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Vital capacity and valvular dysfunction could serve as non-invasive predictors to screen for exercise pulmonary hypertension in the elderly based on a new diagnostic score

Introduction: Exercise pulmonary hypertension (exPH) has been defined as total pulmonary resistance (TPR) >3 mm Hg/L/min and mean pulmonary artery pressure (mPAP) >30 mm Hg, albeit with a considerable risk of false positives in elderly patients with lower cardiac output during exercise. Method...

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Detalles Bibliográficos
Autores principales: Wernhart, Simon, Hedderich, Jürgen, Weihe, Eberhard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Tabriz University of Medical Sciences 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8007893/
https://www.ncbi.nlm.nih.gov/pubmed/33815705
http://dx.doi.org/10.34172/jcvtr.2021.05
Descripción
Sumario:Introduction: Exercise pulmonary hypertension (exPH) has been defined as total pulmonary resistance (TPR) >3 mm Hg/L/min and mean pulmonary artery pressure (mPAP) >30 mm Hg, albeit with a considerable risk of false positives in elderly patients with lower cardiac output during exercise. Methods: We retrospectively analysed patients with unclear dyspnea receiving right heart catheterisation at rest and exercise (n=244) between January 2015 and January 2020. Lung function testing, blood gas analysis, and echocardiography were performed. We elaborated a combinatorial score to advance the current definition of exPH in an elderly population (mean age 67.0 years±11.9). A stepwise regression model was calculated to non-invasively predict exPH. Results: Analysis of variables across the achieved peak power allowed the creation of a model for defining exPH, where three out of four criteria needed to be fulfilled: Peak power ≤100 Watt, pulmonary capillary wedge pressure ≥18 mm Hg, pulmonary vascular resistance >3 Wood Units, and mPAP ≥35 mm Hg. The new scoring model resulted in a lower number of exPH diagnoses than the current suggestion (63.1% vs. 78.3%). We present a combinatorial model with vital capacity (VC(max)) and valvular dysfunction to predict exPH (sensitivity 93.2%; specificity 44.2%, area under the curve 0.73) based on our suggested criteria. The odds of the presence of exPH were 2.1 for a 1 l loss in VC(max) and 3.6 for having valvular dysfunction. Conclusion: We advance a revised definition of exPH in elderly patients in order to overcome current limitations. We establish a new non-invasive approach to predict exPH by assessing VC(max) and valvular dysfunction for early risk stratification in elderly patients.