Noninvasive Combinatorial Model Predicts Pulmonary Hypertension

A combinatorial model was devised to predict pulmonary hypertension using systolic pulmonary artery pressure and forced vital capacity in older adults.

A combinatorial model to predict pulmonary hypertension had a sensitivity of 87.2% and a specificity of 62.5% in adults, according to the results of a recent study published in the journal JRSM Cardiovascular Disease.

Noninvasive parameters such as lung function testing results, analysis of blood gas samples, 6 minute walk distance, and echocardiography were retrospectively used to predict the presence of pulmonary hypertension. Pulmonary hypertension was defined as mean pulmonary artery pressure >25mmHg. Predictions from the model were then compared to results derived from right heart catheterization.

Among the 134 adults who underwent right heart catheterization as a part of their diagnostic workup for dyspnea, the mean age was 70 years and 44.9% were male. In this cohort there was a high prevalence of cardiovascular risk factors: 80.5% had hypertension, 21.6% had diabetes, and 24.6% were smokers.

The combinatorial logistical model yielded a sensitivity of 87.2% and a specificity of 62.5% with systolic pulmonary artery pressure and forced vital capacity.

Forced vital capacity was shown to be specific (83.3%) predictor for pulmonary hypertension, while systolic pulmonary artery pressure was a sensitive (79.1%) predictor for pulmonary hypertension.

“This easily applicable model could be used as a standard in cardiopulmonary practice to predict PH in older adults and help to further reduce invasive procedures in older patients without missing treatment options,” the study authors concluded.


Wernhart S, Hedderich J. Prediction of pulmonary hypertension in older adults based on vital capacity and systolic pulmonary artery pressure. JRSM Cardiovasc Dis. 2020. Published online Nov 12, 2020. doi:10.1177/2048004020973834