Left Ventricular Ejection Fraction Reserve and Its Association with Myocardial Perfusion, Coronary Calcification, and Strain in Type 2 Diabetes Without Overt Cardiovascular Disease

Left Ventricular Ejection Fraction Reserve and Its Association with Myocardial Perfusion, Coronary Calcification, and Strain in Type 2 Diabetes Without Overt Cardiovascular Disease | 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 Ejection Fraction Reserve and Its Association with Myocardial Perfusion, Coronary Calcification, and Strain in Type 2 Diabetes Without Overt Cardiovascular Disease Adam Chebli, Ida K. B. Rasmussen, Anne-Cathrine Skriver-Møller, and 14 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6870088/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 31 Aug, 2025 Read the published version in Cardiovascular Diabetology → Version 1 posted 8 You are reading this latest preprint version Abstract Background : Type 2 diabetes (T2D) is a major risk factor for cardiovascular disease (CVD), but the relationships between myocardial function, microvascular function, and atherosclerotic burden remain underexplored in asymptomatic individuals. This study investigates the associations between left ventricular ejection fraction (LVEF)-reserve, myocardial flow reserve (MFR), perfusion defects, coronary artery calcium score (CACS), and global longitudinal strain (GLS) in individuals with T2D but without overt CVD. Methods : Cross-sectional analysis of 871 individuals with T2D without overt CVD, recruited between 2020-2023. All underwent cardiac 82-Rubidium PET/CT to assess LVEF-reserve, MFR, perfusion defects, and CACS. GLS was measured using echocardiography. Associations were examined using linear regression adjusted for cardiovascular risk factors. Results : Mean (SD) age was 64.9 (±9.0) years, diabetes duration was 13.9 (±8.4) years, and 262 (30%) were women. Higher MFR was associated with higher LVEF-reserve (β = 1.64, 95% CI: 1.18 to 2.11, p 300 had lower LVEF-reserve than those with CACS ≤ 300 (β = -1.31, 95% CI: -2.01 to -0.60, p<0.001). Presence of Perfusion defects were associated with lower LVEF-reserve (β = -1.58, 95% CI: -2.32 to -0.85, p<0.001). LVEF-reserve was not associated with GLS (p=0.28). Sensitivity analysis excluding 248 participants with perfusion defects confirmed the association between MFR and LVEF-reserve (β = 1.52 (95% CI: 1.01, 2.04), p300 were associated with lower LVEF-reserve. Underscoring a potential role of microvascular dysfunction in subclinical systolic impairment. myocardial flow microcirculation vasodilator stress myocardial perfusion imaging Figures Figure 1 Research Insights What is currently known about this topic? The LVEF-reserve reflects the heart’s ability to increase function under stress, potentially identifying early myocardial dysfunction. Myocardial flow reserve (MFR), coronary artery calcium score (CACS), global longitudinal strain (GLS) and perfusion defects are established indicators of cardiovascular function. What is the key research question? Is the LVEF-reserve associated with MFR, CACS, GLS, and perfusion defects in individuals with T2D but without overt cardiovascular disease? What is new? Lower MFR, as well as presence of CACS>300 and perfusion defects were independently associated with lower LVEF-reserve. How might this study influence clinical practice? Microvascular dysfunction may contribute to subclinical systolic impairment in high-risk individuals. Introduction Type 2 diabetes (T2D) is linked to a wide range of cardiovascular complications, which constitute the leading cause of morbidity and mortality among people with diabetes [ 1 ]. Accordingly, international diabetes and cardiology guidelines have been revised to address the integrated management of both T2D and cardiovascular disease (CVD) [ 2 , 3 ]. A critical goal in managing T2D is to assess and diagnose cardiac risk early, enabling timely interventions for those at the highest risk. With the advancement of cardiac positron emission tomography/computed tomography (PET/CT) technology, several imaging-derived markers are now available, each offering potentially complementary or overlapping insights into cardiac function. One such marker is left ventricular ejection fraction (LVEF)-reserve, a measure of the myocardial ability to increase the ejection fraction under stress compared to rest. This measurement may prove useful in identifying subtle impairments in cardiac function that are not detectable at rest, though its clinical utility is still being explored. Impaired LVEF-reserve evaluated using cardiac rubidium-82 ( 82 Rb) PET/CT has been demonstrated as a risk marker for future cardiac events in high-risk populations with known or suspected coronary artery disease (CAD), independent of classical cardiac risk factors, resting LVEF, and perfusion abnormalities assessed by cardiac PET/CT [ 4 – 7 ]. However, a standardized reference range for LVEF-reserve has not been established, and data on its association with other cardiac measures in individuals without overt CVD remain limited. The myocardial microvascular function can be examined using myocardial blood flow quantified by cardiac PET/CT. The myocardial flow reserve (MFR) is calculated as the ratio between myocardial blood flow during stress and rest. In the absence of CAD, MFR, quantified by cardiac PET/CT, is considered a reliable measure of the myocardial microvascular function [ 8 ]. Impaired MFR (< 2) is increasingly acknowledged as a reliable risk marker for CVD among people with symptoms of or known CVD, but the potential as a risk marker in asymptomatic individuals is yet to be clearly defined [ 9 , 10 ]. The association between MFR and the LVEF-reserve, as measured by cardiac 82 Rb PET/CT, remains, to the best of our knowledge, unexplored. Coronary artery calcium score (CACS) is a well-established marker of atherosclerotic burden and is used to stratify cardiovascular risk in individuals with and without T2D [ 11 , 12 ]. Higher CACS (≥ 400) is associated with increased likelihood of myocardial perfusion defects which, alongside impaired MFR, reflect functional consequences of CAD and may contribute to the development of left ventricular systolic dysfunction. [ 13 ]. Global longitudinal strain (GLS), a sensitive echocardiographic measure of ventricular systolic function, has been linked to increased cardiovascular risk in T2D, even in the absence of overt CVD [ 14 ]. As both GLS and LVEF-reserve reflect aspects of left ventricular function, their relationship may offer insights into early myocardial dysfunction. The aim of this post hoc analysis was to assess the association between the LVEF-reserve and MFR in individuals with T2D free of overt CVD. In addition, associations between the LVEF-reserve and perfusion defects, CACS and GLS were evaluated. We hypothesized that a lower LVEF-reserve is associated with lower MFR, presence of perfusion defects, higher CACS, and lower GLS, and that these associations persist after adjustment for other cardiovascular risk factors. Methods Study population: The study population for this analysis was prospectively recruited, as previously described [15]. In brief, the cohort consisted of 901 individuals with T2D but free of previous CVD and without any symptoms of CVD. Eligible individuals were identified using electronic health records and recruited via advertisements in local newspapers. Potential participants attended a screening visit at the Steno Diabetes Center Copenhagen, Zealand University Hospital, or Holbaek Hospital, Denmark. Participants were aged 40-85 years and had to be able to understand and provide informed consent. Participants between 40 and 50 years were required to have at least two cardiovascular risk factors in addition to T2D (current smoking, hypertension, dyslipidemia, or a family history of CVD). Exclusion criteria included a history of stroke, CAD, or other cardiovascular diseases; non‐diabetic kidney disease; and contraindications for cardiac 82 Rb PET/CT. Depending on the site, participants either attended three separate visits for consent, cardiac 82 Rb PET/CT, and transthoracic echocardiography, or completed both imaging procedures in a single visit after providing consent and clinical data locally [15]. Thirty individuals were excluded due to suboptimal image quality for assessment of LVEF-reserve on the cardiac 82 Rb PET/CT scan, resulting in a final sample of 871 subjects. The study was performed from January 2020 to August 2023 and conducted in accordance with the Declaration of Helsinki. All participants provided written consent, and the protocol was approved by the Danish National Committee on Health Research Ethics (H-19063311). Demography and clinical characteristics: Information on demographics, medical history, and current medical treatment was collected through structured interviews and cross-referenced with electronic medical records. Current smoking was defined as the daily use of at least one cigarette, pipe, or cigar. Height and weight were measured to calculate body mass index (BMI). Lipid profile, HbA1c, and plasma creatinine, were measured using standardized procedures immediately after each participant's visit. The estimated glomerular filtration rate (eGFR) was calculated using the CKD-EPI equation [16]. The urine albumin-to-creatinine ratio (UACR) was assessed as the geometric mean of three consecutive morning urine samples analyzed via enzyme immunoassay. Albuminuria was classified as normal (UACR: 300 mg/g). Office blood pressure was measured after five minutes of rest, with the mean of three readings recorded. 82 Rb-PET/CT imaging: After administering 1,100 MBq of 82 Rb, cardiac PET/CT imaging was obtained using a hybrid PET/CT scanner in 3D mode (Siemens Biograph mCT 128, Siemens, Munich, Germany). Scans were performed under both rest and stress conditions, with stress induced by adenosine infusion at 140 µg/kg/min for 6 minutes to achieve maximal myocardial hyperemia. Myocardial blood flow was quantified using Siemens Syngo MBF 2.3 software (Siemens Medical Solutions, Malvern, PA, USA), employing a one-compartment tracer kinetic model for 82 Rb and a non-linear extraction function developed by Lortie et al. [17]. The MFR, calculated as the ratio of stress to rest myocardial blood flow, was assessed globally across the myocardium. MFR is considered reduced when ≤2 [18]. Systolic LVEF was evaluated from ECG-gated PET data at both rest and stress, where gated images were acquired using 8-frame gating. The LVEF-reserve was calculated as the difference between stress and rest LVEF. CACS was evaluated using the method outlined by Agatston et al. [19], summing calcium scores within the three main coronary arteries, analyzed with Syngo.via software (Siemens Healthineers, Germany). CACS was categorized into two groups: > 300 and ≤ 300, in accordance with established clinical guidelines [20]. Echocardiography : All echocardiographic examinations were conducted according to a standardized research protocol by trained investigators using the GE Vingmed Ultrasound Vivid IQ (Horten, Norway). Echocardiographic analyses were performed by experienced investigators blinded to study details, utilizing post-processing analysis software (EchoPac version 206). Resting LVEF was assessed from the apical 4- and 2-chamber views using a semi-automatic tool that tracks myocardial deformation and volume changes throughout the cardiac cycle. GLS was measured using Automated Function Imaging, a novel semi-automatic speckle-tracking algorithm, incorporating apical 4-, 2-, and 3-chamber views for comprehensive strain analysis [21]. Statistical analysis: Continuous variables with a normal distribution are presented as the mean with standard deviation (SD), while those with a non-normal distribution are reported as the median with interquartile range (IQR). Categorical variables are presented as frequencies and percentages and compared between tertiles of the LVEF-reserve using the Chi-squared test. Continuous variables were compared between tertiles using either analysis of variance or the Kruskal-Wallis test, as appropriate. Associations between the LVEF-reserve and MFR, GLS, perfusion defects (reversible and irreversible), and CACS were evaluated using multiple linear regression models. Model 1 included sex and age, and Model 2 additionally included diabetes duration, BMI, LDL cholesterol, smoking, systolic blood pressure, HbA1c, eGFR, and UACR. The model fit was assessed through visual inspection of the residuals' distribution. For perfusion defects, participants with no reversible or irreversible perfusion defects ( and ≤ 300), with the latter serving as the reference group in the regression analyses. Results for MFR and GLS are presented as unstandardized and standardized beta-coefficients with 95% confidence intervals (95% CI). Supplementary analyses were performed to assess possible effects of perfusion defects in the association between MFR and the LVEF-reserve. A two-sided P -value of <0.05 was considered statistically significant. Statistical analyses were performed using the statistical software R (version 4.4.2, R Foundation for Statistical Computing, Vienna, Austria) within the RStudio environment (version 2024.12.0+467, Posit Software, PBC, Boston, MA, USA). Results Clinical characteristics: Among the 871 participants, 262 (30%) were women. The mean (SD) age was 64.9 (±9.0) years, and average duration of diabetes was 13.9 (±8.4) years. The mean LVEF-reserve in the total population was 5.3 (±4.3) %. Table 1 summarizes the clinical characteristics, stratified by the LVEF-reserve in tertiles. Participants in the highest tertile were less frequently prescribed sodium glucose transporter 2 inhibitors compared to those in tertile one and two. No other clinical characteristics