Systemic sclerosis (SSc) patients experience disproportionate morbidity and mortality from pulmonary arterial hypertension (PAH) and right ventricular (RV) dysfunction [1]. Two-dimensional speckle tracking echocardiography (2D-STE) can be used for noninvasive assessment of impaired RV contractile reserve in SSc patients at risk for PAH [2, 3]. However, there are no established statistical models that are predictive of emerging pulmonary vascular disease (PVD) in systemic sclerosis. In the present study, we first sought to establish whether abnormal RV contractile reserve associates with future elevation in pulmonary arterial pressures. We then sought to identify whether changes in 2D-STE derived strain with exercise improve prediction of PAH in SSc.
We studied prevalent SSc patients without known PVD who underwent supine bicycle echocardiography (SBE) and subsequent RHC. Inclusion criteria included: resting RVSP ≥ 40 mmHg on a routine screening echocardiogram with associated dyspnea, an RVSP ≥ 45 mmHg on routine screening echocardiogram without symptoms, or unexplained dyspnea in the absence of symptomatic interstitial lung disease, significant chronic obstructive pulmonary disease (FEV1/FVC ratio <0.7 with history of smoking), or a left ventricular (LV) ejection fraction <50%. The study protocol was approved by the Johns Hopkins Medicine Institutional Review Board. All participants met the American College of Rheumatology classification criteria for SSc [4, 5]. Patients were exercised to fatigue with continuous echocardiographic monitoring. RV systolic pressure (RVSP), tricuspid annular plane systolic excursion (TAPSE), and fractional area change (FAC) were obtained at baseline and peak exercise. RV longitudinal systolic strain (RVLSS) measurements were calculated using STE-based analysis. Rest-stress changes in apical, mid, basal, and global RVLSS (Δapical/Δmid/Δbasal/Δglobal RVLSS) as well as TAPSE (ΔTAPSE), FAC (ΔFAC), and TAPSE/RVSP (ΔTAPSE/RVSP) were quantified. PAH was defined as a mean pulmonary arterial pressure (mPAP) > 20 mmHg, a pulmonary capillary wedge pressure (PCWP) < 15 mmHg, and pulmonary vascular resistance (PVR) > 3 Wood Units [6]. Univariate linear regression analysis was used to evaluate associations between echo/strain parameters and mPAP. Whitney U and Fisher Exact tests were used to compare continuous and categorical variables, respectively. Logistic regression was used to examine relationships between PAH and exercise strain indices.
Our cohort consisted of 34 SSc patients; 8/34 (23%) of these patients developed PAH by follow-up. Among the 26 patients without PAH, 7/26 had mPAP>20 mmHg and only 2/26 had Group 2 PH (mPAP>20 mmHg; PCWP≥15 mmHg). There were no significant differences in age, SSc subtype, or autoantibody positivity between groups. The median (IQR) duration between SBE and RHC was 1.0 (0.2-2.5) years. Other demographics and clinical characteristics are summarized in Table 1. We next sought to identify whether rest-stress changes in RV reserve correlated with mPAP. ΔGlobal RVLSS positively correlated with mPAP (β=0.44; p=0.026). ΔTAPSE (β=−0.40; p=0.98), ΔFAC (β=−0.39; p=0.06), and ΔTAPSE/RVSP (β=2.3 ; p=0.64), were not significantly associated with mPAP. We then constructed two scores to identify PAH in the cohort, the “echo score,” which included traditional measures of RV reserve (ΔRVSP, ΔTAPSE, ΔFAC, ΔTAPSE/RVSP), a “strain score,” which included all the same parameters as the echo score as well as Δglobal RVLSS, and a “segmental strain score”, which additionally included Δapical/Δmid/Δbasal RVLSS, generated using a logistic regression model. We performed receiver operating characteristic analysis (Figure 1) to quantify the score association with PAH and found that inclusion of strain improved area under the curve (AUC) by 7% and only a 1% additional improvement with inclusion of segmental strain (AUC = 75%, segmental strain score, AUC = 74%, strain score vs. AUC = 68%, echo score).
Table 1.
