Screening for obstructive sleep apnea: comparing the American Academy of Sleep Medicine proposed criteria with the STOP-Bang, NoSAS, and GOAL instruments.

STUDY OBJECTIVES: We evaluated the performance of the 2017 American Academy of Sleep Medicine criteria (AASM2017) in screening obstructive sleep apnea (OSA) and compared them with 3 other validated instruments: NoSAS score, STOP-Bang, and GOAL questionnaires. METHODS: From July 2019 to December 2021, 4,499 adults undergoing overnight polysomnography were included. The AASM2017 instrument considers an increased high risk for moderate-to-severe OSA in the presence of excessive daytime sleepiness and at least 2 of the following 3 criteria: loud snoring; observed apnea, gasping, or choking; and hypertension. OSA severity was based on polysomnography-derived apnea-hypopnea index cutoffs: 5.0 events/h, 15.0 events/h, and 30.0 events/h. Predictive performance was evaluated by the area under the curve and contingency tables. RESULTS: When screening for any OSA severity, AASM2017 displayed a sensitivity of 31.0-40.6% and a specificity of 80.8-89.6%. For all apnea-hypopnea index thresholds, AASM2017, unlike the GOAL, STOP-Bang, and NoSAS, exhibited superior specificity but markedly lower sensitivity. GOAL, STOP-Bang, and NoSAS, but not AASM2017 criteria, emerged as an adequate screening tool for any OSA severity (all areas under the curve > 0.7) and performed significantly better than AASM2017 in predicting any OSA severity (all P < .001). For all severity OSA levels, GOAL, STOP-Bang, and NoSAS displayed similar performance when compared to each other (all P > .05). CONCLUSIONS: GOAL, STOP-Bang, and NoSAS instruments, but not AASM2017 criteria, emerge as useful OSA screening tools in a large referral single-center clinical cohort. CITATION: Duarte RLM, Magalhães-da-Silveira FJ, Gozal D. Screening for obstructive sleep apnea: comparing the American Academy of Sleep Medicine proposed criteria with the STOP-Bang, NoSAS, and GOAL instruments. J Clin Sleep Med. 2023;19(7):1239-1246.

Predictive factors for obstructive sleep apnea in adults with severe asthma receiving biologics: a single-center cross-sectional study.

PURPOSE: To evaluate the prevalence and potential predictors of obstructive sleep apnea (OSA) in a cohort of adults with severe asthma. METHODS: From March 2021 to December 2021, this cross-sectional study enrolled patients with severe asthma receiving biologics, who were consecutively referred for sleep evaluation irrespective of sleep-related symptoms. Clinical and functional data, including three OSA screening instruments (GOAL, STOP-Bang, and NoSAS) were recorded. All participants underwent a portable sleep test (ApneaLink Air™). OSA diagnosis was based on the respiratory disturbance index ≥ 5.0/h and subclassified according to severity thresholds. Data were subjected to logistic regression tests to identify possible predictors for OSA. Discrimination was estimated from the area under the curve (AUC). RESULTS: Overall, 56 outpatients were included (80% females): 54% with any OSA, 13% with moderate-to-severe OSA, and 4% with severe OSA. In the multivariate analysis, no parameter emerged as an independent predictor for OSA: age (p = 0.080), body mass index (p = 0.060), loud snoring (p = 0.130), and hypertension (p = 0.848). No screening instrument was useful to predict any OSA: GOAL (AUC: 0.714; 95% confidence interval (CI): 0.579-0.849), NoSAS (AUC: 0.645; 95% CI: 0.497-0.793), and STOP-Bang (AUC: 0.640; 95% CI: 0.493-0.788). Similarly, no screening tool was also useful for predicting moderate-to-severe OSA or severe OSA. CONCLUSION: Patients with evere asthma receiving biologics exhibit a high prevalence of OSA. However, no clinical, functional, or OSA screening instrument showed acceptable discriminatory ability to predict the presence of OSA in these patients with severe asthma.

Clinical and polysomnographic predictors of suboptimal auto-adjusting CPAP titration in adult OSA patients: a single-center study.

