# Echocardiographic phenotypes of diabetic myocardial disorder: evolution over 15 months follow-up in the ARISE-HF trial

Thomas H Marwick, Carolyn Lam, Yuxi Liu, Stefano del Prato, Julio Rosenstock, Javed Butler, Justin Ezekowitz, Nasrien E Ibrahim, W H Wilson Tang, Faiez Zannad, et al.

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## To cite this version:

Thomas H Marwick, Carolyn Lam, Yuxi Liu, Stefano del Prato, Julio Rosenstock, et al., Echocardiographic phenotypes of diabetic myocardial disorder: evolution over 15 months follow-up in the ARISE-HF trial. Cardiovascular Diabetology, 2025, 24 (1), pp.16. 10.1186/s12933-024-02554-y. hal-04904547

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# Echocardiographic phenotypes of diabetic myocardial disorder: evolution over 15 months follow-up in the ARISE-HF trial

Thomas H. Marwick<sup>1,14*</sup>, Carolyn Lam<sup>2</sup>, Yuxi Liu<sup>3</sup>, Stefano Del Prato<sup>4</sup>, Julio Rosenstock<sup>5</sup>, Javed Butler<sup>6,7</sup>, Justin Ezekowitz<sup>8</sup>, Nasrien E. Ibrahim<sup>9</sup>, W. H. Wilson Tang<sup>10</sup>, Faiez Zannad<sup>12</sup>, Riccardo Perfetti<sup>11</sup> and James L. Januzzi<sup>3,13</sup>

**Abstract**

**Background** Diabetic myocardial disorder (DbMD, evidenced by abnormal echocardiography or cardiac biomarkers) is a form of stage B heart failure (SBHF) at high risk for progression to overt HF. SBHF is defined by abnormal LV morphology and function and/or abnormal cardiac biomarker concentrations.

**Objective** To compare the evolution of four DbMD groups based on biomarkers alone, systolic and diastolic dysfunction alone, or their combination.

**Methods** The Aldose Reductase Inhibition for Stabilization of Exercise Capacity in Heart Failure (ARISE-HF) trial was a Phase 3 randomised trial of an aldose reductase inhibitor in patients with well-controlled type 2 diabetes mellitus (T2DM). The 1858 potential participants (age 67 ± 7 years; 50% women) were screened for SBHF based on abnormal echocardiography or biomarkers (N-terminal pro-B-type natriuretic peptide ≥ 40 ng/L or high sensitivity cardiac troponin T ≥ 10 ng/L [women] and ≥ 16 ng/L [men]). Exercise capacity (peak VO₂) was reduced in 669 with DbMD (age 68 ± 7, 50% women), and peak VO₂ was reassessed at 15 months.

**Results** The 1463 (79%) participants with DbMD were allocated to four clusters; 907 (49%) showed *isolated elevation of cardiac biomarkers*, 301 (16%) with *systolic dysfunction/hypertrophy*, 162 (9%) with *diastolic dysfunction* and 93 (5%) comprised an *overlap cluster* (combined diastolic, systolic or LV geometric abnormalities). Reduced VO₂ (< 75% predicted) was present in 669 (46%); 72% of those with both systolic and diastolic dysfunction, 56% of those with systolic dysfunction and LVH, 53% of those with diastolic dysfunction and 38% with biomarkers alone (p < 0.0001). In 669 patients followed over 15 months, there was a similar small decrement in VO₂ in all groups.

**Conclusions** Among individuals with T2DM and SBHF, reduced functional capacity is most prevalent in those with multiple physiological disturbances. However, there was no difference between phenogroups in the evolution of exercise intolerance.

**Trial Registration:** ARISE-HF, NCT04083339.

**Keywords** Diabetic myocardial disorder, Biomarkers, Systolic dysfunction, Diastolic dysfunction

Full list of author information is available at the end of the article

<footnote>*Correspondence:
Thomas H. Marwick
tom.marwick@baker.edu.au</footnote>
## Background

Of all patients with HF, the group with type 2 diabetes (T2DM) are at the highest risk of adverse outcomes [1]. Heart failure (HF) may be the most common cardiac complication of T2DM, and is the most unrecognized among cardiovascular diseases in this population [2]. Before patients present with symptomatic HF, they commonly have Stage B HF (SBHF)— evidenced by abnormal structure, function or biomarkers in patients with risk factors, but no symptoms or signs of HF [3]. Despite having minimal or no symptoms, these patients commonly show reduced exercise capacity [4]. Recognition of patients during this stage may provide an opportunity to initiate cardioprotective therapy, and thereby prevent or delay the onset of clinical HF. T2DM is more likely to lead to HFpEF than HFrEF [5], especially in individuals with well controlled BP and absence of major CAD. Although sodium/glucose co-transporter 2 (SGLT2) inhibitors [6] and glucagon-like peptide-1 (GLP-1) receptor agonists [7] have been shown to be effective in patients with T2DM and overt HFpEF, their value in Stage B heart failure (SBHF) is unproven.

There are multiple causes of HF in T2DM— ranging from diabetic myocardial disorder (DbMD) reported by Rubler et al. [8], to common HF etiologies including hypertension and coronary artery disease [9]. The variety of different mechanisms [10] might be expected to engender a variety of phenotypes, potentially with different prognostic and management implications. Indeed, diagnostic approaches for subclinical LV dysfunction include elevated cardiac biomarkers [11], as well as various echocardiographic phenotypes that have been differentiated in a previous cluster analysis [12], involving remodeling, systolic and diastolic dysfunction (DD) [13]. However, acute disturbances of myocardial function in response to hyperglycemia or hypertension may explain some of these findings - previous observational studies of T2DM phenotypes had inconsistent levels of metabolic control. In addition, the implications of the subgroups in follow-up have not been investigated.

The ARISE-HF Trial (Aldose Reductase Inhibition for Stabilization of Exercise Capacity in Heart Failure) [14] was a phase 3 randomized study which showed that an aldose reductase inhibitor (AT-001) was safe but did not prevent decline in cardiac functional capacity in individuals T2DM and SBHF, compared with placebo. Participants had imaging and biomarkers at baseline and 15 months, with well-controlled metabolism and blood pressure, and no ischemic heart disease. The ARISE-HF database therefore provides a well-phenotyped cohort to better understand the presence, expression and evolution of SBHF among individuals with T2DM. We hypothesized that; (1) the phenogroups of individuals with DbMD would reflect the severity of functional

compromise at baseline, (2) the phenogroups would show differences in evolution over 15 months of follow-up.

