Validity of the Berlin Questionnaire in identifying obstructive sleep apnea syndrome when administered to the informants of stroke patients

Wireless wearable sensors can facilitate rapid detection of sleep apnea in hospitalized stroke patients

STUDY OBJECTIVES

To evaluate wearable devices and machine learning for detecting sleep apnea in patients with stroke at an acute inpatient rehabilitation facility (IRF).

METHODS

A total of 76 individuals with stroke wore a standard home sleep apnea test (ApneaLink Air), a multimodal, wireless wearable sensor system (ANNE), and a research-grade actigraphy device (ActiWatch) for at least one night during their first week after IRF admission as part of a larger clinical trial. Logistic regression algorithms were trained to detect sleep apnea using biometric features obtained from the ANNE sensors and ground truth apnea rating from the ApneaLink Air. Multiple algorithms were evaluated using different sensor combinations and different apnea detection criteria based on the Apnea-Hypopnea Index (AHI≥5, AHI≥15).

RESULTS

Seventy-one (96%) participants wore the ANNE sensors for multiple nights. In contrast, only forty-eight participants (63%) could be successfully assessed for OSA by ApneaLink; 28 (37%) refused testing. The best-performing model utilized photoplethysmography (PPG) and finger temperature features to detect moderate-severe sleep apnea (AHI≥15), with 88% sensitivity and a positive likelihood ratio (LR+) of 44.00. This model was tested on additional nights of ANNE data achieving 71% sensitivity (10.14 LR+) when considering each night independently and 86% accuracy when averaging multi-night predictions.

CONCLUSIONS

This research demonstrates the feasibility of accurately detecting moderate-severe sleep apnea early in the stroke recovery process using wearable sensors and machine learning techniques. These findings can inform future efforts to improve early detection for post-stroke sleep disorders, thereby enhancing patient recovery and long-term outcomes.

Obstructive Sleep Apnea and Stroke: Determining the Mechanisms Behind their Association and Treatment Options

Sleep-disordered breathing (SDB) can be a sequela of stroke caused by vascular injury to vital respiratory centers, cerebral edema, and increased intracranial pressure of space-occupying lesions. Likewise, obstructive sleep apnea (OSA) contributes to increased stroke risk through local mechanisms such as impaired ischemic cerebrovascular response and systemic effects such as promoting atherosclerosis, hypercoagulability, cardiac arrhythmias, vascular-endothelial dysfunction, and metabolic syndrome. The impact of OSA on stroke outcomes has been established, yet it receives less attention in national guidelines on stroke management than hyperglycemia and blood pressure dysregulation. Furthermore, whether untreated OSA worsens stroke outcomes is not well-described in the literature. This scoping review provides an updated investigation of the correlation between OSA and stroke, including inter-relational pathophysiology. This review also highlights the importance of OSA treatment and its role in stroke outcomes. Knowledge of pathophysiology, the inter-relationship between these common disorders, and the impact of OSA therapy on outcomes affect the clinical management of patients with acute ischemic stroke. In addition, understanding the relationship between stroke outcomes and pre-existing OSA will allow clinicians to predict outcomes while treating acute stroke.

Sleep traits and associated factors among people living with HIV/AIDS in Iran: a two-step clustering analysis

Sleep plays an essential role in improving the quality of life of people living with HIV (PLWH); however, sleep traits in this population are not well studied. This study aims to evaluate the sleep traits and related associated factors among PLWH in Iran. A nationwide cross-sectional study was conducted with 1185 PLWH who attended Voluntary Counseling and Testing centers in 15 provinces in Iran between April 2021 and March 2022. The Berlin Obstructive Sleep Apnea questionnaire, Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale and Insomnia Severity Index were used. A two-step clustering method was employed to identify the number of sleep clusters in PLWH. Prevalence of poor sleep quality, sleepiness and insomnia were 49.6%, 21.15% and 42.7% respectively. Three sleep trait clusters were identified: I. minor sleep problems (45.6%); II. Snoring & sleep apnea (27.8%), and III. poor sleep quality and insomnia (26.7%). Age (Odds Ratio (OR) 1.033, 95% Confidence Interval (CI) 1.017-1.050), academic education (OR 0.542, 95% CI 0.294-0.998) and HIV duration were associated with being in Snoring & sleep apnea cluster, while age (OR = 1.027, 95% CI 1.009-1.040) was associated with being in Poor sleep quality and insomnia cluster. PLWH with depression had higher odds of being in Poor sleep quality and insomnia cluster, and those with anxiety had higher odds of being in Snoring & sleep apnea cluster and Poor sleep quality and insomnia cluster. A significant proportion of PLWH have poor sleep quality, sleepiness, and insomnia. The identification of three distinct sleep trait clusters underscores the need for increased attention and tailored interventions to address the specific sleep issues experienced by PLWH.

Heterogeneity of obstructive sleep apnea phenotypes after ischemic stroke: Outcome variation by cluster analysis

INTRODUCTION

Obstructive sleep apnea (OSA) is common but under-recognized after stroke. The aim of this study was to determine whether post-stroke phenotypic OSA subtypes are associated with stroke outcome in a population-based observational cohort.