PURPOSE: To examine potential clinical, demographic, anthropometric, and polysomnographic predictors of successful auto-adjusting continuous positive airway pressure (CPAP) titration for treatment of obstructive sleep apnea (OSA). METHODS: This cross-sectional study was conducted in adults diagnosed with moderate-to-severe OSA (baseline apnea-hypopnea index [AHI] ≥ 15.0/h), who underwent auto-adjusting CPAP titration (S9 or S10 AutoSet ResMed®) in a sleep laboratory setting while wearing a nasal or pillow mask. Participants were then grouped into two groups: optimal CPAP titration (residual AHI < 5.0/h) or suboptimal CPAP titration (residual AHI ≥ 5.0/h). Multivariate logistic regression analysis was used to assess possible independent predictive factors for suboptimal CPAP titration. RESULTS: A total of 1222 adults consisting of 874 subjects with optimal CPAP titration (71.5%) and 348 subjects with suboptimal CPAP titration (28.5%) were evaluated. Multivariate analysis resulted in a model with an adequate calibration (Hosmer-Lemeshow chi-square-test: 7.088; p = 0.527), with male sex, higher values of baseline AHI, therapeutic pressure (95th percentile), and mask leak (95th percentile) emerging as significant and independent predictors for suboptimal CPAP titration: adjusted odds ratio (OR): 1.456 (95% confidence interval [CI] 1.076-1.971; p = 0.015), OR: 1.009 (95% CI 1.002-1.016; p = 0.013), OR: 1.281 (95% CI 1.206-1.361; p < 0.001), and 1.035 (1.026-1.043; p < 0.001), respectively. CONCLUSIONS: In a large cohort of adults undergoing auto-adjusting CPAP titration due to moderate-to-severe OSA, male sex, increased values of baseline AHI, pressure requirements, and mask leak were significant predictors for less than optimal CPAP titration.

Sleep-Disordered Breathing in Adults with Precapillary Pulmonary Hypertension: Prevalence and Predictors of Nocturnal Hypoxemia.

PURPOSE: To evaluate the frequency of sleep-disordered breathing (SDB) and predictors of the presence of nocturnal desaturation in adults with pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension. METHODS: Outpatients with a hemodynamic diagnosis of precapillary pulmonary hypertension who underwent portable polysomnography were evaluated. Diagnosis and severity of SDB were assessed using three well-established respiratory disturbance index (RDI) thresholds: 5.0/h, 15.0/h, and 30.0/h, while nocturnal hypoxemia was defined by the average oxygen saturation (SpO2) < 90%. Multiple linear regression analysis evaluated the potential relationships among explanatory variables with the dependent variable (average SpO2 values), with comparisons based on the standardized regression coefficient (ß). The R-squared (R2; coefficient of determination) was used to evaluate the goodness-of-fit measure for the linear regression model. RESULTS: Thirty-six adults were evaluated (69.4% females). The majority of the participants (75.0%) had SDB (26 with obstructive sleep apnea [OSA] and one with central sleep apnea [CSA]); while 50% of them had nocturnal hypoxemia. In the linear regression model (R2 = 0.391), the mean pulmonary artery pressure [mPAP] (ß - 0.668; p = 0.030) emerged as the only independent parameter of the average SpO2. CONCLUSION: Our study found that the majority of the participants had some type of SDB with a marked predominance of OSA over CSA, while half of them had nocturnal desaturation. Neither clinical and hemodynamic parameters nor the RDI was a predictor of nocturnal desaturation, except for mPAP measured during a right heart catheterization, which emerged as the only independent and significant predictor of average SpO2.

Predictive Factors for Obstructive Sleep Apnea Diagnosis in Bariatric Surgery Candidates with or Without Chronic Insomnia Complaints.

