# The role of TAPSE/sPAP ratio in predicting pulmonary hypertension and mortality in the systemic sclerosis EUSTAR cohort.

Amalia Colalillo, Anna-Maria Hoffmann-Vold, Chiara Pellicano, Antonella

Romaniello, Armando Gabrielli, Eric Hachulla, Vanessa Smith, Carmen-Pilar

Simeón-Aznar, Ivan Castellví, Paolo Airò, et al.

► To cite this version:

Amalia Colalillo, Anna-Maria Hoffmann-Vold, Chiara Pellicano, Antonella Romaniello, Armando Gabrielli, et al. The role of TAPSE/sPAP ratio in predicting pulmonary hypertension and mortality in the systemic sclerosis EUSTAR cohort. Autoimmunity Reviews, 2023, Autoimmunity Reviews, 22, pp.103290. 10.1016/j.autrev.2023.103290. hal-04488026

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# The role of TAPSE/sPAP ratio in predicting pulmonary hypertension and mortality in the systemic sclerosis EUSTAR cohort

Amalia Colalillo<sup>a</sup>, Anna-Maria Hoffmann-Vold<sup>b</sup>, Chiara Pellicano<sup>a</sup>, Antonella Romaniello<sup>c</sup>, Armando Gabrielli<sup>d</sup>, Eric Hachulla<sup>e</sup>, Vanessa Smith<sup>f</sup>, Carmen-Pilar Simeón-Aznar<sup>g</sup>, Ivan Castellví<sup>h</sup>, Paolo Airò<sup>i</sup>, Marie-Elise Truchetet<sup>j</sup>, Elise Siegert<sup>k,1</sup>, Oliver Distler<sup>m</sup>, Edoardo Rosato<sup>a,*</sup>, the EUSTAR collaborators

<figure><img src="image_3.png" /></figure>

## ARTICLE INFO

**Keywords:**

TAPSE/sPAP ratio

Systemic sclerosis

Pulmonary hypertension

Right ventricle

## ABSTRACT

**Objectives:** The study aim was to evaluate the predictive role of the echocardiography-derived tricuspid annular plane systolic excursion/systolic pulmonary artery pressure (TAPSE/sPAP) ratio for pulmonary hypertension (PH) diagnosis and mortality in the European Scleroderma Trials and Research (EUSTAR) cohort.

**Methods:** Eligible patients were systemic sclerosis (SSc) patients registered in the EUSTAR database with at least one visit recording TAPSE and sPAP data. Individual centres were required to provide TAPSE and sPAP data at 12 ± 3 months before right heart catheterization (RHC). Logistic regression analysis was applied to analyse the predictive ability of TAPSE/sPAP ratio for PH diagnosis. Cox regression analysis was performed to evaluate TAPSE/sPAP ratio as a predictive factor for all-cause mortality.

**Results:** 2555 SSc patients met the inclusion criteria for this study with 355 SSc patients having available RHC data at baseline. PH was confirmed by RHC in 195 SSc patients (54.9%). TAPSE/sPAP ratio < 0.55 mm/mmHg [OR 0.251 (95% CI 0.084–0.753), *p* < 0.05] and FVC/DL~CO~ [OR 2.568 (95% CI 1.227–5.375), *p* < 0.05] were significantly associated with PH diagnosis. In logistic regression analysis with echocardiographic parameters at 12 ± 3 months before RHC, TAPSE/sPAP ratio < 0.55 mm/mmHg [OR 0.265 (95% CI 0.102–0.685), *p* < 0.01] and FVC/DL~CO~ [OR 2.529 (95% CI 1.358–4.711), *p* < 0.01] were associated with PH diagnosis. In multivariate Cox regression analysis, TAPSE/sPAP ratio ≤ 0.32 mm/mmHg [HR 0.310 (0.164–0.585), *p* < 0.001] was the most significant predictive factor for death.

**Conclusions:** TAPSE/sPAP ratio < 0.55 mm/mmHg is a predictive risk factor for PH. TAPSE/sPAP ratio ≤ 0.32 mm/mmHg is a predictive risk marker for all-cause mortality.

<footnote><sup>a</sup> Department of Translational and Precision Medicine, Sapienza University of Rome, Rome, Italy</footnote>

<footnote><sup>b</sup> Department of Rheumatology, Oslo University Hospital, Oslo, Norway</footnote>

<footnote><sup>c</sup> Division of Cardiology, Sant'Andrea Hospital, Sapienza University of Rome, Rome, Italy</footnote>

<footnote><sup>d</sup> Fondazione di Medicina Molecolare e Terapia Cellulare, Università Politecnica delle Marche, Ancona, Italy</footnote>

<footnote><sup>e</sup> Department of Internal Medicine and Clinical Immunology, Referral Centre for Centre for rare systemic autoimmune diseases North and North-West of France (CeRAINO), CHU Lille, University of Lille, Inserm, U1286 - INFINITE - Institute for Translational Research in Inflammation, Lille, France</footnote>

<footnote><sup>f</sup> Department of Rheumatology, Ghent University Hospital, Ghent, Belgium</footnote>

<footnote><sup>g</sup> Unit of Autoimmune Diseases, Department of Internal Medicine, Hospital Universitario Vall d'Hebron, Barcelona, Spain</footnote>

<footnote><sup>h</sup> Department of Rheumatology, Hospital Universitari de la Santa Creu i Sant Pau, Barcelona, Spain</footnote>

<footnote><sup>i</sup> Rheumatology and Clinical Immunology Unit, ASST Spedali Civili of Brescia, Brescia, Italy</footnote>

<footnote><sup>j</sup> Department of Rheumatology, CHU de Bordeaux, Bordeaux, France</footnote>

<footnote><sup>k</sup> Department of Rheumatology and Clinical Immunology, Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt, Universität zu Berlin, Berlin, Germany</footnote>

<footnote><sup>l</sup> Berlin Institut of Health at Charité, Universitätsmedizin Berlin, Berlin, Germany</footnote>

<footnote><sup>m</sup> Department of Rheumatology, University Hospital Zürich, Zürich, Switzerland</footnote>

<footnote>**Abbreviations:** TAPSE/sPAP, tricuspid annular plane systolic excursion/systolic pulmonary artery pressure.</footnote>

<footnote>* Corresponding author at: Department of Translational and Precision Medicine, Sapienza University of Rome, Viale dell'Università 37, 00185 Rome, Italy.</footnote>

