainer E, Shah AM, Gupta DK, Santos A, Claggett B, Pieske B, Zile MR, Voors AA, Lefkowitz MP, Packer M, McMurray JJ, Solomon SD (2014) PARAMOUNT Investigators. Impaired systolic function by strain imaging in heart failure with preserved ejection fraction. J Am Coll Cardiol. ;63(5):447 – 56. 10.1016/j.jacc.2013.09.052 . Epub 2013 Oct 30. Erratum in: J Am Coll Cardiol. 2014;64(3):335. PMID: 24184245; PMCID: PMC7195816 Dunlay SM, Roger VL, Weston SA, Jiang R, Redfield MM (2012) Longitudinal changes in ejection fraction in heart failure patients with preserved and reduced ejection fraction. Circ Heart Fail 5(6):720–726. 10.1161/CIRCHEARTFAILURE.111.966366 Epub 2012 Aug 30. PMID: 22936826; PMCID: PMC3661289 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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10:53:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5268112/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5268112/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":67618722,"identity":"cd21274c-34b3-4e92-bd20-3abd7aff2a9b","added_by":"auto","created_at":"2024-10-28 06:52:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":26249,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5268112/v1/cc793c1081691eec3f1ed880.png"},{"id":73302966,"identity":"ded5df15-ad3c-4329-a719-97905fdd91d0","added_by":"auto","created_at":"2025-01-08 16:23:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":623115,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5268112/v1/f65bb606-ed5b-4e46-b78b-04cab336131e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Left ventricular myocardial constructive work predicts reduction of ejection fraction in patients with heart failure with preserved ejection fraction","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHeart failure (HF) is a worldwide health problem with high morbidity and mortality. Its prevalence has been increased over time, mainly due to increase in share of heart failure with preserved ejection fraction (HFpEF) in overall HF syndrome, because of increased life expectancy and the emergence of age-related comorbidities which in turn predispose to HFpEF [1].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHFpEF remained an unresolved issue for years regarding its management. Proven therapies for heart failure with reduced EF (HFrEF) failed to show benefit in that category.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRecently SGLT2 inhibitors have been proven to reduce hospitalization in patients with HFpEF [2]. However, despite the advances in the treatment of HFpEF, its management remains challenging. SGLT2 inhibitors benefits across the full range of ejection fraction [3], and sacubitril/valsartan benefits\u0026nbsp;up to the lower end of preserved EF \u0026lt;57% [4] imply that in some patients with HFpEF some pathophysiological mechanisms of HFrEF might co-exist, and some subset of HFpEF patients might benefit from proven therapies of HFrEF, particularly those with EF deterioration over time. EF changes are not infrequent in patients with HF and many patients move from one HF category to another [5].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWe aimed to find out predictors of EF deterioration in HFpEF patients assuming that we might start treating these patients subset earlier with proven therapies of HFrEF, preventing further deterioration\u003c/strong\u003e.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy population\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll patients with dyspnea admitted to our hospital between 2019 and 2020 were examined for HFpEF. Diagnosis of HFpEF was made based on the HFA-PEFF algorithm [6]. Exclusion criteria were poor acoustic window, age \u0026gt; 80 years old, acute coronary syndrome at the time of admission, significant valvular heart disease (moderate to severe regurgitations or stenosis), atrial fibrillation, constrictive pericarditis or hypertrophic cardiomyopathy. 215 patients (63% women) 71\u0026plusmn;8 years with HFpEF and excellent echo acoustic windows were enrolled. Patients were followed up for 3 years.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatients baseline characteristics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHyperlipidemia was defined by the patient\u0026rsquo;s serum lipid spectrum. Diabetes mellitus (DM) was defined by fasting blood glucose levels, A1C Hb or previous records. Chronic obstructive lung disease was identified from previous medical records. Hypertension was identified by the patient\u0026rsquo;s history or if office triple measurements of systolic blood pressure or diastolic blood pressure are \u0026gt;140 mm Hg and/or \u0026gt;90 mm Hg respectively. Coronary artery disease (CAD) was diagnosed from previous medical records as a history of myocardial infarction (MI), coronary intervention, or coronary artery bypass grafting. Anemia was diagnosed if hemoglobin \u0026lt;13.5 mg/dL in men and \u0026lt;12 mg/dL in women. Glomerular filtration rate was calculated from creatinine levels by the estimation fromula [7]. Patients\u0026rsquo; height and weight were taken at the time of enrolment for body mass index calculation. The level of comorbidity was evaluated \u0026nbsp;by Comorbidity Index [8]. The use of \u0026beta; blockers, angiotensin-converting enzyme inhibitors (ACE-I), angiotensin receptor blockers (ARB), and mineralocorticoid receptor antagonists (MRA) prior to the study enrollment was documented.