Risk assessment in patients with functional class II pulmonary arterial hypertension: Comparison of physician gestalt with ESC/ERS and the REVEAL 2.0 risk score.

Background Accurate and regular risk assessment is important for evaluation and treatment of pulmonary arterial hypertension (PAH) patients, including those with functional class (FC) II symptoms, a population considered at low risk for disease progression. Risk assessment methods include subjective and objective evaluations. Multiparametric assessments include tools based on the European Society of Cardiology/European Respiratory Society (ESC/ERS) guidelines (COMPERA and FPHR methods, respectively) and the Registry to Evaluate Early and Long-Term PAH Disease Management (REVEAL; REVEAL 2.0 tool). To better understand risk status determination in FC II patients, we compared physician-reported risk assessments with objective multiparameter assessment tools. Methods This retrospective chart analysis included PAH patients with FC II symptoms receiving monotherapy or dual therapy. Physicians were surveyed (via telephone) to obtain an assessment of patient risk using their typical methodology, which might have been informed by objective risk assessment. Patient risk was then calculated independently using COMPERA, FPHR and REVEAL 2.0 tools. Factors associated with incongruent risk assessment were identified. Results Of the 153 patients, 41%, 46%, and 13% were classified as low, intermediate, and high risk, respectively, by physicians. Concordance between physician gestalt and objective methods ranged from 43%-54%. Among patients considered as low risk by physician gestalt, 4%-28% were categorized as high risk using objective methods. The most common physician factor associated with incongruent risk assessment was less frequent echocardiography during follow-up (every 7-12 months vs. every 3 months; p = 0.01). Conclusions More than half of FC II PAH patients were classified as intermediate/high risk using objective multiparameter assessments. Incorporating objective risk-assessment algorithms into clinical practice may better inform risk assessment and treatment strategies.