METHODS

Ischemic stroke patients (n = 804) diagnosed with OSA (respiratory event index ≥10) soon after ischemic stroke were identified from the Brain Attack Surveillance in Corpus Christi (BASIC) project. Functional, cognitive, and quality of life outcomes were assessed at 90 days post-stroke and long-term stroke recurrence was ascertained. Latent profile analysis was performed based on demographic and clinical features, pre-stroke sleep characteristics, OSA severity, and vascular risk factors. Regression models were used to assess the association between phenotypic clusters and outcomes.

RESULTS

Four distinct phenotypic clusters provided the best fit. Cluster 1 was characterized by more severe stroke; cluster 2 by severe OSA and higher prevalence of medical comorbidities; cluster 3 by mild stroke and mild OSA; and cluster 4 by moderate OSA and mild stroke. Compared to cluster 3 and after adjustment for baseline stroke severity, cluster 1 and cluster 2 had worse 90-day functional outcome and cluster 1 also had worse quality of life. No difference in cognitive outcome or stroke recurrence rate was noted by cluster.

CONCLUSION

Post-stroke OSA is a heterogeneous disorder with different clinical phenotypes associated with stroke outcomes, including both daily function and quality of life. The unique presentations of OSA after stroke may have important implications for stroke prognosis and personalized treatment strategies.

Functional recovery after ischemic stroke: Impact of different sleep health parameters

Sleep disturbances after ischaemic stroke include alterations of sleep architecture, obstructive sleep apnea, restless legs syndrome, daytime sleepiness and insomnia. Our aim was to explore their impacts on functional outcomes at month 3 after stroke, and to assess the benefit of continuous positive airway pressure in patients with severe obstructive sleep apnea. Ninety patients with supra-tentorial ischaemic stroke underwent clinical screening for sleep disorders and polysomnography at day 15 ± 4 after stroke in a multisite study. Patients with severe obstructive apnea (apnea-hypopnea index ≥ 30 per hr) were randomized into two groups: continuous positive airway pressure-treated and sham (1:1 ratio). Functional independence was assessed with the Barthel Index at month 3 after stroke in function of apnea-hypopnea index severity and treatment group. Secondary objectives were disability (modified Rankin score) and National Institute of Health Stroke Scale according to apnea-hypopnea index. Sixty-one patients (71.8 years, 42.6% men) completed the study: 51 (83.6%) had obstructive apnea (21.3% severe apnea), 10 (16.7%) daytime sleepiness, 13 (24.1%) insomnia, 3 (5.7%) depression, and 20 (34.5%) restless legs syndrome. Barthel Index, modified Rankin score and Stroke Scale were similar at baseline and 3 months post-stroke in the different obstructive sleep apnea groups. Changes at 3 months in those three scores were similar in continuous positive airway pressure versus sham-continuous positive airway pressure patients. In patients with worse clinical outcomes at month 3, mean nocturnal oxygen saturation was lower whereas there was no association with apnea-hypopnea index. Poorer outcomes at 3 months were also associated with insomnia, restless legs syndrome, depressive symptoms, and decreased total sleep time and rapid eye movement sleep.

Clinical prediction models for the early diagnosis of obstructive sleep apnea in stroke patients: a systematic review

BACKGROUND

Obstructive sleep apnea (OSA) is a common sleep disorder characterized by repetitive cessation or reduction in airflow during sleep. Stroke patients have a higher risk of OSA, which can worsen their cognitive and functional disabilities, prolong their hospitalization, and increase their mortality rates.

METHODS

We conducted a comprehensive literature search in the databases of PubMed, CINAHL, Embase, PsycINFO, Cochrane Library, and CNKI, using a combination of keywords and MeSH words in both English and Chinese. Studies published up to March 1, 2022, which reported the development and/or validation of clinical prediction models for OSA diagnosis in stroke patients.

RESULTS

We identified 11 studies that met our inclusion criteria. Most of the studies used logistic regression models and machine learning approaches to predict the incidence of OSA in stroke patients. The most frequently selected predictors included body mass index, sex, neck circumference, snoring, and blood pressure. However, the predictive performance of these models ranged from poor to moderate, with the area under the receiver operating characteristic curve varying from 0.55 to 0.82. All the studies have a high overall risk of bias, mainly due to the small sample size and lack of external validation.

CONCLUSION

Although clinical prediction models have shown the potential for diagnosing OSA in stroke patients, their limited accuracy and high risk of bias restrict their implications. Future studies should focus on developing advanced algorithms that incorporate more predictors from larger and representative samples and externally validating their performance to enhance their clinical applicability and accuracy.

The mobile sleep medicine model in neurologic practice: Rationale and application

Background

Undiagnosed obstructive sleep apnea (OSA) is prevalent in neurological practice and significantly contributes to morbidity and mortality. OSA is prevalent in US adults and causes poor quality sleep and significant neurocognitive, cardiovascular, and cerebrovascular impairments. Timely treatment of OSA reduces cardio-cerebrovascular risks and improves quality of life. However, most of the US population has limited systematic access to sleep medicine care despite its clinical significance.

Focus

We discuss the importance of systematic screening, testing, and best-practice management of OSA and hypoventilation/hypoxemia syndromes (HHS) in patients with stroke, neurocognitive impairment, and neuromuscular conditions. This review aims to introduce and describe a novel integrated Mobile Sleep Medicine (iMSM) care model and provide the rationale for using an iMSM in general neurological practice to assist with systematic screening, testing and best-practice management of OSA, HHS, and potentially other sleep conditions.