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEchocardiography\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEchocardiography (EchoCG) was performed by two experienced echocardiographers using GE vivid 7 ultrasound system. All linear, volumetric measurements and assessment of left ventricular filling pressures were done according to joint ASE and EACVI recommendations [9,10]. 3D images were obtained by full volume acquisition from four cycles with the patient holding breath at the best visualization. All images were stored and analyzed offline using software EchoPac v.203. Speckle tracking were performed offline using Q analysis by manually tracing endocardium in 3 apical and 3 parasternal short axis views, after which the program automatically delineated left ventricular walls, manual correction were performed if needed, and then the program automatically obtained longitudinal (LS), circumferential (CS), radial strain (RS), area strain (AS) and LV twist values. Global work index (GWI) was obtained from pressure-strain loops derived from 2D speckle tracking analysis\u0026nbsp;multiplied by brachial\u0026nbsp;blood pressure measured right before the echocardiography exam with patient in the left lateral\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003edecubitus position. Global constructive work (GCW) as the sum of positive work due to myocardial shortening during systole and negative work due to lengthening during isovolumic relaxation, global wasted work (GWW) as energy loss by myocardial lengthening in systole and shortening in isovolumic relaxation, and global work efficiency (GWE) as the percentage ratio of constructive work to the sum of constructive work and wasted work were obtained. Ejection fraction and area strain (AS) were calculated in 3D using LVQ analysis on EchoPac. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStatistical analysis was conducted using SAS Version 9.2.1 with a significance level set at P \u0026lt; 0.05. Baseline clinical variables were summarized as means with standard deviations, medians with interquartile ranges for variables with skewed distributions, or as frequencies. Differences between groups were analyzed using t-tests for continuous variables and chi-square tests for categorical variables. To evaluate the longitudinal change in ejection fraction (EF), linear mixed effects regression models were employed, allowing for the fitting of a linear regression line for everyone. The cohort results were aggregated to assess overtime changes in EF. Only age and left ventricular end-diastolic diameter (LVEDD) were analyzed as continuous variables within the model, the other results were expressed categorically for simplicity in interpretation. In order to assess the prognostic importance of EF changes, EF was considered a time-varying variable in the Cox proportional hazards regression models.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003ePatients with HFpEF have high prevalence of hypertension, CAD and DM, anemia, the prevalence of smokers was relatively low (table 1). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e \u003cstrong\u003eBaseline patient characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71.2991%;\"\u003e\n \u003cp\u003eAge, y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.7009%;\"\u003e\n \u003cp\u003e71\u0026plusmn;8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71.2991%;\"\u003e\n \u003cp\u003eGender (Women), n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.7009%;\"\u003e\n \u003cp\u003e144 (67.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71.2991%;\"\u003e\n \u003cp\u003eCurrent smoking n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.7009%;\"\u003e\n \u003cp\u003e39 (18.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71.2991%;\"\u003e\n \u003cp\u003eDiabetes mellitus n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.7009%;\"\u003e\n \u003cp\u003e69 (32.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71.2991%;\"\u003e\n \u003cp\u003eHyperlipidemia n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.7009%;\"\u003e\n \u003cp\u003e90 (41.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71.2991%;\"\u003e\n \u003cp\u003eCAD n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.7009%;\"\u003e\n \u003cp\u003e82 (38.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71.2991%;\"\u003e\n \u003cp\u003eAnemia n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.7009%;\"\u003e\n \u003cp\u003e71 (33.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71.2991%;\"\u003e\n \u003cp\u003eCOPD n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.7009%;\"\u003e\n \u003cp\u003e60 (27.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71.2991%;\"\u003e\n \u003cp\u003eCerebrovascular disease n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.7009%;\"\u003e\n \u003cp\u003e88 (40.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71.2991%;\"\u003e\n \u003cp\u003eEDVi (ml/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.7009%;\"\u003e\n \u003cp\u003e60.0 \u0026plusmn; 12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71.2991%;\"\u003e\n \u003cp\u003eeGFR, ml/min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.7009%;\"\u003e\n \u003cp\u003e56.9 \u0026plusmn; 21.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71.2991%;\"\u003e\n \u003cp\u003eCharlson index\u0026nbsp;\u0026ge;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.7009%;\"\u003e\n \u003cp\u003e81 (37.