Clinical risk assessment model for pediatric obstructive sleep apnea

2016 ◽  
Vol 126 (10) ◽  
pp. 2403-2409 ◽  
Author(s):  
Kun-Tai Kang ◽  
Wen-Chin Weng ◽  
Chia-Hsuan Lee ◽  
Tzu-Yu Hsiao ◽  
Pei-Lin Lee ◽  
...  

Objective: To develop a clinical assessment model for predicting moderate to severe obstructive sleep apnea (OSA). Materials and Methods: All patients suspected of having OSA and undergoing the laboratory polysomnography (PSG) were enrolled. The clinical data, associated factors and PSG finding were reviewed. Significant risk factors for the model were chosen using multivariate logistic regression analysis. The predictive parameters of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated. Results: Of the 929 patients, 580 (62.4%) had moderate to severe OSA. Patient ages ranged between 18 and 85 years, with the majority between 30 and 60 years (71.5%). Males were significantly prominent in the moderate to severe OSA group (76.4%). Forty-three percent had a body mass index (BMI) greater than 30 and 52% had a neck circumference (NC) greater than 40. Multivariate analysis showed the male gender, a BMI of 30 or greater, a NC of 40 or greater, a waist to height ratio (WHtR) of 0.5 or greater, the presence of hypertension (HT), and observed apnea were significant factors correlated with moderate to severe OSA. The clinical assessment model was created by using their estimated coefficients. The optimal cutoff points for predicting apnea-hypopnea index (AHI) of 15 or greater was 2, with sensitivity of 85.5% and specificity of 49.6%. Conclusion: The present clinical risk assessment model appears to be a useful practical tool for identifying patients at risk for moderate to severe OSA, with acceptable predictive performance. Keywords: Obstructive sleep apnea, Clinical assessment model, Predicting, Sleep apnea


2020 ◽  
Vol 20 ◽  
pp. 100270 ◽  
Author(s):  
Banne Nemeth ◽  
Delphine Douillet ◽  
Saskia le Cessie ◽  
Andrea Penaloza ◽  
Thomas Moumneh ◽  
...  

2010 ◽  
Vol 06 (05) ◽  
pp. 467-472 ◽  
Author(s):  
Tracey L. Stierer ◽  
Christopher Wright ◽  
Anu George ◽  
Richard E. Thompson ◽  
Christopher L. Wu ◽  
...  

2019 ◽  
Vol 64 ◽  
pp. S175
Author(s):  
J.-Y. Jeon ◽  
H.-J. Moon ◽  
K.T. Kim ◽  
Y.W. Cho

Medicina ◽  
2019 ◽  
Vol 55 (8) ◽  
pp. 468 ◽  
Author(s):  
Alexia Alexandropoulou ◽  
Georgios D. Vavougios ◽  
Chrissi Hatzoglou ◽  
Konstantinos I. Gourgoulianis ◽  
Sotirios G. Zarogiannis

Background and objectives: The risk assessment of Obstructive Sleep Apnea (OSA) and Excessive Daytime Sleepiness (EDS) in specific occupational populations is important due to its association with morbidity. The aim of the present study was to identify the risk of OSA development and EDS in a Greek nursing staff population. Materials and Methods: In this cross-sectional study a total of 444 nurses, 56 males (age = 42.91 ± 5.76 years/BMI = 27.17 ± 4.32) and 388 females (age = 41.41 ± 5.92 years/BMI = 25.08 ± 4.43) working in a Greek secondary and tertiary hospital participated during the period from 18 January 2015 to 10 February 2015. The participants completed the Berlin Questionnaire (BQ), concerning the risk for OSA and the Epworth Sleepiness Scale (ESS), concerning the EDS. The work and lifestyle habits of the participants were correlated with the results of the questionnaires. Results: According to the BQ results 20.5% (n = 91) of the nursing staff was at high risk for OSA. Increased daytime sleepiness affected 27.7% (n = 123) of the nurses according to ESS results. Nurses at risk for Obstructive Sleep Apnea Syndrome (OSAS), positive for both BQ and ESS, were 7.66% (n = 34). Out of the nurses that participated 77% (n = 342) were working in shifts status and had significant meal instability (breakfast p < 0.0001, lunch p < 0.0001, dinner p = 0.0008). Conclusions: The population at high risk for OSA and EDS in the nursing staff was found to be 20% and 28% respectively. High risk for OSAS was detected in 7.66% of the participants. The high risk for OSA and EDS was the same irrespective of working in shift status. In specific, nursing population age was an independent predictor for high risk for OSA and skipping lunch an independent predictor of daytime sleepiness.


2018 ◽  
Vol 13 (4) ◽  
pp. 221-230 ◽  
Author(s):  
Nitin Joseph ◽  
Arun Shirali ◽  
Anjana Bhami Shenoy ◽  
Devu Krishna Thulaseedharan ◽  
Malavika Ramgopal ◽  
...  

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