## Methods

### Study design

The study group comprised patients recruited to the ARISE-HF trial (NCT04083339), a Phase 3, randomized, placebo-controlled trial that sought whether an aldose reductase inhibitor (AT-001) could stabilize exercise capacity in adults with T2DM and DbMD. Details of the study design and methodology have been published [14]. In this trial, patients with T2DM, with no cardiac history or cardiac symptoms, were screened for DbMD with cardiac biomarkers and echocardiography for the detection of LV remodeling, or systolic or diastolic dysfunction. Entry was restricted to those with adequate glycemic and blood pressure control [14], to exclude these as a cause for cardiac functional responses. SBHF was identified in patients with risk factors, no symptoms or signs, and one of structural, functional or biomarker evidence, consistent with the uniform definition of HF [3].

In the baseline analysis, we compared the clinical and exercise characteristics of predefined phenogroups, including those with reduced exercise capacity. For the follow-up analysis, we considered baseline and follow-up data in all participants with reduced exercise capacity at baseline (including both groups on AT-001 and placebo). We assessed the evolution of exercise capacity over 15 months in the biomarker and echocardiographic phenogroups defined at baseline.

### Clinical features

The baseline clinical data included demographics, past medical history, medication use and questionnaires regarding health status (KCCQ-23, a modification of the Kansas City Cardiomyopathy Questionnaire for a study population without overt HF) [15] and activity (the Physical Activity Score for the Elderly, PASE score) [16]. In addition to standard laboratory tests (including estimated glomerular filtration rate [eGFR], albumin/creatinine ratio, serum lipids and hemoglobin A1c [HbA1c]), we obtained N-terminal pro-B type natriuretic peptide (NT-proBNP; subclinical LVD threshold < 40 ng/L) and high sensitivity cardiac troponin T (hs-cTnT; < 10 ng/L for women and < 16 ng/L for men).

### Echocardiography

A complete 2-dimensional and Doppler echocardiogram was performed using a standard acquisition [17]. Measurement and interpretation were blinded to clinical characteristics and treatment allocation, and provided by a core laboratory. Systolic dysfunction was measured as LV ejection fraction [LVEF] (LVEF < 40% was an exclusion for the trial), and global longitudinal shortening strain
(GLS, abnormal < 16%) [18]. LV hypertrophy was defined by LV mass indexed for body surface area (LVMi ≥ 95 g/ m² and 115 g/m² in women and men, respectively). DD was based on abnormal left atrial volume (LAVi > 34 mL/ m²), increased ratio of early transmitral Doppler flow [E] over the early septal annular velocity [e'] (≥ 13), or estimated pulmonary artery pressures (right ventricu- lar systolic pressure; RVSP > 35 mm Hg). We divided the patients into phenogroups based upon previous work showing different systolic and diastolic phenotypes and their combination [12]. As that work preceded the inclu- sion of biomarkers as a marker of SBHF, we added a 4th group characterized by abnormal biomarkers alone.

**Cardiopulmonary exercise testing**

As described in the Methods paper [14], maximal car-
diopulmonary exercise tests (CPET) were obtained
using bicycle stress, with standard ECG monitoring and
expired gas analysis. We assessed the duration of exer-
cise, peak VO₂, and peak respiratory exchange rate (RER;
>1.05 indicates adequate test performance).

**Statistical analysis**

For the baseline analysis, we considered all candidates
undergoing echocardiography (including those ultimately
excluded owing to normal exercise capacity). The dis-
tribution and characteristics of patients with preserved
and reduced functional capacity (based on the peak VO₂
cut-point of < 75% of predicted normal) were compared.

To elucidate the differences between the identified phe-
nogroups, we used the chi-square test to assess the sig-
nificance of differences between the clustering groups for
categorical variables. The Wilcoxon rank-sum test was
utilized to compare the medians between groups for non-
normally distributed continuous variables and t-test for
continuous variables that followed a normal distribution.
The association of baseline variables with key compo-
nents of the phenogroups were assessed in multivariable
linear stepwise models, adjusted for demographics (age,
sex, race), clinical features and biomarkers (blood pres-
sure, NT-proBNP, hs-cTnT, Hb A1c, eGFR), echocardiо-
graphic findings (LV function, geometry and diastolic
markers), and exercise testing (peak VO₂, exercise dura-
tion, peak RER). The strength of association between
clinical features and the phenogroups were assessed
using a stepwise model selection approach for the mul-
tivariable logistic models, with odds ratios (OR) and 95%
confidence intervals (CI) reported. Missing variables
were addressed through imputation using the MICE
algorithm.

All statistical analyses were performed using the R
version 4.2.3 (R Foundation for Statistical Computing,
Vienna, Austria. URL: https://www.R-project.org/). P
values are two-sided with values < 0.05 considered statis-
tically significant. The datasets generated during and/or
analyzed during the current study are not publicly avail-
able due to the ongoing ARISE-HF Trial.

<figure><img src="image_4.png" /><figcaption>**Fig. 1** Selection of patients with DbMD and impaired functional capacity, and follow-up</figcaption></figure>
# Results

## Patient selection

The recruitment, selection and follow-up of patients is summarized in Fig. 1. Clinical and echocardiographic evaluation was undertaken in 1858 individuals ≥ 60 years old with T2DM (or ≥ 40 with > 10 years of T2DM or renal impairment) who had no history or symptoms of CVD (Table 1). Of these, 395 had normal echocardiographic and biomarker results and were excluded; this resulted in a baseline DbMD cohort of 1463 participants. This overall group with DbMD (age 67 years, 50% women) was ethnically diverse and represented patients with T2DM, at risk of HF (average T2DM duration of 14 years). Overall, a quarter had an NT-proBNP ≥ 125 ng/L and hs-cTnT was at or above the 99th percentile for a healthy population in 20% of the participants. While most study participants had a history of hypertension, by study protocol, only those well-controlled hypertension— most commonly taking angiotensin converting enzyme inhibitors or angiotensin II receptor blockers—were enrolled. Again, by study protocol, recruitment was restricted to patients with excellent glycemic control, with therapy

most commonly including metformin, and with significant numbers of patients with SGLT2 inhibitors and GLP-1 receptor agonists.