OBJECTIVE: This study aims to evaluate the frequency of insomnia complaints in bariatric patients and to assess obstructive sleep apnea (OSA) predictors according to the presence or absence of chronic insomnia. METHODS: Insomnia was defined as the presence of at least one specific symptom: difficulty falling asleep, difficulty maintaining sleep, and/or waking up earlier than expected. Diagnosis of OSA was objectively obtained from in-laboratory polysomnography. Multivariate logistic regression analysis was used to assess OSA predictors. RESULTS: This cross-sectional study contains 1,737 bariatric surgery candidates: 59.6% without insomnia and 40.4% with insomnia. OSA prevalence was similar among participants with or without insomnia either for any OSA (p = 0.168) or for moderate-to-severe OSA (p = 0.185). Patients without insomnia showed a higher prevalence of severe OSA than those with insomnia (p = 0.005). In both cohorts, five parameters were independent OSA predictors: sex, age, body mass index (BMI), neck circumference (NC), and excessive daytime sleepiness (EDS). Male sex was the most important predictor, whether in individuals without insomnia (adjusted odds ratio [OR] ranging from 4.874 to 8.369) or in those with insomnia (adjusted OR ranging from 5.672 to 12.441). CONCLUSIONS: A considerable proportion of bariatric patients report insomnia complaints. The probability of suffering from OSA was similar among bariatric candidates with or without insomnia, except for severe OSA diagnosis. Sex, age, BMI, NC, and EDS were independent predictors for OSA diagnosis irrespective of insomnia symptoms, and male sex was the main predictor for OSA in bariatric individuals with or without insomnia.

Gender-related sleep duration perception in a Brazilian sleep clinic cohort.

PURPOSE: This study aims to evaluate if gender influences the sleep duration perception in adults referred for polysomnography (PSG). METHODS: A cross-sectional study was undertaken from December 2019 to January 2021. Total sleep time was objectively assessed from the overnight PSG and subjectively estimated. The sleep perception index (SPI) was defined by the ratio of subjective and objective values. Diagnosis of obstructive sleep apnea (OSA) was based on an apnea-hypopnea index ≥ 5.0/h. Insomnia was defined by the presence of one or more specific complaints: difficulty falling asleep, difficulty maintaining sleep, and/or waking up earlier than desired. The association between continuous variables and SPI was assessed by linear regression analysis. RESULTS: This study enrolled 2,004 outpatients (56% men) who were grouped into four subsamples: controls (n = 139), insomnia (n = 154), OSA (n = 912), and insomnia comorbid with OSA [COMISA] (n = 799). In women, the median SPI differed among groups and ranged from 89 to 102% (p = 0.001); while in men, it ranged from 90% to 99% (p = 0.007). However, no gender-related SPI value differences emerged within each of the subgroups: controls (p = 0.907), insomnia (p = 0.830), OSA (p = 0.070), and COMISA (p = 0.547). The presence of insomnia (ß, - 0.101, p < 0.001) or OSA (ß, - 0.082, p = 0.001), but not gender (ß, - 0.017, p = 0.612), were independent predictors of the SPI. CONCLUSION: In a clinical referral cohort, no evidence of sex dimorphism emerged for SPI irrespective of the underlying sleep diagnosis.

Influence of nocturnal insomnia symptoms on obstructive sleep apnea diagnosis in a clinical referral cohort.

STUDY OBJECTIVES: To assess whether nocturnal symptoms of insomnia influence the prevalence of obstructive sleep apnea (OSA) in a clinical referral cohort. METHODS: Insomnia was defined by the presence of 1 or more of the following complaints: difficulty initiating sleep, difficulty maintaining sleep, and/or early morning awakenings. OSA severity was based on an apnea-hypopnea index: ≥ 5.0 events/h (any OSA), ≥ 15.0 events/h (moderate/severe OSA), and ≥ 30 events/h (severe OSA). Multivariate logistic regression analysis was used to evaluate predictive factors for OSA diagnosis and severity. RESULTS: Overall, 12,021 outpatients referred for polysomnography were grouped into 2 cohorts: without insomnia (58.2%) and with insomnia (41.8%). Individuals without insomnia had a higher prevalence of OSA than those with insomnia (P < .001, for all OSA severity levels). The presence of insomnia was negatively associated with diagnosis of any OSA (adjusted odds ratio: 0.852; 95% confidence interval: 0.769-0.944), moderate/severe OSA (adjusted odds ratio: 0.819; 95% confidence interval: 0.751-0.892), and severe OSA (adjusted odds ratio: 0.816; 95% confidence interval: 0.746-0.892). Moreover, the number of nocturnal symptoms of insomnia was associated with a lower likelihood of OSA, even when adjusted for other confounders such as sex, age, body mass index, neck circumference, excessive daytime sleepiness, hypertension, and type 2 diabetes mellitus. CONCLUSIONS: In this present study that included a large sample of consecutive outpatients, there was an inverse relationship between the number of nocturnal symptoms of insomnia and OSA diagnosis. CITATION: Duarte RLM, Magalhães-da-Silveira FJ, Gozal D. Influence of nocturnal insomnia symptoms on obstructive sleep apnea diagnosis in a clinical referral cohort. J Clin Sleep Med. 2022;18(5):1271-1278.

