An Integrated Imaging and Circulating Biomarker Approach for Secondary Tricuspid Regurgitation
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Population
2.2. Clinical Measurements and Follow-Up
2.3. Laboratory Measurements and Hemodynamic Assessment
2.4. Echocardiographic Assessment
2.5. Statistical Analysis
3. Results
3.1. Baseline Characteristics
3.2. Baseline Characteristics According to Severity of Tricuspid Regurgitation
3.3. Severity of Tricuspid Regurgitation and Outcome
3.4. Activation of Neurohormones in Severe Tricuspid Regurgitation
3.5. Association of Neurohumoral Activation with Hemodynamic and Morphologic Characteristics
4. Discussion
4.1. Neurohumoral Activation in Secondary Tricuspid Regurgitation
4.2. Neurohormones as Indicators of Morphologic and Hemodynamic Changes in sTR
4.3. Clinical Implications of Neurohumoral Activation in the Diagnosis of Severe sTR
4.4. Limitations
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Baseline Characteristics | Total Study Population (n = 576) | No/Mild sTR (n = 377) | Moderate sTR (n = 136) | Severe sTR (n = 63) | p-Value |
---|---|---|---|---|---|
Age, median years (IQR) | 58 (50–64) | 57 (50–63) | 58 (50–65) | 60 (50–65) | 0.391 |
Male sex, n (%) | 476 (83) | 317 (84) | 110 (81) | 49 (78) | 0.391 |
BMI, kg/m2 (IQR) | 26 (24–29) | 27 (24–29) | 26 (24–28) | 26 (22–28) | 0.001 |
Systolic blood pressure, mmHg (IQR) | 115 (100–130) | 120 (105–135) | 109 (95–120) | 100 (90–115) | <0.001 |
Ischemic etiology of HF, n (%) | 225 (39) | 160 (42) | 49 (36) | 16 (25) | 0.026 |
Hypertension, n (%) | 284 (49) | 210 (56) | 57 (42) | 17 (27) | <0.001 |
Diabetes, n (%) | 130 (23) | 92 (24) | 27 (20) | 11 (17) | 0.326 |
Hypercholesterolemia, n (%) | 234 (41) | 175 (46) | 46 (34) | 13 (21) | <0.001 |
Left bundle branch block, n (%) | 112 (19) | 80 (21) | 23 (17) | 9 (14) | 0.872 |
Atrial fibrillation, n (%) | 119 (21) | 58 (15) | 45 (33) | 16 (25) | <0.001 |
NYHA functional class | <0.001 | ||||
NYHA II, n (%) | 153 (27) | 121 (32) | 24 (18) | 8 (13) | |
NYHA III, n (%) | 236 (41) | 151 (40) | 62 (46) | 23 (37) | |
NYHA IV, n (%) | 121 (21) | 49 (13) | 42 (31) | 30 (48) | |
Creatinine, mg/dL (IQR) | 1.2 (1.0–1.4) | 1.2 (1.0–1.3) | 1.2 (1.0–1.5) | 1.3 (1.1–1.7) | <0.001 |
Blood urea nitrogen, mg/dL (IQR) | 20 (17–30) | 20 (15–26) | 23 (18–37) | 30 (20–38) | <0.001 |
Echocardiographic characteristics | |||||
Left ventricular end-diastolic diameter, mm (IQR) | 64 (58–71) | 63 (56–70) | 64 (59–70) | 66 (61–73) | 0.048 |
Left ventricular function | |||||
Moderately reduced (EF 30–40%), n (%) | 159 (28) | 120 (32) | 32 (24) | 7 (11) | 0.001 |
Severely reduced (EF < 30%), n (%) | 325 (56) | 177 (47) | 93 (68) | 55 (87) | <0.001 |
Left ventricular ejection fraction, % (IQR) | 27 (20–35) | 30 (22–37) | 26 (20–35) | 22 (14–26) | <0.001 |
Left atrial diameter, mm (IQR) | 64 (57–71) | 61 (55–68) | 69 (64–74) | 72 (66–77) | <0.001 |
Right ventricular end-diastolic diameter, mm (IQR) | 36 (31–42) | 34 (30–38) | 41 (35–45) | 44 (40–49) | <0.001 |
Right ventricular function | |||||
Moderately reduced, n (%) | 23 (4) | 4 (1) | 6 (4) | 13 (21) | <0.001 |
Severely reduced, n (%) | 13 (2) | 4 (1) | 6 (4) | 3 (5) | 0.030 |
Right atrial diameter, mm (IQR) | 58 (52–66) | 55 (50–62) | 65 (58–71) | 70 (60–77) | <0.001 |
Mitral regurgitation (≥moderate), n (%) | 193 (34) | 71 (19) | 73 (54) | 49 (78) | <0.001 |
Systolic pulmonary artery pressure, mmHg (IQR) | 46 (39–56) | 41 (35–50) | 50 (43–59) | 54 (46–60) | <0.001 |
Medication | |||||
RAS-antagonist, n (%) | 551 (96) | 363 (96) | 128 (94) | 60 (95) | 0.559 |
Percent of maximal recommended dose, median % | 100 | 100 | 100 | 100 | 0.15 |
