Predicting Sleep Apnea and Excessive Day Sleepiness in the Severely Obese
| Autor: | John Dixon, Paul E. O'Brien, Linda M Schachter |
|---|---|
| Rok vydání: | 2003 |
| Předmět: |
Pulmonary and Respiratory Medicine
medicine.medical_specialty Sleep disorder medicine.diagnostic_test business.industry Epworth Sleepiness Scale Sleep apnea Polysomnography Critical Care and Intensive Care Medicine medicine.disease nervous system diseases respiratory tract diseases Surgery Obstructive sleep apnea Apnea–hypopnea index Internal medicine medicine medicine.symptom Cardiology and Cardiovascular Medicine business Body mass index Somnolence |
| Zdroj: | Chest. 123:1134-1141 |
| ISSN: | 0012-3692 |
| DOI: | 10.1378/chest.123.4.1134 |
| Popis: | Background: Obstructive sleep apnea (OSA) is common in severely obese subjects (body mass index [BMI] > 35). Overnight polysomnography (OPS) is the “gold standard” method of evaluating this condition; however, it is time-consuming, inconvenient, and expensive. Selection of patients for OPS would be enhanced if we could better predict those likely to have clinically significant OSA. Study objective: To look for clinical and biochemical predictors of OSA in symptomatic patients presenting for obesity surgery. Design and patients: Symptoms suggestive of OSA were sought in a structured interview. We report OPS results of 99 consecutive subjects in whom OSA was clinically suspected. Predictors of apnea-hypopnea index (AHI) were sought from an extensive preoperative data collection. Multivariate linear and logistic analysis was used to identify independent predictors of AHI. Results: Symptoms were poor predictors of AHI, with observed sleep apnea the only positive predictor. Four clinical and two biochemical factors independently predicted AHI: observed sleep apnea, male sex, higher BMI, age, fasting insulin, and glycosylated hemoglobin AIc (r 2 0.42). Neck circumference (the best single measure) could replace BMI and sex in the analysis (r 2 0.43). With cutoffs selected, a simple scoring system using these six factors provides a method of predicting those with moderate or severe OSA. A score > 3 provides a sensitivity and specificity of 89% and 81%, and 96% and 71% for AHIs of > 15 and > 30, respectively. None of the 31 subjects with scores of 0 or 1 were found to have an AHI > 15. Conclusion: We explore sleep disturbance and report a simple method of predicting OSA in severely obese symptomatic subjects. This should assist in limiting the use of OPS to those with greater risk and provide a method of assessing risk in those not presenting primarily with a sleep problem. Abbreviations: AHI apnea-hypopnea index; ANOVA analysis of variance; BASH’IM body mass index, age, observed sleep apnea, glycosylated hemoglobin AIc, insulin, and male gender; BMI body mass index; CI confidence interval; ESS Epworth sleepiness scale; HbAIc glycosylated hemoglobin AIc; HDL high-density lipoprotein; OPS overnight polysomnography; OR odds ratio; OSA obstructive sleep apnea; REM rapid eye movement; ROC receiver operating characteristic; SF-36 Short-Form 36 Health Survey |
| Databáze: | OpenAIRE |
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