Red cell distribution width: A new tool for the severity prediction of sleep apnoea syndrome in children

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Abstract

Introduction: Red cell distribution width (RDW) is a parameter included in the complete blood count which informs about the size of the circulating red blood cell population and its distribution. In adults, an increase in RDW was shown to be associated both with obstructive sleep apnoea (OSA) and with an increase in cardiovascular mortality. The aim of this study was to determine whether RDW is a potential biomarker for screening children with moderate–severe OSA. Methods: An observational study in snoring patients was performed. All patients underwent a sleep study and were classified either as simple snorers (apnoea–hypopnoea index (AHI) <1 event·h−1) or as patients with OSA (mild AHI ⩾1 to <5 events·h−1; moderate–severe AHI ⩾5 events·h−1). Blood analyses (complete blood count and C-reactive protein) were performed for every individual. Results: A total of 175 individuals were recruited. The mean age was 8.3±3.6 years. Correlation studies between RDW and several sleep-related parameters showed negative significant associations with minimum oxygen saturation, and positive significant associations with oxygen desaturation index (⩾3% and ⩾4%), AHI and the arousal index. A predictive model for paediatric severe OSA (AHI ⩾5 events·h−1) was found based on mean corpuscular haemoglobin concentration (MCHC) <34.9 g·dL−1 and RDW >13.1% values, adjusting for body mass index z-score and age (area under the curve 0.657; p=0.004). In addition, differences were found in eosinophil count and C-reactive protein concentrations among the three subgroups. Conclusions: In children, RDW stands out as a biomarker associated with the severity of OSA. The use of RDW and MCHC could be a simple but useful tool for the severity prediction of paediatric OSA in snoring patients.

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Morell-Garcia, D., Toledo-Pons, N., Sanchis, P., Bauça, J. M., Sánchez, J. M., Peña-Zarza, J., … Barceló, A. (2020). Red cell distribution width: A new tool for the severity prediction of sleep apnoea syndrome in children. ERJ Open Research, 6(4), 1–10. https://doi.org/10.1183/23120541.00278-2019

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