AI Article Synopsis
- The study aimed to investigate how obstructive sleep apnea syndrome (OSAS) affects voice performance and the impact of continuous positive airway pressure (CPAP) treatment on this performance.
- Twenty-seven OSAS patients were compared with 28 control subjects through voice assessments, including a Voice Handicap Index (VHI) and acoustic analyses like fundamental frequency, jitter, and shimmer.
- Results indicated that OSAS patients had significantly poorer voice performance, but after one month of CPAP treatment, their acoustic parameters and VHI scores showed notable improvement.
Article Abstract
Objective: Obstructive sleep apnea syndrome (OSAS) may affect voice performance due to alterations that occur in the upper respiratory tract. The aim of the study was to assess the effect of OSAS and continuous positive airway pressure (CPAP) treatment on voice performance.
Materials And Methods: Twenty-seven patients with moderate to severe OSAS (apnea-hypopnea index ≥15/h) who underwent polysomnographic examination and 28 age- and gender-matched normal control subjects were enrolled in the study. The patients and the control subjects completed Voice Handicap Index (VHI) questionnaires, and their acoustic voice analyses were performed. Fundamental frequency (F0), jitter %, and shimmer % parameters were statistically compared. Acoustic analyses were performed again 1 month after regular CPAP use in OSAS patients, and the parameters before and after the treatment were compared.
Results: F0 was 160.82 Hz, jitter was 0.70%, shimmer was 1.05%, and VHI was 1.18 in the control group. In OSAS patients before CPAP treatment, F0 was 157.04 Hz, jitter was 0.82%, shimmer was 1.33%, and VHI was 13.11. These results showed that shimmer and VHI parameters were significantly worse in OSAS patients. After CPAP treatment, F0 was 169.19 Hz, jitter was 0.62%, shimmer was 0.93% and VHI was 5.00. The differences were statistically significant in all parameters.
Conclusion: The acoustic parameters of OSAS patients differed from those of the normal control subjects. The patients' voice performance improved after a regular use of CPAP treatment for 1 month.
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| http://dx.doi.org/10.1007/s11325-014-1092-8 | DOI Listing |
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Article Synopsis
- Continuous positive airway pressure (CPAP) is primarily prescribed for obstructive sleep apnea (OSA), but many patients still experience respiratory issues or need higher pressures during treatment.
- The study aimed to create predictive models to better forecast CPAP outcomes using both clinical and physiological data, comparing traditional regression methods to more advanced machine learning techniques.
- Results showed that machine learning models, particularly random forest methods that included physiological traits, significantly outperformed traditional regression models in predicting residual apnea-hypopnea index (AHI), highlighting the importance of using diverse data for more accurate predictions in OSA therapy.
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