"The M-APNE score: an objective screening tool for OSA highlighting the area under the inspiratory flow-volume curve"

Area of Science:

• Sleep Medicine
• Respiratory Medicine
• Diagnostic Tools

Background:

• Polysomnography (PSG) is the gold standard for Obstructive Sleep Apnea (OSA) diagnosis but is resource-intensive.
• Current screening tools may under-diagnose OSA due to reliance on self-reported symptoms.
• There is a need for objective screening tools to improve OSA diagnosis and resource allocation.

Purpose of the Study:

• To develop and validate an objective scoring system for screening Obstructive Sleep Apnea (OSA).
• To identify individuals at higher risk for OSA, optimizing the use of diagnostic resources.
• To overcome the limitations of subjective, symptom-based screening tools.

Main Methods:

• Developed a multivariate logistic regression model using data from 884 patients (490 with OSA).
• Incorporated objective variables: male sex, age, sawtooth pattern, area under the inspiratory flow-volume curve (AreaFI), and neck circumference.
• Compared the M-APNE Score's discriminative accuracy against the No-Apnea Score and Symptomless Multivariable Apnea Prediction (sMVAP) model using Area Under the Curve (AUC) metrics.

Main Results:

• The M-APNE Score demonstrated good performance across training, validation, and test sets, with AUCs ranging from 0.76 to 0.82.
• The M-APNE Score showed superior discriminative accuracy compared to the No-Apnea Score and sMVAP model (p < 0.001).
• The model exhibited good calibration, indicated by the Hosmer Lemeshow test (p = 0.46).

Conclusions:

• The M-APNE Score is a reliable and objective tool for screening Obstructive Sleep Apnea (OSA).
• This scoring system has the potential to reduce misclassification errors and enhance diagnostic accuracy.
• The M-APNE Score can aid in better resource allocation for OSA diagnosis.