Key points

The iMSM is an innovative, patient-centered, clinical outcome-based program that uses a Mobile Sleep Medicine Unit—a “sleep lab on wheels”—designed to improve access to OSA management and sleep care at all levels of health care system. The protocol for the iMSM care model includes three levels of operations to provide effective and efficient OSA screening, timely testing/treatment plans, and coordination of further sleep medicine care follow-up. The iMSM care model prioritizes effective, efficient, and patient-centered sleep medicine care; therefore, all parties and segments of care that receive and provide clinical sleep medicine services may benefit from adopting this innovative approach.

Relationship between sleep disorders and the prognosis of neurological function after stroke

OBJECTIVE

This study aims to investigate the effects of sleep disorders on the prognosis of neurological function after stroke and other factors affecting the prognosis after stroke.

METHOD

We designed a cohort study. A total of 1,542 patients with their first stroke were hospitalized in the department of neurology of Tianjin Huanhu Hospital from 2015.6.1 to 2016.12.31. We recorded the personal histories of patients. The MMSE (mini-mental state examination), MoCA (Montreal Cognitive Assessment), HAMD (Hamilton Depression Scale), National Institutes of Health Stroke Scale (NIHSS) score, mRS (Modified Rankin Scale), BI (Barthel Index), PSQI (Pittsburgh Sleep Quality Index), ESS (Epworth Sleepiness Scale), Berlin questionnaire, and nocturnal TST (Total sleep time) were assessed before discharge, 3 months, 6 months, and 4 years (2019-2020) after stroke.

RESULT

Low sleep quality (OR 2.019, 95%CI 1.199-3.398, p = 0.008), nocturnal TST (<7 h) (OR 4.060, 95%CI 1.494-11.034, p = 0.006), nocturnal TST (>8 h) (OR 5.928, 95% CI 2.134-16.464, p = 0.001) were risk factors for poor neurological function recovery at 3 months after stroke. Nocturnal TST (<7 h) (OR 13.042, 95%-CI 2.576-66.027, p = 0.002) and nocturnal TST (>8 h) (OR 11.559, 95%-CI 2.108-63.390, p = 0.005) were risk factors for poor neurological function at 6 months after stroke. Nocturnal TST (<7 h) (OR 2.668, 95% CI 1.250-5.698, p = 0.011) and nocturnal TST (>8 h) (OR 2.516, 95% CI 1.080-5.861, p = 0.033) were risk factors for poor neurological function at 4 years after stroke. High risk of OSA (HR 1.582, 95%CI 1.244-2.012, p < 0.001) was a risk factor for all-cause death in patients followed up for 4 years after stroke.

CONCLUSION

Low sleep quality is associated with short-term poor neurological function after stroke. Unusual nocturnal TST (long or short) is associated with short-term or long-term poor neurological function after stroke. A high risk of OSA is associated with a higher risk of all-cause death after stroke.

An Update on Obstructive Sleep Apnea for Atherosclerosis: Mechanism, Diagnosis, and Treatment

The occurrence and development of atherosclerosis could be influenced by intermittent hypoxia. Obstructive sleep apnea (OSA), characterized by intermittent hypoxia, is world-wide prevalence with increasing morbidity and mortality rates. Researches remain focused on the study of its mechanism and improvement of diagnosis and treatment. However, the underlying mechanism is complex, and the best practice for OSA diagnosis and treatment considering atherosclerosis and related cardiovascular diseases is still debatable. In this review, we provided an update on research in OSA in the last 5 years with regard to atherosclerosis. The processes of inflammation, oxidative stress, autonomic nervous system activation, vascular dysfunction, platelet activation, metabolite dysfunction, small molecule RNA regulation, and the cardioprotective occurrence was discussed. Additionally, improved diagnosis such as, the utilized of portable device, and treatment especially with inconsistent results in continuous positive airway pressure and mandibular advancement devices were illustrated in detail. Therefore, further fundamental and clinical research should be carried out for a better understanding the deep interaction between OSA and atherosclerosis, as well as the suggestion of newer diagnostic and treatment options.

Sleep apnea and stroke

PURPOSE OF REVIEW

Stroke and sleep apnea are highly prevalent conditions with a physiologically plausible bidirectional relationship. This review addresses prestroke sleep apnea, wake-up stroke and sleep apnea, and poststroke sleep apnea, with an attempt to highlight research published in the last 18 months.

RECENT FINDINGS

Sleep apnea is highly prevalent poststroke. Poststroke sleep apnea is associated with worse poststroke functional and cognitive outcomes and a higher risk of recurrent stroke. Physiologic tests are needed to diagnose sleep apnea in poststroke patients as sleep apnea questionnaires do not perform well in this population. The role of CPAP in poststroke management is not yet well established.

SUMMARY

Sleep apnea is a well established independent risk factor for stroke that confers an approximately two-fold increased risk of incident stroke. Sleep apnea is highly prevalent poststroke and is associated with worse outcomes after stroke. Sleep apnea is an attractive target for research addressing secondary stroke prevention and recovery.

