Ann Rheum Dis doi:10.1136/annrheumdis-2013-203301
  • Clinical and epidemiological research
  • Extended Report

Evidence-based detection of pulmonary arterial hypertension in systemic sclerosis: the DETECT study

Open Access
  1. on behalf of the DETECT study group
  1. 1Cardiology Department, Royal Free Hospital, London, UK
  2. 2Centre for Rheumatology, Royal Free Hospital, London, UK
  3. 3Centre for Pulmonary Hypertension, University Hospital, Heidelberg, Germany
  4. 4Medical University of Vienna, Department of Internal Medicine II, Division of Cardiology, Vienna, Austria
  5. 5Department of Rheumatology, University Hospital Zurich, Zurich, Switzerland
  6. 6Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
  7. 7Department of Rheumatology and Clinical Immunology, Justus-Liebig-University Giessen, Kerckhoff Clinic Bad Nauheim, Germany
  8. 8Department of Medicine, Division of Rheumatology, Western University of Canada, London, Ontario, Canada
  9. 9Department of Rheumatology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
  10. 10Global Medical Affairs, Actelion Pharmaceuticals Ltd, Allschwil, Switzerland
  11. 11Clinical Development, Actelion Pharmaceuticals Ltd, Allschwil, Switzerland
  12. 12Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
  13. 13Scleroderma Research Consultants LLC, Avon, Connecticut, USA
  1. Correspondence to Dr J Gerry Coghlan, Cardiology Department, Royal Free Hospital, Pond Street, Hampstead, London NW3 2QG, UK; gerry.coghlan{at}
  • Accepted 14 April 2013
  • Published Online First 18 May 2013


Objective Earlier detection of pulmonary arterial hypertension (PAH), a leading cause of death in systemic sclerosis (SSc), facilitates earlier treatment. The objective of this study was to develop the first evidence-based detection algorithm for PAH in SSc.

Methods In this cross-sectional, international study conducted in 62 experienced centres from North America, Europe and Asia, adults with SSc at increased risk of PAH (SSc for >3 years and predicted pulmonary diffusing capacity for carbon monoxide <60%) underwent a broad panel of non-invasive assessments followed by diagnostic right heart catheterisation (RHC). Univariable and multivariable analyses selected the best discriminatory variables for identifying PAH. After assessment for clinical plausibility and feasibility, these were incorporated into a two-step, internally validated detection algorithm. Nomograms for clinical practice use were developed.

Results Of 466 SSc patients at increased risk of PAH, 87 (19%) had RHC-confirmed PAH. PAH was mild (64% in WHO functional class I/II). Six simple assessments in Step 1 of the algorithm determined referral to echocardiography. In Step 2, the Step 1 prediction score and two echocardiographic variables determined referral to RHC. The DETECT algorithm recommended RHC in 62% of patients (referral rate) and missed 4% of PAH patients (false negatives). By comparison, applying European Society of Cardiology/European Respiratory Society guidelines to these patients, 29% of diagnoses were missed while requiring an RHC referral rate of 40%.

Conclusions The novel, evidence-based DETECT algorithm for PAH detection in SSc is a sensitive, non-invasive tool which minimises missed diagnoses, identifies milder disease and addresses resource usage.

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