Nocturnal oximetry in bariatric surgery patients referred to overnight in-lab polysomnography.

OBJECTIVE: This study aimed to evaluate nocturnal oximetry approaches in identifying obstructive sleep apnea (OSA) among bariatric surgical candidates. METHODS: This was a cross-sectional study involving adult bariatric patients who were undergoing in-lab polysomnography and who were previously screened with the GOAL questionnaire. OSA severity was established as any OSA, moderate/severe OSA, and severe OSA. Oximetry data were evaluated as oxygen saturation (average and nadir), oxygen desaturation index (ODI) at 3%, and proportion of time spent with oxygen saturation <90%. Associations between oximetry data and the apnea-hypopnea index (AHI) were assessed by Spearman correlation index (r), linear regression, logistic regression, and discrimination. RESULTS: All oximetry values were significantly correlated with the AHI among 1,178 individuals, with the ODI emerging as the better parameter (r = 0.911, p < 0.001). Using linear regression, the ODI was the only predictor of the AHI (ß = 0.952, p < 0.001). In the multivariate analysis, the ODI was the only independent parameter predicting OSA at all severity levels. In addition, the ODI exhibited excellent discrimination to predict OSA and displayed improved performance among individuals screened as being at high risk versus those at low risk with the GOAL instrument. CONCLUSIONS: The ODI emerges as a valid surrogate predictor of the AHI, particularly among those screened as being at high risk for OSA.

Are there sex-related differences in therapeutic CPAP levels in adults undergoing in-laboratory titration?

STUDY OBJECTIVES: The first-choice therapy for adults with moderate/severe obstructive sleep apnea is continuous positive airway pressure (CPAP). However, studies evaluating whether the therapeutic CPAP level obtained from a titration is affected by sex are surprisingly scarce. Our main objective was to verify if sex influenced the optimal CPAP measurement obtained during a titration. METHODS: This cross-sectional study was conducted in adults diagnosed with moderate/severe obstructive sleep apnea [baseline apnea-hypopnea index (AHI) ≥ 15.0 events/h] who underwent auto-adjusting CPAP titration (S9 or S10 AutoSet ResMed) in a sleep laboratory setting. All participants used a nasal mask during the titration. The optimal pressure, leak, and residual AHI values were registered. Multiple linear regression was used to evaluate if clinical and polysomnographic data influenced the therapeutic CPAP level setting (95th percentile pressure). RESULTS: A total of 1,006 adults were enrolled: 354 women and 652 men. There were no statistically significant sex-related differences in the CPAP requirements and leak values delineated during the titration; all P-values > .005. However, the median residual AHI was significantly higher in males vs females: 2.7 events/h vs 2.2 events/h (P = .008). Body mass index (ß: 0.292, P < .001), baseline AHI (ß: 0.167, P < .001), and age (ß: 0.065, P = .035) were independent predictors of the therapeutic CPAP level settings. CONCLUSIONS: Sex does not significantly influence the therapeutic CPAP settings. However, age, BMI, and baseline AHI emerge as independent predictors of the 95th percentile CPAP requirement during an auto-adjusting CPAP titration. CITATION: Duarte RLM, Magalhães-da-Silveira FJ, Gozal D. Are there sex-related differences in therapeutic CPAP levels in adults undergoing in-laboratory titration? J Clin Sleep Med. 2021;17(9):1815-1820.

Prediction of obstructive sleep apnea using GOAL questionnaire in adults with or without excessive daytime sleepiness: A cross-sectional study.

