A Systematic Review and Meta-Analysis of Mean Platelet Volume and Platelet Distribution Width in Patients with Obstructive Sleep Apnoea Syndrome.
Biagio Di LorenzoChiara ScalaArduino Aleksander MangoniStefano ZorodduPanagiotis PaliogiannisPietro PirinaAlessandro Giuseppe FoisCiriaco CarruAngelo ZinelluPublished in: Biomedicines (2024)
Obstructive sleep apnoea syndrome (OSAS) is a highly prevalent yet underestimated disorder caused by the complete or partial obstruction of the upper airways. Although polysomnography is the gold standard for OSAS diagnosis, there is an active search for easily accessible biomarkers of disease presence and severity, particularly those reflecting morphological changes in specific blood cells. We investigated the associations between the presence and severity of OSAS, continuous positive airway pressure (CPAP) treatment, mean platelet volume (MPV), and platelet distribution width (PDW), routinely assessed as part of the complete blood count. From 262 retrieved records from PubMed, the Web of Science, Scopus, and Google Scholar, 31 manuscripts were selected for a final analysis, 30 investigating MPV and 15 investigating PDW. MPV was not statistically different between OSAS patients and healthy controls; however, it progressively increased with disease severity. By contrast, OSAS patients had significantly higher PDW values than controls (SMD = 0.40, 95% CI: 0.25 to 0.56; p ˂ 0.001), and the difference increased with disease severity. In a univariate meta-regression, there were significant associations between the MPV and publication year, the apnoea-hypopnea index, and diabetes mellitus, while no associations were observed with the PDW. No significant between-group differences were observed in the subgroup analyses. These data suggest that PDW, and to a lesser extent, MPV, are potential biomarkers of OSAS and require further research to ascertain their pathophysiological significance (PROSPERO, CRD42023459413).
Keyphrases
- positive airway pressure
- obstructive sleep apnea
- sleep apnea
- end stage renal disease
- ejection fraction
- newly diagnosed
- chronic kidney disease
- magnetic resonance
- public health
- physical activity
- clinical trial
- metabolic syndrome
- skeletal muscle
- patient reported outcomes
- cystic fibrosis
- artificial intelligence
- machine learning
- big data
- weight loss
- combination therapy
- phase iii