<footnote>**E-mail address:** edoardo.rosato@uniroma1.it (E. Rosato).</footnote>
# 1. Introduction

Pulmonary arterial hypertension (PAH) is a major cause of morbidity and mortality in systemic sclerosis (SSc), affecting approximately 6–12% of SSc patients [1–4]. Despite therapeutic advances, long-term survival is still disappointing [5,6]. Early diagnosis and treatment are crucial to significantly improve patient outcomes [7]. The echocardiography-estimated systolic pulmonary artery pressure (sPAP) has a key role in PAH annual screening. However, the diagnostic accuracy of echocardiography or other tests alone in detecting PAH is sub-optimal. The new 2022 pulmonary hypertension (PH) guidelines recommend the use of composite measures for PAH screening in SSc patients [8]. In particular, the DETECT algorithm, combining clinical features, echocardiography, pulmonary function tests (PFTs) and N-terminal pro-brain natriuretic peptide (NT-proBNP), improves diagnostic accuracy and patient selection for right heart catheterization (RHC) referral to confirm PAH diagnosis [8–10].

The right ventricular - pulmonary arterial (RV-PA) coupling describes the RV adaptation to its afterload. In PAH the progressive pulmonary vascular remodelling leads to an increasing pulmonary vascular resistance and pulmonary artery pressure, an additional load on the contracting RV and an altered RV-PA coupling [11,12]. Tricuspid annular plane systolic excursion/systolic pulmonary artery pressure (TAPSE/sPAP) ratio is the validated non-invasive estimation of RV-PA coupling easily obtained during a standard Doppler echocardiography [13].

A previous study on 51 SSc patients, comparing the positive predictive value (PPV) between a TAPSE/sPAP ratio of ≤0.60 mm/mmHg and the DETECT algorithm, suggested the potential utility of TAPSE/sPAP ratio in addition to the DETECT algorithm in selecting patients requiring RHC to confirm PAH diagnosis [14]. In the new 2022 pulmonary hypertension (PH) guidelines, the TAPSE/sPAP ratio has been included among the additional echocardiographic signs suggestive of PH [8]. However, to date, the role of TAPSE/sPAP ratio as a screening tool for PH in SSc patients is underinvestigated.

A previous European Scleroderma Trials and Research (EUSTAR) study showed that a sPAP >36 mmHg was significantly and independently associated with reduced survival in SSc patients [15]. The role of TAPSE/sPAP ratio in risk stratification and predicting mortality has already been described in several conditions, including heart failure and PH [16–22]. In patients with PH, a TAPSE/sPAP ratio < 0.31 mm/mmHg has been identified as the cut-off value discriminating RV-PA uncoupling and has been associated with a significantly worse prognosis [13]. Besides, TAPSE/sPAP ratio was independently associated with overall mortality in 290 patients with PAH and the worst overall survival was reported for a TAPSE/sPAP ratio < 0.19 mm/mmHg [21]. In the new 2022 PH guidelines, the TAPSE/sPAP ratio has been included among the echocardiographic parameters for 1-year mortality risk assessment [8]. To date, only a few studies with small sample size specifically investigated the prognostic role of TAPSE/sPAP ratio in SSc patients [23,24].

The primary aim of the study was to evaluate the RV-PA coupling by the echocardiography-derived TAPSE/sPAP ratio and to assess the predictive role of TAPSE/sPAP ratio in the diagnosis of PH in the SSc EUSTAR cohort. The secondary aim of the study was to evaluate the prognostic role of TAPSE/sPAP ratio in predicting mortality in the SSc EUSTAR cohort.

# 2. Materials and methods

## 2.1. Study design and inclusion criteria

The prospective cohort study was a post hoc analysis of data from the multinational EUSTAR database. The structure of the online database, the collected data set and definitions of clinical variables have been described in detail previously [1,25].

Patients registered since 2010 in the EUSTAR database (start of the online version), aged ≥18 years, who fulfilled the 2013 American College of Rheumatology/European League Against Rheumatism SSc classification criteria [26] and with available TAPSE and sPAP measurements on echocardiography at baseline were included. The first visit with available TAPSE and sPAP data was considered as the study baseline. TAPSE/sPAP ratio is not present in the EUSTAR database and was calculated for all SSc patients with recorded TAPSE and sPAP data. All-cause mortality was assessed in all SSc patients with available TAPSE and sPAP values at baseline. The time interval (months) between the date of study baseline and the date of death was calculated.

The presence of PH, reported in the EUSTAR database as PH “yes”, “no” or “unknown”, independently of RHC confirmation, was also evaluated in these patients.

The outcomes evaluated in this population were:

a. The predictive value of sPAP and TAPSE/sPAP ratio for all-cause mortality;

b. The association between sPAP and TAPSE/sPAP ratio and PH.

## 2.2. Patients with available RHC data

All SSc patients with available RHC data (mean PAP) at baseline were selected among enrolled patients. PH was defined by a mPAP >20 mmHg [8]. In all SSc patients with available RHC at baseline, TAPSE and sPAP values at 12 ± 3 months before RHC were also evaluated. TAPSE and sPAP measurements at 12 ± 3 months before RHC were not reported in the EUSTAR database. Principal investigators of individual centres were required to provide missing data. All-cause mortality was assessed in all SSc patients with available RHC data. The time interval (months) between the date of RHC and the date of death was calculated.

The outcomes evaluated in this population were:

a. The association between sPAP and TAPSE/sPAP ratio and PH diagnosis confirmed by RHC;

b. The predictive value of sPAP and TAPSE/sPAP ratio at 12 ± 3 months before RHC for PH diagnosis confirmed by RHC;

c. The predictive value of sPAP and TAPSE/sPAP ratio for all-cause mortality.

## 2.3. Echocardiographic data

sPAP was reported in mmHg and a value of >36 mmHg was considered increased [8,15,27]. TAPSE/sPAP ratio was expressed in mm/mmHg and a cut-off of <0.55 mm/mmHg for PH diagnosis was selected according to the new 2022 PH guidelines [8]. As for mortality risk assessment, a cut-off of TAPSE/sPAP ratio ≤ 0.32 mm/mmHg for intermediate-high risk of mortality and a cut-off of <0.19 for high risk of mortality were selected according to the new 2022 PH guidelines [8].