Dynamic Prevalence of Sleep Disorders Following Stroke or Transient Ischemic Attack: Systematic Review and Meta-Analysis

BACKGROUND AND PURPOSE

The exact prevalence of sleep disorders following stroke or transient ischemic attack (TIA) remains unclear. We aimed to determine the prevalence of sleep-disordered breathing, insomnia, periodic leg movement during sleep, and restless leg syndrome following stroke or TIA in acute, subacute, and chronic phases and examine the moderating effects of patient characteristics (eg, age) and methodological features (eg, study quality) on the prevalence.

METHODS

We performed a systematic review and meta-analysis. Embase and PubMed were searched from inception to December 18, 2019. We included 64 047 adults in 169 studies (prospective, retrospective, case-control, and cross-sectional study designs) reporting the prevalence of sleep disorders following stroke or TIA.

RESULTS

In the acute phase, the overall prevalence of mild, moderate, and severe sleep-disordered breathing was 66.8%, 50.3%, and 31.6% (95% CIs, 63.8-69.7, 41.9-58.7, and 24.9-39.1). In the subacute phase, the prevalence of mild, moderate, and severe sleep-disordered breathing was 65.5%, 44.3%, and 36.1% (95% CIs, 58.9-71.5, 36.1-52.8, and 22.2-52.8). In the chronic phase, the summary prevalence of mild, moderate, and severe sleep-disordered breathing was 66.2%, 33.1%, and 25.1% (95% CIs, 58.6-73.1, 24.8-42.6, and 10.9-47.6). The prevalence rates of insomnia in the acute, subacute, and chronic phases were 40.7%, 42.6%, and 35.9% (95% CIs, 31.8-50.3, 31.7-54.1, and 28.6-44.0). The pooled prevalence of periodic leg movement during sleep in the acute, subacute, and chronic phases was 32.0%, 27.3%, and 48.2% (95% CIs, 7.4-73.5, 11.6-51.7, and 33.1-63.5). The summary prevalence of restless leg syndrome in the acute and chronic phases was 10.4% and 13.7% (95 CIs, 6.4-16.4 and 2.3-51.8). Age, sex, comorbidities, smoking history, and study region had significant moderating effects on the prevalence of sleep disorders.

CONCLUSIONS

Sleep disorders following stroke or TIA are highly prevalent over time. Our findings indicate the importance of early screening and treating sleep disorders following stroke or TIA.

The STOP-Bang and Berlin questionnaires to identify obstructive sleep apnoea in Alzheimer's disease patients

BACKGROUND

A close relationship between obstructive sleep apnoea (OSA) and Alzheimer's disease (AD) has been described in recent years. OSA is a risk factor for AD, but the diagnosis and clinical characteristics of OSA in patients with AD is not well understood. This study evaluated the clinical utility of two screening questionnaires, the STOP-Bang questionnaire (SBQ) and the Berlin questionnaire (BQ), to identify which patients with mild AD are at higher risk of having OSA and to determine the clinical predictors of OSA in this population.

METHODS

In this study, 91 consecutive outpatients with mild AD were prospectively evaluated with the SBQ and the BQ. All patients underwent level 1 in-laboratory polysomnography. The predictive performance of the questionnaires were calculated for different apnoea-hypopnoea index (AHI) cut-offs.

RESULTS

The median age of the patients was 76.0 (73.0; 80.0) years, and 58 (63.7%) were female. Of those, 81 patients (89.02%) were found to have OSA defined by an AHI > 5 events/h. Comparing the predictive performances of the SBQ and the BQ, the SBQ was found to have a higher diagnostic sensitivity (85% vs 4%), a lower specificity (35% vs. 96%), a higher positive predictive value (PPV) (44% vs 33%) and negative predictive value (NPV) (80% vs 65%) for detecting severe OSA at an AHI cut-off of 30 events/h. None of the items alone in the two questionnaires predicted the risk of OSA. A modified version of the SBQ, with new cut-off points for several variables according to the characteristics of AD patients, showed a slightly greater AUC than the standard SBQ (AUC 0.61 vs 0.72).

CONCLUSION

There is a high prevalence of OSA among patients with mild AD. The SBQ and the BQ are not good screening tools for detecting OSA in patients with AD. A modified version of SBQ could increase the detection of these patients.

Oximetry as an Accurate Tool for Identifying Moderate to Severe Sleep Apnea in Patients With Acute Stroke

STUDY OBJECTIVES

Sleep-disordered breathing (SDB) is highly prevalent in patients with acute stroke. SDB is often underdiagnosed and associated with neurological deterioration and stroke recurrence. Polysomnography or home sleep apnea testing (HSAT) is typically used as the diagnostic modality; however, it may not be feasible to use regularly in patients with acute stroke. We investigated the predictive performance of pulse oximetry, a simpler alternative, to identify SDB.

METHODS

The records of 254 patients, who were admitted to Boston Medical Center for acute stroke and underwent HSAT, were retrospectively reviewed. Oxygen desaturation index (ODI) from pulse oximetry channel were compared to respiratory event index (REI) obtained from HSAT devices. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ODI were calculated, and different ODI cutoff values to predict SDB were proposed.

RESULTS

ODI had a strong correlation (r = .902) and agreement with REI. ODI was accurate in predicting SDB at different REI thresholds (REI ≥ 5, REI ≥ 15, and REI ≥ 30 events/h) with the area under the curve (AUC) of .965, .974, and .951, respectively. An ODI ≥ 5 events/h rules in the presence of SDB (specificity 91.7%, PPV 96.3%). An ODI ≥ 15 events/h rules in moderate to severe SDB (specificity 96.4%, PPV 95%) and an ODI < 5 events/h rules out moderate to severe SDB (sensitivity 100%, NPV 100%).