## Phenogroups of T2DM at baseline

Most participants had abnormal biomarkers alone (Fig. 1; Table 1); this group had more female participants and a shorter T2DM duration than those with the echocardiographic phenotypes. The biomarker group had a slightly higher EF (although both groups were in the normal range), and mean functional capacity, sedentariness and symptom status were similar (Appendix Table 1). Although the number with abnormal biomarkers fell when an NT-proBNP cut-off of 125 ng/L was used, the overall comparison with the group with abnormal echocardiograms was similar (Appendix Table 2).

Of participants with an abnormal echocardiogram, the group with systolic dysfunction or LV hypertrophy had lower body-mass index than those with DD, and had significantly lower natriuretic peptide levels with greater exercise capacity. The 255 patients with DD either in isolation or combined with systolic dysfunction were the

<table><caption>**Table 1** Baseline characteristics of 1463 DbMD patients in the four phenotype groups</caption><thead><tr><th></th><th>Full cohort</th><th>Elevated Biomarkers</th><th>Systolic/LVH</th><th>Diastolic</th><th>Overlap</th><th>p</th></tr></thead><tbody><tr><td>n</td><td>1463</td><td>907 (62%)</td><td>301 (21%)</td><td>162 (11%)</td><td>93 (6%)</td><td></td></tr><tr><td><em>Demographic and clinical features</em></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Age (mean (SD))</td><td>67.3 (7.5)</td><td>67.3 (7.5)</td><td>66.0 (7.4)</td><td>68.5 (8.0)</td><td>69.6 (6.9)</td><td>&lt; 0.001</td></tr><tr><td>Male sex (%)</td><td>797 (54.5)</td><td>496 (54.7)</td><td>178 (59.1)</td><td>90 (55.6)</td><td>33 (35.5)</td><td>0.001</td></tr><tr><td>Race (%) - White</td><td>925 (63.2)</td><td>597 (65.8)</td><td>175 (58.1)</td><td>105 (64.8)</td><td>48 (51.6)</td><td>0.008</td></tr><tr><td>Hispanic</td><td>300 (20.5)</td><td>179 (19.7)</td><td>58 (19.3)</td><td>36 (22.2)</td><td>27 (29.0)</td><td></td></tr><tr><td>Black</td><td>116 (7.9)</td><td>61 (6.7)</td><td>39 (13.0)</td><td>10 (6.2)</td><td>6 (6.5)</td><td></td></tr><tr><td>Asian</td><td>99 (6.8)</td><td>58 (6.4)</td><td>23 (7.6)</td><td>10 (6.2)</td><td>8 (8.6)</td><td></td></tr><tr><td>AI/AN</td><td>5 (0.3)</td><td>3 (0.3)</td><td>2 (0.7)</td><td>0 (0.0)</td><td>0 (0.0)</td><td></td></tr><tr><td>Other</td><td>18 (1.2)</td><td>9 (1.0)</td><td>4 (1.3)</td><td>1 (0.6)</td><td>4 (4.3)</td><td></td></tr><tr><td>SBP (mmHg, mean [SD])</td><td>130 (13)</td><td>130 (13)</td><td>128 (12)</td><td>133 (13)</td><td>131 (17)</td><td>0.008</td></tr><tr><td>DBP (mmHg, mean [SD])</td><td>75.99 (8.83)</td><td>76.08 (8.87)</td><td>76.18 (8.63)</td><td>76.19 (8.27)</td><td>74.63 (10.00)</td><td>0.56</td></tr><tr><td><em>Laboratory Test</em></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>NT-proBNP (ng/L, median [IQR])</td><td>77 [39, 139]</td><td>77 [44, 138]</td><td>62 [29, 118]</td><td>93 [45, 161]</td><td>118 [56, 200]</td><td>&lt; 0.001</td></tr><tr><td>hs-cTnT (ng/L, median [IQR])</td><td>9 [7, 14]</td><td>9 [7, 13]</td><td>9 [6, 13]</td><td>11 [8, 15]</td><td>9 [6, 14]</td><td>0.02</td></tr><tr><td>HbA1 (%, mean [SD])</td><td>7.18 (1.16)</td><td>7.22 (1.27)</td><td>7.20 (1.01)</td><td>7.05 (0.83)</td><td>6.94 (0.91)</td><td>0.06</td></tr><tr><td>Hgb (g/dL, mean [SD])</td><td>13.68 (1.47)</td><td>13.70 (1.50)</td><td>13.76 (1.48)</td><td>13.62 (1.34)</td><td>13.28 (1.40)</td><td>0.05</td></tr><tr><td>eGFR (mL/min/1.73 m2, mean [SD])</td><td>78.31 (18.06)</td><td>77.7 (18.4)</td><td>80.7 (17.7)</td><td>78.9 (16.5)</td><td>75.2 (18.1)</td><td>0.03</td></tr><tr><td><em>Echocardiogram</em></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>LVEF (%, median [IQR])</td><td>62 [59, 65]</td><td>63 [60, 66]</td><td>60 [57, 63]</td><td>63 [60, 66]</td><td>62 [60, 65]</td><td>&lt; 0.001</td></tr><tr><td>GLS (%, median [IQR])</td><td>-17.4 [-19.4, -15.1]</td><td>-18.8 [-20.2, -17.9]</td><td>-14.8 [-15.5, -13.9]</td><td>-19.1 [-20.9, -17.7]</td><td>-15.4 [-18.9, -14.1]</td><td>&lt; 0.001</td></tr><tr><td>LAVI (ml/m<sup>2</sup>, median [IQR])</td><td>23 [19, 29]</td><td>22 [19, 26]</td><td>22 [18, 26]</td><td>34 [25, 37]</td><td>35 [26, 37]</td><td>&lt; 0.001</td></tr><tr><td>LVMI (g/m<sup>2</sup>, median [IQR])</td><td>73 [62, 88]</td><td>68 [60, 79]</td><td>74 [63, 91]</td><td>88 [67, 94.30]</td><td>101.50 [95.75, 115]</td><td>&lt; 0.001</td></tr><tr><td>E/e' (median [IQR])</td><td>9.3 [7.7, 11.5]</td><td>8.7 [7.4, 10.3]</td><td>8.9 [7.4, 10.2]</td><td>13.7 [10.5, 14.8]</td><td>14.7 [13.2, 16.5]</td><td>&lt; 0.001</td></tr><tr><td>RVSP (mmHg, median [IQR])</td><td>23 [19, 28]</td><td>23 [19, 26]</td><td>22 [18, 26]</td><td>28 [22, 36]</td><td>27 [21, 32]</td><td>&lt; 0.001</td></tr><tr><td><em>CPET</em></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>PEAK VO2 (mL/kg/min, mean [SD])</td><td>16.26 (4.84)</td><td>16.52 (4.91)</td><td>16.35 (4.58)</td><td>16.38 (5.27)</td><td>14.34 (3.99)</td><td>0.003</td></tr><tr><td>Duration of CPET (min, mean ± SD)</td><td>9.88 (2.86)</td><td>9.98 (2.79)</td><td>10.08 (2.94)</td><td>9.80 (3.07)</td><td>8.97 (2.49)</td><td>0.02</td></tr><tr><td>Peak RER (mean ± SD)</td><td>1.16 (0.10)</td><td>1.16 (0.10)</td><td>1.17 (0.11)</td><td>1.15 (0.11)</td><td>1.16 (0.10)</td><td>0.22</td></tr></tbody></table>