## 2.4. Statistical analysis

Statistical analysis was performed using IBM SPSS Statistics version 26. Data were reported as mean and standard deviation (SD); categorical data were represented as frequencies and proportions. Student's test was used to evaluate the difference between numerical variables. Chi-square test or Fisher's exact test were used to compare categorical variables. Receiver Operating Characteristic (ROC) curves were used to evaluate the diagnostic performance of sPAP and TAPSE/sPAP ratio. Univariate and multivariate logistic regression analyses with odds ratio (OR) and 95% confidence interval (CI) were applied to analyse the association between variables and PH at baseline and the predictive ability of variables for PH at 12 ± 3 months before RHC. The variables included in logistic regression analysis were: categorical variables [increased sPAP (yes or no), reduced TAPSE/sPAP ratio (yes or no)] and numerical variables [NT-proBNP (pg/mL), forced vital capacity/diffusing capacity
of the lungs for carbon monoxide (FVC/DL<sub>CO</sub>) and age (years)]. Overall survival (OS) data were represented by Kaplan-Meier curves and the log-rank test was used for statistical comparisons. Univariate Cox regression analysis was applied to evaluate the significant variables for overall survival. Multivariate Cox regression analysis was performed on the significant variables in univariate Cox regression analysis. Hazard Ratio (HR) and 95% CI were reported. A significance level of 0.05 was used for all tests.

## 3. Results

From the EUSTAR database, 2555 SSc patients met the inclusion criteria for this study. Demographic and clinical characteristics of all included 2555 SSc patients are reported in Table 1. sPAP and TAPSE/ sPAP ratio mean values were 30 ± 14 mmHg and 0.83 ± 0.30 mm/ mmHg, respectively. With a cut-off of >36 mmHg for sPAP, 513 (20.1%) SSc patients had an increased sPAP value. 460 (18%) SSc patients had a reduced TAPSE/sPAP ratio with a cut-off of <0.55 mm/mmHg; 152 (5.9%) and 39 (1.5%) SSc patients had a reduced TAPSE/sPAP ratio with a cut-off of ≤0.32 mm/mmHg and < 0.19 mm/mmHg, respectively.

### 3.1. Overall survival in all EUSTAR cohort

After excluding 107 (4.2%) SSc patients lost at follow-up, all-cause mortality was analyzed in 2448 (95.8%) SSc patients. Of these, 116 (4.7%) SSc patients died after a follow-up of 24.6 ± 21.5 months. The ROC curve analysis showed an AUC of 0.759 (0.709–0.809, *p* < 0.001) for sPAP and 0.765 (0.716–0.813, *p* < 0.001) for TAPSE/sPAP ratio.

Overall survival was evaluated with a cut-off of >36 mmHg for sPAP and a cut-off of ≤0.32 mm/mmHg for TAPSE/sPAP ratio. Kaplan Meier curves showed a higher mortality in SSc patients with increased sPAP (Log Rank χ² 124.1, *p* < 0.001) and in SSc patients with reduced TAPSE/ sPAP ratio (Log Rank χ² 105, *p* < 0.001). In univariate Cox regression

analysis, increased sPAP [HR 0.147 (0.099–0.217), *p* < 0.001], reduced TAPSE/sPAP ratio [HR 0.160 (0.107–0.240), *p* < 0.001] and age [HR 1.052 (1.035–1.069), *p* < 0.001]] were predictive factors for death; while male sex was not [HR 0.816 (0.512–1.301), *p* = 0.394]. In multivariate Cox regression analysis, increased sPAP [HR 0.252 (0.159–0.399), *p* < 0.001], reduced TAPSE/sPAP ratio [HR 0.460 (0.293–0.723), *p* < 0.01] and age [HR 1.030 (1.013–1.048), *p* < 0.01] were predictive factors for all-cause mortality.

Overall survival was also assessed with a cut-off of >36 mmHg for sPAP and a cut-off of <0.19 mm/mmHg for TAPSE/sPAP ratio. Kaplan Meier curves showed a higher mortality in SSc patients with increased sPAP (Log Rank χ² 124.1, *p* < 0.001) and in SSc patients with reduced TAPSE/sPAP ratio (Log Rank χ² 81.7, *p* < 0.001). In univariate Cox regression analysis, increased sPAP [HR 0.147 (0.099–0.217), *p* < 0.001], reduced TAPSE/sPAP ratio [HR 0.111 (0.063–0.199), *p* < 0.001] and age [HR 1.052 (1.035–1.069), *p* < 0.001]] were predictive factors for death; while sex was not [HR 0.816 (0.512–1.301), *p* = 0.394]. In multivariate Cox regression analysis, increased sPAP [HR 0.215 (0.140–0.329), *p* < 0.001], reduced TAPSE/sPAP ratio [HR 0.330 (0.181–0.600), *p* < 0.001] and age [HR 1.029 (1.012–1.047), *p* < 0.01] were predictive factors for all-cause mortality.

### 3.2. Echocardiographic parameters in SSc patients with available PH data

TAPSE, sPAP and PH (yes or no) data were available in 664 (26%) SSc patients at baseline. In this group of patients, PH was reported as present in 307 (46.2%) SSc patients. Demographic and clinical characteristics of 664 SSc patients with available PH data are reported in Table 1.

The mean values of sPAP and TAPSE/sPAP ratio were 41 ± 19 mmHg and 0.61 ± 0.28 mm/mmHg, respectively. Analyzing PH data, a cut-off of >36 mmHg for sPAP and a cut-off of <0.55 mm/mmHg for TAPSE/sPAP ratio were selected. In this group of SSc patients, 322