differed significantly among the tertiles. Cardiac PET/CT and echocardiography measurements The MFR differed significantly across the tertiles, with higher levels in the higher tertiles (P<0.001) (Table 2). The prevalence of impaired MFR (≤2), was highest in the 1 st tertile (33%) and lowest in the 3 rd tertile (12%); P<0.001. Myocardial blood flow at rest and during stress were also different across tertiles with lower levels at rest and higher levels during stress as the tertiles increased (P<0.001). The proportion of individuals with reversible and/or irreversible perfusion defects varied among the tertiles, with a lower frequency observed in the higher tertiles. The median level of CACS also differed between tertiles, with the highest scores in the 1 st tertile and the lowest in the 3 rd tertile (P<0.001). The echocardiographic measurement of LVEF and GLS did not differ between tertiles. Associations between the LVEF-reserve and MFR and other cardiovascular measures Higher MFR was associated with higher LVEF-reserve in both Model 1 and Model 2 (table 3). Figure 1 illustrates the unadjusted association between MFR and LVEF-reserve. To assess the clinical impact of MFR on LVEF-reserve, we selected two representative MFR values: one corresponding to the 25th percentile of 2.07 (low MFR) and one corresponding to the 75th percentile of 2.9 (high MFR). This allowed us to compare the predicted LVEF-reserve for individuals with low and high MFR, as estimated by Model 1. A 60-year-old man with an MFR of 2.07 had a predicted LVEF-reserve of 4.4%. In contrast, a 60-year-old man with an MFR of 2.9 had a predicted LVEF-reserve of 5.8%. This represents an absolute difference of 1.4 percentage points, or a 32% increase in LVEF-reserve. However, the physiological or clinical significance of this difference is still not fully understood and requires further investigation including long term follow up of this cohort. There were no significant associations between the LVEF-reserve and GLS in either of the two models. Individuals with CACS > 300 had significantly lower LVEF-reserve compared to those with CACS ≤ 300 in both Model 1 and Model 2 (β = -1.31, 95% CI: -2.01 to -0.60, p < 0.001 in Model 2). Likewise, individuals with perfusion defects had significantly lower LVEF-reserve compared to those without perfusion defects in both models (β = -1.58, 95% CI: -2.31 to -0.85, p < 0.001 in Model 2). Sensitivity analyses A sensitivity analysis excluding the 248 participants with either reversible or irreversible perfusion defects did not change the association between MFR and the LVEF-reserve in model 2, however the effect size decreased: β = 1.52 (95% CI: 1.01, 2.04), p<0.001. Discussion The primary finding of this study was that higher MFR was associated with higher LVEF-reserve, even after adjustment for cardiovascular risk factors. This underscores the potential role of microvascular dysfunction in subclinical systolic impairment in individuals with T2D. The observed association is physiologically plausible, as an impaired ability to augment myocardial blood flow during stress may limit the myocardium’s capacity to increase contractile function, thereby reducing the LVEF-reserve [22]. Only one prior study has examined the association between the LVEF-reserve and MFR using cardiac 82 Rb PET/CT [23]. The study included 205 individuals with known or suspected CAD and demonstrated an association between higher MFR and higher LVEF-reserve. A larger cohort of 2,299 individuals, of whom 1,424 (62%) were without prior CAD, demonstrated that both the LVEF-reserve and MFR were significantly lower in the participants with perfusion defects identified on cardiac 82 Rb PET/CT compared to those without perfusion defects, irrespective of CAD status [24]. Although the findings offer a reference for microvascular function and cardiac performance in people without overt CAD, the study primarily focused on comparing these measures across different CAD severity groups, rather than directly analyzing their association. One prior study explored the association between the LVEF-reserve and MFR in individuals with T2D using other methods than cardiac PET [25]. The study included only 20 individuals with T2D free of clinical CVD and demonstrated a positive association between MFR and the LVEF-reserve using stress echocardiography. Although this method is considered inferior to cardiac PET/CT [18], their findings support a positive relationship between the LVEF-reserve and MFR in individuals with T2D, though direct comparability is limited. Another key finding of our study was that the LVEF-reserve was lower in participants with CACS > 300 compared to those with CACS ≤ 300, suggesting an inverse relationship between atherosclerotic burden and the LVEF-reserve. A potential physiological mechanism is that extensive coronary calcification impairs vascular function, reducing myocardial contractile response to stress [26]. While CACS provides a surrogate marker of atherosclerotic plaque burden, it does not directly evaluate ischemia. CACS indicates the degree of coronary calcification, which can lead to impaired myocardial perfusion, a reduction in MFR, and potentially a lower LVEF-reserve. Therefore, the association between CACS and LVEF-reserve may reflect an indirect pathway, where CACS affects myocardial perfusion and, consequently, LVEF-reserve. In line with previous findings in individuals with suspected CAD [6, 24, 27], we demonstrated that the LVEF-reserve was significantly lower in those with perfusion defects – even among individuals without known or suspected CAD – showing that the LVEF-reserve is inversely related to the severity of perfusion defects. No trials have explored the association between the LVEF-reserve and GLS in populations without CVD. The unexpected lack of an association between the LVEF-reserve and resting GLS in our study may be attributed by the fact that diastolic dysfunction generally precedes systolic dysfunction in the early stages of diabetic cardiomyopathy, with reduced systolic function manifesting in more advanced disease [28]. The LVEF-reserve may be impaired earlier in the progression of myocardial dysfunction, as it reflects the heart’s ability to respond to stress, while GLS may become impaired later due to myocardial strain or damage. This suggests that the LVEF-reserve and GLS capture different aspects of myocardial dysfunction at varying stages of the disease. Among all participants, 290 had a LVEF-reserve of less than 4%, and 204 had a GLS of less than 16% (considered low) [29]. Only 62 participants had both low LVEF-reserve and low GLS. However, reference values for LVEF-reserve are not well established, which limits the ability to compare and assess the clinical significance of these findings. These findings suggest that while resting GLS may be a valuable marker of systolic dysfunction in people with diabetes, it might not be as closely linked to the dynamic changes in myocardial performance observed during stress, as those captured by the LVEF-reserve. Future studies with longitudinal designs are needed to establish causality and refine risk stratification strategies in individuals with T2D. Strengths and limitations: To our knowledge, this is the largest cohort assessing the LVEF-reserve and MFR in individuals with T2D without known or suspected CVD. Another strength is the use of cardiac PET/CT, a highly reliable method for evaluating the LVEF-reserve and MFR, enabling an accurate assessment of the myocardial function during stress. The limitations include the overrepresentation of white men, which may limit the generalizability of the findings to women and other ethnic groups. Since the participants were selected to be asymptomatic and without known CVD, our findings could be subject to selection bias. However, this was required to accurately assess the role of advanced cardiac imaging in individuals with T2D free of CVD. While participants were included based on the absence of known or suspected CVD, this was determined through medical history and symptom screening, without systematic diagnostic testing to definitively rule out subclinical disease. Conclusion In individuals with T2D but without known CVD, the present study demonstrated that lower MFR, as well as presence of CACS>300 and perfusions defects were independently associated with lower LVEF-reserve as hypothesized. No significant association between GLS and the LVEF-reserve was observed. Abbreviations BMI body mass index CACS coronary artery calcium score CAD coronary artery disease CVD cardiovascular disease CI confidence interval eGFR Estimated glomerular filtration rate GLP-1 RA Glucagon-like peptide-1 receptor agonists CT computer tomography GLS global longitudinal strain HbA1c Glycated hemoglobin LDL Low-density lipoprotein LVEF left ventricular ejection fraction MFR myocardial flow reserve PET positron emission tomography RAAS Renin-angiotensin-aldosterone system Rb rubidium SD Standard deviation UACR Urine albumin creatinine ratio Declarations Ethics approval and consent to participate The study was conducted in accordance with the Declaration of Helsinki. All participants provided written consent, and the protocol was approved by the Danish National Committee on Health Research Ethics (H-19063311). Availability of data and materials The data supporting the findings of this study are available from the corresponding author upon reasonable request. Competing interest PR has received speaking fees and/or consultancy to Steno Diabetes Center Copenhagen from Eli Lilly, Novo Nordisk, Sanofi Aventis, Vifor, Boehringer Ingelheim, Astellas, Gilead, Bayer, AstraZeneca, Mundipharma, and MSD. PR has received research grants from Novo Nordisk AstraZeneca. AC, PR, TWH and RSR had shares in Novo Nordisk. AK and RSR has received consultancy fees from Novo Nordisk. EHZ is a full-time employee in Novo Nordisk and has shares in Novo Nordisk. IKR is a full-time employee at Novo Nordisk. ML: has received speaker and consultancy fees from AstraZeneca, Bayer, Boeringer Ingelheim, Novo Nordisk, GlaxoSmithKline, and is an investigator in clinical studies sponsored by Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Eli Lilly, Janssen, MSD and Novo Nordisk. JPG has served as consultant for Novo Nordisk on measurement of bioactive peptides. TBS has received research grants from Pfizer, Sanofi Pasteur, GSK, Novo Nordisk, AstraZeneca, Boston Scientific and GE Healthcare, consulting fees from Novo Nordisk, IQVIA, Parexel, Amgen, CSL Seqirus, GSK and Sanofi Pasteur, and lecture fees from Bayer, Novartis, Sanofi Pasteur, GE healthcare and GSK. The other authors declare that there is no duality of interest associated with this manuscript. Funding This study was funded by Novo Nordisk Foundation (grant number NNF19OC0054674.). Authors’ contributions AC, ACSM, IKBR, RSR, EHZ, MBB, PH, LH, AK, PR and TWH contributed to the study design and data interpretation. ACSM, IKBR, VSW, PH, ULK, ML, AKE, JPG, TBS, MCHL and RSR, acquired data. ACSM, IKBR and VSW recruited participants. AC and MBB performed statistical analysis. AC drafted the manuscript. The final manuscript was critically read, revised, and approved by all authors. TWH is the guarantor of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Acknowledgements The authors would like to thank all participants and acknowledge the work of study nurses and laboratory technicians from Steno Diabetes Center Copenhagen, Rigshospitalet, Holbaek Hospital and University Hospital Zealand, Denmark. References International Diabetes Federation. IDF Diabetes Atlas, 10th edn. Brussels Belgium: International Diabetes Federation; 2021. American Diabetes Association Professional Practice Committee. 10. Cardiovascular Disease and Risk Management: Standards of Care in Diabetes-2024. Diabetes Care. 2024;47(Suppl 1):S179–S218. doi.org/10.2337/dc24-S010. Correction to: 2023 ESC Guidelines for the management of cardiovascular disease in patients with diabetes: Developed by the task force on the management of cardiovascular disease in patients with diabetes of the European Society of Cardiology (ESC). Eur Heart J. 2024;45(7):518–518. doi.org/10.1093/eurheartj/ehad857. Thein PM, Mirzaee S, Cameron JD, Nasis A. Left ventricular contractile reserve as a determinant of adverse clinical outcomes: a systematic review. Intern Med J. 2022;52(2):186–197. doi: 10.1111/imj.14995. Dorbala S, Hachamovitch R, Curillova Z, et al. Incremental prognostic value of gated Rb-82 positron emission tomography myocardial perfusion imaging over clinical variables and rest LVEF. J Am Coll Cardiol Img. 2009;2(7):846–854. doi.org/10.1016/j.jcmg.2009.04.009. Dorbala S, Vangala D, Sampson U, et al. Value of vasodilator left ventricular ejection fraction reserve in evaluating the magnitude of myocardium at risk and the extent of angiographic coronary artery disease: A 82Rb PET/CT study. J Nucl Med. 2007;48(3):349–358. Rauf M, Hansen KW, Galatius S, et al. Prognostic implications of myocardial perfusion imaging by 82-rubidium positron emission tomography in male and female patients with angina and no perfusion defects. Eur Heart J Cardiovasc Imaging. 2023;24(2):212–222. doi.org/10.1093/ehjci/jeac217. Højstrup S, Hansen KW, Talleruphuus U, et al. Myocardial Flow Reserve, an Independent Prognostic Marker of All-Cause Mortality Assessed by 82Rb PET Myocardial Perfusion Imaging: A Danish Multicenter Study. Circ Cardiovasc Imaging. 2023;16(8):e015184. doi.org/10.1161/CIRCIMAGING.122.015184. Patel KK, Spertus JA, Chan PS, et al. Myocardial blood flow reserve assessed by positron emission tomography myocardial perfusion imaging identifies patients with a survival benefit from early revascularization. Eur Heart J. 2020;41(6):759–768. doi.org/10.1093/eurheartj/ehz389. Jensen SM, Prescott EIB, Abdulla J. The prognostic value of coronary flow reserve in patients with non-obstructive coronary artery disease and microvascular dysfunction: A systematic review and meta-analysis. Int J Cardiovasc Imaging. 