Baseline demographics, co-morbidities, and clinical characteristics for SSc patients with and without PAH.
| Parameter | All SSc patients (n=34) |
SSc patients with PAH (n=8) |
SSc patients without PAH (n=26) |
P-value |
|---|---|---|---|---|
| Age (years) | 62 (49-69) | 65 (53-71) | 60 (48-69) | 0.350 |
| Women, No. (%) | 30 (88) | 8 (100) | 22 (85) | 0.551 |
| Race, No. (%) | 0.462 | |||
| White | 27 (79) | 8 (100) | 19 (73) | |
| Black | 6 (18) | 0 (0) | 6 (23) | |
| Asian | 1 (3) | 0 (0) | 1 (4) | |
| Ever smoker, No. (%) | 11 (32) | 3 (38) | 8 (31) | 0.519 |
| BMI, mean ± SD | 26 (23-32) | 22 (19-31) | 27 (24-32) | 0.138 |
| Scleroderma disease duration at SBE (years), n=30 | 18 (5-29) | 12 (8-21) | 20 (4-46) | 0.149 |
| Scleroderma subtype, No (%) | 0.616 | |||
| Limited | 21 (62) | 4 (50) | 17 (65) | |
| Diffuse | 6 (18) | 2 (25) | 4 (15) | |
| Mixed Connective Tissue Disease | 7 (21) | 2 (25) | 5 (19) | |
| Autoantibody status, No. (%) | ||||
| Centromere (n=22) | 15 (68) | 4 (80) | 11 (65) | 1.000 |
| Scl70 (n=26) | 7 (27) | 0 (0) | 7 (33) | 0.278 |
| RNA polymerase III (n=16) | 3 (19) | 0 (0) | 3 (20) | 1.000 |
| Pulmonary function | ||||
| Forced vital capacity (FVC), % predicted | 88 (77-93) | 89 (78-95) | 87 (77-93) | 0.611 |
| Diffusing capacity (DLCO), % predicted | 65 (50-82) | 58 (47-64) | 71 (52-92) | 0.062 |
| FVC/DLCO ratio | 1.4 (1.0-1.7) | 1.5 (1.4-1.8) | 1.1 (0.9-1.7) | 0.088 |
| Time between SBE and RFIC (years), mean ± SD | 1.0 (0.2-2.5) | 0.7 (0.5-1.0) | 1.7 (0.1-2.9) | 0.843 |
| RHC values, mean ± SD | ||||
| Right atrial pressure mm Hg | 4 (2-6) | 3 (2-4) | 5 (3-6) | 0.097 |
| Systolic pulmonary arterial pressure, mm Hg | 32 (28-35) | 39 (34-44) | 32 (25-35) | 0.007 |
| Diastolic pulmonary arterial pressure, mm Hg | 12 (10-14) | 15 (14-16) | 11 (10-13) | 0.009 |
| Mean pulmonary arterial pressure , mm Hg | 20 (16-23) | 25 (22-26) | 19 (15-22) | 0.002 |
| Pulmonary capillary wedge pressure mm Hg, | 8 (5-12) | 6 (5-8) | 9 (6-12) | 0.142 |
| Pulmonary vascular resistance , Wood Unit | 2.1 (1.7-3.1) | 4.0 (3.6-4.6) | 2.0 (1.5-2.5) | 0.0001 |
| Cardiac output, L·min−1 | 4.6 (3.8-5.3) | 4.6 (3.7-5.1) | 4.6 (3.9-5.8) | 0.612 |
| Cardiac index, L/min/m2 | 2.6 (2.3-3.0) | 2.9 (2.4-3.1) | 2.6 (2.3-3.0) | 0.516 |
| Systemic vascular resistance, dynes/seconds/cm−5. | 2640 (2260-2960) | 2500 (2060-2820) | 2650 (2300-3030) | 0.465 |
| SBE values, mean ± SD | ||||
| Max watts | 75 (50-100) | 75 (50-75) | 75 (50-100) | 0.243 |
| Rest RVSP, mm Hg | 30 (23-39) | 32 (19-36) | 20 (23-40) | 0.464 |
| Peak RVSP, mm Hg | 48 (42-63) | 60 (43-60) | 50 (42-65) | 0.622 |
| ΔRVSP, mm Hg (n=31) | 23 (12-32) | 23 (16-29) | 20 (12-33) | 0.888 |
| ΔBasal RVLSS (%) | −1 (−9-5) | −2 (−9- −0.5) | −0.5 (−8-6) | 0.440 |
| ΔMid RVLSS (%) | −1 (−6-2) | −1 (−3.5-2) | −1.5 (−8-0) | 0.392 |
| ΔApical RVLSS (%) | −2 (−6-0) | −2 (−4-1) | −1.5 (−7-0) | 0.791 |
| ΔGIobal RVLSS (%) | −2 (−5-1) | −2 (−5-1) | −2 (−6-2) | 0.817 |
| ΔTAPSE, cm | 0.3 (0.2-0.5) | 0.5 (0.4-0.6) | 0.3 (0.2-0.6) | 0.721 |