AI/AN - American Indian/Alaskan native, RER = respiratory exchange rate
most distinct from the other groups (Appendix Table 3). These patients were older, more likely to be female and from racial/ethnic minority groups, with the highest average blood pressure (BP) and NT pro-BNP, and the most cardiac dysfunction and LV hypertrophy. The mixed group had the greatest proportion with impaired functional capacity (Fig. 2) (Table 2).

## Baseline features associated with phenotypic groups

The association of clinical, echocardiographic and exercise variables with the phenogroups and their underlying physiologic variables are summarized in Tables 3 and 4, respectively. Age and male sex were associated with LVMI, diastolic parameters and NT-proBNP, but they were not strongly associated with phenogroups. However, there were significant associations between race and hsTnT. Although blood pressure was independently associated with GLS, E/e' and NT-pro-BNP, systolic BP was only associated with the overlap group. Exercise capacity was independently associated with GLS and diastolic

markers, and was only associated with the diastolic phenogroup (Fig. 3).

## Impaired baseline functional capacity

The limited reporting of symptoms typically associated with overt HF was confirmed by the KCCQ scores (Table 1). The selection process identified reduced functional capacity, evidenced by CPET results, and confirmed by PASE scores, in fewer than half of the screened patients. Nonetheless, substantial reduction of exercise capacity (to <75% predicted VO₂) required for entry into the ARISE-HF trial was more commonly seen in the echocardiographic phenotypes (Fig. 4) and among older individuals (Table 2) even in those with near-normal KCCQ or PASE scores. Patients with preserved exercise capacity (excluded from the trial) were more frequent in the abnormal biomarker group (62%), and less frequent in systolic and diastolic dysfunction and mixed groups (47 to 28%, *p* < 0.0001) (Fig. 4). Appendix Table 4 shows the similarities of patients with impaired and preserved exercise capacity within each of the phenogroups.

<figure><img src="image_5.png" /><figcaption>**Fig. 2** Proportion of participants with preserved and reduced exercise capacity according to baseline phenogroup. Reduced exercise capacity was most frequent in the mixed phenogroup</figcaption></figure>
<table><caption>**Table 2** Baseline characteristics of 1463 patients in the ARISE HF Trial</caption><thead><tr><th></th><th>Preserved exercise</th><th>Reduced exercise</th><th>p</th></tr></thead><tbody><tr><td>n</td><td>794</td><td>669</td><td></td></tr><tr><td>Age (mean (SD))</td><td>67.14 (7.82)</td><td>67.46 (7.14)</td><td>0.43</td></tr><tr><td>Male sex (%)</td><td>460 (57.9)</td><td>337 (50.4)</td><td>0.005</td></tr><tr><td>Race (%)</td><td></td><td></td><td>0.15</td></tr><tr><td>White</td><td>501 (63.1)</td><td>424 (63.4)</td><td></td></tr><tr><td>Hispanic</td><td>154 (19.4)</td><td>146 (21.8)</td><td></td></tr><tr><td>Black</td><td>75 (9.4)</td><td>41 (6.1)</td><td></td></tr><tr><td>Asian</td><td>50 (6.3)</td><td>49 (7.3)</td><td></td></tr><tr><td>AI/AN</td><td>2 (0.3)</td><td>3 (0.4)</td><td></td></tr><tr><td>Other</td><td>12 (1.5)</td><td>6 (0.9)</td><td></td></tr><tr><td>SBP (mmHg, mean [SD])</td><td>132.94 (18.04)</td><td>129.17 (11.22)</td><td>&lt;0.001</td></tr><tr><td>DBP (mmHg, mean [SD])</td><td>76.46 (10.32)</td><td>75.84 (8.29)</td><td>0.37</td></tr><tr><td>NT-proBNP (ng/L, median [IQR])</td><td>80.00 [42.00, 142.00]</td><td>73.00 [37.00, 136.00]</td><td>0.18</td></tr><tr><td>hs-cTnt (ng/L, median [IQR])</td><td>10.00 [7.00, 15.00]</td><td>9.00 [6.00, 12.00]</td><td>&lt;0.001</td></tr><tr><td>HbA1 (%, mean [SD])</td><td>7.35 (1.38)</td><td>6.98 (0.79)</td><td>&lt;0.001</td></tr><tr><td>Hgb (g/dL, mean [SD])</td><td>13.69 (1.54)</td><td>13.66 (1.40)</td><td>0.69</td></tr><tr><td>eGFR (mL/min/1.73 m2, mean [SD])</td><td>76.72 (19.40)</td><td>80.20 (16.15)</td><td>&lt;0.001</td></tr><tr><td>LVEF (%, median [IQR])</td><td>62.00 [58.00, 65.00]</td><td>62.00 [59.00, 66.00]</td><td>0.10</td></tr><tr><td>GLS (%, median [IQR])</td><td>-17.10 [-19.10, -14.90]</td><td>-17.70 [-19.50, -15.10]</td><td>0.10</td></tr><tr><td>LAVI (ml/m², median [IQR])</td><td>22.90 [18.90, 27.80]</td><td>23.50 [19.10, 29.00]</td><td>0.12</td></tr><tr><td>LVMI (g/m², median [IQR])</td><td>72.00 [61.00, 88.00]</td><td>74.00 [64.00, 88.30]</td><td>0.05</td></tr><tr><td>E/e' (median [IQR])</td><td>9.10 [7.50, 11.20]</td><td>9.40 [7.80, 11.90]</td><td>0.002</td></tr><tr><td>RVSP (mmHg, median [IQR])</td><td>23.15 [19.00, 27.50]</td><td>23.40 [19.02, 27.67]</td><td>0.77</td></tr><tr><td>Peak VO2 (mL/kg/min, mean [SD])</td><td>17.99 (6.82)</td><td>15.68 (3.80)</td><td>&lt;0.001</td></tr><tr><td>Duration of CPET (min, mean ± SD)</td><td>10.28 (3.87)</td><td>9.75 (2.41)</td><td>0.02</td></tr><tr><td>Peak RER (mean ± SD)</td><td>1.11 (0.11)</td><td>1.18 (0.10)</td><td>&lt;0.001</td></tr></tbody></table>