Beta blockers, n (%) | 410 (71) | 274 (73) | 96 (71) | 40 (63) | 0.324 |
Percent of maximal recommended dose, median % | 50 | 50 | 50 | 44 | 0.66 |
Mineral corticoid receptor antagonist, n (%) | 189 (33) | 100 (27) | 62 (46) | 27 (42) | <0.001 |
Furosemide, n (%) | 429 (75) | 253 (67) | 118 (87) | 58 (92) | <0.001 |
Device therapy | |||||
Implanted cardioverter defibrillator, n (%) | 69 (12) | 40 (11) | 19 (14) | 10 (16) | 0.352 |
Pacemaker, n (%) | 100 (17) | 50 (13) | 33 (24) | 17 (27) | 0.002 |
Cardiac resynchronization therapy, n (%) | 55 (10) | 41 (11) | 11 (8) | 13 (21) | 0.250 |
Hemodynamic characteristics | N = 150 | N = 150 | |||
mPAP, mmHg (IQR) | 38 (31–43) | 39 (33–46) | 36 (31–40) | 38 (33–42) | 0.194 |
PAWP, mmHg (IQR) | 23 (20–26) | 24 (21–26) | 22 (20–26) | 23 (21–28) | 0.543 |
Cardiac Index, l/min/m2 (IQR) | 1.8 (1.5–2.1) | 1.8 (1.5–2.1) | 1.9 (1.6–2.1) | 1.7 (1.5–2.0) | 0.512 |
Pulmonary vascular resistance, dyn∙s/cm5 (IQR) | 635 (480–811) | 699 (499–898) | 595 (395–722) | 600 (467–770) | 0.142 |
Systemic vascular resistance, dyn∙s/cm5 (IQR) | 2766 (2360–3368) | 2905 (2480–3721) | 2641 (2282–3057) | 2746 (2452–3095) | 0.131 |
Neurohormones | |||||
NT-proBNP, pg/mL (IQR) | 2360 (867–5163) | 1632 (541–3510) | 4131 (2262–7408) | 5700 (2875–9083) | <0.001 |
MR-proANP, pmol/L (IQR) | 275 (131–479) | 202 (102–359) | 429 (258–592) | 510 (329–799) | <0.001 |
MR-proADM, nmol/L (IQR) | 0.67 (0.42–1.06) | 0.59 (0.37–0.84) | 0.91 (0.65–1.50) | 1.25 (0.62–2.12) | <0.001 |
Copeptin, pmol/L (IQR) | 11.3 (5.8–21.8) | 8.8 (5.0–17.2) | 16.8 (7.9–28.7) | 24.6 (11.4–43.9) | <0.001 |
CT-pro-ET1, pmol/L (IQR) | 62 (31–106) | 55 (26–85) | 87 (44–132) | 118 (56–173) | <0.001 |
Univariable Model | Selected Neurohormones | |||||||
---|---|---|---|---|---|---|---|---|
SD | OR | 95% CI | p-Value | ROC | Adj. HR 1 | 95% CI | p-Value | |
Neurohormones | ||||||||
CT-pro-ET1 | 65.3 | 2.08 | 1.65–2.63 | <0.001 | 0.70 | 1.46 | 1.11–1.91 | 0.006 |
MR-proANP | 347 | 1.80 | 1.44–2.24 | <0.001 | 0.77 | 1.45 | 1.13–1.87 | 0.004 |
NT-proBNP | 5452 | 1.63 | 1.34–1.98 | <0.001 | 0.75 | |||
Copeptin | 23.7 | 1.60 | 1.31–1.95 | <0.001 | 0.73 | |||
MR-proADM | 2.19 | 1.17 | 0.96–1.43 | 0.121 | 0.72 |
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Spinka, G.; Bartko, P.E.; Heitzinger, G.; Teo, E.; Prausmüller, S.; Arfsten, H.; Pavo, N.; Winter, M.-P.; Mascherbauer, J.; Hengstenberg, C.; et al. An Integrated Imaging and Circulating Biomarker Approach for Secondary Tricuspid Regurgitation. J. Pers. Med. 2020, 10, 233. https://doi.org/10.3390/jpm10040233
Spinka G, Bartko PE, Heitzinger G, Teo E, Prausmüller S, Arfsten H, Pavo N, Winter M-P, Mascherbauer J, Hengstenberg C, et al. An Integrated Imaging and Circulating Biomarker Approach for Secondary Tricuspid Regurgitation. Journal of Personalized Medicine. 2020; 10(4):233. https://doi.org/10.3390/jpm10040233
Chicago/Turabian StyleSpinka, Georg, Philipp E. Bartko, Gregor Heitzinger, Eliza Teo, Suriya Prausmüller, Henrike Arfsten, Noemi Pavo, Max-Paul Winter, Julia Mascherbauer, Christian Hengstenberg, and et al. 2020. "An Integrated Imaging and Circulating Biomarker Approach for Secondary Tricuspid Regurgitation" Journal of Personalized Medicine 10, no. 4: 233. https://doi.org/10.3390/jpm10040233
APA StyleSpinka, G., Bartko, P. E., Heitzinger, G., Teo, E., Prausmüller, S., Arfsten, H., Pavo, N., Winter, M. -P., Mascherbauer, J., Hengstenberg, C., Hülsmann, M., & Goliasch, G. (2020). An Integrated Imaging and Circulating Biomarker Approach for Secondary Tricuspid Regurgitation. Journal of Personalized Medicine, 10(4), 233. https://doi.org/10.3390/jpm10040233