Study Suggests CPET as Way to Identify PAH in Systemic Sclerosis Patients

Study Suggests CPET as Way to Identify PAH in Systemic Sclerosis Patients

Cardiopulmonary exercise testing can improve the ability of an algorithm to identify systemic sclerosis patients who have pulmonary arterial hypertension (PAH), a new study suggests.

The study, “Cardiopulmonary exercise testing in a combined screening approach to individuate pulmonary arterial hypertension in systemic sclerosis,” was published in the journal Rheumatology.

Systemic sclerosis (SSc) is one of the main conditions that predisposes a person to develop PAH. Identifying people with SSc-associated PAH as early as possible is important, because early diagnosis and starting treatment rapidly are predictors of good clinical outcomes in this patient population.

The gold standard for detecting PAH is right heart catheterization (RHC), but this invasive technique involves putting a catheter in a patient’s heart, so researchers have tried to come up with ways to identify PAH in a less invasive manner.

In a previously published study, researchers developed an algorithm, called DETECT, with the aim of identifying those with SSc most at risk of PAH. Using RHC as the gold standard to detect PAH, this algorithm was found to be quite good at identifying PAH, but it also had a high (over 50%) false-positive rate, which limits its clinical utility.

In the new study, researchers hypothesized that the predictive power of DETECT could be improved by using cardiopulmonary exercise testing (CPET) — a tool to measure the functionality of the heart and lungs during exercise.

To test this hypothesis, the researchers screened 314 people with SSc over a 30-month period using the DETECT algorithm. PAH-positive individuals were referred for CPET before undergoing RHC.

In total, 54 SSc patients were considered positive for PAH (meaning at higher risk) based on the DETECT criteria. These individuals then underwent CPET, as well as RHC, which was again used as the gold standard. Results showed that 17 of the patients (31.5%) had PAH.

Researchers then used statistical models to identify CPET parameters that were predictive of PAH. They found that the best predictor was the relationship between minute ventilation (VE) and carbon dioxide production (VCO2), termed the VE/VCO2 slope. In simple terms, the VE/VCO2 slope is the ratio between the total amount of air a person moves into and out of the lungs in a minute, and the amount of carbon dioxide that is breathed out after transporting oxygen through the body.

The VE/VCO2 slope had a sensitivity of 1.0 in 87% of the models tested — that is, it correctly identified all individuals with PAH 87% of the time. The median specificity — meaning how well the test identifies patients who do not have PAH — was 0.778.

Based on the results, the team stated that “in association with the DETECT algorithm, CPET may be considered as a useful tool in the workup of SSc-related pulmonary hypertension.”

“The sequential determination of the VE/VCO2 slope in DETECT-positive subjects may reduce the number of unnecessary invasive procedures without any loss in the capability to capture PAH,” the researchers added.

Marisa holds an MS in Cellular and Molecular Pathology from the University of Pittsburgh, where she studied novel genetic drivers of ovarian cancer. She specializes in cancer biology, immunology, and genetics. Marisa began working with BioNews in 2018, and has written about science and health for SelfHacked and the Genetics Society of America. She also writes/composes musicals and coaches the University of Pittsburgh fencing club.
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Patrícia holds her PhD in Medical Microbiology and Infectious Diseases from the Leiden University Medical Center in Leiden, The Netherlands. She has studied Applied Biology at Universidade do Minho and was a postdoctoral research fellow at Instituto de Medicina Molecular in Lisbon, Portugal. Her work has been focused on molecular genetic traits of infectious agents such as viruses and parasites.
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Marisa holds an MS in Cellular and Molecular Pathology from the University of Pittsburgh, where she studied novel genetic drivers of ovarian cancer. She specializes in cancer biology, immunology, and genetics. Marisa began working with BioNews in 2018, and has written about science and health for SelfHacked and the Genetics Society of America. She also writes/composes musicals and coaches the University of Pittsburgh fencing club.
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