CONCLUSIONS

Nocturnal pulse oximetry has a high diagnostic accuracy in predicting moderate to severe SDB in patients with acute stroke. Oximetry can be a simple modality to rapidly recognize patients with more severe SDB and facilitate the referral to the confirmation sleep study.

Pre-screening of sleep-disordered breathing after stroke: A systematic review

OBJECTIVES

Sleep-Disordered Breathing (SDB) is frequent in stroke patients. Polysomnography (PSG) and cardiorespiratory polygraphy are used to confirm SDB, but the need for PSG exceeds the available resources for systematic testing. Therefore, a simple and robust pre-screening instrument is necessary to identify the patients with an urgent need for a targeted PSG. The aim of this systematic review was to identify and evaluate the available methods to pre-screen stroke patients possibly suffering from SDB.

MATERIALS AND METHODS

Eleven studies out of 3,561 studies met the inclusion criteria. The selected studies assessed the efficiency of seven instruments based on the data acquired clinically or by inquiries (Berlin Questionnaire, Epworth Sleepiness Scale, SOS, Modified Sleep Apnea Scale of the Sleep Disorders Questionnaire, STOP-BANG, Four-variable Screening Tool and Multivariate Apnea Index) and three physiological measures (capnography, nocturia, nocturnal oximetry). The instruments were used to predict SDB in patients after acute or subacute stroke. Either PSG or cardiorespiratory polygraphy was used as a standard to measure SDB.

RESULTS

No independent studies using the same questionnaires, methods or criteria were published reducing generalizability. Overall, the questionnaires were quite sensitive in finding SDB but not highly specific in identifying the non-affected. The physiological measures (capnography) indicated promising results in predicting SDB, but capnography is not an ideal pre-screening instrument as it requires a specialist to interpret the results.

CONCLUSIONS

The results of pre-screening of SDB in acute and subacute stroke patients are promising but inconsistent. The current pre-screening methods cannot readily be referred to clinicians in neurologic departments. Thus, it is necessary to conduct more research on developing novel pre-screening methods for detecting SDB after stroke.

Sleep-disordered breathing in patients with cardiovascular diseases cannot be detected by ESS, STOP-BANG, and Berlin questionnaires

Sleep-disordered breathing (SDB) is highly prevalent in patients with cardiovascular diseases (CVD) and associated with poor outcome. At least 50% of heart failure (HF) patients present with SDB, equally divided in obstructive sleep apnea (OSA) and central sleep apnea (CSA). CVD patients with SDB do not always present with typical SDB symptoms. Therefore, we asked whether established questionnaires allow for the reliable detection of SDB. In this prospective cohort study, 89 CVD patients (54 male, 59 ± 15 years, BMI 30 ± 6 kg/m²) in stable clinical state underwent an ambulatory polygraphy. SDB was defined as an apnea-hypopnea index (AHI) ≥ 15/h. We evaluated the Epworth Sleepiness Scale (ESS), STOP-BANG and Berlin questionnaires as well as anthropometric data and comorbidities regarding their ability to predict SDB. The ESS showed no correlation with SDB. The sensitivity of the Berlin Questionnaire to detect SDB was 73%, specificity was 42%. The STOP-BANG questionnaire showed a sensitivity of 97% while specificity was 13%. Coronary heart disease and/or history of myocardial infarction, hyperuricemia and age significantly contributed to a logistic regression model predicting presence of SDB. However, our regression model explains only 36% of the variance regarding the presence or absence of SDB. The approach to find variables, which would allow an early and reliable differentiation between patients with CVD and coexistence or absence of SDB, failed. Thus, as CVD patients show a high SDB prevalence and poor outcome, only a systematic screening based on measures of respiration-related parameters (i.e., respiratory flow, blood oxygen saturation, etc.) allows for a reliable SDB assessment.

Screening Questionnaires for Obstructive Sleep Apnea: An Updated Systematic Review

Obstructive sleep apnea (OSA) is the most common sleep-related breathing disorder and is associated with significant morbidity. We sought to present an updated systematic review of the literature on the accuracy of screening questionnaires for OSA against polysomnography (PSG) as the reference test. Using the main databases (including Medline, Cochrane Database of Systematic Reviews and Scopus) we used a combination of relevant keywords to filter studies published between January 2010 and April 2017. Population-based studies evaluating the accuracy of screening questionnaires for OSA against PSG were included in the review. Thirty-nine studies comprising 18 068 subjects were included. Four screening questionnaires for OSA had been validated in selected studies including the Berlin questionnaire (BQ), STOP-Bang Questionnaire (SBQ), STOP Questionnaire (SQ), and Epworth Sleepiness Scale (ESS). The sensitivity of SBQ in detecting mild (apnea-hypopnea index (AHI) ≥ 5 events/hour) and severe (AHI ≥ 30 events/hour) OSA was higher compared to other screening questionnaires (range from 81.08% to 97.55% and 69.2% to 98.7%, respectively). However, SQ had the highest sensitivity in predicting moderate OSA (AHI ≥ 15 events/hour; range = 41.3% to 100%). SQ and SBQ are reliable tools for screening OSA among sleep clinic patients. Although further validation studies on the screening abilities of these questionnaires on general populations are required.

