A Pilot Study on the Relationship between Obstructive Sleep Apnoea-Hypopnea Syndrome, Neurodevelopment, and Ricketts' Cephalometry.
Teresa I González RobaynaCarlos Pérez-Albacete MartínezJesús M GandíaMª Dolores Austro MartínezÁngela Sempere PérezRaúl Ferrando CascalesPublished in: Journal of clinical medicine (2024)
Background : The aim of this research is to achieve the early detection of facial characteristics in patients diagnosed with neurodevelopmental deficits and obstructive sleep apnoea-hypopnea syndrome (OSAHS) through the analysis of the VERT index and Ricketts' cephalometry to minimise the neurocognitive morbidity associated with these disorders. Methods : This clinical study was conducted on 44 patients aged 4 to 15 years. Participants completed an initial questionnaire about sleep disturbances, followed by a polysomnography, a radiographic study, and an oral examination. Results : The maximum variability in the data was obtained in the mandibular plane angle, where we observed that the measurement was higher in patients diagnosed with OSAHS. The relative and normalised indices of facial depth and the mandibular plane showed variations between patients with a clinical picture compatible with OSAHS and the control group without pathology. Conclusions : Our findings indicate that Ricketts' VERT index by itself is unable to provide evidence of a diagnosis compatible with OSAHS in patients with early neurodevelopmental deficits, but, after analysing the results obtained, we observed that for the cephalometric measurements of the mandibular plane angle and facial depth relative to the patient's age, there are sufficiently strong variations for creating a solid method of differential diagnosis, thus preventing complications at the neurocognitive level.
Keyphrases
- end stage renal disease
- ejection fraction
- newly diagnosed
- obstructive sleep apnea
- chronic kidney disease
- physical activity
- traumatic brain injury
- prognostic factors
- peritoneal dialysis
- clinical trial
- bipolar disorder
- positive airway pressure
- sleep apnea
- mass spectrometry
- artificial intelligence
- double blind
- patient reported
- data analysis