2023;39(12):2545–2556. doi: 10.1007/s10554-023-02948-1. Shaw LJ, Raggi P, Schisterman E, Berman DS, Callister TQ. Prognostic value of cardiac risk factors and coronary artery calcium screening for all-cause mortality. Radiology. 2003;228(3):826–833. doi.org/10.1148/radiol.2283021006. Raggi P, Shaw LJ, Berman DS, Callister TQ. Prognostic value of coronary artery calcium screening in subjects with and without diabetes. J Am Coll Cardiol. 2004;43(9):1663–1669. doi.org/10.1016/j.jacc.2003.09.068. Patel KK, Peri-Okonny PA, Qarajeh R, et al. Prognostic Relationship Between Coronary Artery Calcium Score, Perfusion Defects, and Myocardial Blood Flow Reserve in Patients With Suspected Coronary Artery Disease. Circ Cardiovasc Imaging. 2022;15(4):e012599. doi: 10.1161/CIRCIMAGING.121.012599. Liu JH, Chen Y, Yuen M, et al. Incremental prognostic value of global longitudinal strain in patients with type 2 diabetes mellitus. Cardiovasc Diabetol. 2016;15:22. doi: 10.1186/s12933-016-0333-5. Skriver-Møller AC, Hasbak P, Rasmussen IKB, et al. Sex differences in myocardial flow reserve among individuals with type 2 diabetes: insights from the DiaHeart study. Cardiovasc Diabetol. 2025;24(1):172. doi: 10.1186/s12933-025-02717-5. Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150(9):604–612. doi: 10.7326/0003-4819-150-9-200905050-00006. Lortie M, Beanlands RS, Yoshinaga K, Klein R, Dasilva JN, DeKemp RA. Quantification of myocardial blood flow with 82Rb dynamic PET imaging. Eur J Nucl Med Mol Imaging. 2007;34(11):1765–1774. doi: 10.1007/s00259-007-0478-2. Kelshiker MA, Seligman H, Howard JP, et al. Coronary flow reserve and cardiovascular outcomes: a systematic review and meta-analysis. Eur Heart J. 2022;43(16):1582–1593. doi: 10.1093/eurheartj/ehab775. Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M Jr, Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol. 1990;15(4):827–832. doi: 10.1016/0735-1097(90)90282-t. Golub I, Termeie O, Kristo S, et al. Major global coronary artery calcium guidelines. J Am Coll Cardiol Img. 2023;16(1):98–117. doi.org/10.1016/j.jcmg.2022.06.018. Cusmà-Piccione M, Zito C, Oreto L, et al. Longitudinal strain by automated function imaging detects single-vessel coronary artery disease in patients undergoing dipyridamole stress echocardiography. J Am Soc Echocardiogr. 2015;28(10):1214–1221. doi: 10.1016/j.echo.2015.06.001. Abel RM, Reis RL. Effects of coronary blood flow and perfusion pressure on left ventricular contractility in dogs. Circ Res. 1970;27(6):961–971. doi: 10.1161/01.res.27.6.961. Van Tosh A, Votaw JR, Reichek N, Palestro CJ, Nichols KJ. The relationship between ischemia-induced left ventricular dysfunction, coronary flow reserve, and coronary steal on regadenoson stress-gated 82Rb PET myocardial perfusion imaging. J Nucl Cardiol. 2013;20(6):1060–1068. doi: 10.1007/s12350-013-9784-1. Frey SM, Honegger U, Clerc OF, et al. Left ventricular ejection fraction, myocardial blood flow and hemodynamic variables in adenosine and regadenoson vasodilator 82-Rubidium PET. J Nucl Cardiol. 2022;29(3):921–933. doi.org/10.1007/s12350-021-02729-0. Yonaha O, Matsubara T, Naruse K, et al. Effects of reduced coronary flow reserve on left ventricular function in type 2 diabetes. Diabetes Res Clin Pract. 2008;82(1):98–103. doi: 10.1016/j.diabres.2008.06.020. Wang L, Jerosch-Herold M, Jacobs DR Jr, et al. Coronary artery calcification and myocardial perfusion in asymptomatic adults: the MESA (Multi-Ethnic Study of Atherosclerosis). J Am Coll Cardiol. 2006;48(5):1018–1026. doi: 10.1016/j.jacc.2006.04.089. Hsiao E, Ali B, Blankstein R, et al. Detection of obstructive coronary artery disease using regadenoson stress and 82Rb PET/CT myocardial perfusion imaging. J Nucl Med. 2013;54(10):1748–1754. doi: 10.2967/jnumed.113.120063. Paolillo S, Marsico F, Prastaro M, et al. Diabetic cardiomyopathy: definition, diagnosis, and therapeutic implications. Heart Fail Clin. 2019;15(3):341–347. doi: 10.1016/j.hfc.2019.02.003. Nyberg J, Jakobsen EO, Østvik A, et al. Echocardiographic reference ranges of global longitudinal strain for all cardiac chambers using guideline-directed dedicated views. J Am Coll Cardiol Img. 2023;16(12):1516–1531. doi: 10.1016/j.jcmg.2023. Tables Table 1: Clinical characteristics by tertiles of the LVEF-reserve Characteristic Overall N = 871 1st tertile -22 to <4% N = 290 2nd tertile ≥4 to <7% N = 290 3rd tertile ≥7 to 23% N = 291 p-value Age (years) 64.9 ±9.0 65.5 ±8.9 65.1 ±8.9 64.1 ±9.1 0.20 Men, n (%) 609 (70) 205 (71) 197 (68) 207 (71) 0.70 Known duration of diabetes (years) 13.7 ±8.4 14.2 ±8.6 13.6 ±8.1 13.2 ±8.5 0.30 Body mass index (kg/m 2 ) 30.2 ±5.5 29.8 ±5.5 30.3 ±5.7 30.4 ±5.2 0.30 Systolic blood pressure (mmHg) 139 ±15.8 140 ±15.9 137 ±16.5 138 ±15.0 0.10 HbA1c (mmol/mol) 55.7 ±12.9 56.7 ±13.0 54.7 ±13.2 55.5 ±12.5 0.20 LDL cholesterol (mmol/l) 1.7 ±0.8 1.7 ±0.7 1.8 ±0.8 1.7 ±0.8 0.082 eGFR (ml/min/1.73m 2 ) 84.1 ±20.3 84.9 ±21.1 84.4 ±19.7 82.9 ±20.0 0.50 Urine Albumin-to-Creatinine Ratio (mg/g) 7.0 (5.0 - 21.5) 8.0 (5.0 - 26.0) 8.0 (5.0 - 23.0) 7.0 (5.0 - 17.0) >0.90 Historic albuminuria * , n (%) 0.070 Normal 564 (65) 180 (62) 179 (62) 205 (70) Moderately increased 215 (25) 76 (26) 79 (27) 60 (21) Severely increased 69 (7.9) 30 (10) 22 (7.6) 17 (5.8) Current smoker, n (%) 105 (12) 39 (13) 34 (12) 32 (11) 0.13 Medical treatment Lipid-lowering, n (%) 702 (81) 233 (80) 239 (83) 230 (79) 0.50 Antihypertensive drugs, n (%) 660 (76) 229 (79) 215 (74) 216 (74) 0.30 RAAS-blockade, n (%) 589 (68) 205 (71) 195 (67) 189 (65) 0.30 Betablockers, n (%) 147 (17) 54 (19) 55 (19) 38 (13) 0.10 Acetylsalicylic acid, n (%) 259 (30) 89 (31) 85 (29) 85 (29) >0.90 Metformin, n (%) 704 (81) 234 (81) 236 (81) 234 (80) >0.90 Insulin, n (%) 355 (41) 124 (43) 112 (39) 119 (41) 0.60 SGLT-2i, n (%) 398 (46) 148 (51) 138 (48) 112 (38) 0.007 GLP-1 RA, n (%) 439 (50) 153 (53) 146 (50) 140 (48) 0.50 Both SGLT2 and GLP-1 † , n (%) 244 (28) 90 (31) 82 (28) 72 (25) 0.20 Data are expressed as mean ±SD, median (interquartile range) or number (%) as appropriate. For each variable, the percentage of missing data is expressed if it exceeds 5%. * Albuminuria: Normal: UACR 300 mg/g. † Participants receiving both medications are also included in the sum of each medication separately. eGFR: estimated glomerular filtration rate. GLP-1 RA: glucagon-like peptide-1 receptor agonist. HbA1c: glycosylated hemoglobin. LVEF: left ventricular ejection fraction. RAAS: renin-angiotensin-aldosterone system. SGLT-2i: sodium glucose transporter 2 inhibitor. Table 2: Cardiac PET/CT and echocardiography measurements stratified by tertiles of the LVEF-reserve. Characteristic Overall N = 871 1st tertile -22 to <4% N = 290 2nd tertile ≥4 to <7% N = 290 3rd tertile ≥7 to 23% N = 291 p-value LVEF-reserve (%) 5.3 ±4.3 0.7 ±2.9 5.4 ±1.1 9.8 ±2.3 <0.001 MFR 2.55 ±0.73 2.33 ±0.67 2.58 ±0.71 2.75 ±0.74 <0.001 MFR ≤ 2, n (%) 190 (22) 96 (33) 56 (19) 38 (13) <0.001 MBF stress 2.93 ±0.71 2.84 ±0.82 2.91 ±0.68 3.03 ±0.61 0.015 MBF rest 1.21 ±0.34 1.27 ±0.36 1.19 ±0.33 1.17 ±0.33 <0.001 CACS 137 (12, 599) 206 (27, 811) 136 (17, 594) 76 (1, 403) 300, n (%) 336 (39) 131 (45) 91 (31) 114 (39) 0.027 LVEF at stress (%) 72 ±8 70 ±10 72 ±8 73 ±7 <0.001 LVEF at rest (%) 66 ±8 69 ±9 67 ±8 64 ±7 <0.001 LVEF from echocardiogram (%) 55 ±6 56 ±6 55 ±5 55 ±6 0.11 GLS from echocardiogram (%) 16.3 ±2.6 16.3 ±2.7 16.4 ±2.8 16.3 ±2.4 0.80 Reversible perfusion defect (≥5%), n (%) 229 (26) 92 (32) 75 (26) 62 (21) 0.015 Reversible perfusion defect, (extent%) * 7.0 (5.0, 11.0) 7.0 (6.0, 13.5) 7.0 (5.0, 10.0) 6.0 (5.0, 9.0) 0.008 Irreversible perfusion defect (≥5%), n (%) 19 (2) 12 (4) 5 (2) 2 (1) 0.023 Irreversible perfusion defect, (extent%) † 6.0 (5.0, 8.0) 6.5 (5.0, 9.0) 6.0 (5.0, 6.0) 6.5 (5.0, 8.0) 0.70 Data are expressed as mean ±SD, median (interquartile range) or number (%) as appropriate. * Calculated among the participants with a reversible perfusion defect. † Calculated among the participants with an irreversible perfusion defect. P values were calculated using one-way analysis of means (not assuming equal variances); or the Chi-squared test. CACS: Coronary artery calcium score, GLS: Global Longitudinal Strain, LVEF: Left ventricular ejection fraction, MBF: Myocardial blood flow, MFR: Myocardial flow reserve. Table 3: Associations between the LVEF-reserve and measures of cardiovascular function Model 1 Model 2 Variable Beta 95 % CI p-value Std. beta Beta 95 % CI p-value Std. beta Myocardial flow reserve 1.61 1.22, 2.01 <0.001 1.18 1.64 1.18, 2.11 300 * -1.35 -1.97, -0.73 <0.001 -1.31 -2.01, -0.60 <0.001 Perfusion defects † -1.34 -1.99, -0.70 <0.001 -1.58 -2.32, -0.85 <0.001 Beta coefficients with 95% confidence intervals (CI) and standardized beta coefficients (for continuous variables) calculated using multiple linear regression. * Participants with CACS ≤ 300 served as reference group. † Participants without reversible and irreversible perfusion defects served as reference group. Model 1 is adjusted for sex and age. Model 2 is additionally adjusted for diabetes duration, BMI, LDL cholesterol, current smoking, systolic blood pressure, HbA1c, eGFR, and UACR. CACS: Coronary artery calcium score. LVEF: Left ventricular ejection fraction Additional Declarations Competing interest reported. PR has received speaking fees and/or consultancy to Steno Diabetes Center Copenhagen from Eli Lilly, Novo Nordisk, Sanofi Aventis, Vifor, Boehringer Ingelheim, Astellas, Gilead, Bayer, AstraZeneca, Mundipharma, and MSD. PR has received research grants from Novo Nordisk AstraZeneca. AC, PR, TWH and RSR had shares in Novo Nordisk. AK and RSR has received consultancy fees from Novo Nordisk. EHZ is a full-time employee in Novo Nordisk and has shares in Novo Nordisk. IKR is a full-time employee at Novo Nordisk. ML: has received speaker and consultancy fees from AstraZeneca, Bayer, Boeringer Ingelheim, Novo Nordisk, GlaxoSmithKline, and is an investigator in clinical studies sponsored by Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Eli Lilly, Janssen, MSD and Novo Nordisk. JPG has served as consultant for Novo Nordisk on measurement of bioactive peptides. TBS has received research grants from Pfizer, Sanofi Pasteur, GSK, Novo Nordisk, AstraZeneca, Boston Scientific and GE Healthcare, consulting fees from Novo Nordisk, IQVIA, Parexel, Amgen, CSL Seqirus, GSK and Sanofi Pasteur, and lecture fees from Bayer, Novartis, Sanofi Pasteur, GE healthcare and GSK. The other authors declare that there is no duality of interest associated with this manuscript. Supplementary Files Graphicalabstract.docx Cite Share Download PDF Status: Published Journal Publication published 31 Aug, 2025 Read the published version in Cardiovascular Diabetology → Version 1 posted Editorial decision: Revision requested 22 Jul, 2025 Reviews received at journal 11 Jul, 2025 Reviewers agreed at journal 01 Jul, 2025 Reviewers agreed at journal 12 Jun, 2025 Reviewers invited by journal 12 Jun, 2025 Editor assigned by journal 11 Jun, 2025 Submission checks completed at journal 11 Jun, 2025 First submitted to journal 11 Jun, 2025 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. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6870088","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":470546933,"identity":"5ecabf10-f7b6-4662-84a3-7bb07c146339","order_by":0,"name":"Adam Chebli","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIiWNgGAWjYFCCBAYGxgaGBD5mxoYDHxtAIoyNB4jSwsbM3HhwZgODBIhLpBYG9ubDvGAtDAx4tfC3Jz/d8HOHTR4bO2PDYdsdNnW67YeBttTYROPSInHmmdnN3jNpxWxAvxzOPZMmYXYmEajlWFpuAy49NxLMbjO2HU5sA2tpOyxhdgCoBcTGpUX+Rvo3oJb/EC2WIC3nH+LXYnAjB2TLAYgWRpCWGwRsMTzzpuxmb1sy2C8He9vSJLfdANqSgMcvcsfTt9342WaXx89//PGHn202/Gbn0x8++FBjg9v72EECacpHwSgYBaNgFKABALpTavXSeS+nAAAAAElFTkSuQmCC","orcid":"","institution":"Steno Diabetes Center Copenhagen","correspondingAuthor":true,"prefix":"","firstName":"Adam","middleName":"","lastName":"Chebli","suffix":""},{"id":470546934,"identity":"689df25e-fc04-43f3-b496-f029f4bbdc8b","order_by":1,"name":"Ida K. B. Rasmussen","email":"","orcid":"","institution":"Steno Diabetes Center Copenhagen","correspondingAuthor":false,"prefix":"","firstName":"Ida","middleName":"K. B.","lastName":"Rasmussen","suffix":""},{"id":470546935,"identity":"90cc2a10-06db-4617-8c8a-9718fc7d718c","order_by":2,"name":"Anne-Cathrine Skriver-Møller","email":"","orcid":"","institution":"Steno Diabetes Center Copenhagen","correspondingAuthor":false,"prefix":"","firstName":"Anne-Cathrine","middleName":"","lastName":"Skriver-Møller","suffix":""},{"id":470546936,"identity":"79cae2a7-38e6-4360-920f-34f58f198b73","order_by":3,"name":"Philip Hasbak","email":"","orcid":"","institution":"Rigshospitalet","correspondingAuthor":false,"prefix":"","firstName":"Philip","middleName":"","lastName":"Hasbak","suffix":""},{"id":470546937,"identity":"6bcf92db-608b-4f25-93e7-cb70a82112f5","order_by":4,"name":"Martin B. Blond","email":"","orcid":"","institution":"Steno Diabetes Center Copenhagen","correspondingAuthor":false,"prefix":"","firstName":"Martin","middleName":"B.","lastName":"Blond","suffix":""},{"id":470546938,"identity":"ef1f9d99-62c1-4293-84fd-567b939f66d6","order_by":5,"name":"Victor S. Wasehuus","email":"","orcid":"","institution":"Steno Diabetes Center Copenhagen","correspondingAuthor":false,"prefix":"","firstName":"Victor","middleName":"S.","lastName":"Wasehuus","suffix":""},{"id":470546939,"identity":"c9e45c6b-fe75-4069-8044-4fc8e3efe0fa","order_by":6,"name":"Mats C. H. Lassen","email":"","orcid":"","institution":"Herlev and