<table><caption>**Table 1**
Demographic and clinical characteristics of systemic sclerosis (SSc) patients.</caption><thead><tr><th rowspan="2"></th><th colspan="2">TAPSE and sPAP data available at baseline (n = 2555)</th><th colspan="2">PH data (yes or no) available at baseline (n = 664)</th><th colspan="3">RHC data available at baseline (n = 355)</th></tr><tr><th>Results</th><th>N</th><th>Results</th><th>N</th><th>T<sub>0</sub></th><th>T(-1)</th><th>N</th></tr></thead><tbody><tr><td>Age, years, mean ± SD</td><td>62 ± 14</td><td>2555</td><td>67 ± 12</td><td>664</td><td>69 ± 11</td><td>68 ± 11</td><td>355</td></tr><tr><td>Male, n (%)</td><td>414 (16.2)</td><td>2555</td><td>125 (18.8)</td><td>664</td><td>59 (16.6)</td><td>N.A.</td><td>355</td></tr><tr><td>Disease duration, years, mean ± SD</td><td>14 ± 10</td><td>2215</td><td>17 ± 10</td><td>592</td><td>16 ± 11</td><td>N.A.</td><td>302</td></tr><tr><td>Limited cutaneous SSc, n (%)</td><td>1479 (70.5)</td><td>2097</td><td>349 (64.7)</td><td>539</td><td>196 (70.5)</td><td>N.A.</td><td>278</td></tr><tr><td>Diffuse cutaneous SSc, n (%)</td><td>618 (29.5)</td><td>2097</td><td>190 (35.3)</td><td>539</td><td>82 (29.5)</td><td>N.A.</td><td>278</td></tr><tr><td>ACA, n (%)</td><td>815 (43.9)</td><td>1857</td><td>206 (41.3)</td><td>499</td><td>123 (48.2)</td><td>N.A.</td><td>255</td></tr><tr><td>Scl-70, n (%)</td><td>628 (33.5)</td><td>1876</td><td>166 (33.2)</td><td>500</td><td>70 (27)</td><td>N.A.</td><td>259</td></tr><tr><td>RNA Pol III, n (%)</td><td>138 (9.5)</td><td>1448</td><td>23 (6.2)</td><td>373</td><td>13 (6.2)</td><td>N.A.</td><td>210</td></tr><tr><td>mRSS, mean ± SD</td><td>6 ± 8</td><td>1916</td><td>8 ± 8</td><td>462</td><td>8 ± 8</td><td>N.A.</td><td>206</td></tr><tr><td>Digital ulcers history, n (%)</td><td>1075 (45.5)</td><td>2364</td><td>301 (52.3)</td><td>575</td><td>154 (50.8)</td><td>N.A.</td><td>303</td></tr><tr><td>Tendon friction rubs, n (%)</td><td>87 (3.6)</td><td>2394</td><td>33 (5.6)</td><td>591</td><td>16 (5.4)</td><td>N.A.</td><td>296</td></tr><tr><td>Telangiectasias, n (%)</td><td>1493 (63.5)</td><td>2352</td><td>430 (72.6)</td><td>592</td><td>229 (75.1)</td><td>N.A.</td><td>205</td></tr><tr><td>NT-proBNP, pg/mL, mean ± SD</td><td>643 ± 3508</td><td>1514</td><td>1035 ± 2487</td><td>315</td><td>1172 ± 2961</td><td>N.A.</td><td>157</td></tr><tr><td>FVC, % predicted, mean ± SD</td><td>92 ± 22</td><td>2200</td><td>87 ± 23</td><td>585</td><td>88 ± 24</td><td>92 ± 22</td><td>308</td></tr><tr><td>DL<sub>CO</sub>, % predicted, mean ± SD</td><td>66 ± 22</td><td>2087</td><td>51 ± 20</td><td>531</td><td>51 ± 19</td><td>56 ± 18</td><td>265</td></tr><tr><td>FVC/DL<sub>CO</sub>, mean ± SD</td><td>1.58 ± 0.63</td><td>2047</td><td>1.97 ± 0.80</td><td>526</td><td>2 ± 0.78</td><td>1.79 ± 0.64</td><td>263</td></tr><tr><td>LVEF, %, mean ± SD</td><td>60.9 ± 6.5</td><td>2322</td><td>60.4 ± 7</td><td>589</td><td>60.7 ± 7.3</td><td>N.A.</td><td>297</td></tr><tr><td>Diastolic dysfunction, n (%)</td><td>625 (28.9)</td><td>2160</td><td>239 (41.8)</td><td>572</td><td>121 (42.3)</td><td>N.A.</td><td>286</td></tr><tr><td>TAPSE, mm, mean ± SD</td><td>21.8 ± 4.2</td><td>2555</td><td>20.7 ± 4.8</td><td>664</td><td>20.4 ± 5</td><td>21.2 ± 4.6</td><td>355</td></tr><tr><td>sPAP, mmHg, mean ± SD</td><td>30 ± 14</td><td>2555</td><td>41 ± 19</td><td>664</td><td>46 ± 19</td><td>39.7 ± 17.2</td><td>355</td></tr><tr><td>TAPSE/sPAP, mm/mmHg, mean ± SD</td><td>0.83 ± 0.30</td><td>2555</td><td>0.61 ± 0.28</td><td>664</td><td>0.52 ± 0.24</td><td>0.64 ± 0.29</td><td>355</td></tr><tr><td>sPAP >36 mmHg, n (%)</td><td>513 (20.1)</td><td>2555</td><td>322 (48.5)</td><td>664</td><td>224 (63.1)</td><td>169 (47.6)</td><td>355</td></tr><tr><td>TAPSE/sPAP <0.55 mm/mmHg, n (%)</td><td>460 (18)</td><td>2555</td><td>288 (43.4)</td><td>664</td><td>199 (56.1)</td><td>154 (43.4)</td><td>355</td></tr><tr><td>TAPSE/sPAP ≤0.32 mm/mmHg, n (%)</td><td>152 (5.9)</td><td>2555</td><td>113 (17)</td><td>664</td><td>76 (21.4)</td><td>49 (13.8)</td><td>355</td></tr><tr><td>TAPSE/sPAP <0.19 mm/mmHg, n (%)</td><td>39 (1.5)</td><td>2555</td><td>33 (5)</td><td>664</td><td>25 (7)</td><td>10 (2.8)</td><td>355</td></tr></tbody></table>

Percentages are calculated on the number of available data. TAPSE: tricuspid annular plane systolic excursion; sPAP: systolic pulmonary arterial pressure; PH: pulmonary hypertension; RHC: right heart catheterization; N: number of patients with available data; T<sub>0</sub>: baseline; T(-1): 12 ± 3 months before RHC; N.A.: not applicable; ACA: anticentromere antibodies; Scl-70: antitopoisomerase I antibodies; RNA Pol III: RNA polymerase III antibodies; mRSS: modified Rodnan skin score; NT-proBNP: N-terminal pro-B-type natriuretic peptide; FVC: forced vital capacity; DL<sub>CO</sub>: diffusing capacity of the lungs for carbon monoxide; LVEF: left ventricular ejection fraction.
(48.5%) had an increased sPAP value and 288 (43.4%) had a reduced TAPSE/sPAP ratio. The ROC curve analysis showed an AUC of 0.833 (0.802–0.864, *p* < 0.001) for sPAP and 0.845 (0.815–0.874, *p* < 0.001) for TAPSE/sPAP ratio. The OR for PH was 9.8 (95% CI 6.9–14) for sPAP and 11.1 (95% CI 7.7–16) for TAPSE/sPAP ratio. The logistic regression analysis showed that increased sPAP [OR 0.395 (95% CI 0.182–0.854), *p* < 0.05], reduced TAPSE/sPAP ratio [OR 0.268 (95% CI 0.124–0.579), *p* < 0.01] and FVC/DL<sub>CO</sub> [OR 1.707 (95% CI 1.125–2.592), *p* < 0.05] were significantly associated with PH (Table 2).

