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A clinical prediction formula for apnea-hypopnea index.

Sahin M, Bilgen C, Tasbakan MS, Midilli R, Basoglu OK - Int J Otolaryngol (2014)

Bottom Line: The relationship between these data and the PSG results was analyzed.Useful parameters were found in this analysis in terms of body mass index (BMI), waist circumference (WC), neck circumference (NC), oxygen saturation measured by pulse oximetry (SpO2), and tonsil size (TS) to predict the AHI.Conclusion.

View Article: PubMed Central - PubMed

Affiliation: Department of Otorhinolaryngology, Diskapi Yildirim Beyazit Research and Training Hospital, Irfan Bastug Street, Dıskapi, 06110 Ankara, Turkey.

ABSTRACT
Objectives. There are many studies regarding unnecessary polysomnography (PSG) when obstructive sleep apnea syndrome (OSAS) is suspected. In order to reduce unnecessary PSG, this study aims to predict the apnea-hypopnea index (AHI) via simple clinical data for patients who complain of OSAS symptoms. Method. Demographic, anthropometric, physical examination and laboratory data of a total of 390 patients (290 men, average age 50 ± 11) who were subject to diagnostic PSG were obtained and evaluated retrospectively. The relationship between these data and the PSG results was analyzed. A multivariate linear regression analysis was performed step by step to identify independent AHI predictors. Results. Useful parameters were found in this analysis in terms of body mass index (BMI), waist circumference (WC), neck circumference (NC), oxygen saturation measured by pulse oximetry (SpO2), and tonsil size (TS) to predict the AHI. The formula derived from these parameters was the predicted AHI = (0.797 × BMI) + (2.286 × NC) - (1.272 × SpO2) + (5.114 × TS) + (0.314 × WC). Conclusion. This study showed a strong correlation between AHI score and indicators of obesity. This formula, in terms of predicting the AHI for patients who complain about snoring, witnessed apneas, and excessive daytime sleepiness, may be used to predict OSAS prior to PSG and prevent unnecessary PSG.

No MeSH data available.


Related in: MedlinePlus

Distribution of predicted AHI values regarding real AHI values.
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Related In: Results  -  Collection


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fig1: Distribution of predicted AHI values regarding real AHI values.

Mentions: We found this model to be statistically significant (F = 155.348, P < 0.05). According to this formula, 68.2% of the variation in the AHI could be explained via these variables, while 32.8% could be attributed to other variables. Bland Altman plot comparing real AHI values obtained from PSG and the predicted AHI values obtained from the prediction formula is shown in Figure 1.


A clinical prediction formula for apnea-hypopnea index.

Sahin M, Bilgen C, Tasbakan MS, Midilli R, Basoglu OK - Int J Otolaryngol (2014)

Distribution of predicted AHI values regarding real AHI values.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4199210&req=5

fig1: Distribution of predicted AHI values regarding real AHI values.
Mentions: We found this model to be statistically significant (F = 155.348, P < 0.05). According to this formula, 68.2% of the variation in the AHI could be explained via these variables, while 32.8% could be attributed to other variables. Bland Altman plot comparing real AHI values obtained from PSG and the predicted AHI values obtained from the prediction formula is shown in Figure 1.

Bottom Line: The relationship between these data and the PSG results was analyzed.Useful parameters were found in this analysis in terms of body mass index (BMI), waist circumference (WC), neck circumference (NC), oxygen saturation measured by pulse oximetry (SpO2), and tonsil size (TS) to predict the AHI.Conclusion.

View Article: PubMed Central - PubMed

Affiliation: Department of Otorhinolaryngology, Diskapi Yildirim Beyazit Research and Training Hospital, Irfan Bastug Street, Dıskapi, 06110 Ankara, Turkey.

ABSTRACT
Objectives. There are many studies regarding unnecessary polysomnography (PSG) when obstructive sleep apnea syndrome (OSAS) is suspected. In order to reduce unnecessary PSG, this study aims to predict the apnea-hypopnea index (AHI) via simple clinical data for patients who complain of OSAS symptoms. Method. Demographic, anthropometric, physical examination and laboratory data of a total of 390 patients (290 men, average age 50 ± 11) who were subject to diagnostic PSG were obtained and evaluated retrospectively. The relationship between these data and the PSG results was analyzed. A multivariate linear regression analysis was performed step by step to identify independent AHI predictors. Results. Useful parameters were found in this analysis in terms of body mass index (BMI), waist circumference (WC), neck circumference (NC), oxygen saturation measured by pulse oximetry (SpO2), and tonsil size (TS) to predict the AHI. The formula derived from these parameters was the predicted AHI = (0.797 × BMI) + (2.286 × NC) - (1.272 × SpO2) + (5.114 × TS) + (0.314 × WC). Conclusion. This study showed a strong correlation between AHI score and indicators of obesity. This formula, in terms of predicting the AHI for patients who complain about snoring, witnessed apneas, and excessive daytime sleepiness, may be used to predict OSAS prior to PSG and prevent unnecessary PSG.

No MeSH data available.


Related in: MedlinePlus