Economic Assessment of 4 Approaches to the Diagnosis and Initial Treatment of Sleep Apnea

BACKGROUND

A dilemma faced by health-care administrators is that need greatly outstrips capacity for diagnosing and treating sleep apnea, with such decisions carrying significant economic consequences. Our objective was to develop an economic model to estimate the relative costs of 4 approaches for diagnosis and initial treatment of sleep apnea.

METHODS

The analysis consisted of developing a mathematical model depicting possible diagnostic and treatment approaches to the care of patients with sleep apnea; developing 4 clinical scenarios to describe distinct approaches to the management of sleep apnea patients (in-laboratory, unattended, direct-to-autotitrating PAP [auto-PAP], and mixed); and identifying costs associated with each scenario. We created a hypothetical cohort of 1,000 patients with 85% prevalence of sleep apnea to generate cost estimates.

RESULTS

The driver of per-patient costs was the total number of sleep studies, which varied widely across scenarios: from 425 for the direct-to-auto-PAP approach to 1,441 in the unattended approach. The scenarios also differed in per-patient costs: Per-patient costs excluding facility startup costs were $456 for direct-to-auto-PAP, $913 for in-laboratory, $991 for mixed, and $1,090 for unattended.

CONCLUSIONS

Approaches to diagnosing and treating sleep apnea that emphasized early application of auto-PAP had lower per-patient costs.

Diagnosing and managing sleep apnea in patients with chronic cerebrovascular disease: a randomized trial of a home-based strategy

BACKGROUND

Obstructive sleep apnea is common and associated with poor outcomes after stroke or transient ischemic attack (TIA). We sought to determine whether the intervention strategy improved sleep apnea detection, obstructive sleep apnea (OSA) treatment, and hypertension control among patients with chronic cerebrovascular disease and hypertension.

METHODS

In this randomized controlled strategy trial intervention, patients received unattended polysomnography at baseline, and patients with OSA (apnea-hypopnea index ≥5 events/h) received auto-titrating continuous positive airway pressure (CPAP) for up to 1 year. Control patients received usual care and unattended polysomnography at the end of the study, to identify undiagnosed OSA. Both groups received 24-h blood pressure assessments at baseline and end of the study. "Excellent" CPAP adherence was defined as cumulative use of ≥4 h/night for ≥70% of the nights.

RESULTS

Among 225 randomized patients (115 control; 110 intervention), 61.9% (120/194) had sleep apnea. The strategy successfully diagnosed sleep apnea with 97.1% (102/105) valid studies; 90.6% (48/53, 95% CI 82.7-98.4%) of sleep apnea was undiagnosed among control patients. The intervention improved long-term excellent CPAP use: 38.6% (22/57) intervention versus 0% (0/2) control (p < 0.0001). The intervention did not improve hypertension control in this population with well-controlled baseline blood pressure: intervention, 132.7 mmHg (±standard deviation, 14.1) versus control, 133.8 mmHg (±14.0) (adjusted difference, -1.1 mmHg, 95% CI (-4.2, 2.0)), p = 0.48).

CONCLUSIONS

Patients with cerebrovascular disease and hypertension have a high prevalence of OSA. The use of portable polysomnography, and auto-titrating CPAP in the patients' homes, improved both the diagnosis and the treatment for sleep apnea compared with usual care but did not lower blood pressure.

Development, Validation, and Assessment of an Ischemic Stroke or Transient Ischemic Attack-Specific Prediction Tool for Obstructive Sleep Apnea

BACKGROUND

Screening instruments for obstructive sleep apnea (OSA), as used routinely to guide clinicians regarding patient referral for polysomnography (PSG), rely heavily on symptomatology. We sought to develop and validate a cerebrovascular disease-specific OSA prediction model less reliant on symptomatology, and to compare its performance with commonly used screening instruments within a population with ischemic stroke or transient ischemic attack (TIA).

METHODS

Using data on demographic factors, anthropometric measurements, medical history, stroke severity, sleep questionnaires, and PSG from 2 independently derived, multisite, randomized trials that enrolled patients with stroke or TIA, we developed and validated a model to predict the presence of OSA (i.e., Apnea-Hypopnea Index ≥5 events per hour). Model performance was compared with that of the Berlin Questionnaire, Epworth Sleepiness Scale (ESS), the Snoring, Tiredness, Observed apnea, high blood Pressure, Body mass index, Age, Neck circumference, and Gender instrument, and the Sleep Apnea Clinical Score.

RESULTS

The new SLEEP Inventory (Sex, Left heart failure, ESS, Enlarged neck, weight [in Pounds], Insulin resistance/diabetes, and National Institutes of Health Stroke Scale) performed modestly better than other instruments in identifying patients with OSA, showing reasonable discrimination in the development (c-statistic .732) and validation (c-statistic .731) study populations, and having the highest negative predictive value of all in struments.

CONCLUSIONS

Clinicians should be aware of these limitations in OSA screening instruments when making decisions about referral for PSG. The high negative predictive value of the SLEEP INventory may be useful in determining and prioritizing patients with stroke or TIA least in need of overnight PSG.