### 3.3. Echocardiographic parameters in SSc patients with available RHC data at baseline

RHC data at baseline were available in 355 SSc patients. No patient had a previously reported diagnosis of PH at the study baseline in the EUSTAR database. Demographic and clinical characteristics of 355 SSc patients with available RHC data are reported in Table 1.

mPAP mean value was 27 ± 11 mmHg. sPAP and TAPSE/sPAP ratio mean values were 46 ± 19 mmHg and 0.52 ± 0.24 mm/mmHg, respectively. With a cut-off of >36 mmHg for sPAP and a cut-off of <0.55 mm/mmHg for TAPSE/sPAP ratio, 224 (63.1%) SSc patients had an increased sPAP value and 199 (56.1%) had a reduced TAPSE/sPAP ratio. In this group of SSc patients, the prevalence of PH, confirmed by RHC, was 54.9% (n = 195). As for PH diagnosis by RHC, the ROC curve analysis showed an AUC of 0.815 (0.771–0.858, *p* < 0.001) for sPAP and 0.832 (0.790–0.874, *p* < 0.001) for TAPSE/sPAP ratio (Fig. 1, A and B). The OR for PH was 7.8 (95% CI 4.7–12.7) for sPAP and 9 (95% CI 5.6–14.6) for TAPSE/sPAP ratio. The logistic regression analysis showed that only reduced TAPSE/sPAP ratio [OR 0.251 (95% CI 0.084–0.753), *p* < 0.05] and FVC/DL<sub>CO</sub> [OR 2.568 (95% CI 1.227–5.375), *p* < 0.05] were significantly associated with PH diagnosis (Table 2).

### 3.4. Echocardiographic parameters at 12 ± 3 months before RHC

In this group of 355 SSc patients, the mean values of sPAP and TAPSE/sPAP ratio at 12 ± 3 months before RHC were 39.7 ± 17.2

<caption>**Table 2**</caption>

Logistic regression analysis in different groups of systemic sclerosis (SSc) patients.

<table><thead><tr><th colspan="3">PH in 664 SSc patients</th></tr><tr><th></th><th>OR (95% CI)</th><th>p</th></tr></thead><tbody><tr><td>sPAP >36 mmHg</td><td>0.395 (0.182–0.854)</td><td>&lt;0.05</td></tr><tr><td>TAPSE/sPAP &lt;0.55 mm/mmHg</td><td>0.268 (0.124–0.579)</td><td>&lt;0.01</td></tr><tr><td>NT-proBNP, pg/mL</td><td>1.000 (1.000–1.000)</td><td>0.118</td></tr><tr><td>FVC/DL<sub>CO</sub></td><td>1.707 (1.125–2.592)</td><td>&lt;0.05</td></tr><tr><td>Age, years</td><td>1.009 (0.982–1.037)</td><td>0.519</td></tr></tbody><thead><tr><th colspan="3">PH in 355 SSc patients at T0</th></tr><tr><th></th><th>OR (95% CI)</th><th>p</th></tr></thead><tbody><tr><td>sPAP >36 mmHg</td><td>0.785 (0.282–2.188)</td><td>0.643</td></tr><tr><td>TAPSE/sPAP &lt;0.55 mm/mmHg</td><td>0.251 (0.084–0.753)</td><td>&lt;0.05</td></tr><tr><td>NT-proBNP, pg/mL</td><td>1.000 (1.000–1.001)</td><td>0.242</td></tr><tr><td>FVC/DL<sub>CO</sub></td><td>2.568 (1.227–5.375)</td><td>&lt;0.05</td></tr><tr><td>Age, years</td><td>0.974 (0.934–1.015)</td><td>0.205</td></tr></tbody><thead><tr><th colspan="3">PH in 355 SSc patients at T(-1)</th></tr><tr><th></th><th>OR (95% CI)</th><th>p</th></tr></thead><tbody><tr><td>sPAP >36 mmHg</td><td>0.521 (0.226–1.201)</td><td>0.126</td></tr><tr><td>TAPSE/sPAP &lt;0.55 mm/mmHg</td><td>0.265 (0.102–0.685)</td><td>&lt;0.01</td></tr><tr><td>FVC/DL<sub>CO</sub></td><td>2.529 (1.358–4.711)</td><td>&lt;0.01</td></tr><tr><td>Age, years</td><td>1.021 (0.991–1.053)</td><td>0.176</td></tr></tbody></table>

OR: odds ratio; PH: pulmonary hypertension; TAPSE: tricuspid annular plane systolic excursion; sPAP: systolic pulmonary arterial pressure; NT-proBNP: N-terminal pro-B-type natriuretic peptide; FVC: forced vital capacity; DL<sub>CO</sub>: diffusing capacity of the lungs for carbon monoxide; T0: baseline; T(-1): 12 ± 3 months before right heart catheterization.

mmHg and 0.64 ± 0.29 mm/mmHg, respectively. With a cut-off of >36 mmHg for sPAP and a cut-off of <0.55 mm/mmHg for TAPSE/sPAP ratio, 160 (47.6%) had an increased sPAP value and 154 (43.4%) had a reduced TAPSE/sPAP ratio. As for PH diagnosis by RHC, the ROC curve analysis showed an AUC of 0.775 (0.728–0.822, *p* < 0.001) for sPAP and 0.783 (0.736–0.830, *p* < 0.001) for TAPSE/sPAP ratio (Fig. 1, C and D). The OR for PH was 4.7 (95% CI 3–7.4) for sPAP and 5.6 (95% CI 3.5–9) for TAPSE/sPAP ratio. The logistic regression analysis showed that only TAPSE/sPAP ratio [OR 0.265 (95% CI 0.102–0.685), *p* < 0.01] and FVC/DL<sub>CO</sub> [OR 2.529 (95% CI 1.358–4.711), *p* < 0.01] at 12 ± 3 months before RHC were significantly associated with PH diagnosis (Table 2).

