High sensitivity and negative predictive value of the DETECT algorithm for an early diagnosis of pulmonary arterial hypertension in systemic sclerosis: application in a single center

Abstract Background Pulmonary arterial hypertension (PAH) is one of the most relevant causes of death in systemic sclerosis. The aims of this study were to analyse the recently published DETECT algorithm comparing it with European Society of Cardiology/European Respiratory Society (ESC/ERS) 2009 guidelines: as screening of PAH; (2) identifying median pulmonary arterial pressure (mPAP) ≥21 mmHg; and (3) determining any group of pulmonary hypertension (PH). Methods Eighty-three patients fulfilling LeRoy’s systemic sclerosis diagnostic criteria with at least right heart catheterization were studied retrospectively. Clinical data, serological biomarkers, echocardiographic and hemodynamic features were collected. SPSS 20.0 was used for statistical analysis. Results According to right heart catheterization findings, 35 patients with PAH and 28 with no PH met the standards for DETECT algorithm analysis: 27.0% of patients presented with functional class III/IV. Applying DETECT, the sensitivity was 100%, specificity 42.9%, the positive predictive value 68.6% and the negative predictive value 100%, whereas employing the ESC/ERS guidelines these were 91.4%, 85.7%, 88.9% and 89.3%, respectively. There were no missed diagnoses of PAH using DETECT compared with three patients missed (8.5%) using ESC/ERS guidelines. The DETECT algorithm also showed greater sensitivity and negative predictive value to identify patients with mPAP ≥21 mmHg or with any type of PH. Conclusions The DETECT algorithm is confirmed as an excellent screening method due to its high sensitivity and negative predictive value, minimizing missed diagnosis of PAH. DETECT would be accurate either for early diagnosis of borderline mPAP or any group of PH.