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* From Centre Médical de Forcilles (Drs. Herer, Roig, and Poujol), Férolles-Attilly, France; and Service de Pneumologie (Drs. Roche and Huchon) and Département d’Informatique Médicale et de Biostatistiques (Dr. Carton), Université de Paris René Descartes, Hôpital Ambroise-Paré, Boulogne, France.
Correspondence to: Gérard J. Huchon, MD, FCCP, Service de Pneumologie et Réanimation, Hôpital de l’Hôtel-Dieu 1 Place du Parvis de Notre Dame, F-75181 Paris Cedex 4, France; e-mail: gerard.huchon{at}htd.ap-hop-paris.fr
Objective: To evaluate the diagnostic value of clinical features, pulmonary function testing, blood gas tensions, and oximetric data for case finding of obstructive sleep apnea (OSA) before polysomnography (PSG) in a series of consecutive overweight patients.
Methods: We studied a population of 102
consecutive patients referred by an obesity clinic for suspected OSA,
in whom body mass index was 
25 kg/m2. The following
tests were performed: clinical score (CS), pulmonary function tests
(PFTs), measurement of arterial blood gas tensions, nocturnal
oximetry, and full-night PSG.
Results: Six of 34 women
and 34 of 68 men had OSA, defined by an apnea-hypopnea index 15. CS
and the cumulative time spent below 80% arterial oxygen saturation
(SaO2) were higher, and
PaO2, minimal SaO2, and
mean nocturnal SaO2
(mSaO2) were lower in OSA patients than in
non-OSA patients. Logistic regression showed that sex, CS, and the
ratio of FEV1 over forced expiratory volume in 0.5 s
(an index of upper airway obstruction on flow-volume curves) and
mSaO2, expressed as categorical variables, were
independent predictors of OSA. None of these individual variables had a
satisfactory diagnostic value for the diagnosis of OSA. A logistic
regression model including sex and all continuous variables would have
allowed us to predict the presence or absence of OSA confidently in
72.5% of the population, in whom the positive predictive value of the
model was 94% and the negative predictive value was 90%.
Conclusion: In obese patients referred to a respiratory sleep laboratory and evaluated by CS, PFTs, arterial blood gases, and oximetry, no individual sign or symptom may accurately predict the presence or absence of OSA. Provided that it is validated in prospective studies, a logistic regression model using these variables may be useful for the prediction of OSA.
Key Words: clinical score • obesity • obstructive sleep apnea • oximetry • polysomnography • upper airway obstruction
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