### 3.5. Mortality in SSc patients with available RHC data

In this group of 355 SSc patients, the predictive value of sPAP and TAPSE/sPAP ratio for all-cause mortality was also analyzed. 41 of 355 (11.5%) SSc patients died after a follow-up of 38.8 ± 25.1 months. The ROC curve analysis showed an AUC of 0.735 (0.666–0.805, *p* < 0.001) for sPAP and 0.773 (0.703–0.843, *p* < 0.001) for TAPSE/sPAP ratio.

Overall survival was evaluated with a cut-off of >36 mmHg for sPAP and a cut-off of ≤0.32 mm/mmHg for TAPSE/sPAP ratio. Kaplan Meier curves showed a higher mortality in SSc patients with increased sPAP (Log Rank χ² 24.6, *p* < 0.001) and in SSc patients with reduced TAPSE/sPAP ratio (Log Rank χ² 41.1, *p* < 0.001) (Fig. 2, A and B). In univariate Cox regression analysis, increased sPAP [HR 0.066 (0.016–0.276), *p* < 0.001], reduced TAPSE/sPAP ratio [HR 0.167 (0.089–0.310), *p* < 0.001] and age [HR 1.047 (1.014–1.080), *p* < 0.01]] were predictive factors for death. In multivariate Cox regression analysis, reduced TAPSE/sPAP ratio [HR 0.310 (0.164–0.585), *p* < 0.001] was the most significant predictive factor for all-cause mortality (Table 3).

Overall survival was also assessed with a cut-off of >36 mmHg for sPAP and a cut-off of <0.19 mm/mmHg for TAPSE/sPAP ratio. Kaplan Meier curves showed a higher mortality in SSc patients with increased sPAP (Log Rank χ² 24.6, *p* < 0.001) and in SSc patients with reduced TAPSE/sPAP ratio (Log Rank χ² 29.3, *p* < 0.001) (Fig. 2, A and C). In univariate Cox regression analysis, increased sPAP [HR 0.066 (0.016–0.276), *p* < 0.001], reduced TAPSE/sPAP ratio [HR 0.173 (0.084–0.356), *p* < 0.001] and age [HR 1.047 (1.014–1.080), *p* < 0.01]] were predictive factors for death. In multivariate Cox regression analysis, increased sPAP [HR 0.092 (0.022–0.388), *p* < 0.01] and reduced TAPSE/sPAP ratio [HR 0.317 (0.154–0.656), *p* < 0.01] were predictive factors for all-cause mortality (Table 3).

## 4. Discussion

This is the first study to show the association between a reduced TAPSE/sPAP ratio and PH diagnosis and, even more important, its predictive ability 12 months before PH diagnosis in a large cohort of SSc patients. Moreover, this is the largest study to demonstrate the predictive role of a reduced TAPSE/sPAP ratio for all-cause mortality in SSc patients.

According to the new 2022 PH guidelines, we assessed all-cause mortality selecting two different cut-off values for TAPSE/sPAP ratio. For both cut-off values, a reduced TAPSE/sPAP ratio was a predictive risk factor for all-cause mortality and SSc patients with a reduced TAPSE/sPAP ratio had worse survival than patients with higher values. Previous studies described the prognostic role of different TAPSE/sPAP cut-off values in several conditions, including heart failure [16–18], valvular heart disease [28–30], pulmonary embolism [31], chronic lung disease [32] and PH [19–22]. Only two small sample size studies specifically evaluated the prognostic role of TAPSE/sPAP ratio in SSc patients. Lai et al. reported the association between a TAPSE/sPAP ratio ≤ 0.194 mm/mmHg and the composite endpoint of all-cause death and clinical worsening in 60 SSc patients with PAH [23]. Instead, Xanthouli et al. identified a TAPSE/sPAP ratio ≤ 0.6 mm/mmHg as an independent predictor of survival in 225 SSc patients [24]. Furthermore, a previous
<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Receiver Operating Characteristic (ROC) curves for the echocardiographic parameters for the prediction of pulmonary hypertension in 355 systemic sclerosis patients. **A:** ROC curve for systolic pulmonary artery pressure (sPAP) at baseline; **B:** ROC curve for tricuspid annular plane systolic excursion (TAPSE)/sPAP ratio at baseline; **C:** ROC curve for sPAP at 12 ± 3 months before right heart catheterization (RHC); **D:** ROC curve for TAPSE/sPAP ratio at 12 ± 3 months before RHC.</figcaption></figure>

EUSTAR study showed that a sPAP >36 mmHg was associated with reduced survival in SSc patients [15]. In our study, a TAPSE/sPAP ratio ≤ 0.32 mm/mmHg emerged as a stronger predictor of all-cause mortality than a sPAP >36 mmHg in a large cohort of SSc patients undergoing RHC, independently of PH diagnosis and PH group. The TAPSE/sPAP ratio, the ratio between an index of RV function (TAPSE) and an index of RV afterload (sPAP), is the validated non-invasive measure of RV-PA coupling. A TAPSE/sPAP ratio < 0.36 mm/mmHg and a TAPSE/sPAP ratio < 0.31 mm/mmHg have been identified as the cut-off values discriminating RV-PA uncoupling in heart failure and PH, respectively [13,18]. RV-PA uncoupling occurs when RV contractility is unable to match RV afterload. Prompt detection of RV-PA uncoupling, before RV failure occur, is therefore crucial to identify patients at higher risk of clinical deterioration and mortality and to optimise treatment strategies. Vicenzi et al. reported that including TAPSE/sPAP ratio in two different risk scores improved risk stratification in 102 patients with PAH [20]. Our results confirm that TAPSE/sPAP ratio should be included in the prognostic assessment of SSc patients.

