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PURPOSE: An early prescreening in suspected obstructive sleep apnea (OSA) patients is desirable to expedite diagnosis and treatment. However, the accuracy and applicability of current prescreening tools is insufficient. We developed and tested an unbiased scoring system based solely on objective variables, which focuses on the diagnosis of severe OSA and exclusion of OSA. PATIENTS AND METHODS: The OSA prediction score was developed (n = 150) and validated (n = 50) within German sleep center patients that were recruited as part of the Sleep Apnea Global Interdisciplinary Consortium (SAGIC). Six objective variables that were easy to assess and highly correlated with the apnea-hypopnea index were chosen for the score, including some known OSA risk factors: body-mass index, neck circumference, waist circumference, tongue position, male gender, and age (for women only). To test the predictive ability of the score and identify score thresholds, the receiver-operating characteristics (ROC) and curve were calculated. RESULTS: A score ≥8 for predicting severe OSA resulted in an area under the ROC curve (ROC-AUC) of 90% (95% confidence interval: 84%, 95%), test accuracy of 82% (75%, 88%), sensitivity of 82% (65%, 93%), specificity of 82% (74%, 88%), and positive likelihood ratio of 4.55 (3.00, 6.90). A score ≤5 for predicting the absence of OSA resulted in a ROC-AUC of 89% (83%, 94%), test accuracy of 80% (73%, 86%), sensitivity of 72% (55%, 85%), specificity of 83% (75%, 89%), and positive likelihood ratio of 4.20 (2.66, 6.61). Performance characteristics were comparable in the small validation sample. CONCLUSION: We introduced a novel prescreening tool combining easily obtainable objective measures with predictive power and high general applicability. The proposed tool successfully predicted severe OSA (important due to its high risk of cardiovascular disease) and the exclusion of OSA (rarely a feature of previous screening instruments, but important for better differential diagnosis and treatment).
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Study Objectives: A recent study of patients with moderate-severe obstructive sleep apnea (OSA) in Iceland identified three clinical clusters based on symptoms and comorbidities. We sought to verify this finding in a new cohort in Iceland and examine the generalizability of OSA clusters in an international ethnically diverse cohort. Methods: Using data on 972 patients with moderate-severe OSA (apnea-hypopnea index [AHI] ≥ 15 events per hour) recruited from the Sleep Apnea Global Interdisciplinary Consortium (SAGIC), we performed a latent class analysis of 18 self-reported symptom variables, hypertension, cardiovascular disease, and diabetes. Results: The original OSA clusters of disturbed sleep, minimally symptomatic, and excessively sleepy replicated among 215 SAGIC patients from Iceland. These clusters also generalized to 757 patients from five other countries. The three clusters had similar average AHI values in both Iceland and the international samples, suggesting clusters are not driven by OSA severity; differences in age, gender, and body mass index were also generally small. Within the international sample, the three original clusters were expanded to five optimal clusters: three were similar to those in Iceland (labeled disturbed sleep, minimal symptoms, and upper airway symptoms with sleepiness) and two were new, less symptomatic clusters (labeled upper airway symptoms dominant and sleepiness dominant). The five clusters showed differences in demographics and AHI, although all were middle-aged (44.6-54.5 years), obese (30.6-35.9 kg/m2), and had severe OSA (42.0-51.4 events per hour) on average. Conclusions: Results confirm and extend previously identified clinical clusters in OSA. These clusters provide an opportunity for a more personalized approach to the management of OSA.