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71.2991%;\"\u003e\n \u003cp\u003eACE/ARB n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.7009%;\"\u003e\n \u003cp\u003e161 (75)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71.2991%;\"\u003e\n \u003cp\u003e\u0026nbsp;n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.7009%;\"\u003e\n \u003cp\u003e137 (64)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71.2991%;\"\u003e\n \u003cp\u003eMRA\u0026nbsp;n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.7009%;\"\u003e\n \u003cp\u003e146 (68)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe mean baseline value of EF was 58.7%.\u0026nbsp;Baseline EF was higher in women, in patients \u0026gt;70 years, with anemia, and with end-diastolic volume index \u0026lt;60 ml/m\u003csup\u003e2\u003c/sup\u003e. Overall reduction in EF was 7.3% over 3 years and was statistically significant and more prominent in patients \u0026gt;70 years, and in patients with CAD and did not relate to sex, LV size, CI, and GFR (table 2). 5 patients who developed myocardial infarction were excluded from the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Ejection fraction values at baseline relative to patients\u0026rsquo; characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eBaseline parameters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eEF values\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eEF mean (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e58.7 \u0026plusmn; 3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eWomen, n=144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e61,2 \u0026plusmn; 3,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eMen, n=71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e56,4 \u0026plusmn; 2,7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003e\u0026gt;70 years, n=112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e62,4 \u0026plusmn; 2,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003e\u0026lt;70 years, n=103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e56,7 \u0026plusmn; 2,3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eCAD yes, n=82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e58,9 \u0026plusmn; 2,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eCAD no, n=133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e57,6 \u0026plusmn; 3,3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eEDVi (ml/m\u003csup\u003e2\u003c/sup\u003e) \u0026lt;median (60), n=87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e63.4 \u0026plusmn; 2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eEDVi (ml/m\u003csup\u003e2\u003c/sup\u003e)\u0026nbsp;\u0026ge;median, n=128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e56.1 \u0026plusmn; 3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eComorbidity\u0026nbsp;Index \u0026ge;3, n=90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e59.2 \u0026plusmn; 3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eComorbidity\u0026nbsp;Index\u0026nbsp;\u0026le;3, n=125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e58.1 \u0026plusmn; 3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eeGFR (ml/min) \u0026lt;median (56.9), n=76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e58.2 \u0026plusmn; 3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eeGFR \u0026lt;median, n=139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e57.8 \u0026plusmn; 3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eAnemia yes, n=71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e62.1 \u0026plusmn; 3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt; 0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eAnemia no, n=144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e56.9 \u0026plusmn; 3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThere was an overall decrease in EF by -7.3 \u0026plusmn; 1.6% irrespective of baseline EF values. Reduction in EF was more prominent in patients \u0026gt;70 years, and in patients with CAD and did not relate to sex, LV size, CI, and GFR. \u0026nbsp;(table 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Changes in EF for 3 years follow up\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eParameters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eChange in EF over 3 years FU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eOverall change in EF (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e-7.3 \u0026plusmn; 1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eWomen, n=142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e-7.0 \u0026plusmn; 1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eMen, n=68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e-7.4 \u0026plusmn; 2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003e\u0026gt;70 years, n=109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e-7.9 \u0026plusmn; 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003e\u0026lt;70 years, n=101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e-5.7 \u0026plusmn; 1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eCAD yes, n=80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e-7,8 \u0026plusmn; 1,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eCAD no, n=130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e-5,3 \u0026plusmn; 1,6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eEDVi (ml/m\u003csup\u003e2\u003c/sup\u003e) \u0026lt;median (60), n=85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e-6.8 \u0026plusmn; 1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eEDVi (ml/m\u003csup\u003e2\u003c/sup\u003e)\u0026nbsp;\u0026ge;median, n=125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e-7.1 \u0026plusmn; 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eComorbidity\u0026nbsp;Index \u0026ge;3, n=87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e-7.2 \u0026plusmn; 1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eComorbidity\u0026nbsp;Index\u0026nbsp;\u0026le;3, n=123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e-7.1 \u0026plusmn; 1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eeGFR (ml/min) \u0026lt;median (56.9), n=73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e-6.9 \u0026plusmn; 1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eeGFR \u0026lt;median, n=137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e-7.2 \u0026plusmn; 2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eAnemia yes, n=68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e-7.3 \u0026plusmn; 1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eAnemia no, n=142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e-7.2 \u0026plusmn; 1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eWe observed significant reduction in AS, LS, GCW. (table 4)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e. \u003cstrong\u003eChanges in global strain values and myocardial work\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42.5676%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3964%;\"\u003e\n \u003cp\u003e\u0026nbsp;Baseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.1712%;\"\u003e\n \u003cp\u003e3 years FU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42.5676%;\"\u003e\n \u003cp\u003eLongitudinal strain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3964%;\"\u003e\n \u003cp\u003e-19.7\u0026plusmn;2.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.1712%;\"\u003e\n \u003cp\u003e-17.1\u0026plusmn;1.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003e\u0026lt;0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42.5676%;\"\u003e\n \u003cp\u003eCircumferential strain\u0026nbsp;(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3964%;\"\u003e\n \u003cp\u003e14.3\u0026plusmn;3.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.1712%;\"\u003e\n \u003cp\u003e13.9\u0026plusmn;3.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42.5676%;\"\u003e\n \u003cp\u003eRadial strain\u0026nbsp;(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3964%;\"\u003e\n \u003cp\u003e31.7\u0026plusmn;10.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.1712%;\"\u003e\n \u003cp\u003e29.8\u0026plusmn;10.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42.5676%;\"\u003e\n \u003cp\u003eLV twist\u0026nbsp;(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3964%;\"\u003e\n \u003cp\u003e1.9\u0026plusmn;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.1712%;\"\u003e\n \u003cp\u003e1.8\u0026plusmn;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003e0.150\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42.5676%;\"\u003e\n \u003cp\u003eArea\u0026nbsp;strain (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3964%;\"\u003e\n \u003cp\u003e-27.9\u0026plusmn;8.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.1712%;\"\u003e\n \u003cp\u003e-24.7\u0026plusmn;5.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003e\u0026lt;0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42.5676%;\"\u003e\n \u003cp\u003eGWI (mg%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3964%;\"\u003e\n \u003cp\u003e2470\u0026plusmn;161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.1712%;\"\u003e\n \u003cp\u003e2210\u0026plusmn;147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003e\u0026lt;0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42.5676%;\"\u003e\n \u003cp\u003eGCW (mg%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3964%;\"\u003e\n \u003cp\u003e2378\u0026plusmn;117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.1712%;\"\u003e\n \u003cp\u003e2102\u0026plusmn;101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003e\u0026lt;0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42.5676%;\"\u003e\n \u003cp\u003eGWW (mg%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3964%;\"\u003e\n \u003cp\u003e112\u0026plusmn;9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.1712%;\"\u003e\n \u003cp\u003e116\u0026plusmn;7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42.5676%;\"\u003e\n \u003cp\u003eGWE (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3964%;\"\u003e\n \u003cp\u003e95\u0026plusmn;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.1712%;\"\u003e\n \u003cp\u003e94\u0026plusmn;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8649%;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThere was a correlation of EF with LS, AS, GWI, and GCW (table 5)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u003c/strong\u003e. \u003cstrong\u003eCorrelation of deformation and myocardial work parameter with EF\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.93%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.5079%;\"\u003e\n \u003cp\u003eLS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4447%;\"\u003e\n \u003cp\u003eAS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.219%;\"\u003e\n \u003cp\u003eGWI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8984%;\"\u003e\n \u003cp\u003eGCW\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.93%;\"\u003e\n \u003cp\u003eEF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.5079%;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4447%;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.219%;\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8984%;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.93%;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25.5079%;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4447%;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.219%;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8984%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e58(27%) patients had EF\u0026lt;50%. Patients with EF \u0026lt;50% at the end of the study had significantly less AS and GCW baseline values compared with patients with EF\u0026gt;50%. (table 6).