Gentofte Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mats","middleName":"C. H.","lastName":"Lassen","suffix":""},{"id":470546940,"identity":"e01348f1-9874-443b-a1f9-ef4043de2186","order_by":7,"name":"Morten Lindhardt","email":"","orcid":"","institution":"Holbæk Sygehus","correspondingAuthor":false,"prefix":"","firstName":"Morten","middleName":"","lastName":"Lindhardt","suffix":""},{"id":470546941,"identity":"b5223e76-32ec-4247-ba4f-4c48c717d573","order_by":8,"name":"Allan Kofoed-Enevoldsen","email":"","orcid":"","institution":"Zealand University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Allan","middleName":"","lastName":"Kofoed-Enevoldsen","suffix":""},{"id":470546942,"identity":"d3080e19-d1e5-40b7-b1bf-9e7eafe1441a","order_by":9,"name":"Urd L. Kielgast","email":"","orcid":"","institution":"Zealand University Hospital Køge","correspondingAuthor":false,"prefix":"","firstName":"Urd","middleName":"L.","lastName":"Kielgast","suffix":""},{"id":470546943,"identity":"434c3b1b-9ab0-4df6-9f70-5644a5b43d49","order_by":10,"name":"Emilie H. Zobel","email":"","orcid":"","institution":"Steno Diabetes Center Copenhagen","correspondingAuthor":false,"prefix":"","firstName":"Emilie","middleName":"H.","lastName":"Zobel","suffix":""},{"id":470546944,"identity":"20699f46-a018-424b-a362-11eaca3b5e6b","order_by":11,"name":"Lene Holmvang","email":"","orcid":"","institution":"University of Copenhagen","correspondingAuthor":false,"prefix":"","firstName":"Lene","middleName":"","lastName":"Holmvang","suffix":""},{"id":470546945,"identity":"38cfe7a6-966f-4e44-a17d-16b4b373bb46","order_by":12,"name":"Tor Biering-Sørensen","email":"","orcid":"","institution":"Steno Diabetes Center Copenhagen","correspondingAuthor":false,"prefix":"","firstName":"Tor","middleName":"","lastName":"Biering-Sørensen","suffix":""},{"id":470546946,"identity":"a543e96d-83ae-4608-990e-764f8eb06ffd","order_by":13,"name":"Peter Rossing","email":"","orcid":"","institution":"Steno Diabetes Center Copenhagen","correspondingAuthor":false,"prefix":"","firstName":"Peter","middleName":"","lastName":"Rossing","suffix":""},{"id":470546947,"identity":"c31f94bf-6727-404f-84f8-2acca05c0910","order_by":14,"name":"Rasmus S. Ripa","email":"","orcid":"","institution":"Bispebjerg Hospital","correspondingAuthor":false,"prefix":"","firstName":"Rasmus","middleName":"S.","lastName":"Ripa","suffix":""},{"id":470546948,"identity":"9173ecec-2f6f-447a-8cd5-a6fc9461f358","order_by":15,"name":"Andreas Kjaer","email":"","orcid":"","institution":"University of Copenhagen","correspondingAuthor":false,"prefix":"","firstName":"Andreas","middleName":"","lastName":"Kjaer","suffix":""},{"id":470546949,"identity":"487f5979-bd2e-4382-a556-e04084a63601","order_by":16,"name":"Tine W. Hansen","email":"","orcid":"","institution":"Steno Diabetes Center Copenhagen","correspondingAuthor":false,"prefix":"","firstName":"Tine","middleName":"W.","lastName":"Hansen","suffix":""}],"badges":[],"createdAt":"2025-06-11 09:23:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6870088/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6870088/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12933-025-02886-3","type":"published","date":"2025-08-31T15:56:57+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":84819254,"identity":"051e60bf-13e3-4092-ae0f-9bb47a922c45","added_by":"auto","created_at":"2025-06-17 15:58:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":127282,"visible":true,"origin":"","legend":"\u003cp\u003eUnadjusted association between myocardial flow reserve and the LVEF-reserve.\u003c/p\u003e\n\u003cp\u003eFigure 1 Scatter plot of the unadjusted association between myocardial flow reserve and left ventricular ejection fraction reserve. The regression line represents the positive association, and the shaded area around the line indicates the 95% confidence interval. Two outliers (LVEF-reserve values of -22 and 23%) were removed for improved visualization. LVEF: Left Ventricular Ejection Fraction.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6870088/v1/28ae8297e0b41db0734d54ed.png"},{"id":90344819,"identity":"2d392c83-3eb8-4dd4-915e-97039519ce8c","added_by":"auto","created_at":"2025-09-01 16:04:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1615865,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6870088/v1/77114357-b4cb-4ca7-9fac-046a0a820738.pdf"},{"id":84820109,"identity":"637d32cd-01a4-4b92-b61a-ff9020b715d6","added_by":"auto","created_at":"2025-06-17 16:06:36","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":81027,"visible":true,"origin":"","legend":"","description":"","filename":"Graphicalabstract.docx","url":"https://assets-eu.researchsquare.com/files/rs-6870088/v1/9462497d0829f4d8e6c050a9.docx"}],"financialInterests":"Competing interest reported. PR has received speaking fees and/or consultancy to Steno Diabetes Center Copenhagen from Eli Lilly, Novo Nordisk, Sanofi Aventis, Vifor, Boehringer Ingelheim, Astellas, Gilead, Bayer, AstraZeneca, Mundipharma, and MSD. PR has received research grants from Novo Nordisk AstraZeneca. AC, PR, TWH and RSR had shares in Novo Nordisk. AK and RSR has received consultancy fees from Novo Nordisk. EHZ is a full-time employee in Novo Nordisk and has shares in Novo Nordisk. IKR is a full-time employee at Novo Nordisk. ML: has received speaker and consultancy fees from AstraZeneca, Bayer, Boeringer Ingelheim, Novo Nordisk, GlaxoSmithKline, and is an investigator in clinical studies sponsored by Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Eli Lilly, Janssen, MSD and Novo Nordisk. JPG has served as consultant for Novo Nordisk on measurement of bioactive peptides. TBS has received research grants from Pfizer, Sanofi Pasteur, GSK, Novo Nordisk, AstraZeneca, Boston Scientific and GE Healthcare, consulting fees from Novo Nordisk, IQVIA, Parexel, Amgen, CSL Seqirus, GSK and Sanofi Pasteur, and lecture fees from Bayer, Novartis, Sanofi Pasteur, GE healthcare and GSK. The other authors declare that there is no duality of interest associated with this manuscript.","formattedTitle":"Left Ventricular Ejection Fraction Reserve and Its Association with Myocardial Perfusion, Coronary Calcification, and Strain in Type 2 Diabetes Without Overt Cardiovascular Disease","fulltext":[{"header":"Research Insights","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 642px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWhat is currently known about this topic?\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe LVEF-reserve reflects the heart\u0026rsquo;s ability to increase function under stress, potentially identifying early myocardial dysfunction.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMyocardial flow reserve (MFR), coronary artery calcium score (CACS), global longitudinal strain (GLS) and perfusion defects are established indicators of cardiovascular function.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 642px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWhat is the key research question?\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eIs the LVEF-reserve associated with MFR, CACS, GLS, and perfusion defects in individuals with T2D but without overt cardiovascular disease?\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 642px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWhat is new?\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eLower MFR, as well as presence of CACS\u0026gt;300 and perfusion defects were independently associated with lower LVEF-reserve.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 642px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHow might this study influence clinical practice?\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMicrovascular dysfunction may contribute to subclinical systolic impairment in high-risk individuals.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Introduction","content":"\u003cp\u003eType 2 diabetes (T2D) is linked to a wide range of cardiovascular complications, which constitute the leading cause of morbidity and mortality among people with diabetes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Accordingly, international diabetes and cardiology guidelines have been revised to address the integrated management of both T2D and cardiovascular disease (CVD) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. A critical goal in managing T2D is to assess and diagnose cardiac risk early, enabling timely interventions for those at the highest risk.\u003c/p\u003e \u003cp\u003eWith the advancement of cardiac positron emission tomography/computed tomography (PET/CT) technology, several imaging-derived markers are now available, each offering potentially complementary or overlapping insights into cardiac function. One such marker is left ventricular ejection fraction (LVEF)-reserve, a measure of the myocardial ability to increase the ejection fraction under stress compared to rest. This measurement may prove useful in identifying subtle impairments in cardiac function that are not detectable at rest, though its clinical utility is still being explored. Impaired LVEF-reserve evaluated using cardiac rubidium-82 (\u003csup\u003e82\u003c/sup\u003eRb) PET/CT has been demonstrated as a risk marker for future cardiac events in high-risk populations with known or suspected coronary artery disease (CAD), independent of classical cardiac risk factors, resting LVEF, and perfusion abnormalities assessed by cardiac PET/CT [\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, a standardized reference range for LVEF-reserve has not been established, and data on its association with other cardiac measures in individuals without overt CVD remain limited.\u003c/p\u003e \u003cp\u003eThe myocardial microvascular function can be examined using myocardial blood flow quantified by cardiac PET/CT. The myocardial flow reserve (MFR) is calculated as the ratio between myocardial blood flow during stress and rest. In the absence of CAD, MFR, quantified by cardiac PET/CT, is considered a reliable measure of the myocardial microvascular function [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Impaired MFR (\u0026lt;\u0026thinsp;2) is increasingly acknowledged as a reliable risk marker for CVD among people with symptoms of or known CVD, but the potential as a risk marker in asymptomatic individuals is yet to be clearly defined [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The association between MFR and the LVEF-reserve, as measured by cardiac \u003csup\u003e82\u003c/sup\u003eRb PET/CT, remains, to the best of our knowledge, unexplored.\u003c/p\u003e \u003cp\u003eCoronary artery calcium score (CACS) is a well-established marker of atherosclerotic burden and is used to stratify cardiovascular risk in individuals with and without T2D [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Higher CACS (\u0026ge;\u0026thinsp;400) is associated with increased likelihood of myocardial perfusion defects which, alongside impaired MFR, reflect functional consequences of CAD and may contribute to the development of left ventricular systolic dysfunction. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Global longitudinal strain (GLS), a sensitive echocardiographic measure of ventricular systolic function, has been linked to increased cardiovascular risk in T2D, even in the absence of overt CVD [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. As both GLS and LVEF-reserve reflect aspects of left ventricular function, their relationship may offer insights into early myocardial dysfunction.\u003c/p\u003e \u003cp\u003eThe aim of this post hoc analysis was to assess the association between the LVEF-reserve and MFR in individuals with T2D free of overt CVD. In addition, associations between the LVEF-reserve and perfusion defects, CACS and GLS were evaluated.\u003c/p\u003e \u003cp\u003eWe hypothesized that a lower LVEF-reserve is associated with lower MFR, presence of perfusion defects, higher CACS, and lower GLS, and that these associations persist after adjustment for other cardiovascular risk factors.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003e\u003cstrong\u003eStudy population:\u0026nbsp;\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe study population for this analysis was prospectively recruited, as previously described [15]. In brief, the cohort consisted of 901 individuals with T2D but free of previous CVD and without any symptoms of CVD.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eEligible individuals were identified using electronic health records and recruited via advertisements in local newspapers. Potential participants attended a screening visit at the Steno Diabetes Center Copenhagen, Zealand University Hospital, or Holbaek Hospital, Denmark. Participants were aged 40-85 years and had to be able to understand and provide informed consent. Participants between 40 and 50 years were required to have at least two cardiovascular risk factors in addition to T2D (current smoking, hypertension, dyslipidemia, or a family history of CVD). Exclusion criteria included a history of stroke, CAD, or other cardiovascular diseases; non‐diabetic kidney disease; and contraindications for cardiac \u003csup\u003e82\u003c/sup\u003eRb PET/CT. Depending on the site, participants either attended three separate visits for consent, cardiac \u003csup\u003e82\u003c/sup\u003eRb PET/CT, and transthoracic echocardiography, or completed both imaging procedures in a single visit after providing consent and clinical data locally [15].\u003c/p\u003e\n\u003cp\u003eThirty individuals were excluded due to suboptimal image quality for assessment of LVEF-reserve on the cardiac \u003csup\u003e82\u003c/sup\u003eRb PET/CT scan, resulting in a final sample of 871 subjects. The study was performed from January 2020 to August 2023 and conducted in accordance with the Declaration of Helsinki. All participants provided written consent, and the protocol was approved by the Danish National Committee on Health Research Ethics (H-19063311).