Dataset Information

Validation of the NoSAS Score for the Screening of Sleep-Disordered Breathing in a Sleep Clinic.

ABSTRACT: Background:There is a growing number of patients with sleep-disordered breathing (SDB) referred to sleep clinics. Therefore, a simple but useful screening tool is urgent. The NoSAS score, containing only five items, has been developed and validated in population-based studies. Aim:To evaluate the performance of the NoSAS score for the screening of SDB patients from a sleep clinic in China, and to compare the predictive value of the NoSAS score with the STOP-Bang questionnaire. Methods:We enrolled consecutive patients from a sleep clinic who had undergone apnea-hypopnea index (AHI) testing by type III portable monitor device at the hospital and completed the STOP-Bang questionnaire. The NoSAS score was assessed by reviewing medical records. Sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) of both screening tools were calculated at different AHI cutoffs to compare the performance of SDB screening. Results:Of the 596 eligible patients (397 males and 199 female), 514 were diagnosed with SDB. When predicting overall (AHI???5), moderate-to-severe (AHI???15), and severe (AHI???30) SDB, the sensitivity and specificity of the NoSAS score were 71.2, 80.4, and 83.1% and 62.4, 49.3, and 40.7%, respectively. At all AHI cutoffs, the AUC ranged from 0.688 to 0.715 for the NoSAS score and from 0.663 to 0.693 for the STOP-Bang questionnaire. The NoSAS score had the largest AUC (0.715, 95% CI: 0.655-0.775) of diagnosing SDB at AHI cutoff of ?5 events/h. NoSAS performed better in discriminating moderate-to-severe SDB than STOP-Bang with a marginally significantly higher AUC (0.697 vs. 0.663, P=0.046). Conclusion:The NoSAS score had good performance on the discrimination of SDB patients in sleep clinic and can be utilized as an effective screening tool in clinical practice.

SUBMITTER: Rong Y

PROVIDER: S-EPMC6977329 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Validation of the NoSAS Score for the Screening of Sleep-Disordered Breathing in a Sleep Clinic.

Rong Yi Y Wang Shihan S Wang Hui H Wang Feng F Tang Jingjing J Kang Xiuhong X Li Guangxi G Liu Zhiguo Z

Canadian respiratory journal 20200108

<h4>Background</h4>There is a growing number of patients with sleep-disordered breathing (SDB) referred to sleep clinics. Therefore, a simple but useful screening tool is urgent. The NoSAS score, containing only five items, has been developed and validated in population-based studies.<h4>Aim</h4>To evaluate the performance of the NoSAS score for the screening of SDB patients from a sleep clinic in China, and to compare the predictive value of the NoSAS score with the STOP-Bang questionnaire.<h4> ...[more]

PMID: 31998424

Similar Datasets

Project description:IntroductionObstructive sleep apnea (OSA) may increase stroke risk; retinal arteriolar (central retinal arteriolar equivalent, CRAE) diameter narrowing and/or retinal venular (central retinal venule equivalent, CRVE) widening may predict stroke. We examined relationships between sleep disordered breathing (SDB) and CRAE and CRVE and in a diabetes-free sleep clinic cohort.MethodsPatients for SDB assessment were recruited (Main Group, n = 264, age: 58.5 ± 8.9 yrs [mean ± SD]; males: 141) for in-laboratory polysomnography (standard metrics, eg apnea hypopnea index, AHI) and retinal photographs (evening and morning). A more severe SDB sub-group (n = 85) entered a 12-month cardiovascular risk factor minimisation (hypertension/hypercholesterolemia control; RFM) and continuous positive airway pressure (CPAP) intervention (RFM/CPAP Sub-Group); successfully completed by n = 66 (AHI = 32.4 [22.1-45.3] events/hour, median[IQR]). Univariate (Spearman's correlation, t-test) and multiple linear regression models examined non-SDB and SDB associations with CRAE and CRVE measures.ResultsMain Group: Evening CRAE predictors were: systolic blood pressure (0.18μm decrease per mmHg, p = 0.001), age (2.47μm decrease per decade, p = 0.012), Caucasian ethnicity (4.45 μm versus non-Caucasian, p = 0.011), height (0.24 μm decrease per cm increase, p = 0.005) and smoking history (3.08 μm increase, p = 0.052). Evening CRVE predictors were: Caucasian ethnicity (11.52 μm decrease versus non-Caucasian, p>0.001), diastolic blood pressure (0.34 μm increase in CRVE per mmHg, p = 0.001), hypertension history (6.5 μm decrease, p = 0.005), and smoking history (4.6 μm increase, p = 0.034). No SDB metric (all p>0.08) predicted CRAE or CRVE measures. RFM/CPAP Sub-Group: A one-unit increase in ln(AHI+1) was associated with a 0.046μm increase in CRAE (n = 85; p = 0.029). Mean evening CRAE and CRVE values did not change across the intervention (n = 66), but evening CRVE decreased ~6.0 μm for individuals with AHI >30 events/hr.ConclusionNo major SDB associations with CRAE or CRVE were identified, although the RFM/CPAP intervention reduced evening CRVE for severe OSA patients. Implications for cerebro-vascular disease risk remain uncertain.Trial registrationThe protocol was registered with the Australian New Zealand Clinical Trials Registry (Trial Id: ACTRN12620000694910).