OBJECTIVE: Obstructive sleep apnea (OSA) is a prevalent disorder and excessive daytime sleepiness (EDS) is a frequently associated complaint. Our objectives were (1) to evaluate the predictive performance of the GOAL questionnaire in patients with or without EDS and (2) to compare its discrimination with that of 3 other validated instruments: STOP-Bang, No-Apnea, and NoSAS. METHODS: A cross-sectional study from July 2019 to March 2020 was designed with consecutive adults undergoing full polysomnography. Participants were grouped into 2 cohorts according to the Epworth Sleepiness Scale (ESS): without EDS (ESS <11) or with EDS (ESS ≥11). Discrimination was assessed by area under the curve, while predictive parameters were calculated using contingency tables. OSA severity was classified based on apnea/hypopnea index thresholds: ≥ 5.0/h (OSA≥5), ≥ 15.0/h (OSA≥15), and ≥ 30.0/h (OSA≥30). RESULTS: Overall, 2627 patients were enrolled. In 1477 individuals without EDS, for the screening of OSA≥5, OSA≥15, and OSA≥30, GOAL showed sensitivities ranging from 79.3% to 91.5% and specificities ranging from 60.6% to 40.2%. In 1150 individuals with EDS, for the screening of OSA≥5, OSA≥15, and OSA≥30, GOAL reported sensitivities ranging from 86.2% to 94.5% and specificities ranging from 63.9% to 36.0%. In both cohorts, GOAL showed similar discrimination to STOP-Bang, No-Apnea, and NoSAS for predicting OSA≥5, OSA≥15, and OSA≥30 (all P values >.05). CONCLUSIONS: The GOAL questionnaire, a practical 4-item instrument, showed adequate predictive performance for the prediction of OSA. Moreover, its discrimination was satisfactory and non-inferior to that of STOP-Bang, No-Apnea, and NoSAS.

Perception of sleep duration in adult patients with suspected obstructive sleep apnea.

PURPOSE: Discrepancies between subjective and objective measures of total sleep time (TST) are frequent among insomnia patients, but this issue remains scarcely investigated in obstructive sleep apnea (OSA). We aimed to evaluate if sleep perception is affected by the severity of OSA. METHODS: We performed a 3-month cross-sectional study of Brazilian adults undergoing overnight polysomnography (PSG). TST was objectively assessed from PSG and by a self-reported questionnaire (subjective measurement). Sleep perception index (SPI) was defined by the ratio of subjective and objective values. Diagnosis of OSA was based on an apnea/hypopnea index (AHI) ≥ 5.0/h, being its severity classified according to AHI thresholds: 5.0-14.9/h (mild OSA), 15.0-29.9/h (moderate OSA), and ≥ 30.0/h (severe OSA). RESULTS: Overall, 727 patients were included (58.0% males). A significant difference was found in SPI between non-OSA and OSA groups (p = 0.014). Mean SPI values significantly decreased as the OSA severity increased: without OSA (100.1 ± 40.9%), mild OSA (95.1 ± 24.6%), moderate OSA (93.5 ± 25.2%), and severe OSA (90.6 ± 28.2%), p = 0.036. Using logistic regression, increasing SPI was associated with a reduction in the likelihood of presenting any OSA (p = 0.018), moderate/severe OSA (p = 0.019), and severe OSA (p = 0.028). However, insomnia was not considered as an independent variable for the presence of any OSA, moderate/severe OSA, and severe OSA (all p-values > 0.05). CONCLUSION: In a clinical referral cohort, SPI significantly decreases with increasing OSA severity, but is not modified by the presence of insomnia symptoms.

Validation of the GOAL Questionnaire as an Obstructive Sleep Apnea Screening Instrument in Bariatric Surgery Candidates: a Brazilian Single-Center Study.

OBJECTIVE: To validate the GOAL questionnaire as obstructive sleep apnea (OSA) screening tool in bariatric surgery (BS) patients and compare it with other existing instruments. METHODS: Before performing full polysomnography (PSG), all participants were screened for OSA with the following instruments: GOAL, STOP, STOP-Bang, No-Apnea, NoSAS, and Epworth Sleepiness Scale (ESS). Discrimination was assessed by area under the curve (AUC), while predictive parameters were calculated by contingency tables. Correlation was evaluated by the Spearman correlation coefficient (r). OSA severity was classified based on the apnea/hypopnea index (AHI): ≥ 5.0/h (OSA≥ 5), ≥ 15.0/h (OSA≥ 15), and ≥ 30.0/h (OSA≥ 30). RESULTS: Overall, 814 BS individuals (70.8% of females) were enrolled. We found a high prevalence of OSA≥ 5 (82.6%), OSA≥ 15 (60.0%), and OSA≥ 30 (38.8%). GOAL questionnaire was positively correlated with the AHI (r = 0.570, p < 0.001). Using a score ≥ 2 to classify patients at high risk of OSA, GOAL questionnaire had sensitivities ranging from 73.7 to 89.2% and specificities ranging from 78.2 to 51.0% for predicting OSA≥ 5, OSA≥ 15, and OSA≥ 30. At all OSA severity levels, GOAL exhibited similar and non-inferior discrimination when compared with STOP-Bang, No-Apnea, and NoSAS (all p values > 0.05), and performed significantly better than STOP and ESS (all p values < 0.001). CONCLUSIONS: In a cohort of BS patients, GOAL, No-Apnea, STOP-Bang, and NoSAS, but not ESS and STOP, enable satisfactory discrimination as OSA screening instruments at all disease severity levels.

Nasal versus oronasal mask in patients under auto-adjusting continuous positive airway pressure titration: a real-life study.

PURPOSE: Mask type (nasal versus oronasal) can affect the optimal pressure required to correct the apnea/hypopnea index (AHI) in obstructive sleep apnea (OSA) subjects treated with CPAP. Our objective was to evaluate if mask type influenced CPAP titration outcomes in OSA patients. METHODS: A retrospective study of individuals with a baseline AHI ≥ 15.0/h, who received an auto-adjusting CPAP titrating device (S9 AutoSet ResMed®) in a sleep-lab setting. The mask type oronasal (OM) or nasal (NM) was always selected by the patients. Optimal pressure requirements, leak, and residual AHI were compared based on mask type. RESULTS: Overall, 436 patients were included: 283 with NM (64.9%) and 153 with OM (35.1%). At baseline, NM and OM cohorts had similar AHI (p = 0.160). Patients allocated to the OM cohort had a higher 95th percentile pressure, a higher 95th percentile leak, and a higher residual AHI than those with a NM: pressure requirement: 12.9 cm H2O (IQR: 10.6-15.0) versus 10.7 cm H2O (IQR: 9.2-12.3); leak: 21.6 L/min (IQR: 9.6-37.2) versus 9.6 L/min (IQR: 3.6-19.2); and residual AHI: 4.9/h (IQR: 2.4-10.2) versus 2.2/h (IQR: 1.0-4.4), respectively (p < 0.001 for all). CONCLUSIONS: CPAP mask type based on individual preferences exerts profound effects on optimal CPAP pressures and efficacy. Patients titrated with OM showed higher pressure requirements, had higher a leak, and higher residual AHI when compared to NM, which may adversely impact treatment adherence and other health outcomes.

Predicting Obstructive Sleep Apnea in Patients with Insomnia: A Comparative Study with Four Screening Instruments.

PURPOSE: Obstructive sleep apnea (OSA) and insomnia are very prevalent disorders, especially in sleep-lab setting, and insomnia may be the presenting complaint of OSA. Here, we aimed to validate No-Apnea as screening tool for OSA in patients with self-reported insomnia complaints and to compare its performance with other models. METHODS: This cross-sectional study involved evaluation of No-Apnea as well as STOP-Bang, NoSAS and Epworth Sleepiness Scale (ESS) in subjects with insomnia being evaluated with full in-lab polysomnography. Discrimination was assessed by area under the curve (AUC), while predictive parameters were calculated by contingency tables. OSA severity was classified based on the apnea/hypopnea index: ≥ 5.0/h as any OSA (OSA≥5), ≥ 15.0/h as moderate/severe OSA (OSA≥15), and ≥ 30.0/h as severe OSA (OSA≥30). RESULTS: Overall, 2591 patients with a clinical diagnosis of insomnia were included. Diagnosis of OSA≥5, OSA≥15, and OSA≥30 was of 76.3%, 53.1%, and 32.6%, respectively. At all levels of OSA severity, No-Apnea had sensitivity ranging from 84.5 to 94.1% and specificity ranging from 58.2 to 35.1%. For screening of OSA≥5, OSA≥15, and OSA≥30, discriminatory ability (AUC) of No-Apnea was: 0.790 [95% confidence interval (CI) 0.770-0.810], 0.758 (95% CI 0.740-0.777), and 0.753 (95% CI 0.734-0.772), respectively. Based on AUCs, No-Apnea, STOP-Bang, and NoSAS performed similar at all levels of OSA severity. The ESS did not present satisfactory discrimination as OSA screening model. CONCLUSIONS: In a large sample of patients with insomnia, No-Apnea, STOP-Bang, and NoSAS, but not ESS, enable satisfactory and similar discrimination at all levels of OSA severity.

Comparative performance of screening instruments for obstructive sleep apnea in morbidly obese patients referred to a sleep laboratory: a prospective cross-sectional study.

PURPOSE: Obstructive sleep apnea (OSA) is very common occurrence among morbidly obese patients. Our main objectives were to validate the No-Apnea, a 2-item screening tool, in morbidly obese patients and compare its performance with three other instruments: STOP-Bang questionnaire, NoSAS score, and Epworth Sleepiness Scale (ESS). METHODS: A cross-sectional analysis of morbidly obese patients (body mass index [BMI] ≥ 35.0 kg/m2) grouped into two independent samples: bariatric surgery patients (BS) and non-bariatric surgery patients (NBS). All patients underwent overnight polysomnography. Discriminatory ability was assessed by area under the curve (AUC). OSA severity was defined by apnea/hypopnea index cut-off points: ≥ 5.0/h (OSA≥5), ≥ 15.0/h (OSA≥15), and ≥ 30.0/h (OSA≥30). RESULTS: A total of 1017 subjects (40.4% in BS cohort and 59.6% in NBS cohort) were evaluated. In the BS cohort, No-Apnea had similar discrimination to STOP-Bang and NoSAS for predicting OSA≥5 (p = 0.979 and p = 0.358, respectively), OSA≥15 (p = 0.158 and p = 0.399, respectively), and OSA≥30 (p = 0.388 and p = 0.903, respectively). In the NBS cohort, No-Apnea had similar discrimination to STOP-Bang and NoSAS for predicting OSA≥5 (p = 0.528 and p = 0.428, respectively), OSA≥15 (p = 0.825 and p = 0.108, respectively), and OSA≥30 (p = 0.458 and p = 0.186, respectively). Moreover, No-Apnea performed significantly better than ESS in both BS and NBS cohorts (p < 0.001). CONCLUSIONS: No-Apnea is a useful and practical tool for screening of OSA in morbidly obese patients, with non-inferior performance to STOP-Bang questionnaire and NoSAS score.

Fractional Exhaled Nitric Oxide Measurements and Screening of Obstructive Sleep Apnea in a Sleep-Laboratory Setting: A Cross-Sectional Study.

PURPOSE: Obstructive sleep apnea (OSA) is a common condition characterized by repetitive collapse of the upper airways and intermittent oxygen desaturation, which may lead to airway inflammation. Here, we explored whether fractional exhaled nitric oxide (FeNO) levels provide a non-invasive screening tool of OSA. METHODS: Over a 3-month period, FeNO levels were measured in consecutive non-smoking patients referred for a sleep laboratory. All patients underwent full polysomnography. OSA severity was classified based on the apnea/hypopnea index: ≥ 5.0/h as any OSA, ≥ 15.0/h as moderate/severe OSA, and ≥ 30.0/h as severe OSA. FeNO was measured by a portable device (NIOX-MINO®; Aerocrine AB, Solna, Sweden) and expressed as parts per billion (ppb). Discrimination by area under the curve (AUC) and binary logistic regression were performed. RESULTS: A total of 229 subjects were evaluated. Mean FeNO values were similar among subjects without OSA or with OSA: 16.9 ± 10.6 ppb versus 20.2 ± 14.5 ppb, p = 0.221; respectively. FeNO was not an inclusionary parameter to predict any OSA, moderate/severe OSA, and severe OSA: odds ratio (OR) 1.023 (95% confidence interval [CI]: 0.986-1.062); OR 1.012 (95% CI: 0.991-1.034); and OR 0.999 (95% CI: 0.980-1.018), respectively. The AUC values for FeNO in the diagnosis of any OSA, moderate/severe OSA, and severe OSA showed no discriminatory properties: AUC: 0.567 (95% CI: 0.464-0.670), AUC: 0.541 (95% CI: 0.465-0.618), and AUC: 0.535 (95% CI: 0.459-0.610); respectively. CONCLUSIONS: In a sleep-lab setting, our findings suggest that FeNO measurements are inconsequential in the screening of OSA in adults.

Simplifying the Screening of Obstructive Sleep Apnea With a 2-Item Model, No-Apnea: A Cross-Sectional Study.

STUDY OBJECTIVES: To develop and validate a practical model for obstructive sleep apnea (OSA) screening in adults based on objectively assessed criteria, and then compare it with two widely used tools, namely STOP-BANG and NoSAS. METHODS: This is a retrospective study of an existing database of consecutive outpatients who were referred for polysomnography for suspected sleep-disordered breathing by their primary care physicians. Area under the curve (AUC) and 2 × 2 contingency tables were employed to obtain the performance of the new instrument. RESULTS: A total of 4,072 subjects were randomly allocated into two independent cohorts: one for derivation (n = 2,037) and one for validation (n = 2,035). A mnemonic model, named No-Apnea, with two variables (neck circumference and age) was developed (total score: 0-9 points). We used the cutoff ≥ 3 to classify patients at high risk of having OSA. OSA severity was categorized by apnea-hypopnea index (AHI): any OSA (AHI 5 ≥ events/h; OSA-5), moderate/ severe OSA (AHI 15 ≥ events/h; OSA-15); and severe OSA (AHI 30 ≥ events/h; OSA-30). In the derivation cohort, the AUCs for screening of OSA-5, OSA-15, and OSA-30 were: 0.784, 0.758, and 0.754; respectively. The rate of subjects correctly screened was 78.1%, 68.8%, and 54.4%, respectively for OSA-5, OSA-15, and OSA-30. Subsequently, the model was validated confirming its reproducibility. In both cohorts, No-Apnea discrimination was similar to STOP-BANG or NoSAS. CONCLUSIONS: The No-Apnea, a 2-item model, appears to be a useful and practical tool for OSA screening, mainly when limited resources constrain referral evaluation. Despite its simplicity when compared to previously validated tools (STOP-BANG and NoSAS), the instrument exhibits similar performance characteristics.

The cigarette burden (measured by the number of pack-years smoked) negatively impacts the response rate to platinum-based chemotherapy in lung cancer patients.

PURPOSE: To evaluate the impact of the cigarette burden (CB) on the response rate to platinum-based chemotherapy (CT) in patients with lung cancer (LC). METHODS: Retrospective study of patients with LC treated by CT from 2000 to 2005, in a tertiary referral center in Brazil. The CB was measured by the number of pack-years smoked (PY). To evaluate the response (by RECIST), it was necessary to accomplish two cycles of CT. The relevant variables were studied by univariate and multivariate statistical techniques. RESULTS: Two hundred and eighty-five patients (203 men) were studied (mean age=60.6+/-10.1 years, mean PY=58.3+/-35.4). 62.8% were current smokers, 26.7% were former smokers, and 10.5% were non-smokers. 63.2% had non-small-cell lung cancer (NSCLC), and 36.8% had small-cell lung cancer (SCLC). The treatment intent was palliative in 63.9% and curative in 36.1%. All 285 patients received platinum-based CT (etoposide/cisplatin in 68.8% and etoposide/carboplatin in 31.2%). Of these, 155 patients (54.4%) received RT (median dose=50.0 Gy; range=45.0-80.0). The 94 patients (33.0%) who responded to treatment had a mean PY of 38.7+/-27.1, and the 191 patients (67.0%) who did not respond had a mean PY of 67.8+/-35.1, p<0.001. In the multivariate analysis, the main independent negative predictor was CB>or=40 PY (adjusted OR=10.42; 95% CI=5.13-21.28). The others independent negative predictors were: CT (no. of cycles=2-4) (adjusted OR=4.86; 95% CI=2.44-9.68), treatment regimen with CT alone (adjusted OR=3.38; 95% CI=1.67-6.84), and NSCLC histology (adjusted OR=2.75; 95% CI=1.12-6.76). CONCLUSION: Patients with CB>or=40 PY have a worse response to platinum-based CT compared to those who have a CB<40 PY.