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eDemography and clinical characteristics:\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eInformation on demographics, medical history, and current medical treatment was collected through structured interviews and cross-referenced with electronic medical records. Current smoking was defined as the daily use of at least one cigarette, pipe, or cigar. Height and weight were measured to calculate body mass index (BMI). Lipid profile, HbA1c, and plasma creatinine, were measured using standardized procedures immediately after each participant\u0026apos;s visit.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe estimated glomerular filtration rate (eGFR) was calculated using the CKD-EPI equation [16]. The urine albumin-to-creatinine ratio (UACR) was assessed as the geometric mean of three consecutive morning urine samples analyzed via enzyme immunoassay. Albuminuria was classified as normal (UACR: \u0026lt; 30 mg/g), moderately increased (UACR: 30\u0026ndash;300 mg/g) or severely increased (UACR \u0026gt;300 mg/g). Office blood pressure was measured after five minutes of rest, with the mean of three readings recorded.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003e\u003csup\u003e82\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003eRb-PET/CT imaging:\u0026nbsp;\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eAfter administering 1,100 MBq of \u003csup\u003e82\u003c/sup\u003eRb, cardiac PET/CT imaging was obtained using a hybrid PET/CT scanner in 3D mode (Siemens Biograph mCT 128, Siemens, Munich, Germany). Scans were performed under both rest and stress conditions, with stress induced by adenosine infusion at 140 \u0026micro;g/kg/min for 6 minutes to achieve maximal myocardial hyperemia.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMyocardial blood flow was quantified using Siemens Syngo MBF 2.3 software (Siemens Medical Solutions, Malvern, PA, USA), employing a one-compartment tracer kinetic model for \u003csup\u003e82\u003c/sup\u003eRb and a non-linear extraction function developed by Lortie et al. [17]. The MFR, calculated as the ratio of stress to rest myocardial blood flow, was assessed globally across the myocardium. MFR is considered reduced when \u0026le;2 [18].\u003c/p\u003e\n\u003cp\u003eSystolic LVEF was evaluated from ECG-gated PET data at both rest and stress, where gated images were acquired using 8-frame gating. The LVEF-reserve was calculated as the difference between stress and rest LVEF. CACS was evaluated using the method outlined by Agatston et al. [19], summing calcium scores within the three main coronary arteries, analyzed with Syngo.via software (Siemens Healthineers, Germany). CACS was categorized into two groups: \u0026gt; 300 and \u0026le; 300, in accordance with established clinical guidelines [20].\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eEchocardiography\u003c/strong\u003e:\u003c/h2\u003e\n\u003cp\u003eAll echocardiographic examinations were conducted according to a standardized research protocol by trained investigators using the GE Vingmed Ultrasound Vivid IQ (Horten, Norway). Echocardiographic analyses were performed by experienced investigators blinded to study details, utilizing post-processing analysis software (EchoPac version 206).\u003c/p\u003e\n\u003cp\u003eResting LVEF was assessed from the apical 4- and 2-chamber views using a semi-automatic tool that tracks myocardial deformation and volume changes throughout the cardiac cycle. GLS was measured using Automated Function Imaging, a novel semi-automatic speckle-tracking algorithm, incorporating apical 4-, 2-, and 3-chamber views for comprehensive strain analysis [21].\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eStatistical analysis:\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eContinuous variables with a normal distribution are presented as the mean with standard deviation (SD), while those with a non-normal distribution are reported as the median with interquartile range (IQR). Categorical variables are presented as frequencies and percentages and compared between tertiles of the LVEF-reserve using the Chi-squared test. Continuous variables were compared between tertiles using either analysis of variance or the Kruskal-Wallis test, as appropriate.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAssociations between the LVEF-reserve and MFR, GLS, perfusion defects (reversible and irreversible), and CACS were evaluated using multiple linear regression models. Model 1 included sex and age, and Model 2 additionally included diabetes duration, BMI, LDL cholesterol, smoking, systolic blood pressure, HbA1c, eGFR, and UACR. The model fit was assessed through visual inspection of the residuals\u0026apos; distribution.\u003c/p\u003e\n\u003cp\u003eFor perfusion defects, participants with no reversible or irreversible perfusion defects (\u0026lt;5%) served as the reference group in the regression analyses. Similarly, CACS was analyzed in the two groups (\u0026gt; and \u0026le; 300), with the latter serving as the reference group in the regression analyses.\u003c/p\u003e\n\u003cp\u003eResults for MFR and GLS are presented as unstandardized and standardized beta-coefficients with 95% confidence intervals (95% CI). Supplementary analyses were performed to assess possible effects of perfusion defects in the association between MFR and the LVEF-reserve.\u003c/p\u003e\n\u003cp\u003eA two-sided \u003cem\u003eP\u003c/em\u003e-value of \u0026lt;0.05 was considered statistically significant. Statistical analyses were performed using the statistical software R (version 4.4.2, R Foundation for Statistical Computing, Vienna, Austria) within the RStudio environment (version 2024.12.0+467, Posit Software, PBC, Boston, MA, USA).\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003e\u003cstrong\u003eClinical characteristics:\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eAmong the 871 participants, 262 (30%) were women. The mean (SD) age was 64.9 (\u0026plusmn;9.0) years, and average duration of diabetes was 13.9 (\u0026plusmn;8.4) years. The mean LVEF-reserve in the total population was 5.3 (\u0026plusmn;4.3) %. Table 1 summarizes the clinical characteristics, stratified by the LVEF-reserve in tertiles. Participants in the highest tertile were less frequently prescribed sodium glucose transporter 2 inhibitors compared to those in tertile one and two. No other clinical characteristics differed significantly among the tertiles.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eCardiac PET/CT and echocardiography measurements\u0026nbsp;\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe MFR differed significantly across the tertiles, with higher levels in the higher tertiles (P\u0026lt;0.001) (Table 2). The prevalence of impaired MFR (\u0026le;2), was highest in the 1\u003csup\u003est\u003c/sup\u003e tertile (33%) and lowest in the 3\u003csup\u003erd\u003c/sup\u003e tertile (12%); P\u0026lt;0.001.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMyocardial blood flow at rest and during stress were also different across tertiles with lower levels at rest and higher levels during stress as the tertiles increased (P\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003eThe proportion of individuals with reversible and/or irreversible perfusion defects varied among the tertiles, with a lower frequency observed in the higher tertiles.\u003c/p\u003e\n\u003cp\u003eThe median level of CACS also differed between tertiles, with the highest scores in the 1\u003csup\u003est\u003c/sup\u003e tertile and the lowest in the 3\u003csup\u003erd\u003c/sup\u003e tertile (P\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003eThe echocardiographic measurement of LVEF and GLS did not differ between tertiles.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eAssociations between the LVEF-reserve and MFR and other cardiovascular measures\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eHigher MFR was associated with higher LVEF-reserve in both Model 1 and Model 2 (table 3). Figure 1 illustrates the unadjusted association between MFR and LVEF-reserve.\u003c/p\u003e\n\u003cp\u003eTo assess the clinical impact of MFR on LVEF-reserve, we selected two representative MFR values: one corresponding to the 25th percentile of 2.07 (low MFR) and one corresponding to the 75th percentile of 2.9 (high MFR). This allowed us to compare the predicted LVEF-reserve for individuals with low and high MFR, as estimated by Model 1. A 60-year-old man with an MFR of 2.07 had a predicted LVEF-reserve of 4.4%. In contrast, a 60-year-old man with an MFR of 2.9 had a predicted LVEF-reserve of 5.8%. This represents an absolute difference of 1.4 percentage points, or a 32% increase in LVEF-reserve. However, the physiological or clinical significance of this difference is still not fully understood and requires further investigation including long term follow up of this cohort.\u003c/p\u003e\n\u003cp\u003eThere were no significant associations between the LVEF-reserve and GLS in either of the two models. Individuals with CACS \u0026gt; 300 had significantly lower LVEF-reserve compared to those with CACS \u0026le; 300 in both Model 1 and Model 2 (\u0026beta; = -1.31, 95% CI: -2.01 to -0.60, p \u0026lt; 0.001 in Model 2). Likewise, individuals with perfusion defects had significantly lower LVEF-reserve compared to those without perfusion defects in both models (\u0026beta; = -1.58, 95% CI: -2.31 to -0.85, p \u0026lt; 0.001 in Model 2).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eSensitivity analyses\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eA sensitivity analysis excluding the 248 participants with either reversible or irreversible perfusion defects did not change the association between MFR and the LVEF-reserve in model 2, however the effect size decreased: \u0026beta; = 1.52 (95% CI: 1.01, 2.04), p\u0026lt;0.001.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe primary finding of this study was that higher MFR was associated with higher LVEF-reserve, even after adjustment for cardiovascular risk factors. This underscores the potential role of microvascular dysfunction in subclinical systolic impairment in individuals with T2D.\u0026nbsp;The observed association is physiologically plausible, as an impaired ability to augment myocardial blood flow during stress may limit the myocardium\u0026rsquo;s capacity to increase contractile function, thereby reducing the LVEF-reserve [22].\u003c/p\u003e\n\u003cp\u003eOnly one prior study has examined the association between the LVEF-reserve and MFR using cardiac \u003csup\u003e82\u003c/sup\u003eRb PET/CT [23]. The study included 205 individuals with known or suspected CAD and demonstrated an association between higher MFR and higher LVEF-reserve.\u003c/p\u003e\n\u003cp\u003eA larger cohort of 2,299 individuals, of whom 1,424 (62%) were without prior CAD, demonstrated that both the LVEF-reserve and MFR were significantly lower in the participants with perfusion defects identified on cardiac \u003csup\u003e82\u003c/sup\u003eRb PET/CT compared to those without perfusion defects, irrespective of CAD status [24]. Although the findings offer a reference for microvascular function and cardiac performance in people without overt CAD, the study primarily focused on comparing these measures across different CAD severity groups, rather than directly analyzing their association.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOne prior study explored the association between the LVEF-reserve and MFR in individuals with T2D using other methods than cardiac PET [25]. The study included only 20 individuals with T2D free of clinical CVD and demonstrated a positive association between MFR and the LVEF-reserve using stress echocardiography. Although this method is considered inferior to cardiac PET/CT [18], their findings support a positive relationship between the LVEF-reserve and MFR in individuals with T2D, though direct comparability is limited.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAnother key finding of our study was that the LVEF-reserve was lower in participants with CACS \u0026gt; 300 compared to those with CACS \u0026le; 300, suggesting an inverse relationship between atherosclerotic burden and the LVEF-reserve. A potential physiological mechanism is that extensive coronary calcification impairs vascular function, reducing myocardial contractile response to stress [26].\u003c/p\u003e\n\u003cp\u003eWhile CACS provides a surrogate marker of atherosclerotic plaque burden, it does not directly evaluate ischemia. CACS indicates the degree of coronary calcification, which can lead to impaired myocardial perfusion, a reduction in MFR, and potentially a lower LVEF-reserve. Therefore, the association between CACS and LVEF-reserve may reflect an indirect pathway, where CACS affects myocardial perfusion and, consequently, LVEF-reserve.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn line with previous findings in individuals with suspected CAD [6, 24, 27], we demonstrated that the LVEF-reserve was significantly lower in those with perfusion defects \u0026ndash; even among individuals without known or suspected CAD \u0026ndash; showing that the LVEF-reserve is inversely related to the severity of perfusion defects.