In the present study, a TAPSE/sPAP ratio < 0.55 mm/mmHg was significantly and independently associated with the presence of PH in a large cohort of SSc patients. Besides, we evaluated the association between TAPSE/sPAP ratio measured 12 months before RHC and PH diagnosis. We demonstrated for the first time that a TAPSE/sPAP ratio < 0.55 mm/mmHg 12 months before RHC was a risk factor for PH confirmed by RHC. In healthy subjects of all ages, a median (5th–95th percentiles) normative value of 1.25 (0.81–1.78) mm/mmHg has been

reported for TAPSE/sPAP ratio [33]. Early PH detection, before RV-PA uncoupling and RV dysfunction occur, is crucial to promptly start treatment and significantly improve patients exercise capacity, quality of life and survival. According to 2022 PH guidelines, our findings suggest that a cut-off of <0.55 mm/mmHg for TAPSE/sPAP ratio is the optimal cut-off value identifying SSc patients who are more likely to have PH. Our results are in line with a previous study that investigated the role of TAPSE/sPAP ratio as a potential screening tool for PAH in 51 SSc patients comparing the PPV between TAPSE/sPAP ratio and DETECT algorithm. The PPV of TAPSE/sPAP ratio was higher than the PPV of DETECT algorithm, suggesting potential utility for TAPSE/sPAP ratio in SSc patients with a DETECT algorithm step 2 total score > 35 to select patients requiring RHC to confirm PAH diagnosis [14]. According to PH guidelines, echocardiography has a central role in PH screening and a TRV >2.8 m/s, corresponding to an estimated sPAP >36 mmHg, is the cut-off value discriminating patients with intermediate-high probability of PH [8]. In our study, a TAPSE/sPAP ratio < 0.55 mm/mmHg emerged as a stronger risk factor for PH than a sPAP >36 mmHg in a large cohort of SSc patients. To date, there is an unmet need for screening tools able to improve the selection of patients requiring further diagnostic testing to exclude or confirm PH. Our results confirm that TAPSE/sPAP ratio should be included in the PH screening algorithm of SSc patients.

Strengths of the study are the large sample size and the applicability of results to clinical practice due to the use of representative real-world data. Nevertheless, this study has several limitations. This is a
<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /><figcaption>**Fig. 2.** Overall survival in 355 systemic sclerosis (SSc) patients. **A:** overall survival in SSc patients with systolic pulmonary artery pressure (sPAP) >36 mmHg (dotted line) and sPAP <36 mmHg (continuous line); **B:** overall survival in SSc patients with tricuspid annular plane systolic excursion (TAPSE)/sPAP ratio ≤ 0.32 mm/mmHg (dotted line) and TAPSE/sPAP ratio > 0.32 mm/mmHg (continuous line); **C:** overall survival in SSc patients with TAPSE/sPAP ratio < 0.19 mm/mmHg (dotted line) and TAPSE/sPAP ratio > 0.19 mm/mmHg (continuous line).</figcaption></figure>

**Table 3**

Univariate and multivariate Cox regression analysis for overall survival using standardized cut-off values of TAPSE/sPAP ratio in 355 systemic sclerosis patients with available right heart catheterization data.

<table><thead><tr><th colspan="5">Intermediate-high risk TAPSE/sPAP ratio</th></tr><tr><th></th><th colspan="2">Univariate analysis</th><th colspan="2">Multivariate analysis</th></tr></thead><tbody><tr><td></td><th>HR (95% CI)</th><th>p</th><th>HR (95% CI)</th><th>p</th></tr><tr><td>sPAP >36 mmHg</td><td>0.066<br>(0.016-0.276)</td><td>&lt;0.001</td><td>0.124<br>(0.029-0.543)</td><td>&lt;0.01</td></tr><tr><td>TAPSE/sPAP<br>≤0.32 mm/mmHg</td><td>0.167<br>(0.089-0.310)</td><td>&lt;0.001</td><td>0.310<br>(0.164-0.585)</td><td>&lt;0.001</td></tr><tr><td>Age, years</td><td>1.047<br>(1.014-1.080)</td><td>&lt;0.01</td><td>1.032<br>(0.998-1.067)</td><td>0.062</td></tr><tr><td>Male sex</td><td>0.881<br>(0.407-1.909)</td><td>0.749</td><td>-</td><td>-</td></tr><tr><th colspan="5">High risk TAPSE/sPAP ratio</th></tr><tr><th></th><th colspan="2">Univariate analysis</th><th colspan="2">Multivariate analysis</th></tr><tr><td></td><th>HR (95% CI)</th><th>p</th><th>HR (95% CI)</th><th>p</th></tr><tr><td>sPAP >36 mmHg</td><td>0.066<br>(0.016-0.276)</td><td>&lt;0.001</td><td>0.092<br>(0.022-0.388)</td><td>&lt;0.01</td></tr><tr><td>TAPSE/sPAP<br>&lt;0.19 mm/mmHg</td><td>0.173<br>(0.084-0.356)</td><td>&lt;0.001</td><td>0.317<br>(0.154-0.656)</td><td>&lt;0.01</td></tr><tr><td>Age, years</td><td>1.047<br>(1.014-1.080)</td><td>&lt;0.01</td><td>1.029<br>(0.995-1.064)</td><td>0.101</td></tr><tr><td>Male sex</td><td>0.881<br>(0.407-1.909)</td><td>0.749</td><td>-</td><td>-</td></tr></tbody></table>

HR: hazard ratio; TAPSE: tricuspid annular plane systolic excursion; sPAP: systolic pulmonary arterial pressure.

retrospective study in which patients were selected on available TAPSE and sPAP data. Patients with available RHC data did not have serial TAPSE and sPAP measurements and therefore a longitudinal analysis was not possible. Many RHC parameters data were missing (e.g. wedge pressure was not recorded in 84/355 SSc patients with RHC) and could not be used for the analysis. Many data were missing for parameters included in the DETECT algorithm (e.g. TRV was documented only in 67/355 patients and right atrium area only in 62/355 patients), so that comparing the PPV of TAPSE/sPAP ratio and DETECT algorithm was not possible. The cause of death for SSc was missing in many patients. PH-specific mortality was not provided by the EUSTAR database.

Routine echocardiography is crucial for early PH diagnosis, for the prognostic assessment of patients with PH and for their follow-up under therapy. TAPSE/sPAP ratio is a non-invasive, low cost, easy repeatable measure of RV performance related to pulmonary hemodynamics that integrates seamlessly into the existing diagnostic work-up and risk assessment strategies.

In conclusion, in SSc patients a TAPSE/sPAP ratio < 0.55 mm/mmHg is significantly and independently associated with PH and is a potential predictive risk factor for PH. A TAPSE/sPAP ratio ≤ 0.32 mm/mmHg is a predictive risk factor for all-cause mortality.