The patients are divided into those with preserved (“screen failed”) and reduced exercise capacity

<table><caption>**Table 3** Association of variables with the phenotypic cluster</caption><thead><tr><th rowspan="2"></th><th colspan="2">Elevated Biomarkers</th><th colspan="2">Systolic/LVH</th><th colspan="2">Diastolic</th><th colspan="2">Overlap</th></tr><tr><th>Odds Ratio<br>(95% CI)</th><th>p</th><th>Odds Ratio<br>(95% CI)</th><th>p</th><th>Odds Ratio<br>(95% CI)</th><th>p</th><th>Odds Ratio<br>(95% CI)</th><th>p</th></tr></thead><tbody><tr><td>Male sex</td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.25 (0.12-0.51)</td><td>&lt;0.001</td></tr><tr><td>SBP (mmHg, mean [SD])</td><td></td><td></td><td></td><td></td><td></td><td></td><td>1.03 (1.00-1.05)</td><td>0.05</td></tr><tr><td>DBP (mmHg, mean [SD])</td><td>1.03 (1.01-1.04)</td><td>0.003</td><td>0.98 (0.96-1.00)</td><td>0.08</td><td></td><td></td><td>0.95 (0.91-1.00)</td><td>0.03</td></tr><tr><td>NT-proBNP (ng/L, median [IQR])*</td><td>1.31 (1.13-1.51)</td><td>&lt;0.001</td><td>0.60 (0.49-0.73)</td><td>&lt;0.001</td><td></td><td></td><td></td><td></td></tr><tr><td>hs-cTnt (ng/L, median [IQR])*</td><td>1.33 (1.04-1.70)</td><td>0.02</td><td>0.66 (0.48-0.92)</td><td>0.01</td><td>1.54 (1.05-2.27)</td><td>0.03</td><td>0.59 (0.34-1.02)</td><td>0.05</td></tr><tr><td>LVEF (%, median [IQR])</td><td>0.97 (0.94-1.00)</td><td>0.08</td><td>1.04 (1.00-1.07)</td><td>0.06</td><td>0.95 (0.91-1.00)</td><td>0.04</td><td>1.07 (1.01-1.14)</td><td>0.03</td></tr><tr><td>GLS (%, median [IQR])</td><td>0.52 (0.48-0.57)</td><td>&lt;0.001</td><td>3.39 (2.90-3.96)</td><td>&lt;0.001</td><td>0.69 (0.62-0.76)</td><td>&lt;0.001</td><td>1.61 (1.41-1.85)</td><td>&lt;0.001</td></tr><tr><td>LAVI (ml/m², median [IQR])</td><td>0.92 (0.89-0.94)</td><td>&lt;0.001</td><td>0.92 (0.88-0.95)</td><td>&lt;0.001</td><td>1.20 (1.16-1.25)</td><td>&lt;0.001</td><td>1.14 (1.09-1.19)</td><td>&lt;0.001</td></tr><tr><td>LVMI (g/m², median [IQR])</td><td>0.97 (0.96-0.98)</td><td>&lt;0.001</td><td>1.05 (1.04-1.07)</td><td>&lt;0.001</td><td>0.95 (0.94-0.97)</td><td>&lt;0.001</td><td>1.06 (1.04-1.08)</td><td>&lt;0.001</td></tr><tr><td>E/e' (median [IQR])</td><td>0.76 (0.72-0.82)</td><td>&lt;0.001</td><td>0.69 (0.63-0.76)</td><td>&lt;0.001</td><td>1.39 (1.29-1.50)</td><td>&lt;0.001</td><td>1.36 (1.23-1.51)</td><td>&lt;0.001</td></tr><tr><td>RVSP (mmHg, median [IQR])</td><td>0.93 (0.91-0.95)</td><td>&lt;0.001</td><td>0.94 (0.91-0.97)</td><td>&lt;0.001</td><td>1.17 (1.13-1.21)</td><td>&lt;0.001</td><td>1.07 (1.02-1.12)</td><td>0.004</td></tr><tr><td>Peak VO2 (mL/kg/min, mean [SD])</td><td>1.03 (1.00-1.06)</td><td>0.07</td><td>0.97 (0.93-1.01)</td><td>0.15</td><td>1.06 (1.01-1.11)</td><td>0.02</td><td></td><td></td></tr></tbody></table>

Age, race, GFR, Hb, HbA1C, exercise duration and RER were not associated *NT-proBNP and hs-cTnt are log-transformed

## Follow-up functional capacity

The evolution of functional capacity according to phenogroup of patients with DbMD and reduced baseline functional capacity is shown in Appendix Table 5. Although functional capacity remained worst in the overlap group, the changes in functional capacity was similar (Fig. 3), as were changes in PASE and KCCQ scores.