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6\u003c/strong\u003e.\u003cstrong\u003e\u0026nbsp;Baseline parameters of patients who consequently had EF \u0026lt;50% or \u0026gt;50% at the end of the study\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.63%;\"\u003e\n \u003cp\u003eParameters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.9251%;\"\u003e\n \u003cp\u003eEF \u0026lt;50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7048%;\"\u003e\n \u003cp\u003eEF \u0026gt;50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.7401%;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.63%;\"\u003e\n \u003cp\u003eLongitudinal strain (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.9251%;\"\u003e\n \u003cp\u003e-18.1 \u0026plusmn; 2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7048%;\"\u003e\n \u003cp\u003e20.2 \u0026plusmn; 2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.63%;\"\u003e\n \u003cp\u003eCircumferential strain\u0026nbsp;(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.9251%;\"\u003e\n \u003cp\u003e-13.4 \u0026plusmn; 3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7048%;\"\u003e\n \u003cp\u003e-14.5 \u0026plusmn; 4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e\u0026lt;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.63%;\"\u003e\n \u003cp\u003eRadial strain\u0026nbsp;(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.9251%;\"\u003e\n \u003cp\u003e31.4 \u0026plusmn; 11.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7048%;\"\u003e\n \u003cp\u003e31.8 \u0026plusmn; 10.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.63%;\"\u003e\n \u003cp\u003eLV twist\u0026nbsp;(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.9251%;\"\u003e\n \u003cp\u003e1.9 \u0026plusmn; 0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7048%;\"\u003e\n \u003cp\u003e1.9 \u0026plusmn; 1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.63%;\"\u003e\n \u003cp\u003eArea\u0026nbsp;strain (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.9251%;\"\u003e\n \u003cp\u003e23.9\u0026plusmn;7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7048%;\"\u003e\n \u003cp\u003e-28.8\u0026plusmn;8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e\u0026lt;0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.63%;\"\u003e\n \u003cp\u003eGWI (mmHg%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.9251%;\"\u003e\n \u003cp\u003e2451\u0026plusmn;142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7048%;\"\u003e\n \u003cp\u003e2493\u0026plusmn;158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.63%;\"\u003e\n \u003cp\u003eGCW (mmHg%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.9251%;\"\u003e\n \u003cp\u003e2081\u0026plusmn;92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7048%;\"\u003e\n \u003cp\u003e2489\u0026plusmn;127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.63%;\"\u003e\n \u003cp\u003eGWW (mmHg%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.9251%;\"\u003e\n \u003cp\u003e118\u0026plusmn;9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7048%;\"\u003e\n \u003cp\u003e111\u0026plusmn;8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.63%;\"\u003e\n \u003cp\u003eGWE (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.9251%;\"\u003e\n \u003cp\u003e94.6 \u0026plusmn; 2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.7048%;\"\u003e\n \u003cp\u003e95.7 \u0026plusmn; 1,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eGCW was the only predictor of EF deterioration (area under curve 0.8853) Fig. 1, Table 7\u003c/p\u003e\n\u003cp\u003eTable 7. \u003cstrong\u003ePredictive values of\u003c/strong\u003e \u003cstrong\u003edeformation and myocardial work parameters for EF\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eParameters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.4949%;\"\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eLongitudinal strain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.4949%;\"\u003e\n \u003cp\u003e0.6348\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eCircumferential strain(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.4949%;\"\u003e\n \u003cp\u003e0.5839\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eRadial strain\u0026nbsp;(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.4949%;\"\u003e\n \u003cp\u003e0.6184\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eLV twist\u0026nbsp;(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.4949%;\"\u003e\n \u003cp\u003e0.5841\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eArea\u0026nbsp;strain (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.4949%;\"\u003e\n \u003cp\u003e0.6972\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eGWI (mg%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.4949%;\"\u003e\n \u003cp\u003e0.6483\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eGCW (mg%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.4949%;\"\u003e\n \u003cp\u003e0.8853\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eGWW (mg%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.4949%;\"\u003e\n \u003cp\u003e0.6235\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64.5051%;\"\u003e\n \u003cp\u003eGWE (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 35.4949%;\"\u003e\n \u003cp\u003e0.6872\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe conducted this study to assess the dynamics of systolic function in patients with HFpEF. We observed significant reduction in systolic function parameters, with average EF reduction of 7.3% over 3 years follow up. About a third of our patients with HFpEF had EF\u0026thinsp;\u0026lt;\u0026thinsp;50% during follow up of which 12% had EF\u0026thinsp;\u0026lt;\u0026thinsp;40% at the end of the study. Though HFpEF is considered as predominantly diastolic deterioration entity there are many pathophysiologic factors that determine concomitant systolic dysfunction [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Though some mechanisms of systolic disfunction has been proposed, including development of myocardial infarction, neurohormonal activation, infiltrative and inflammatory processes, the mechanism remains unclear. We excluded patients with new MI from the study, so it cannot explain EF decline in our study. Also, the Dunlay et al showed that neurohormonal modulator medication did not change the course of EF decline in patients with HFpEF [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn our study changes in EF were not affected by baseline LV dimensions, baseline EF and comorbidity index which suggests that other mechanisms than initial systolic functional status, neurohormonal activation and inflammation might be involved in the development of systolic dysfunction.\u003c/p\u003e \u003cp\u003eWe observed a decline in longitudinal, circumferential and area strain in patients with EF reduction. These parameters positively correlated with EF, but GCW was the only predictor of EF decline. The results of the study allow to predict patients with later decline in EF so start treating them more aggressively. Though Dunlay et al study did not show benefit of ACE/ARB and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\beta\\:\\:\\)\u003c/span\u003e\u003c/span\u003eblockers [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] it is unclear how these patients would respond to the newer heart failure medications such as sacubitril/valsartan and probably gain more benefits from SGLT2 inhibitors when they are still in the normal EF range compared with their counterparts with lower risk of EF deterioration. We speculate that the patients with HFpEF with increased risk of systolic function deterioration might get more benefits from HFrEF evidence-based treatment, and it can be started before EF goes down. Though data from PARAGON-HF showed that ARNI are effective in patients with HFpEF with EF up to 57% [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], in our study EF decline did not relate to baseline EF values, and patients even with higher EF and lower GCW are at risk of EF decline and probably they might benefit from ARNI. Further studies are needed to answer this question.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eHF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eHeart Failure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eHFpEF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eHeart failure with preserves ejection fraction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eHFrEF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eHeart failure with reduced ejection fraction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eEF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eEjection fraction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eDiabetes Mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eMyocardial infarction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eCAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eCoronary artery disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eEchoCG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eEchocardiography\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eASE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eAmerican Society of Echocardiography\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eEACVI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eEuropean Association of Cardiovascular Imaging\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eLS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eLongitudinal strain\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eCircumferential strain\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eRS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eRadial strain\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eAS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eArea strain\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eGWI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eGlobal work index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eGCW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eGlobal constructive work\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eGWE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eGlobal work efficiency\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eLVEDD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eLeft ventricular end-diastolic diameter\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eCOPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eChronic obstructive lung disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eEDVi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eEnd-diastolic volume index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6247%;\"\u003e\n \u003cp\u003eeGFR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83.3753%;\"\u003e\n \u003cp\u003eEstimated glomerular filtration rate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eStudy conduction has been approved by Yerevan MC Ethical Committee. All participants signed the consent.