The algorithm combined eight variables—telangiectasia, anti-centromere antibody (ACA), NT-proBNP, serum urate, forced vital capacity (FVC) percentage predicted/DLCO percentage predicted (FVC/DLCO) on PFT, right axis deviation on electrocardiogram (ECG), right atrium (RA) area, and TRV on TTE—and established a two-step decision tree, which improved the sensitivity of screening for SSc-PAH from 71% to 96% in comparison with the ESC/ERS guidelines. The gene discussed is NPPB; the disease is Telangiectasia.