ABSTRACT
Clinical assessment of obstructive sleep apnea (OSA) is poor. Overnight polysomnography (OPG) is the standard reference test, but it is expensive and time-consuming. We developed an artificial neural network (ANN) using anthropomorphic measurements and clinical information to predict the apnea-hypopnea index (AHI). All patients completed a questionnaire about sleep symptoms, sleep behavior, and demographic information prior to undergoing OPG. Neck circumference, height, and weight were obtained on presentation to the sleep center. Twelve variables were used as inputs. The output was an estimate of the AHI. The network was trained with a back-propagation algorithm on 189 patients and validated prospectively on 80 additional patients. Data from the derivation group was used to calculate the 95% confidence interval of the estimated AHI. Predictive accuracy at different AHI thresholds was assessed by the c-index, which is equivalent to the area under the receiver operator characteristic curve. The c-index for predicting OSA in the validation set was 0.96 +/- 0.0191 SE, 0.951 +/- 0.0203 SE, and 0.935 +/- 0.0274 SE, using thresholds of > 10, > 15, and > 20/hour respectively. The actual AHI of the 80 patients in the validation data set fell within the 95% confidence limits of the values predicted by the ANN. This study suggests that ANN may be useful as a predictive tool for OSA.
Subject(s)
Neural Networks, Computer , Sleep Apnea Syndromes/diagnosis , Adolescent , Adult , Aged , Aged, 80 and over , Cohort Studies , Female , Humans , Male , Middle Aged , Polysomnography , Prospective Studies , Reproducibility of ResultsABSTRACT
The diagnosis of sleep apnea should be considered when a patient complains of snoring and excessive daytime somnolence. Middle-aged obese men are at particular risk, although apnea can occur in women and the elderly, as well as in persons who are not obese. An overnight polysomnographic sleep study can reveal the degree and type of apnea. Effective medical therapy can provide prompt clinical improvement. General treatment measures include weight loss and, in mild cases, training the patient to sleep in a side-lying position. Continuous positive airway pressure administered by masks worn at night is especially effective. Surgical treatment can help properly selected patients. Uvulopalatopharyngoplasty, which increases the volume of the oropharynx, requires follow-up polysomnographic studies. Tracheostomy is extremely effective and can be lifesaving in severe obstructive apnea. Effective therapeutic options make early recognition and treatment of this disorder vital and successful.