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eAll participants signed the consent for publication at the time of signing the consent to participate\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompeting interest\u003c/p\u003e\n\u003cp\u003eAuthors have nothing to declare as a conflict of interests\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThe study was funded by The RA Ministry of Education, Science, Culture and Sports Higher Education and Science Committee\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthors contributions\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAram Chilingaryan Contribute to collecting patient\u0026apos;s data, making and interpreting exams, writing papers.\u003c/p\u003e\n\u003cp\u003eHovik Balyan Contribute to writing papers.\u003c/p\u003e\n\u003cp\u003eMilena Arzumanyan Contribute to collecting patient\u0026apos;s data, making and interpreting exams, writing papers.\u003c/p\u003e\n\u003cp\u003eTsiala Ustyan and Anush Barkhudaryan Contribute to making exams.\u003c/p\u003e\n\u003cp\u003eNadezhda Iskandaryan-Contribute to collecting patient\u0026apos;s data.\u003c/p\u003e\n\u003cp\u003eArmenuhi Asatryan Contribute to interpreting exams.\u003c/p\u003e\n\u003cp\u003eHarutyun Ghrmajyan Contribute to collecting patient\u0026apos;s data.\u003c/p\u003e\n\u003cp\u003eLusine Tunyan Contribute to collecting patient\u0026apos;s data, making and interpreting exams, writing papers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAslanyan Levon for co-participating and providing programs for statistical analysis\u003c/p\u003e\n\u003cp\u003eArzumanyan Ashot for revising the document\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBozkurt B, Ahmad T, Alexander KM, Baker WL, Bosak K, Breathett K, Fonarow GC, Heidenreich P, Ho JE, Hsich E, Ibrahim NE, Jones LM, Khan SS, Khazanie P, Koelling T, Krumholz HM, Khush KK, Lee C, Morris AA, Page RL 2nd, Pandey A, Piano MR, Stehlik J, Stevenson LW, Teerlink JR, Vaduganathan M, Ziaeian B (2023) Writing Committee Members. Heart Failure Epidemiology and Outcomes Statistics: A Report of the Heart Failure Society of America. J Card Fail 29(10):1412\u0026ndash;1451. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.cardfail.2023.07.006\u003c/span\u003e\u003cspan address=\"10.1016/j.cardfail.2023.07.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003eEpub 2023 Sep 26. PMID: 37797885\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJaiswal A, Jaiswal V, Ang SP, Hanif M, Vadhera A, Agrawal V et al (2023) SGLT2 inhibitors among patients with heart failure with preserved ejection fraction: a meta-analysis of randomised controlled trials. Royal College of Surgeons in Ireland. J contribution. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://hdl.handle.net/10779/rcsi.24271234.v1\u003c/span\u003e\u003cspan address=\"https://hdl.handle.net/10779/rcsi.24271234.v1\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVaduganathan M, Docherty KF, Claggett BL, Jhund PS, de Boer RA, Hernandez AF, Inzucchi SE, Kosiborod MN, Lam CSP, Martinez F, Shah SJ, Desai AS, McMurray JJV, Solomon SD (2022) SGLT-2 inhibitors in patients with heart failure: a comprehensive meta-analysis of five randomised controlled trials. Lancet. ;400(10354):757\u0026ndash;767. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0140-6736(22)01429-5\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(22)01429-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2022 Aug 27. Erratum in: Lancet. 2023;401(10371):104. PMID: 36041474\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVaduganathan M, Claggett BL, Greene SJ et al (2021) Potential Implications of Expanded US Food and Drug Administration Labeling for Sacubitril/Valsartan in the US. JAMA Cardiol 6(12):1415\u0026ndash;1423. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jamacardio.2021.3651\u003c/span\u003e\u003cspan address=\"10.1001/jamacardio.2021.3651\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSavarese G, Vedin O, D'Amario D, Uijl A, Dahlstr\u0026ouml;m U, Rosano G, Lam CSP, Lund LH (2019) Prevalence and Prognostic Implications of Longitudinal Ejection Fraction Change in Heart Failure. JACC Heart Fail. ;7(4):306\u0026ndash;317. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jchf.2018.11.019\u003c/span\u003e\u003cspan address=\"10.1016/j.jchf.2018.11.019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2019 Mar 6. Erratum in: JACC Heart Fail. 2019;7(8):735\u0026ndash;736. Abstract corrected. PMID: 30852236\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePieske B, Tsch\u0026ouml;pe C, de Boer RA, Fraser AG, Anker SD, Donal E, Edelmann F, Fu M, Guazzi M, Lam CSP, Lancellotti P, Melenovsky V, Morris DA, Nagel E, Pieske-Kraigher E, Ponikowski P, Solomon SD, Vasan RS, Rutten FH, Voors AA, Ruschitzka F, Paulus WJ, Seferovic P, Filippatos G (2019) How to diagnose heart failure with preserved ejection fraction: the HFA-PEFF diagnostic algorithm: a consensus recommendation from the Heart Failure Association (HFA) of the European Society of Cardiology (ESC). Eur Heart J. ;40(40):3297\u0026ndash;3317. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/eurheartj/ehz641\u003c/span\u003e\u003cspan address=\"10.1093/eurheartj/ehz641\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Erratum in: Eur Heart J. 2021;42(13):1274. PMID: 31504452\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLevey AS, Coresh J, Greene T, Stevens LA, Zhang YL, Hendriksen S, Kusek JW, Van Lente F (2006) Chronic Kidney Disease Epidemiology Collaboration. Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med. ;145(4):247\u0026thinsp;\u0026ndash;\u0026thinsp;54. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.7326/0003-4819-145-4-200608150-00004\u003c/span\u003e\u003cspan address=\"10.7326/0003-4819-145-4-200608150-00004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Erratum in: Ann Intern Med. 2008;149(7):519. Erratum in: Ann Intern Med. 2021;174(4):584. PMID: 16908915\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCharlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. ;40(5):373\u0026thinsp;\u0026ndash;\u0026thinsp;83. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/0021-9681(87)90171-8\u003c/span\u003e\u003cspan address=\"10.1016/0021-9681(87)90171-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 3558716\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLang RM, Badano LP, Mor-Avi V, Afilalo J, Armstrong A, Ernande L, Flachskampf FA, Foster E, Goldstein SA, Kuznetsova T, Lancellotti P, Muraru D, Picard MH, Rietzschel ER, Rudski L, Spencer KT, Tsang W, Voigt JU (2015) Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. J Am Soc Echocardiogr. ;28(1):1\u0026ndash;39.e14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.echo.2014.10.003\u003c/span\u003e\u003cspan address=\"10.1016/j.echo.2014.10.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 25559473\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNagueh SF, Smiseth OA, Appleton CP et al (2016) Recommendations for the evaluation of left ventricular diastolic function by echocardiography: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. J Am Soc Echocardiogr 29:277\u0026ndash;314\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKraigher-Krainer E, Shah AM, Gupta DK, Santos A, Claggett B, Pieske B, Zile MR, Voors AA, Lefkowitz MP, Packer M, McMurray JJ, Solomon SD (2014) PARAMOUNT Investigators. Impaired systolic function by strain imaging in heart failure with preserved ejection fraction. J Am Coll Cardiol. ;63(5):447\u0026thinsp;\u0026ndash;\u0026thinsp;56. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jacc.2013.09.052\u003c/span\u003e\u003cspan address=\"10.1016/j.jacc.2013.09.052\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2013 Oct 30. Erratum in: J Am Coll Cardiol. 2014;64(3):335. PMID: 24184245; PMCID: PMC7195816\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDunlay SM, Roger VL, Weston SA, Jiang R, Redfield MM (2012) Longitudinal changes in ejection fraction in heart failure patients with preserved and reduced ejection fraction. Circ Heart Fail 5(6):720\u0026ndash;726. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/CIRCHEARTFAILURE.111.966366\u003c/span\u003e\u003cspan address=\"10.1161/CIRCHEARTFAILURE.111.966366\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003eEpub 2012 Aug 30. PMID: 22936826; PMCID: PMC3661289\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5268112/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5268112/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"We aimed to found predictors of EF deterioration in HFpEF patients toprevent their further deterioration.\nMethods. We studied 215 patients(63% women) 73±8 years with HFpEF and with records of Charlson index(CI), glomerular filtration rate (GFR). Myocardial work (MW), globallongitudinal (LS), radial (RS), circumferential (SS) and area strain(AS).GW index , global constructive work (GCW), wasted work, GWefficiency were obtained by echocardiography. Patients followed up for 3years.\nResults. 5 patients developed myocardial infarction and wereexcluded from the study.Baseline EF was higher in women (61,2 ± 3,1 vs56,4 ± 2,7; P\u003c0.002), in patients \u003e70 years (62,4 ± 2,1 vs 57,1 ± 2,3;p\u003c0.005), and with end-diastolic volume index \u003c60 ml/m2 (56,1 ± 3,2vs 63,4 ± 2,3; p\u003c0.001). EF decline compared to baseline was -7.3 ±1.6%, p\u003c0.01. EF decline was significantly more in patients \u003e70 years, inpatients with coronary artery disease and did not relate to sex, LV size,CI, and GFR. During follow up 58(27%) patients had EF\u003c50%.,worsening in AS (-27.9±8.5% vs -24.7±5.3%, p\u003c0.003), LS (-19.7±2.4% vs -17.1±1.6%, p\u003c0.005), and GCW (2378±117 vs2102±10, p\u003c0.002). Patients with EF \u003c50% at the end of the study hadless AS and GCWbaseline values compared with patients with EF\u003e50% (22.4±7.2% vs -27.6±8.1%,p\u003c0.002; 2081±92 vs 2489±127, p\u003c0.001). GCW was thepredictor of EF deterioration(area under curve 0,8853).\nConclusion. GCW predicts EF decline in HFpEF patients which may help earlieridentify this subset of patients and prevent their furtherdeterioration.","manuscriptTitle":"Left ventricular myocardial constructive work predicts reduction of ejection fraction in patients with heart failure with preserved ejection fraction","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-28 06:52:27","doi":"10.21203/rs.3.rs-5268112/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"026cfc2e-6cf8-4354-947d-7442d13146ff","owner":[],"postedDate":"October 28th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-25T00:53:08+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-28 06:52:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5268112","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5268112","identity":"rs-5268112","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}