A screening tool for obstructive sleep apnea in cerebrovascular patients

BACKGROUND

A majority of stroke patients suffer from obstructive sleep apnea (OSA), which can go unrecognized as the current OSA screens do not perform well in stroke patients. The objective of this study is to modify the existing OSA screening tools for use in stroke patients.

METHODS

The cohort study consisted of patients who completed the validated OSA STOP screen and underwent polysomnography within one year. Six prediction models were created and sensitivity and specificity of various cut points were calculated.

RESULTS

There were 208 patients with mean age of 55.4 years; 61.0% had sleep apnea. Models with the highest c-statistics included the STOP items plus BMI, age, and sex (STOP-BAG). Addition of neck circumference and other variables did not significantly improve the models. The STOP-BAG2 model, using continuous variables, had a greater sensitivity of 0.94 (95% CI 0.89-0.98) and specificity 0.60 (95% CI 0.49-0.71) compared to the STOP-BAG model, which used dichotomous variables, and had a sensitivity of 0.91 (95% CI 0.85-0.96) and specificity of 0.48 (95% CI 0.37-0.60).

CONCLUSIONS

The STOP-BAG screen can be used to identify cerebrovascular patients at an increased risk of OSA. The use of continuous variables (STOP-BAG2) is preferable if automated score calculation is available. It can improve the efficiency of evaluation for OSA and lead to improved outcomes of patients with cerebrovascular disease.

Chronic fatigue syndrome and sleep disorders: clinical associations and diagnostic difficulties

INTRODUCTION

Chronic fatigue syndrome (CFS) is characterised by the presence of intractable fatigue and non-restorative sleep, symptoms which are also very prevalent in multiple diseases and appear as side effects of different drugs. Numerous studies have shown a high prevalence of sleep disorders in patients with CFS. However, non-restorative sleep and fatigue are frequently symptoms of the sleep disorders themselves, so primary sleep disorders have to be ruled out in many cases of CFS.

DEVELOPMENT

This review was performed using a structured search of the MeSH terms ([Sleep]+[Chronic fatigue syndrome]) in the PubMed database.

CONCLUSION

Identifying primary sleep disorders in patients meeting diagnostic criteria for CFS will allow for a more comprehensive treatment approach involving new diagnostic and therapeutic strategies that may improve quality of life for these patients.

Identifying obstructive sleep apnea after stroke/TIA: evaluating four simple screening tools

OBJECTIVE

Despite its high prevalence and unfavorable clinical consequences, obstructive sleep apnea (OSA) often remains underappreciated after cerebrovascular events. The purpose of our study was to evaluate the clinical utility of four simple paper-based screening tools for excluding OSA after stroke or transient ischemic attack (TIA).

PATIENTS/METHODS

Sixty-nine inpatients and outpatients with stroke or TIA during the past 180 days completed the 4-Variable screening tool (4V), STOP-BAG questionnaire (ie, STOP-BANG questionnaire without the neck circumference measurement), Berlin questionnaire, and the Sleep Obstructive apnea score optimized for Stroke (SOS). They subsequently underwent objective testing using a portable sleep monitoring device. Cutoffs were selected to maximize sensitivity and exclude OSA (AHI ≥ 10) in ≥10% of the cohort.

RESULTS

The mean age was 68.3 ± 14.2 years and 47.8% were male. Thirty-two patients (46.4%) were found to have OSA. Male sex, body mass index (BMI), and atrial fibrillation were independent predictors of OSA. Among the screening tools, the 4V had the greatest area under the curve (AUC) of 0.688 (p = 0.007); the sensitivity was 96.9% for a cutoff of <6. The STOP-BAG also significantly detected OSA with an AUC of 0.677 (p = 0.012); the sensitivity was 93.8% for a cutoff of <2. Scores on the 4V and STOP-BAG were significantly correlated with the AHI.

CONCLUSIONS

The 4V and STOP-BAG questionnaire may aid clinicians with ruling out OSA within 180 days of stroke/TIA. Due to the atypical presentation of poststroke/TIA OSA, these tools are only moderately predictive; objective testing should still be used for OSA diagnosis in this population.

Obstructive sleep apnea and stroke: links to health disparities

Obstructive sleep apnea (OSA) is a novel cardiovascular and cerebrovascular risk factor that presents unique opportunities to understand and reduce seemingly intractable stroke disparity among non-Hispanic blacks and Hispanic/Latinos. Individuals from these 2 groups have up to a 2-fold risk of stroke and greater burden of OSA. Obstructive sleep apnea directly and indirectly increases risk of stroke through a variety of autonomic, chemical, and inflammatory mechanisms and vascular risk factors such as hypertension, obesity, and diabetes mellitus. Untreated OSA exacerbates poststroke prognosis, as it may also influence rehabilitation efforts and functional outcomes such as cognitive function after a stroke. Conversely, treatment of OSA may reduce the risk of stroke and may yield better poststroke prognosis. Unfortunately, in racial/ethnic minority groups, there are limited awareness, knowledge, and screening opportunities for OSA. Increasing awareness and improving screening strategies for OSA in minorities may alleviate stroke risk burden and improve stroke outcomes in these populations. This review article is intended to highlight the epidemiology, clinical characteristics, pathophysiology, diagnosis, and treatment of OSA in relation to stroke risk, with an emphasis on race-ethnic disparities.