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNo trials have explored the association between the LVEF-reserve and GLS in populations without CVD. The unexpected lack of an association between the LVEF-reserve and resting GLS in our study may be attributed by the fact that diastolic dysfunction generally precedes systolic dysfunction in the early stages of diabetic cardiomyopathy, with reduced systolic function manifesting in more advanced disease [28]. The LVEF-reserve may be impaired earlier in the progression of myocardial dysfunction, as it reflects the heart\u0026rsquo;s ability to respond to stress, while GLS may become impaired later due to myocardial strain or damage. This suggests that the LVEF-reserve and GLS capture different aspects of myocardial dysfunction at varying stages of the disease. \u0026nbsp;Among all participants, 290 had a LVEF-reserve of less than 4%, and 204 had a GLS of less than 16% (considered low) [29]. Only 62 participants had both low LVEF-reserve and low GLS. However, reference values for LVEF-reserve are not well established, which limits the ability to compare and assess the clinical significance of these findings. These findings suggest that while resting GLS may be a valuable marker of systolic dysfunction in people with diabetes, it might not be as closely linked to the dynamic changes in myocardial performance observed during stress, as those captured by the LVEF-reserve.\u0026nbsp;\u003cbr\u003e\u0026nbsp;Future studies with longitudinal designs are needed to establish causality and refine risk stratification strategies in individuals with T2D.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eStrengths and limitations:\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eTo our knowledge, this is the largest cohort assessing the LVEF-reserve and MFR in individuals with T2D without known or suspected CVD.\u003c/p\u003e\n\u003cp\u003eAnother strength is the use of cardiac PET/CT, a highly reliable method for evaluating the LVEF-reserve and MFR, enabling an accurate assessment of the myocardial function during stress.\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe limitations include the overrepresentation of white men, which may limit the generalizability of the findings to women and other ethnic groups. Since the participants were selected to be asymptomatic and without known CVD, our findings could be subject to selection bias. However, this was required to accurately assess the role of advanced cardiac imaging in individuals with T2D free of CVD. While participants were included based on the absence of known or suspected CVD, this was determined through medical history and symptom screening, without systematic diagnostic testing to definitively rule out subclinical disease.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn individuals with T2D but without known CVD, the present study demonstrated that lower MFR, as well as presence of CACS\u0026gt;300 and perfusions defects were independently associated with lower LVEF-reserve as hypothesized. No significant association between GLS and the LVEF-reserve was observed.\u0026nbsp;\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eBMI\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003ebody mass index\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCACS\u0026nbsp;\u003c/strong\u003ecoronary artery calcium score\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCAD\u003c/strong\u003e coronary artery disease\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCVD\u003c/strong\u003e cardiovascular disease\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003econfidence interval\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eeGFR\u0026nbsp;\u0026nbsp;\u003c/strong\u003eEstimated glomerular filtration rate\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGLP-1 RA\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003eGlucagon-like peptide-1 receptor agonists\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCT\u003c/strong\u003e computer tomography\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGLS\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003eglobal longitudinal strain\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHbA1c\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003eGlycated hemoglobin\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLDL\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003eLow-density lipoprotein\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLVEF\u003c/strong\u003e left ventricular ejection fraction\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMFR\u003c/strong\u003e myocardial flow reserve\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePET\u003c/strong\u003e positron emission tomography\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRAAS\u003c/strong\u003e Renin-angiotensin-aldosterone system\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRb\u003c/strong\u003e rubidium\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e Standard deviation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUACR\u003c/strong\u003e Urine albumin creatinine ratio\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki. All participants provided written consent, and the protocol was approved by the Danish National Committee on Health Research Ethics (H-19063311).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe data supporting the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003ePR has received speaking fees and/or consultancy to Steno Diabetes Center Copenhagen from Eli Lilly, Novo Nordisk, Sanofi Aventis, Vifor, Boehringer Ingelheim, Astellas, Gilead, Bayer, AstraZeneca, Mundipharma, and MSD. PR has received research grants from Novo Nordisk AstraZeneca. AC, PR, TWH and RSR had shares in Novo Nordisk. AK and RSR has received consultancy fees from Novo Nordisk. EHZ is a full-time employee in Novo Nordisk and has shares in Novo Nordisk. IKR is a full-time employee at Novo Nordisk. ML: has received speaker and consultancy fees from AstraZeneca, Bayer, Boeringer Ingelheim, Novo Nordisk, GlaxoSmithKline, and is an investigator in clinical studies sponsored by Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Eli Lilly, Janssen, MSD and Novo Nordisk. JPG has served as consultant for Novo Nordisk on measurement of bioactive peptides. TBS has received research grants from Pfizer, Sanofi Pasteur, GSK, Novo Nordisk, AstraZeneca, Boston Scientific and GE Healthcare, consulting fees from Novo Nordisk, IQVIA, Parexel, Amgen, CSL Seqirus, GSK and Sanofi Pasteur, and lecture fees from Bayer, Novartis, Sanofi Pasteur, GE healthcare and GSK. The other authors declare that there is no duality of interest associated with this manuscript.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis study was funded by Novo Nordisk Foundation (grant number NNF19OC0054674.).\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eAC, ACSM, IKBR, RSR, EHZ, MBB, PH, LH, AK, PR and TWH contributed to the study design and data interpretation. ACSM, IKBR, VSW, PH, ULK, ML, AKE, JPG, TBS, MCHL and RSR, acquired data. ACSM, IKBR and VSW recruited participants. AC and MBB performed statistical analysis. AC drafted the manuscript. The final manuscript was critically read, revised, and approved by all authors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTWH is the guarantor of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe authors would like to thank all participants and acknowledge the work of study nurses and laboratory technicians from Steno Diabetes Center Copenhagen, Rigshospitalet, Holbaek Hospital and University Hospital Zealand, Denmark.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eInternational Diabetes Federation. IDF Diabetes Atlas, 10th edn. Brussels Belgium: International Diabetes Federation; 2021.\u003c/li\u003e\n\u003cli\u003eAmerican Diabetes Association Professional Practice Committee. 10. Cardiovascular Disease and Risk Management: Standards of Care in Diabetes-2024. Diabetes Care. 2024;47(Suppl 1):S179\u0026ndash;S218. doi.org/10.2337/dc24-S010.\u003c/li\u003e\n\u003cli\u003eCorrection to: 2023 ESC Guidelines for the management of cardiovascular disease in patients with diabetes: Developed by the task force on the management of cardiovascular disease in patients with diabetes of the European Society of Cardiology (ESC). Eur Heart J. 2024;45(7):518\u0026ndash;518. doi.org/10.1093/eurheartj/ehad857.\u003c/li\u003e\n\u003cli\u003eThein PM, Mirzaee S, Cameron JD, Nasis A. Left ventricular contractile reserve as a determinant of adverse clinical outcomes: a systematic review. Intern Med J. 2022;52(2):186\u0026ndash;197. doi: 10.1111/imj.14995.\u003c/li\u003e\n\u003cli\u003eDorbala S, Hachamovitch R, Curillova Z, et al. Incremental prognostic value of gated Rb-82 positron emission tomography myocardial perfusion imaging over clinical variables and rest LVEF. J Am Coll Cardiol Img. 2009;2(7):846\u0026ndash;854. doi.org/10.1016/j.jcmg.2009.04.009.\u003c/li\u003e\n\u003cli\u003eDorbala S, Vangala D, Sampson U, et al. Value of vasodilator left ventricular ejection fraction reserve in evaluating the magnitude of myocardium at risk and the extent of angiographic coronary artery disease: A 82Rb PET/CT study. J Nucl Med. 2007;48(3):349\u0026ndash;358.\u003c/li\u003e\n\u003cli\u003eRauf M, Hansen KW, Galatius S, et al. Prognostic implications of myocardial perfusion imaging by 82-rubidium positron emission tomography in male and female patients with angina and no perfusion defects. Eur Heart J Cardiovasc Imaging. 2023;24(2):212\u0026ndash;222. doi.org/10.1093/ehjci/jeac217.\u003c/li\u003e\n\u003cli\u003eH\u0026oslash;jstrup S, Hansen KW, Talleruphuus U, et al. Myocardial Flow Reserve, an Independent Prognostic Marker of All-Cause Mortality Assessed by 82Rb PET Myocardial Perfusion Imaging: A Danish Multicenter Study. Circ Cardiovasc Imaging. 2023;16(8):e015184. doi.org/10.1161/CIRCIMAGING.122.015184.\u003c/li\u003e\n\u003cli\u003ePatel KK, Spertus JA, Chan PS, et al. Myocardial blood flow reserve assessed by positron emission tomography myocardial perfusion imaging identifies patients with a survival benefit from early revascularization. Eur Heart J. 2020;41(6):759\u0026ndash;768. doi.org/10.1093/eurheartj/ehz389.\u003c/li\u003e\n\u003cli\u003eJensen SM, Prescott EIB, Abdulla J. The prognostic value of coronary flow reserve in patients with non-obstructive coronary artery disease and microvascular dysfunction: A systematic review and meta-analysis. Int J Cardiovasc Imaging. 2023;39(12):2545\u0026ndash;2556. doi: 10.1007/s10554-023-02948-1.\u003c/li\u003e\n\u003cli\u003eShaw LJ, Raggi P, Schisterman E, Berman DS, Callister TQ. Prognostic value of cardiac risk factors and coronary artery calcium screening for all-cause mortality. Radiology. 2003;228(3):826\u0026ndash;833. doi.org/10.1148/radiol.2283021006.\u003c/li\u003e\n\u003cli\u003eRaggi P, Shaw LJ, Berman DS, Callister TQ. Prognostic value of coronary artery calcium screening in subjects with and without diabetes. J Am Coll Cardiol. 2004;43(9):1663\u0026ndash;1669. doi.org/10.1016/j.jacc.2003.09.068.\u003c/li\u003e\n\u003cli\u003ePatel KK, Peri-Okonny PA, Qarajeh R, et al. Prognostic Relationship Between Coronary Artery Calcium Score, Perfusion Defects, and Myocardial Blood Flow Reserve in Patients With Suspected Coronary Artery Disease. Circ Cardiovasc Imaging. 2022;15(4):e012599.\u003cbr\u003edoi: 10.1161/CIRCIMAGING.121.012599.\u003c/li\u003e\n\u003cli\u003eLiu JH, Chen Y, Yuen M, et al. Incremental prognostic value of global longitudinal strain in patients with type 2 diabetes mellitus. Cardiovasc Diabetol. 2016;15:22. doi: 10.1186/s12933-016-0333-5.\u003c/li\u003e\n\u003cli\u003eSkriver-M\u0026oslash;ller AC, Hasbak P, Rasmussen IKB, et al. Sex differences in myocardial flow reserve among individuals with type 2 diabetes: insights from the DiaHeart study. Cardiovasc Diabetol. 2025;24(1):172. doi: 10.1186/s12933-025-02717-5.\u003c/li\u003e\n\u003cli\u003eLevey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150(9):604\u0026ndash;612. doi: 10.7326/0003-4819-150-9-200905050-00006.\u003c/li\u003e\n\u003cli\u003eLortie M, Beanlands RS, Yoshinaga K, Klein R, Dasilva JN, DeKemp RA. Quantification of myocardial blood flow with 82Rb dynamic PET imaging. Eur J Nucl Med Mol Imaging. 2007;34(11):1765\u0026ndash;1774. doi: 10.1007/s00259-007-0478-2.\u003c/li\u003e\n\u003cli\u003eKelshiker MA, Seligman H, Howard JP, et al. Coronary flow reserve and cardiovascular outcomes: a systematic review and meta-analysis. Eur Heart J. 2022;43(16):1582\u0026ndash;1593. doi: 10.1093/eurheartj/ehab775.\u003c/li\u003e\n\u003cli\u003eAgatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M Jr, Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol. 1990;15(4):827\u0026ndash;832. doi: 10.1016/0735-1097(90)90282-t.\u003c/li\u003e\n\u003cli\u003eGolub I, Termeie O, Kristo S, et al. Major global coronary artery calcium guidelines. J Am Coll Cardiol Img. 2023;16(1):98\u0026ndash;117. doi.org/10.1016/j.jcmg.2022.06.018.\u003c/li\u003e\n\u003cli\u003eCusm\u0026agrave;-Piccione M, Zito C, Oreto L, et al. Longitudinal strain by automated function imaging detects single-vessel coronary artery disease in patients undergoing dipyridamole stress echocardiography. J Am Soc Echocardiogr. 2015;28(10):1214\u0026ndash;1221. doi: 10.1016/j.echo.2015.06.001.\u003c/li\u003e\n\u003cli\u003eAbel RM, Reis RL. Effects of coronary blood flow and perfusion pressure on left ventricular contractility in dogs. Circ Res. 1970;27(6):961\u0026ndash;971. doi: 10.1161/01.res.27.6.961.\u003c/li\u003e\n\u003cli\u003eVan Tosh A, Votaw JR, Reichek N, Palestro CJ, Nichols KJ. The relationship between ischemia-induced left ventricular dysfunction, coronary flow reserve, and coronary steal on regadenoson stress-gated 82Rb PET myocardial perfusion imaging. J Nucl Cardiol. 2013;20(6):1060\u0026ndash;1068. doi: 10.1007/s12350-013-9784-1.\u003c/li\u003e\n\u003cli\u003eFrey SM, Honegger U, Clerc OF, et al. Left ventricular ejection fraction, myocardial blood flow and hemodynamic variables in adenosine and regadenoson vasodilator 82-Rubidium PET. J Nucl Cardiol. 