## Discussion

In this study of HF risk evaluation, abnormal echocardiograms and/or biomarkers were identified in 79% of >1800 patients with T2DM with heightened risk of HF despite a lack of manifest ischemic heart disease and with adequate glycemic control and blood pressure. The phenotypic presentation of this group with DbMD was
<table><caption>**Table 4** Association of clinical, echocardiographic and exercise variables with key components of the phenotypes</caption><thead><tr><th rowspan="2"></th><th colspan="2">GLS</th><th colspan="2">LVMI</th><th colspan="2">E/e'</th><th colspan="2">LAVI</th><th colspan="2">NTproBNP</th><th colspan="2">hs-cTnt</th></tr><tr><th>β</th><th>p</th><th>β</th><th>p</th><th>β</th><th>p</th><th>β</th><th>p</th><th>β</th><th>p</th><th>β</th><th>p</th></tr></thead><tbody><tr><td>Age</td><td>0.011</td><td>0.25</td><td>-0.176</td><td>0.004</td><td>0.035</td><td>0.001</td><td>0.843</td><td>0.01</td><td>0.015</td><td>&lt;0.001</td><td>0.491</td><td>&lt;0.001</td></tr><tr><td>Male sex</td><td></td><td></td><td>3.852</td><td>&lt;0.001</td><td>-0.812</td><td>&lt;0.001</td><td></td><td></td><td>-0.298</td><td>&lt;0.001</td><td>-0.071</td><td>0.05</td></tr><tr><td>Hispanic^</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.138</td><td>0.007</td></tr><tr><td>Black^</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.065</td><td>0.24</td></tr><tr><td>Asian^</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.608</td><td>0.009</td></tr><tr><td>AI/AN^</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.112</td><td>0.37</td></tr><tr><td>Other^</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>SBP (mmHg, mean (SD))</td><td>-0.014</td><td>0.004</td><td></td><td></td><td>0.013</td><td>0.04</td><td></td><td></td><td>0.011</td><td>&lt;0.001</td><td></td><td></td></tr><tr><td>DBP (mmHg, mean (SD)mean (SD))</td><td></td><td></td><td></td><td></td><td>-0.022</td><td>0.03</td><td></td><td></td><td>-0.013</td><td>&lt;0.001</td><td></td><td></td></tr><tr><td>NT-proBNP (ng/L, median (IQR))*</td><td></td><td></td><td></td><td></td><td>-0.147</td><td>0.05</td><td>0.738</td><td>&lt;0.001</td><td>0.265</td><td>&lt;0.001</td><td>0.091</td><td>&lt;0.001</td></tr><tr><td>hs-cTnt (ng/L, median (IQR))*</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>HbA1 (%, mean (SD))</td><td>0.046</td><td>0.34</td><td>-0.636</td><td>0.15</td><td>1.719</td><td>0.03</td><td>0.103</td><td>0.08</td><td></td><td></td><td></td><td></td></tr><tr><td>eGFR (mL/min/1.73 m2, mean (SD))</td><td></td><td></td><td>-0.594</td><td>0.08</td><td></td><td></td><td></td><td></td><td>0.026</td><td>0.005</td><td></td><td></td></tr><tr><td>LVEF (%, median (IQR))</td><td>-0.211</td><td>&lt;0.001</td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.241</td><td>&lt;0.001</td><td></td><td></td></tr><tr><td>GLS (%, median (IQR))</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>LAVI (ml/m², median (IQR))</td><td>-0.038</td><td>&lt;0.001</td><td>0.596</td><td>&lt;0.001</td><td>0.131</td><td>&lt;0.001</td><td></td><td></td><td>0.016</td><td>&lt;0.001</td><td></td><td></td></tr><tr><td>LVMI (g/m², median (IQR))</td><td>0.015</td><td>&lt;0.001</td><td>0.958</td><td>&lt;0.001</td><td>0.052</td><td>&lt;0.001</td><td></td><td></td><td>-0.020</td><td>0.02</td><td>0.002</td><td>&lt;0.001</td></tr><tr><td>E/e' (median (IQR))</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.626</td><td>&lt;0.001</td><td>0.012</td><td>&lt;0.001</td></tr><tr><td>RVSP (mmHg, median (IQR))</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>PEAK VO2 (mL/kg/min, mean (SD))</td><td>-0.045</td><td>0.02</td><td></td><td></td><td>0.040</td><td>&lt;0.001</td><td></td><td></td><td>0.126</td><td>0.008</td><td></td><td>0.003</td><td>0.07</td></tr><tr><td>Duration of CPET (min, mean ± SD)</td><td>0.039</td><td>0.27</td><td></td><td></td><td>-0.094</td><td>&lt;0.001</td><td></td><td></td><td>-0.172</td><td>0.04</td><td></td><td>-0.021</td><td>&lt;0.001</td></tr><tr><td>Peak RER (mean ± SD)</td><td></td><td></td><td></td><td></td><td>0.061</td><td>0.12</td><td></td><td></td><td></td><td></td><td></td><td>-0.570</td><td>&lt;0.001</td></tr></tbody></table>

<footnote>^Associations for race are referenced to white participants. *NT-proBNP and hs-cTnt are log-transformed</footnote>
heterogeneous, with the most common being abnormal biomarkers in the absence of echocardiographic abnormalities, followed by DD (alone or with systolic dysfunction), and a smaller group of isolated systolic dysfunction and/or LV hypertrophy. Reduced functional capacity was present in 46%, but this was also heterogeneous between groups - only 38% of patients with abnormal biomarkers, but >50% of those with isolated and >70% of those with multiple echocardiographic abnormalities. These findings suggest that a range of biological processes underlie DbMD. The follow-up data show that the evolution of functional capacity was similar, perhaps because patients were selected on the basis of impaired baseline functional capacity.

## Significance of subclinical dysfunction

Waiting for symptoms to develop before treating a patient with HF carries the risk that the underlying cardiac pathology may be too advanced to make a substantive response to disease-modifying therapy. The asymptomatic nature of early-stage HF is the basis of the recent American Diabetes Association recommendation to screen for HF in DM [2], so as to initiate cardioprotective treatments to prevent progression to overt HF. However, the potential disadvantage of a HF screening strategy is that effort and cost may be directed towards

patients at low risk. Patients with DM are a readily-defined “at risk” group for HF [19], and may constitute an appropriate group for testing the concept of early recognition and treatment of Stage B HF [3]. These results indicate that selection of patients with T2DM at risk of HF, based on age, DM duration or renal impairment provides a very high frequency of abnormal studies (79%), very similar to the 81% prevalence of SBHF in the ARIC study HF [20]. The findings of most functional compromise in patients with both abnormal echo and biomarkers in this study also matched the outcomes in a 7-year follow-up of ARIC, which showed that SBHF defined by echocardiography (7%) or biomarkers (8.5%) were modestly associated with increased HF risk, with patients with both signals having the highest risk for HF (23%) [20]. Both results point towards a high prevalence of SBHF with the application of current definitions—many of these patients will not progress to HF. Using a combination of multiple physiologic parameters could identify a manageable subgroup at risk for progression to overt HF.

