Performance of the DETECT Algorithm for Pulmonary Hypertension Screening in a Systemic Sclerosis Cohort.

Abstract

Pulmonary arterial hypertension (PAH) is one of the leading causes of mortality in systemic sclerosis (SSc). This study was undertaken to assess predictive accuracies of the DETECT algorithm and the 2015 European Society of Cardiology/European Respiratory Society (ESC/ERS) guidelines in SSc patients who underwent right-sided heart catheterization (RHC) for pulmonary hypertension (PH) evaluation. Patients with SSc who had diagnostic RHC, had no PH or had PAH, and had available data on variables to allow application of the DETECT and 2015 ESC/ERS guidelines were included for analysis. PH classification was based on hemodynamics using the 2018 revised criteria and extent of lung fibrosis shown on high-resolution computed tomography. Sensitivity and predictive accuracies of the DETECT algorithm and 2015 ESC/ERS guidelines were calculated, including analysis of subjects with a diffusing capacity for carbon monoxide (DLco) of ≥60% predicted. Sixty-eight patients with SSc had RHC, of whom 58 had no PH and 10 had PAH. The mean age was 60.0 years, and 58.8% had limited cutaneous SSc. The DETECT algorithm had a sensitivity of 1.00 (95% confidence interval [95% CI] 0.69-1.00) and a negative predictive value (NPV) of 1.00 (95% CI 0.80-1.00), whereas the 2015 ESC/ERS guidelines had a sensitivity of 0.80 (95% CI 0.44-0.97) and an NPV of 0.94 (95% CI 0.81-0.99). In patients with a DLco of ≥60% (n = 27), the DETECT algorithm had a sensitivity of 1.00 (95% CI 0.29-1.00) and an NPV of 1.00 (95% CI 0.59-1.00), whereas the 2015 ESC/ERS guidelines had a sensitivity of 0.67 (95% CI 0.09-0.99) and an NPV of 0.94 (95% CI 0.71-1.00). The DETECT algorithm has high sensitivity and NPV for diagnosis of PAH, including among individuals with a DLco of ≥60%.