| Autor: |
Xin Li, Yi Zhang, Qi Jin, Zhihui Zhao, Qing Zhao, Lu Yan, Anqi Duan, Zhihua Huang, Meixi Hu, Changming Xiong, Qin Luo, Zhihong Liu |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Respiratory Research, Vol 23, Iss 1, Pp 1-11 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1465-993X |
| DOI: |
10.1186/s12931-022-02212-5 |
| Popis: |
Abstract Background Ventilatory power is a novel index which could reflect both ventilation efficiency and peripheral blood flow. However, its clinical value in pulmonary hypertension (PH) is rarely discussed. In the present study, we aimed to investigate the diagnostic and prognostic value of ventilatory power as well as its association with disease severity in PH. Methods Consecutive patients with normal hemodynamics and patients diagnosed with PH between September, 2012 and December, 2020 in Fuwai hospital were enrolled. Receiver operating characteristic curves were constructed to determine diagnostic power of ventilatory power and tricuspid regurgitation velocity (TRV). Spearman correlation coefficients were used to evaluate bivariate correlation. Multivariable Cox analysis were used to evaluate the association between ventilatory power and clinical worsening. Results A total of 679 patients were included in the study, among whom 177 were patients with normal hemodynamics, and 502 were patients with PH. Among patients with PH, those experiencing clinical worsening had lower ventilatory power than those did not. The area under the curve of TRV plus ventilatory power was higher than TRV used alone when identifying overt and borderline PH. Ventilatory power was also correlated with well-validated variables that reflected severity of PH, such as NT-proBNP. Multivariable Cox analysis showed that ventilatory power could independently predict clinical worsening and could improve the predictive power of the current PH risk assessment tool. Conclusion Ventilatory power could improve the predictive power of TRV in identifying overt PH and borderline PH. Moreover, it could reflect disease severity and independently predict clinical worsening. |
| Databáze: |
Directory of Open Access Journals |
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