Introduccion: Intermittent chronic hypoxia produced during obstructive sleep apneas (OSA) leads to oxidative stress, and consequently to a state of systemic inflammation. There are no biomarkers that assess the degree of inflammation and are related to the severity of this disease. The red cell distribution amplitude and the ultrasensitive reactive C protein are sensitive to the systemic inflammation generated by oxidative stress. We intend to correlate the reactive C protein and red cell distribution amplitude values with the degree of severity of OSA.
Methods: An observational, prospective, analytical study was performed. OSA patients participated. Spearman's correlation coefficient was used to estimate the correlation between red cell distribution amplitude and reactive C protein with OSA severity according to apnea hypopnea index (AHI).
Results: 95 patients participated, of which 79 were men. Only 10 (10.5%) patients presented normal BMI. The correlations between AHI with reactive C protein and red cell distribution amplitude were weak (r = 0.17; p = 0.1066 and r = 0.06; p = 0.5867, respectively). The correlations between T90 with reactive C protein and red cell distribution amplitude were also weak (r = 0.16; p = 0.1331 and r = 0.24; p = 0.0202, respectively). An association was found between red cell distribution amplitude greater than 14 and severe OSA (p = 0.0369) and with T90 greater than 10% (p = 0.0168).
Conclusions: Although the correlations between AHI and T90 with reactive C protein and red cell distribution amplitude were weak, it was found that severe patients, presented higher values of red cell distribution amplitude and higher T <90. This association could not be tested with reactive C protein.
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http://dx.doi.org/10.31053/1853.0605.v78.n2.30397 | DOI Listing |
Sci Rep
December 2024
Laboratory of Biochemistry and Vascular Biology, Center for Biologic Evaluation and Research, Food and Drug Administration, Bethesda, 20993, MD, USA.
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December 2024
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Sci Rep
December 2024
Department of Cardiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi, People's Republic of China.
There is a lack of an effective prognostic model for predicting outcomes in patients with primary pulmonary hypertension (PPH). A retrospective analysis was conducted on PPH patients from MIMIC and eICU databases. A predictive model was developed to assess mortality risk.
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December 2024
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Department of Nutrition, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
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