Project description:BackgroundSleep Disorder Breathing (SDB) in pregnant patients ranges from 3 to 27% and varies depending on gestational age and method used to diagnose. SDB increases the risk of advanced pregnancy complications such as gestational diabetes mellitus, pregnancy-induced hypertension, and preeclampsia. Screening and diagnosis of SDB during pregnancy remains a challenge, with existing screening tools underperforming during pregnancy. This study aimed to validate a previously developed model for predicting SDB during late pregnancy and compare the predictive value of bedpartner responses.MethodsNinety-six women in the third trimester of pregnancy underwent polysomnography and completed the Berlin Questionnaire (BQ), with 81 bedpartners completing the BQ about their pregnant partner. A subset of BQ items (snoring volume and tiredness upon awakening) along with BMI > 32 kg/m2 was utilised to calculate the Wilson Optimized Model (WOM), which demonstrated strong predictive properties in development.ResultsSDB (RDI/hr ≥ 5) was detected in 43.8% of women. BQ identified 72% of pregnant mothers as high risk for SDB (Sensitivity = 83%, Specificity = 37%), compared to 29% of mothers identified by the WOM (Sensitivity = 45%, Specificity = 83%). At RDI of ≥ 15, the WOM correctly classified more women according to SDB risk than the BQ (76.0% vs. 41.7% cases correct, X2(1) = 23.42, p < .001), with no difference at RDI ≥ 5. Bedpartners were more likely to report high risk for SDB on the WOM than pregnant women themselves (38.3% vs. 28.4%), however predictive ability was not improved by bedpartner input (RDI ≥ 5 bedpartner AUC = 0.69 v mother AUC = 0.73).ConclusionBQ largely overestimates the prevalence of SDB in pregnancy compared to the WOM which underestimates. Utilising bedpartner responses didn't improve screening for SDB in late pregnancy. More work is needed to develop a pregnancy-specific tool for quick and accurate screening for SDB.

Project description:Sleep disordered breathing (SDB) is highly prevalent, but frequently unrecognized among stroke patients. Polysomnography (PSG) is difficult to perform soon after a stroke. We evaluated the use of screening questionnaires and portable sleep testing (PST) for patients with acute stroke, subarachnoid hemorrhage, or transient ischemic attack to expedite SDB diagnosis and management. We performed a single-center retrospective analysis of a quality improvement study on SDB screening of consecutive daytime, weekday, adult admissions to a stroke unit. We excluded patients who were unable to communicate and lacked available family members. Patients were screened with the Epworth Sleepiness Scale, Berlin Questionnaire, and STOP-BANG Questionnaire and underwent overnight PST and/or outpatient PSG. The 4-item STOP Questionnaire was derived from STOP-BANG for a secondary analysis. We compared the sensitivity and specificity of the questionnaires for the diagnosis of at least mild SDB (apnea hypopnea index (AHI) ≥5) on PST and correlated AHI measurements between PST and PSG using the Spearman correlation. Out of sixty-eight patients included in the study, 54 (80%) were diagnosed with SDB. Only one (1.5%) had a previous SDB diagnosis. Thirty-three patients completed all questionnaires and a PST. The STOP-BANG questionnaire had the highest sensitivity for at least mild SDB (0.81, 95% CI (confidence interval): 0.65-0.92) but a low specificity (0.33, 95% CI 0.10, 0.65). The discrimination of all questionnaires was overall poor (C statistic range 0.502-0.640). There was a strong correlation (r = 0.71) between the AHI results estimated using PST and outpatient PSG among 28 patients. The 4-item STOP Questionnaire was the easiest to administer and had a comparable or better sensitivity than the other questionnaires. Inpatient PSTs were useful for screening in the acute setting to facilitate an early diagnosis of SDB and to establish further outpatient evaluations with sleep medicine.

Dataset Information

Validation of the NoSAS Score for the Screening of Sleep-Disordered Breathing in a Sleep Clinic.

Publications

Validation of the NoSAS Score for the Screening of Sleep-Disordered Breathing in a Sleep Clinic.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets