Cardiopulmonary Exercise Testing Is an Accurate Tool for the Diagnosis of Pulmonary Arterial Hypertension in Scleroderma Related Diseases.
Mattia BellanAilia GiubertoniCristina PiccininoMariachiara BuffaDebora CromiDaniele SolaRoberta PedrazzoliIleana GagliardiElisa CalzaduccaErika ZeccaFilippo PatruccoGiuseppe PattiPier Paolo SainaghiMario PirisiPublished in: Pharmaceuticals (Basel, Switzerland) (2021)
The early diagnosis of pulmonary arterial hypertension (PAH) is a major determinant of prognosis in patients affected by connective tissue diseases (CTDs) complicated by PAH. In the present paper we investigated the diagnostic accuracy of cardiopulmonary exercise testing (CPET) in this specific setting. We recorded clinical and laboratory data of 131 patients who underwent a CPET at a pulmonary hypertension clinic. Out of them, 112 (85.5%) had a diagnosis of CTDs; 8 (6.1%) received a diagnosis of CTDs-PAH and 11 (8.4%) were affected PH of different etiology. Among CPET parameters the following parameters showed the best diagnostic performance for PAH: peak volume of oxygen uptake (VO2; AUC: 0.845, CI95% 0.767-0.904), ratio between ventilation and volume of exhaled carbon dioxide (VE/VCO2 slope; AUC: 0.888, CI95%: 0.817-0.938) and end-tidal partial pressures (PetCO2; AUC: 0.792, CI95%: 0.709-0.861). These parameters were comparable among CTDs-PAH and PH of different etiology. The diagnostic performance was even improved by creating a composite score which included all the three parameters identified. In conclusion, CPET is a very promising tool for the stratification of risk of PAH among CTDs patients; the use of composite measures may improve diagnostic performance.
Keyphrases
- pulmonary arterial hypertension
- pulmonary hypertension
- end stage renal disease
- ejection fraction
- chronic kidney disease
- newly diagnosed
- pulmonary artery
- carbon dioxide
- peritoneal dialysis
- prognostic factors
- primary care
- physical activity
- mass spectrometry
- intensive care unit
- systemic sclerosis
- high resolution
- machine learning
- big data
- patient reported outcomes
- extracorporeal membrane oxygenation
- idiopathic pulmonary fibrosis
- patient reported
- interstitial lung disease
- drug induced
- respiratory failure