The definition of DbMD is variable. From a mechanistic standpoint, DbMD is associated with oxidative stress, vascular inflammation and endothelial dysfunction [21]. These phenomena may be evidenced by changes in myocardial mechanics (hence, abnormal GLS), and release of natriuretic peptides. Several recent studies have shown

3.

<figure><img src="image_6.png" /><figcaption>**Fig. 3.** Baseline, 15-month and change in peak VO₂ in each phenogroup. While the 15-month VO₂ was significantly lower (p = 0.001) in the overlap than the other groups, the changes were similar in each phenogroup</figcaption></figure>
gradations of prevalence, prognosis and potential therapeutic response with categories based on abnormal biomarkers and/or echocardiography [22], different degrees of echocardiographic disturbance [23], and their combination [24]. This study adds to these observations by showing gradations in functional disturbance using the same approach. While the cut-points for all of these parameters is arbitrary, it was reassuring to find that the biomarker and echocardiographic groups showed similar differences at the two selected cut-offs.

### Impaired functional capacity

The underlying mechanisms of heart muscle disease in our study participants may also contribute to impaired functional capacity (evidenced in this study by lower PASE score and VO₂)– a common finding in SBHF [25] despite the asymptomatic state of these patients (evidenced here by minimal abnormalities of KCCQ). While echocardiographic [13, 24], biomarker [26] and exercise data [27] have prognostic significance in this setting, none of these associations are specific for DbMD. Reduced VO₂ in particular may be driven by DM-related pathology throughout the oxygen transport system, including pulmonary, cardiovascular and skeletal muscle complications [25]. Nonetheless, the point remains that none are exclusively found in early DbMD– implying that

a screening process may need to include multiple physiologic modalities.

Among those considered in this analysis, 691 with impaired functional capacity (arguably a more advanced population with DbMD) were randomized to receive AT-001, a highly-potent aldose reductase inhibitor. Interestingly, the frequency of lower functional capacity varied according to the phenotype of DbMD. However, aldose reductase therapy did not stabilize exercise capacity– either in the group overall or in the phenotypic subgroups. These remained stable over follow-up, there was no difference in the evolution of exercise impairment among those with reduced exercise capacity at baseline.

### Strengths and limitations

This study provides detailed phenotyping of a large number of patients with T2DM at risk of HF, but with good glycemic and BP control. The results are obtained from the baseline assessment of a clinical trial, and this provides the benefit of uniform acquisition and interpretation provided by core-laboratories for echocardiography and cardiopulmonary testing. In clinical practice, the phenotypes could be modified by less adequate glycemic and BP control, and co-existent chronic kidney disease and other comorbidities, whereas a common feature of trials is the selection of patients with controlled glycemia

Central illustration.

<figure><img src="image_7.png" /><figcaption>**Fig. 4** Central illustration: Distribution of abnormal biomarkers and echocardiograms in 1463 patients with diabetes-related myocardial dysfunction (DbMD) who had no history or symptoms of CVD, and in the subgroup with reduced functional capacity. Impaired exercise capacity was more common in those with abnormal echocardiography (especially with multiple abnormalities) and less frequent in those with isolated abnormal biomarkers (p < 0.0001)</figcaption></figure>
and blood pressure. On the other hand, the control of these aspects does enable the analysis to evaluate the underlying myocardial consequences of DbMD, rather the acute responses of the myocardium to metabolic disturbance. The lack of association of the phenogroups with progression of exercise may reflect the level of baseline impairment in all participants undergoing follow-up; only participants with impaired exercise capacity were followed up after 12 months.

## Conclusions

These results from the ARISE-HF trial show a high prevalence of SBHF, as well as heterogeneity of echocardiography, biomarkers and exercise capacity in early DbMD. However, a small group of patients with multiple underlying pathophysiologies have the most impaired functional capacity.

## Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12933-024-02554-y.

Supplementary Material 1

## Acknowledgements

The ARISE-HF Trial is supported by Applied Therapeutics, Inc.

## Author contributions

THM wrote the manuscript, with review/revision based on input from the rest of the authors. All authors provided substantial contributions to the conception and design of this manuscript.YL performed data analyses. All authors participated in interpretation of the data. All authors have approved the paper and agree to be personally accountable for their contributions.

## Funding

This work was supported by Applied Therapeutics, New York, NY. TM is supported by an Investigator Grant from the National Health and Medical Research Council of Australia (ID: 2008129). Supported in part by The Victorian Government's Operational Infrastructure Support Program. Dr. Lam is supported by a Clinician Scientist Award from the National Medical Research Council of Singapore; Dr. Januzzi is supported in part by the Adolph Hutter Professorship.

## Data availability

No datasets were generated or analysed during the current study.