| RV ΔFAC (%) | 2.6 (0.3-8.4) | −0.7 (−4.4-7.0) | 3.0 (0.8-9.0) | 0.166 |
| ΔTAPSE/RVSP, cm·mm Hg−1 | −0.2 (−0.3- − 0.1) | −0.2 (−0.5 – −0.1) | −0.2 (−0.3 - −0.1) | 0.623 |
| Rest TAPSE/RVSP, cm·mm Hg−1 | 0.7 (0.6-0.9) | 0.6 (0.5-0.9) | 0.7 (0.6-0.9) | 0.543 |
| Peak TAPSE/RVSP, cm·mm Hg−1 | 0.5 (0.4-0.7) | 0.5 (0.3-0.6) | 0.5 (0.4-0.7) | 0.707 |
Figure 1. Receiver operating characteristic analysis of changes in 2DE-STE strain parameters with exercise associated with PAH.
Two scores (Echo Score - ΔRVSP, ΔTAPSE, ΔFAC, ΔTAPSE/RVSP; Strain Score - ΔRVSP, ΔTAPSE, ΔFAC, ΔTAPSE/RVSP, Δglobal RVLSS; Segmental Strain Score - ΔRVSP, ΔTAPSE, ΔFAC, ΔTAPSE/RVSP, Δapical/Δmid/Δbasal/Δglobal RVLSS) were constructed with a logistic regression model.
Presently, there are no prior studies that have established the predictive capacity of stress echocardiographic parameters with incident PVD in SSc. Here, we show that changes in RV contractile reserve, namely global RVLSS and apical RVLSS, with exercise provocation may be an early signal of maladaptive changes to RV contractility that precedes incident increases in mPAP in SSc. Similar findings were not appreciable by resting or rest-stress changes in conventional 2DE parameters such as RVSP, TAPSE, and TAPSE/RVSP by traditional statistical modeling. Our findings align with previous studies from our group and suggest that early deficits in RV contractility associate with emerging PVD in SSc [2, 3]. In addition, our statistical score that incorporates 2DE-STE assessed of RV contractile reserve was able to non invasively identify SSc patients at risk for incident PVD and may improve identification of those who may benefit from early therapeutic interventions. Future studies are required to validate the score with a larger cohort of patients. There are several limitations to this study. First, this was a single-center retrospective study with a small proportion that subsequently developed PAH. However, despite our selective population, it is still impressive that 8/38 patients referred for an SBE went on to develop PAH. Nonetheless, several of the univariate linear regression analyses performed were underpowered, including peak RVSP and ΔRVSP. Second, there are currently no accepted references for STE-derived strain measures with exercise, particularly in SSc. The results from this study are intended as a hypothesis-generating report for application of 2D-STE derived strain measures with exercise as a marker of RV contractile reserve that associates with incident PVD in this patient population.
In summary, we have identified that exertional changes in global and apical RVLSS associated with incident PVD and resting hemodynamics in SSc patients. The results from the study are hypothesis-generating, and future studies are required to validate this in larger cohorts to further identify the prognostic potential of these indices to predict incident PVD.
Footnotes
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