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

OBJECTIVE Pulmonary arterial hypertension (PAH) is one of the leading causes of mortality in systemic sclerosis (SSc). We assessed predictive accuracies of the DETECT algorithm and 2015 European Society of Cardiology/ European Respiratory Society (ESC/ERS) guidelines in a SSc cohort that had a right heart catheterization (RHC) for pulmonary hypertension (PH) evaluation. METHODS Subjects with SSc who had a diagnostic RHC, had no PH or had PAH, and had variables for application of 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 on high resolution computed tomography. Sensitivity and predictive accuracies of the DETECT algorithm and 2015 ESC/ERS guidelines were performed including analysis of subjects with DLCO ≥ 60% predicted. RESULTS Sixty-eight subjects with SSc had RHC; 58 subjects had no PH and 10 had PAH. The mean age of the cohort was 60.0 years and 58.8% had limited cutaneous SSc. The DETECT algorithm had a sensitivity of 1.00 (95% CI 0.69-1.00) and negative predictive value (NPV) of 1.00 (0.80-1.00) whereas 2015 ESC/ERS guidelines had a sensitivity of 0.80 (0.44-0.97) and NPV of 0.94 (0.81-0.99). In subjects with DLCO ≥ 60 % (N=27), the DETECT algorithm had a sensitivity of 1.00 (0.29-1.00) and NPV of 1.00 (0.59-1.00) whereas 2015 ESC/ERS guidelines had a sensitivity of 0.67 (0.09-0.99) and NPV of 0.94 (0.71-1.00). CONCLUSION The DETECT algorithm has a high sensitivity and NPV for diagnosis of PAH, including those with DLCO ≥ 60%.