## Declarations

### Competing interests

Dr Marwick has received research support from General Electric Medical Systems, and is on the Steering Committee for the ARISE-HF trial (Applied Therapeutics). Dr Lam has received research support from NovoNordisk and Roche Diagnostics; has Served as consultant or on the Advisory Board/ Steering Committee/ Executive Committee for Alleviant Medical, Allysta Pharma, AnaCardio AB, Applied Therapeutics, AstraZeneca, Bayer, Bioethics, Boehringer Ingelheim, Boston Scientific, Bristol Myers Squibb, CardioRenal, Cytokinetics, Darma Inc., EchoNous Inc, Eli Lilly, Impulse Dynamics, Intellia Therapeutics, Ionis Pharmaceutical, Janssen Research & Development LLC, Medscape/WebMD Global LLC, Merck, Novartis, Novo Nordisk, Prosciento Inc, Quidel Corporation, Radcliffe Group Ltd., Recardio Inc, ReCor Medical, Roche Diagnostics, Sanofi, Siemens Healthcare Diagnostics and Us2.ai; and serves as co-founder & non-executive director of Us2.ai. Ms. Liu has no disclosures. Dr. Del Prato has served as president of EASD/European Foundation for the Study

of Diabetes (EFSD) (2020–2022); has received research grants to the institution from AstraZeneca and Boehringer Ingelheim; has served as advisor for Abbott, Amarin Corporation, Applied Therapeutics, AstraZeneca, Boehringer Ingelheim, Eli Lilly & Co., EvaPharma, Jiangsu Hengrui Pharmaceuticals Co., Menarini International, Merck Sharpe & Dohme, Novartis Pharmaceutical Co., Novo Nordisk, Sanofi and Sun Pharmaceuticals; and has received fees for speaking from AstraZeneca, Boehringer Ingelheim, Eli Lilly & Co., Laboratori Guidotti, Menarini Itarnational, Merck Sharpe & Dohme and Novo Nordisk. Dr. Rosenstock has served on scientific advisory boards and received honorarium or consulting fees from Applied Therapeutics, Biomea Fusion, Boehringer Ingelheim, Eli Lilly, Endogenex, Hanmi, Novo Nordisk, Oramed, Regor, Sanofi, Scholar Rock, Structure Therapeutics, Terns Pharma and Zealand; and has received grants/research support from Applied Therapeutics, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Hanmi, Merck, Oramed, Novartis, Novo Nordisk, Pfizer and Sanofi. Dr. Butler is a consultant to Abbott, American Regent, Amgen, Applied Therapeutic, AskBio, Astellas, AstraZeneca, Bayer, Boehringer Ingelheim, Boston Scientific, Bristol Myers Squibb, Cardiac Dimension, Cardiocell, Cardior, CSL Bearing, CVRx, Cytokinetics, Daxor, Edwards, Element Science, Faraday, Foundry, G3P, Innolife, Impulse Dynamics, Imbria, Inventiva, Ionis, Lexicon, Lilly, LivaNova, Janssen, Medtronics, Merck, Occlutech, Owkin, Novartis, Novo Nordisk, Pfizer, Pharmacosmos, Pharmain, Pfizer, Prolaio, Regeneron, Renibus, Roche, Salamandra, Sanofi, SC Pharma, Secretome, Sequana, SQ Innovation, Tenex, Tricog, Ultrromics, Vifor, and Zoll; Dr. Ezekowitz reports research support for trial leadership or grants from American Regent, Applied Therapeutics, AstraZeneca, Bayer, Cytokinetics, Merck & Co, Novo Nordisk, Otsuka; honoraria for consultancy from AstraZeneca, Bayer, Boehringer Ingelheim, Novartis, Novo Nordisk, Otsuka; serves as an advisor to US2.aiDr. Ibrahim reports consulting income from Cytokinetics and honoraria from Applied Therapeutics; Dr. Tang is a consultant for Sequana Medical, Cardiol Therapeutics Inc, Genomics plc, Zehna Therapeutics, Boston Scientific, WhiteSwell, Kiniksa Pharmaceuticals, Intellia Therapeutics, CardiaTec Biosciences, Bristol Myers Squibb, Alleviant Medical, and has received honorarium from Springer, Belvoir Media Group, and American Board of Internal Medicine; Dr. Zannad reports personal fees from 89bio, Applied Therapeutics, Bayer, Betagenon, Bioethics, Boehringer, BMS, CVRx, Cardior, Cambrian, Cereno pharmaceutical, Cellprothera, CEVA, Merck, Northsea, Novartis, NovoNordisk, Otsuka, Owkin, Salubris, Servier, having stock options at G3Pharmaceutical and equities at Cereno pharmaceutical, Cardiorenal, Eshmoun Clinical research and being the founder of CVCT. Dr Perfetti is an employee of Applied Therapeutics, Inc. Dr. Januzzi is a Trustee of the American College of Cardiology, is a Board Member of Imbia Pharmaceuticals, is a director at Jana Care, has received research support from Abbott, Applied Therapeutics, HeartFlow Inc, Innolife and Roche Diagnostics, consulting income from Abbott, AstraZeneca, Bayer, Beckman, Boehringer-Ingelheim, Janssen, Novartis, Merck, and Roche Diagnostics, and participates in clinical endpoint committees/data safety monitoring boards for Abbott, AbbVie, Bayer, CVRx, Intercept, Pfizer and Takeda.

## Author details

<footnote n="1">¹Baker Heart and Diabetes Institute, Melbourne and Menzies Institute for Medical Research, Hobart, Australia</footnote>

<footnote n="2">²National Heart Centre Singapore and Duke-National University of Singapore, Singapore, Singapore</footnote>

<footnote n="3">³Cardiology Division, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA</footnote>

<footnote n="4">⁴Interdisciplinary Research Center “Health Science”, Sant’Anna School of Advanced Studies, Pisa, Italy</footnote>

<footnote n="5">⁵Southwestern Medical Center, Velocity Clinical Research at Medical City and University of Texas, Dallas, TX, USA</footnote>

<footnote n="6">⁶Baylor Scott and White Research Institute, Dallas, TX, USA</footnote>

<footnote n="7">⁷University of Mississippi, Jackson, MS, USA</footnote>

<footnote n="8">⁸Canadian VIGOUR Centre, University of Alberta, Edmonton, AB, Canada</footnote>

<footnote n="9">⁹Cardiology Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA</footnote>

<footnote n="10">¹⁰Department of Cardiovascular Medicine, Heart Vascular and Thoracic Institute, Cleveland Clinic, Cleveland, OH, USA</footnote>

<footnote n="11">¹¹CIC Inserm and CHRU Nancy, Université de Lorraine, Metz, France</footnote>

<footnote n="12">¹²Applied Therapeutics Inc., New York, NY, USA</footnote>

<footnote n="13">¹³Heart Failure Trials, Baim Institute for Clinical Research, Boston, USA</footnote>

<footnote n="14">¹⁴Baker Heart and Diabetes Institute, 75 Commercial Road, Melbourne, VIC 3004, Australia</footnote>
Received: 27 October 2024 / Accepted: 19 December 2024

Published online: 13 January 2025

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