2022;29(3):921\u0026ndash;933. doi.org/10.1007/s12350-021-02729-0.\u003c/li\u003e\n\u003cli\u003eYonaha O, Matsubara T, Naruse K, et al. Effects of reduced coronary flow reserve on left ventricular function in type 2 diabetes. Diabetes Res Clin Pract. 2008;82(1):98\u0026ndash;103. doi: 10.1016/j.diabres.2008.06.020.\u003c/li\u003e\n\u003cli\u003eWang L, Jerosch-Herold M, Jacobs DR Jr, et al. Coronary artery calcification and myocardial perfusion in asymptomatic adults: the MESA (Multi-Ethnic Study of Atherosclerosis). J Am Coll Cardiol. 2006;48(5):1018\u0026ndash;1026. doi: 10.1016/j.jacc.2006.04.089.\u003c/li\u003e\n\u003cli\u003eHsiao E, Ali B, Blankstein R, et al. Detection of obstructive coronary artery disease using regadenoson stress and 82Rb PET/CT myocardial perfusion imaging. J Nucl Med. 2013;54(10):1748\u0026ndash;1754. doi: 10.2967/jnumed.113.120063.\u003c/li\u003e\n\u003cli\u003ePaolillo S, Marsico F, Prastaro M, et al. Diabetic cardiomyopathy: definition, diagnosis, and therapeutic implications. Heart Fail Clin. 2019;15(3):341\u0026ndash;347. doi: 10.1016/j.hfc.2019.02.003.\u003c/li\u003e\n\u003cli\u003eNyberg J, Jakobsen EO, \u0026Oslash;stvik A, et al. Echocardiographic reference ranges of global longitudinal strain for all cardiac chambers using guideline-directed dedicated views. J Am Coll Cardiol Img. 2023;16(12):1516\u0026ndash;1531. doi: 10.1016/j.jcmg.2023.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1: Clinical characteristics by tertiles of the LVEF-reserve\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eN = 871\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1st tertile\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-22 to \u0026lt;4%\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eN = 290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2nd tertile\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;4 to \u0026lt;7%\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;N = 290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3rd tertile\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;7 to 23%\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eN = 291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64.9 \u0026plusmn;9.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65.5 \u0026plusmn;8.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65.1 \u0026plusmn;8.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64.1 \u0026plusmn;9.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMen, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e609 (70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e205 (71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e197 (68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e207 (71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eKnown duration of diabetes (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.7 \u0026plusmn;8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.2 \u0026plusmn;8.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.6 \u0026plusmn;8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.2 \u0026plusmn;8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBody mass index (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30.2 \u0026plusmn;5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.8 \u0026plusmn;5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30.3 \u0026plusmn;5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30.4 \u0026plusmn;5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSystolic blood pressure (mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e139 \u0026plusmn;15.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e140 \u0026plusmn;15.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e137 \u0026plusmn;16.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e138 \u0026plusmn;15.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHbA1c (mmol/mol)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55.7 \u0026plusmn;12.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56.7 \u0026plusmn;13.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54.7 \u0026plusmn;13.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55.5 \u0026plusmn;12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLDL cholesterol (mmol/l)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.7 \u0026plusmn;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.7 \u0026plusmn;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.8 \u0026plusmn;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.7 \u0026plusmn;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eeGFR (ml/min/1.73m\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e84.1 \u0026plusmn;20.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e84.9 \u0026plusmn;21.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e84.4 \u0026plusmn;19.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e82.9 \u0026plusmn;20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUrine Albumin-to-Creatinine Ratio (mg/g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.0 (5.0 - 21.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.0 (5.0 - 26.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.0 (5.0 - 23.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.0 (5.0 - 17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistoric albuminuria\u003csup\u003e*\u003c/sup\u003e, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Normal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e564 (65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e180 (62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e179 (62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e205 (70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Moderately increased\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e215 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e76 (26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e79 (27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Severely increased\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e69 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17 (5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent smoker, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e105 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedical treatment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLipid-lowering, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e702 (81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e233 (80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e239 (83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e230 (79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAntihypertensive drugs, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e660 (76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e229 (79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e215 (74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e216 (74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRAAS-blockade, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e589 (68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e205 (71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e195 (67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e189 (65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBetablockers, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e147 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e38 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcetylsalicylic acid, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e259 (30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e89 (31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e85 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e85 (29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMetformin, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e704 (81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e234 (81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e236 (81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e234 (80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eInsulin, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e355 (41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e124 (43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e112 (39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e119 (41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSGLT-2i, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e398 (46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e148 (51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e138 (48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e112 (38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGLP-1 RA, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e439 (50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e153 (53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e146 (50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e140 (48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBoth SGLT2 and GLP-1\u003c/strong\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003cstrong\u003e, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e244 (28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e90 (31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e82 (28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e72 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003eData are expressed as mean \u0026plusmn;SD, median (interquartile range) or number (%) as appropriate. For each variable, the percentage of missing data is expressed if it exceeds 5%.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e*\u003c/sup\u003eAlbuminuria: Normal: UACR \u0026lt; 30 mg/g. Moderately increased UACR 30-300 mg/g. Severely increased: UACR \u0026gt;300 mg/g.\u0026nbsp;\u003csup\u003e\u0026dagger;\u003c/sup\u003eParticipants receiving both medications are also included in the sum of each medication separately.\u003cbr\u003e\u0026nbsp;eGFR: estimated glomerular filtration rate. GLP-1 RA: glucagon-like peptide-1 receptor agonist. HbA1c: glycosylated hemoglobin. LVEF: left ventricular ejection fraction. RAAS: renin-angiotensin-aldosterone system. SGLT-2i: sodium glucose transporter 2 inhibitor.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2: Cardiac PET/CT and echocardiography measurements stratified by tertiles of the LVEF-reserve.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"682\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eN = 871\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1st tertile\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-22 to \u0026lt;4%\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;N = 290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2nd tertile\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;4 to \u0026lt;7%\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;N = 290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3rd tertile\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;7 to 23%\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eN = 291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLVEF-reserve (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.3 \u0026plusmn;4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.7 \u0026plusmn;2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.4 \u0026plusmn;1.1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.8 \u0026plusmn;2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\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\"\u003e\n \u003cp\u003e\u003cstrong\u003eMFR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.55 \u0026plusmn;0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.33 \u0026plusmn;0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.58 \u0026plusmn;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.75 \u0026plusmn;0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\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\"\u003e\n \u003cp\u003e\u003cstrong\u003eMFR \u0026le; 2, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e190 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e96 (33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e38 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\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\"\u003e\n \u003cp\u003e\u003cstrong\u003eMBF stress\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.93 \u0026plusmn;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.84 \u0026plusmn;0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.91 \u0026plusmn;0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.03 \u0026plusmn;0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMBF rest\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.21 \u0026plusmn;0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.27 \u0026plusmn;0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.19 \u0026plusmn;0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.17 \u0026plusmn;0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\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\"\u003e\n \u003cp\u003e\u003cstrong\u003eCACS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e137 (12, 599)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e206 (27, 811)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e136 (17, 594)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e76 (1, 403)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\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\"\u003e\n \u003cp\u003e\u003cstrong\u003eCACS \u0026gt; 300, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e336 (39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e131 (45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e91 (31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e114 (39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLVEF at stress (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e72 \u0026plusmn;8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e70 \u0026plusmn;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e72 \u0026plusmn;8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e73 \u0026plusmn;7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\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\"\u003e\n \u003cp\u003e\u003cstrong\u003eLVEF at rest (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66 \u0026plusmn;8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e69 \u0026plusmn;9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e67 \u0026plusmn;8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64 \u0026plusmn;7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\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\"\u003e\n \u003cp\u003e\u003cstrong\u003eLVEF from echocardiogram (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55 \u0026plusmn;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56 \u0026plusmn;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55 \u0026plusmn;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55 \u0026plusmn;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGLS from echocardiogram (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.3 \u0026plusmn;2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.3 \u0026plusmn;2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.4 \u0026plusmn;2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.3 \u0026plusmn;2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eReversible perfusion defect (\u0026ge;5%), n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e229 (26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e92 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75 (26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e62 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eReversible perfusion defect, (extent%)\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.0 (5.0, 11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.0 (6.0, 13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.0 (5.0, 10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.0 (5.0, 9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIrreversible perfusion defect (\u0026ge;5%), n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIrreversible perfusion defect, (extent%)\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.0 (5.0, 8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.5 (5.0, 9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.0 (5.0, 6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.5 (5.0, 8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003eData are expressed as mean \u0026plusmn;SD, median (interquartile range) or number (%) as appropriate.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e*\u003c/sup\u003eCalculated among the participants with a reversible perfusion defect.\u0026nbsp;\u003csup\u003e\u0026dagger;\u003c/sup\u003eCalculated among the participants with an irreversible perfusion defect. P values were calculated using one-way analysis of means (not assuming equal variances); or the Chi-squared test.\u0026nbsp;\u003cbr\u003e\u0026nbsp;CACS: Coronary artery calcium score, GLS: Global Longitudinal Strain, LVEF: Left ventricular ejection fraction, MBF: Myocardial blood flow, MFR: Myocardial flow reserve.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3: Associations between the LVEF-reserve and measures of cardiovascular function\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"105%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4.4515%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12.5252%;\" colspan=\"5\"\u003e\u003cstrong\u003eModel 1\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 14.2273%;\" colspan=\"6\"\u003e\u003cstrong\u003eModel 2\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.8044%;\"\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2.924%;\"\u003e\u003cstrong\u003eBeta\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 3.0549%;\" colspan=\"2\"\u003e\u003cstrong\u003e95 % CI\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 3.6223%;\"\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 2.924%;\"\u003e\u003cstrong\u003eStd. beta\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 3.0549%;\"\u003e\u003cstrong\u003eBeta\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 3.8405%;\" colspan=\"2\"\u003e\u003cstrong\u003e95 % CI\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 3.7968%;\"\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 3.4914%;\" colspan=\"2\"\u003e\u003cstrong\u003eStd. beta\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.8044%;\"\u003e\n \u003cp\u003eMyocardial flow reserve\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.924%;\"\u003e\n \u003cp\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 3.0549%;\"\u003e\n \u003cp\u003e1.22, 2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.6223%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.924%;\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.0549%;\"\u003e\n \u003cp\u003e1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 3.8405%;\"\u003e\n \u003cp\u003e1.18, 2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.7968%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 3.4914%;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 5.8044%;\"\u003e\n \u003cp\u003eGlobal longitudinal strain\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.924%;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 3.0549%;\"\u003e\n \u003cp\u003e-0.12, 0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.6223%;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.924%;\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.0549%;\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 3.8405%;\"\u003e\n \u003cp\u003e-0.068, 0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.7968%;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 3.4914%;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 5.8044%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 2.924%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBeta\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 3.0549%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95 % CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3.6223%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 2.924%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3.0549%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBeta\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 3.8405%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95 % CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3.7968%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 3.4914%;\"\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: 4.4515%;\"\u003e\n \u003cp\u003eCACS \u0026gt; 300\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.2769%;\"\u003e\n \u003cp\u003e-1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 3.0549%;\"\u003e\n \u003cp\u003e-1.97, -0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.6223%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.924%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.0549%;\"\u003e\n \u003cp\u003e-1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 3.8405%;\"\u003e\n \u003cp\u003e-2.01, -0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.7968%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 3.4914%;\"\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: 4.4515%;\"\u003e\n \u003cp\u003ePerfusion defects\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 4.2769%;\"\u003e\n \u003cp\u003e-1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 3.0549%;\"\u003e\n \u003cp\u003e-1.99, -0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.6223%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 2.924%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.0549%;\"\u003e\n \u003cp\u003e-1.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 3.8405%;\"\u003e\n \u003cp\u003e-2.32, -0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 3.7968%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 3.4914%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" valign=\"top\" style=\"width: 32.5132%;\"\u003e\n \u003cp\u003eBeta coefficients with 95% confidence intervals (CI) and standardized beta coefficients (for continuous variables) calculated using multiple linear regression. \u003csup\u003e*\u003c/sup\u003eParticipants with CACS \u0026le; 300 served as reference group. \u003csup\u003e\u0026dagger;\u003c/sup\u003eParticipants without reversible and irreversible perfusion defects served as reference group.\u003c/p\u003e\n \u003cp\u003eModel 1 is adjusted for sex and age.\u003c/p\u003e\n \u003cp\u003eModel 2 is additionally adjusted for diabetes duration, BMI, LDL cholesterol, current smoking, systolic blood pressure, HbA1c, eGFR, and UACR. \u0026nbsp;\u003cbr\u003e\u0026nbsp;CACS: Coronary artery calcium score. LVEF: Left ventricular ejection fraction \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cardiovascular-diabetology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cvdb","sideBox":"Learn more about [Cardiovascular Diabetology](http://cardiab.biomedcentral.com/)","snPcode":"12933","submissionUrl":"https://submission.nature.com/new-submission/12933/3","title":"Cardiovascular Diabetology","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"myocardial flow, microcirculation, vasodilator stress, myocardial perfusion imaging ","lastPublishedDoi":"10.21203/rs.3.rs-6870088/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6870088/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Type 2 diabetes (T2D) is a major risk factor for cardiovascular disease (CVD), but the relationships between myocardial function, microvascular function, and atherosclerotic burden remain underexplored in asymptomatic individuals. This study investigates the associations between left ventricular ejection fraction (LVEF)-reserve, myocardial flow reserve (MFR), perfusion defects, coronary artery calcium score (CACS), and global longitudinal strain (GLS) in individuals with T2D but without overt CVD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: Cross-sectional analysis of 871 individuals with T2D without overt CVD, recruited between 2020-2023. All underwent cardiac 82-Rubidium PET/CT to assess LVEF-reserve, MFR, perfusion defects, and CACS. GLS was measured using echocardiography. Associations were examined using linear regression adjusted for cardiovascular risk factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Mean (SD) age was 64.9 (±9.0) years, diabetes duration was 13.9 (±8.4) years, and 262 (30%) were women. Higher MFR was associated with higher LVEF-reserve (β = 1.64, 95% CI: 1.18 to 2.11, p\u0026lt;0.001). Individuals with CACS \u0026gt; 300 had lower LVEF-reserve than those with CACS ≤ 300 (β = -1.31, 95% CI: -2.01 to -0.60, p\u0026lt;0.001). Presence of Perfusion defects were associated with lower LVEF-reserve (β = -1.58, 95% CI: -2.32 to -0.85, p\u0026lt;0.001). LVEF-reserve was not associated with GLS (p=0.28). Sensitivity analysis excluding 248 participants with perfusion defects confirmed the association between MFR and LVEF-reserve (β = 1.52 (95% CI: 1.01, 2.04), p\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eIn individuals with T2D without overt CVD, lower MFR, presence of perfusion defects, and CACS \u0026gt;300 were associated with lower LVEF-reserve. Underscoring a potential role of microvascular dysfunction in subclinical systolic impairment.\u003c/p\u003e","manuscriptTitle":"Left Ventricular Ejection Fraction Reserve and Its Association with Myocardial Perfusion, Coronary Calcification, and Strain in Type 2 Diabetes Without Overt Cardiovascular Disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-17 15:58:32","doi":"10.21203/rs.3.rs-6870088/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-22T08:09:06+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-11T21:10:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"188146625706110136471480013962166839607","date":"2025-07-01T10:55:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"171335757023304338291635342070040339649","date":"2025-06-12T19:04:16+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-12T11:36:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-11T15:57:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-11T15:43:07+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cardiovascular Diabetology","date":"2025-06-11T09:13:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cardiovascular-diabetology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cvdb","sideBox":"Learn more about [Cardiovascular Diabetology](http://cardiab.biomedcentral.com/)","snPcode":"12933","submissionUrl":"https://submission.nature.com/new-submission/12933/3","title":"Cardiovascular Diabetology","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ec414427-d1d2-4c3f-b54e-55376d1f7e8e","owner":[],"postedDate":"June 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-09-01T15:59:00+00:00","versionOfRecord":{"articleIdentity":"rs-6870088","link":"https://doi.org/10.1186/s12933-025-02886-3","journal":{"identity":"cardiovascular-diabetology","isVorOnly":false,"title":"Cardiovascular Diabetology"},"publishedOn":"2025-08-31 15:56:57","publishedOnDateReadable":"August 31st, 2025"},"versionCreatedAt":"2025-06-17 15:58:32","video":"","vorDoi":"10.1186/s12933-025-02886-3","vorDoiUrl":"https://doi.org/10.1186/s12933-025-02886-3","workflowStages":[]},"version":"v1","identity":"rs-6870088","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6870088","identity":"rs-6870088","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}