Dataset Information

Predictive equation for optimal continuous positive airway pressure in children with obstructive sleep apnoea.

ABSTRACT:

Aim

A subgroup of children with obstructive sleep apnoea (OSA) requires treatment with continuous positive airway pressure (CPAP). This study's aims were: 1) to determine if the optimal CPAP for the treatment of OSA in children correlates with body mass index (BMI); 2) to determine the correlation between polysomnographic variables and optimal CPAP in children with OSA; and 3) to develop a CPAP predictive equation for children with OSA.

Methods

This was a retrospective study of children with OSA who underwent CPAP titration studies. Patients with craniofacial abnormalities (except Down syndrome) and neuromuscular diseases were excluded. Polysomnograms were done using Sandman Elite. Correlations between optimal CPAP, clinical and polysomnographic variables were analysed. A multivariable linear regression model for optimal CPAP was developed.

Results

198 children (mean±sd age 13.1±3.6?years) were studied. Optimal CPAP had a significant positive correlation with age (rho=0.216, p=0.002), obstructive apnoea-hypopnoea index (rho=0.421, p<0.001), 3% oxygen desaturation index (rho=0.417, p<0.001), rapid eye movement respiratory disturbance index (rho=0.378, p<0.001) and BMI z-score (rho=0.160, p=0.024); and a significant negative correlation with arterial oxygen saturation measured by pulse oximetry nadir (rho=?-0.333, p<0.001). The predictive equation derived was:Optimal CPAP (cmH₂O)=6.486+0.273·age (years)-0.664·adenotonsillectomy(no=1, yes=0)+2.120·Down syndrome (yes=1, no=0)+0.280·BMI z-score.

Conclusion

The equation developed may help to predict optimal CPAP in children with OSA. Further studies are required to validate this equation and to determine its applicability in different populations.

SUBMITTER: Chong J

PROVIDER: S-EPMC7276523 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Publications

Predictive equation for optimal continuous positive airway pressure in children with obstructive sleep apnoea.

Chong Joelle J Bajpai Ram R Teoh Oon Hoe OH Pugalenthi Arun A Allen John C JC Cheng Zai Ru ZR Tan Soh Gin SG Lim Meilan M Tan Jasmine J Goh Anne A Tan Yi Hua YH Thomas Biju B

ERJ open research 20200401 2

<h4>Aim</h4>A subgroup of children with obstructive sleep apnoea (OSA) requires treatment with continuous positive airway pressure (CPAP). This study's aims were: 1) to determine if the optimal CPAP for the treatment of OSA in children correlates with body mass index (BMI); 2) to determine the correlation between polysomnographic variables and optimal CPAP in children with OSA; and 3) to develop a CPAP predictive equation for children with OSA.<h4>Methods</h4>This was a retrospective study of ch ...[more]

PMID: 32537463

Similar Datasets

Project description:Background:Continuous positive airway pressure (CPAP) is an effective treatment for obstructive sleep apnoea (OSA), but an evaluation of CPAP adherence is rarely carried out among patients with acute coronary syndrome (ACS). The goals of the study are to analyse long-term adherence and identify the predictors of non-compliance with CPAP treatment for patients with non-sleepy OSA and ACS. Methods:This is an ancillary study of the ISAACC study, which is a multicentre, prospective, open-label, parallel, randomized, and controlled trial (NCT01335087) in patients with hospital admission for ACS. For the purpose of this study, only non-sleepy patients with moderate or severe OSA and randomized to receive CPAP treatment were analysed (n=357). Non-compliance was defined as CPAP dropout or average cumulative CPAP use of <4 hours/night. Multivariable logistic regression analysis was performed to identify predictors of CPAP adherence. Results:Adherence to treatment was 35.3% at 12 months. According to the unadjusted analysis, higher apnoea-hypopnea index (AHI) (P<0.001) and oxygen desaturation index (ODI) (P=0.001) were associated with a lower risk of non-compliance. Multivariable logistic regression analysis showed that high AHI (P=0.0051), high amounts of smoking pack-year (P=0.0170), and long intensive care unit (ICU) stays (P=0.0263) were associated with lower odds of non-compliance. It also showed a significant interaction between ACS history and age (P=0.0131), such that young patients with their first ACS showed significantly lower odds of CPAP non-compliance than patients with recurrent ACS and significantly lower odds of CPAP non-compliance were associated with ageing only in patients with recurrent ACS. Conclusions:Protective factors against non-compliance with CPAP treatment in non-sleepy patients with ACS were illness severity (high values of AHI or ICU stay length) or smoking amount. Patients with no previous history of ACS showed lower odds of CPAP non-compliance than patients with a recurrent ACS with younger age.

Dataset Information

Predictive equation for optimal continuous positive airway pressure in children with obstructive sleep apnoea.

Aim

Methods

Results

Conclusion

Publications

Predictive equation for optimal continuous positive airway pressure in children with obstructive sleep apnoea.

Similar Datasets

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