[HTML][HTML] Prediction of pulmonary hypertension in idiopathic pulmonary fibrosis
DA Zisman, DJ Ross, JA Belperio, R Saggar… - Respiratory …, 2007 - Elsevier
DA Zisman, DJ Ross, JA Belperio, R Saggar, JP Lynch III, A Ardehali, AS Karlamangla
Respiratory medicine, 2007•ElsevierBACKGROUND: Reliable, noninvasive approaches to the diagnosis of pulmonary
hypertension in idiopathic pulmonary fibrosis are needed. We tested the hypothesis that the
forced vital capacity to diffusing capacity ratio and room air resting pulse oximetry may be
combined to predict mean pulmonary artery pressure (MPAP) in idiopathic pulmonary
fibrosis. METHODS: Sixty-one idiopathic pulmonary fibrosis patients with available right-
heart catheterization were studied. We regressed measured MPAP as a continuous variable …
hypertension in idiopathic pulmonary fibrosis are needed. We tested the hypothesis that the
forced vital capacity to diffusing capacity ratio and room air resting pulse oximetry may be
combined to predict mean pulmonary artery pressure (MPAP) in idiopathic pulmonary
fibrosis. METHODS: Sixty-one idiopathic pulmonary fibrosis patients with available right-
heart catheterization were studied. We regressed measured MPAP as a continuous variable …
BACKGROUND
Reliable, noninvasive approaches to the diagnosis of pulmonary hypertension in idiopathic pulmonary fibrosis are needed. We tested the hypothesis that the forced vital capacity to diffusing capacity ratio and room air resting pulse oximetry may be combined to predict mean pulmonary artery pressure (MPAP) in idiopathic pulmonary fibrosis.
METHODS
Sixty-one idiopathic pulmonary fibrosis patients with available right-heart catheterization were studied. We regressed measured MPAP as a continuous variable on pulse oximetry (SpO2) and percent predicted forced vital capacity (FVC) to percent-predicted diffusing capacity ratio (% FVC/% DLco) in a multivariable linear regression model.
RESULTS
Linear regression generated the following equation: MPAP=−11.9+0.272×SpO2+0.0659×(100−SpO2)2+3.06×(% FVC/% DLco); adjusted R2=0.55, p<0.0001. The sensitivity, specificity, positive predictive and negative predictive value of model-predicted pulmonary hypertension were 71% (95% confidence interval (CI): 50–89%), 81% (95% CI: 68–92%), 71% (95% CI: 51–87%) and 81% (95% CI: 68–94%).
CONCLUSIONS
A pulmonary hypertension predictor based on room air resting pulse oximetry and FVC to diffusing capacity ratio has a relatively high negative predictive value. However, this model will require external validation before it can be used in clinical practice.
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