DETECT Algorithm (for Systemic Sclerosis)
- DETECT Algorithm (for Systemic Sclerosis): Explanation and Clinical Context
The DETECT Algorithm is a validated, evidence-based two-step screening tool for early detection of Pulmonary Arterial Hypertension (PAH) in patients with systemic sclerosis (SSc). It was developed from a large prospective multicenter study (Coghlan et al., Ann Rheum Dis, 2014) that identified key clinical, laboratory, and echocardiographic predictors of PAH in high-risk SSc patients.
In Stage 1, six non-echocardiographic variables (FVC/DLCO ratio, telangiectasia, anti-centromere antibody, NT-proBNP, serum uric acid, and right axis deviation on ECG) are used to determine whether echocardiography is warranted. If the probability exceeds the threshold, the algorithm proceeds to Stage 2, which incorporates right atrial area and tricuspid regurgitation (TR) velocity from echocardiography. If the Stage 2 score surpasses its threshold, right heart catheterization (RHC) is recommended to confirm the diagnosis of PAH.
The DETECT Algorithm demonstrates excellent sensitivity (96%) and high negative predictive value (>98%), ensuring that PAH cases are not missed during screening. This approach allows clinicians to identify SSc-associated PAH at an earlier, more treatable stage, improving long-term outcomes.
Reference:
Coghlan JG, Denton CP, Grünig E, et al. Evidence-based detection of pulmonary arterial hypertension in systemic sclerosis: the DETECT study. Ann Rheum Dis. 2014;73(7):1340–1349.
Humbert M, et al. 2022 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension. Eur Heart J. 2022;43(38):3618–3731.
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