**Funding**

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

**Declaration of Competing Interest**

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Ivan Castellvi' reports a relationship with Janssen-Cilag SAS that
includes: consulting or advisory and funding grants. Ivan Castellvi' reports a relationship with Boehringer Ingelheim Ltd. that includes: consulting or advisory and funding grants. Ivan Castellvi' reports a relationship with Genentech that includes: consulting or advisory and funding grants. Ivan Castellvi' reports a relationship with Kern Pharma SL that includes: funding grants. Paolo Airo' reports a relationship with Bristol Myers Squibb Co that includes: consulting or advisory and travel reimbursement. Paolo Airo' reports a relationship with Boehringer Ingelheim Ltd. that includes: consulting or advisory. Paolo Airo' reports a relationship with Novartis that includes: consulting or advisory. Paolo Airo' reports a relationship with CSL Behring LLC that includes: travel reimbursement. Paolo Airo' reports a relationship with Janssen Pharmaceuticals Inc. that includes: travel reimbursement. Paolo Airo' reports a relationship with Roche that includes: travel reimbursement.

I.C. has had consultancy relationships and/or has received research funding from Boehringer Ingelheim, Janssen-Cilag, Genentech/Roche and Kern in the area of potential treatments of scleroderma and its complications. P.A. received consulting fees from Bristol Myers Squibb; payments or honoraria from Bristol Myers Squibb, Boehringer Ingelheim, and Novartis; and support for attending meetings and travel from CSL Behring, Janssen, Roche, and Bristol Myers Squibb.

## Data availability

The data that has been used is confidential.

## Acknowledgements

**EUSTAR collaborators:** David Launay (Lille, France); Suzana Jor-dan (Zurich, Switzerland); Alfredo Guillén-Del-Castillo (Barcelona, Spain); Maria Grazia Lazzaroni (Brescia, Italy); Claudia Kedor (Berlin, Germany); Patricia E.Carreira (Madrid, Spain); Beatriz E.Joven (Madrid, Spain); Gabriela Riemekasten (Lübeck, Germany); Sabine Sommerlatte (Lübeck, Germany); Jörg Distler (Erlangen, Germany); Antonella Mar-coccia (Roma, Italy); Francesco Bondanini (Roma, Italy); Mickaël Martin (Poitiers, France); Cédric Landron (Poitiers, France); Jeska de Vries-Bouwstra (Leiden, The Netherlands); Hans U Scherer (Leiden, The Netherlands); Britta Maurer (Bern, Switzerland); Adela-Cristina Sarbu (Bern, Switzerland); Florenzo Iannone (Bari, Italy); Fabio Cacciapaglia (Bari, Italy); Alessandro Giollo (Verona, Italy); Ulf Müller-Ladner (Bad Nauheim, Germany); Lorenzo Dagna (Milano, Italy); Giacomo De Luca (Milano, Italy); Juan Jose Alegre-Sancho (Valencia, Spain); Giovanna Cuomo (Napoli, Italy); Marco Matucci Cerinic (Florence, Italy); Hadi Poormoghim (Tehran, Iran); Nicolas Hunzelmann (Köln, Germany); Ana Maria Gheorghiu (Bucharest, Romania); Ana-Maria Ramazan (Con-stanta City, Romania); D'Alessandro Mathieu, Alessandra Vacca (Mon-serrato, Cagliari, Italy); Enrico Selvi (Siena, Italy); Elisabetta Zanatta (Padova, Italy); Francesco Benvenuti (Padova, Italy); Kamal Solanki (Hamilton, New Zealand); Cherumi Silva (Hamilton, New Zealand); J.M. van Laar (Utrecht, The Netherlands); Tomas Soukup (Hradec Kralove, Czech Republic); Michele Iudici (Geneva, Switzerland); Gianluca Moroncini (Ancona, Italy); Masataka Kuwana (Tokyo, Japan); Magda Parvu (Bucharest, Romania); Yannick Allanore (Paris, France); Massi-miliano Limonta (Bergamo, Italy); Lidia P.Ananieva (Moscow, Russia); Yoshiya Tanaka (Kitakyushu, Japan); Satoshi Kubo (Kitakyushu, Japan); Nicoletta Del Papa (Milano, Italy); Carlo Francesco Selmi (Rozzano, Milano, Italy); Luc Mouthon (Paris, France); Simona Rednic (Cluj-Napoca, Romania); Otylia Kowal Bielecka (Bialystok, Poland); Maurizio Cutolo, Carmen Pizzorni (Genova, Italy); Jörg Henes (Tübingen, Germany); Valeria Riccieri (Roma, Italy); Sarah Kahl (Bad Bramstedt, Germany); Christopher Denton (London, United Kingdom); Tim Schmeiser (Wuppertal-Elberfeld, Germany); Marek Brzosko (Szczecin, Poland); Petros Sfikakis (Athens, Greece); Ulrich Walker (Basel, Switzerland); Raffaele De Palma (Genova, Italy); Nihal Fathi (Assiut, Egypt); Fran-cesco Del Galdo (Leeds, United Kingdom); Maura Couto (Viseu, Portugal); Mislav Radic (Split, Croatia); Stefan Heitmann (Stuttgart,

Germany); Francesco Paolo Cantatore (Foggia, Italy); Carolina de Souza Müller (Curitiba, Brasil); Fahrettin Oksel, Figen Yargucu (Bornova, Izmir, Turkey); Rosario Foti (Catania, Italy); Elena Rezus (Lasi, Romania); László Czirják (Pécs, Hungary); Alexandra Balbir-Gurman (Haifa, Israel); Dorota Krasowska (Lublin, Poland); Ruxandra Maria Ionescu (Bucharest, Romania); Kristine Herrmann (Dresden, Germany); Branimir Anic, Marko Baresic, Miroslav Mayer (Zagreb, Croatia); Sule Yavuz (Altunizade-Istanbul, Turkey); Svetlana Agachi (Chisinau, Republic of Moldova); Lesley Ann Saketkoo (New Orleans, USA); Zbigniew Zdrojewski (Gdansk, Poland); Daniel Furst (Los Angeles, USA); Susana Oliveira (Amadora, Portugal); Ignasi Rodriguez-Pinto (Barcelona, Spain); Marija Geroldinger-Simic (Linz, Austria); Gerard Espinosa (Barcelona, Spain); Torsten Kubacki (Köln, Germany); Anastas Batalov (Plovdiv, Bulgaria).

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