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Augmentation area index: a novel approach to disease severity and outcome in patients with WHO group I and group III pulmonary hypertension (1089.2)
Author(s) -
Shterental Sebastian,
Alam Mian,
Bachman Timothy,
Corotto Paul,
Gupta Shikha,
Longhini Anthony,
Nguyen Daniel,
Sciurba Frank,
Simon Marc,
Champion Hunter
Publication year - 2014
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.28.1_supplement.1089.2
Subject(s) - medicine , hemodynamics , logistic regression , cardiology , pulmonary hypertension , copd , blood pressure
Background: Pulmonary hypertension (PH) has a poor outcome overwhelmingly related to right ventricular (RV) failure. Augmentation area index (AI) could capture hemodynamic effects of vessel stiffening on this processes. We studied AI’s relationship to other hemodynamic measures and to clinical outcomes. Methods: This is a retrospective, exploratory clinical and hemodynamic data analysis of PH patients diagnosed with idiopathic pulmonary arterial hypertension (IPAH) or chronic obstructive pulmonary disease (COPD) who were catheterized at UPMC Presbyterian Hospital from 1/1/2006 to 3/26/2012. AI was calculated in a blinded fashion from RV pressure wave‐forms using validated image analysis software. We used linear regression to study the relationships between AI and hemodynamic parameters, multiple regression to study the primary outcome of time to death or transplantation, and logistic regression to study secondary outcome of being World Health Organization functional category 1 or 2 versus 3 or 4. Results: Clinical and hemodynamic data were analyzed for 63 patients. Mean age was 56.3 years (SD 15.0) and 67% were female. There was a positive correlation between AI and PVR (R2=.16 t=2.85 p=0.007) and a negative correlation between AI and CI (R2=.07, t=‐2.04, p=0.046). When adjusted for calcium channel blocker treatment and pulse pressure, AI was a significant predictor of time to death or transplant (R2=0.67, F(3,16)=11, p<.001). Logistic regression testing of AI as the primary predictor of clinical function adjusted for systemic hypertension, tobacco use, prostacyclin treatment, body‐surface area and peripheral vascular resistance, yielded an odds ratio of 1.12 (p=.001, partial p= 0.014). Conclusion: In patients with different etiologies of PH, AI could be a significant predictor of clinical outcome. A novel approach to the pulmonary system, it correlates with other hemodynamic values previously shown to be significant markers of disease progression. Grant Funding Source : NIH TPPG