Validity of the Pittsburgh Sleep Quality Index in Indian University Students

OBJECTIVES

Despite the demonstrated utility of the Pittsburgh Sleep Quality Index (PSQI) in various demographic groups, it has never been validated in a sample of Indian subjects. To extend and confirm the PSQI's applicability for South Asian subjects, this preliminary study aimed to assess its psychometric and diagnostic validity in a sample of university students.

METHODS

Forty-seven male students were recruited from Jamia Millia Islamia, a public central university in New Delhi, India. The mean age of the students was 23.4±3.9 years, and they had a mean body mass index (BMI) of 23.3±3.3kg/m(2). The PSQI was administered to all subjects and overnight polysomnographic testing was carried out as a concurrent validation measure.

RESULTS

Cronbach's alpha for the questionnaire was found to be 0.736. Internal homogeneity was high, with the majority of correlations between questionnaire component scores and the summed global score being significant (p<0.010). Criterion validity-correlations between the PSQI global score and polysomnography (PSG) measures were low. However, the questionnaire component scores and the related polysomnographic measures did show some significant relationships. The optimal cut-off scores for distinguishing students with/without sleep problems was >6 and was generated using receiver operating characteristic curve analysis. The area under the curve, sensitivity, specificity, positive and negative likelihood ratios at the cut-off score were 0.838 (p<0.0001), 75.0%, 88.9%, 6.75, and 0.280, respectively.

CONCLUSION

The study found evidence that the PSQI had internal consistency, internal homogeneity, and diagnostic characteristics that compared well with PSG among a sample of young adult male students in India. This supports the applicability and certain aspects of the validity of the PSQI in the population.

Using the Karolinska Sleep Questionnaire to identify obstructive sleep apnea syndrome in a sleep clinic population

INTRODUCTION

In Scandinavia, portable monitoring has virtually replaced standard polysomnography for diagnosis of obstructive sleep apnea syndrome (OSAS). Because waiting times for specialized OSAS care remain long, an accurate screening tool to exclude low-risk patients from diagnostic testing would be valuable.

OBJECTIVES

To examine the diagnostic accuracy of the Karolinska Sleep Questionnaire (KSQ) for OSAS.

METHODS

Consecutive patients, 30–66 years old, attending a large sleep clinic in Sweden for OSAS evaluation completed the KSQ and underwent in-home portable monitoring and medical history evaluation. OSAS was defined as apnea-hypopnea index ≥5 with symptoms of disease. We calculated sensitivity and specificity of apnea/snoring and sleepiness indices of the KSQ. Retrospectively, we combined six KSQ items (snoring, breathing cessations, disturbed sleep, etc.) and four clinical variables (age, sex, body mass index, smoking status) predictive of OSAS into a new instrument, which we also evaluated. Instrument score ranged between 0 and 21; a higher score indicated more severe symptoms.

RESULTS

Of 103 patients, 62 were diagnosed with OSAS. Sensitivity and specificity of the indices were 0.56 and 0.68 (apnea/snoring), and 0.37 and 0.71 (sleepiness). The new instrument performed optimally at a score of 9. Sensitivity was 0.76 (95% confidence interval 0.63–0.86) and specificity 0.88 (0.74–0.96). Between 19.4% and 50.5% of patients were unaware of having apnea/snoring symptoms.

CONCLUSIONS

Diagnostic accuracy of the apnea/snoring and sleepiness indices for OSAS was poor but could be improved by combining clinical and KSQ items. The usefulness of the apnea/snoring index and the combined instrument was questionable because of extensive symptom unawareness.

Sleep Apnea and Stroke

Stroke is the second leading cause of death worldwide and often has devastating consequences for affected individuals in terms of chronic disability. Traditional risk factors such as age, male sex, ethnicity, hypertension, and atrial fibrillation explain 60%-80% of the risk of stroke. Obstructive sleep apnea (OSA) is highly prevalent in individuals who have had a stroke and its emerging role as a potential modifiable risk factor for stroke has been recognized in the most recent American Heart Association stroke guidelines, which recommend consideration of screening for and treatment of OSA in this regard. In this article we provide an overview of the current evidence-based knowledge related to stroke and sleep apnea. The main focus of this article is key pathophysiological mechanisms by which OSA might increase the risk for stroke. The effect of OSA on stroke outcomes and the efficacy of treatment of OSA on these outcomes is also discussed.

Preliminary validity and reliability of a Thai Berlin questionnaire in stroke patients

BACKGROUND

Obstructive sleep apnea (OSA) is a major risk factor for stroke. The Berlin Questionnaire (BQ) has been shown to be a valid tool to screen for OSA. The literature has limited data on using the BQ in stroke patients; particularly in Thailand and other developing countries. Here, we aimed to develop a Thai-language Berlin Questionnaire (Thai BQ) and to preliminarily assess construct validity, test-retest reliability and the agreement of the Thai BQ with the Thai Epworth Sleepiness Scale (Thai ESS), another screening tool for OSA.

METHODS

A hospital-based cross-sectional study was performed from January to July, 2011. One hundred first-ever stroke patients, including acute and chronic cases, and their caregivers were enrolled. The Thai BQ was developed using the forward-backward translation method. Evaluation of construct validity was done by factor analysis. Internal consistency of the Thai BQ and the Thai ESS were evaluated using Cronbach's alpha coefficient. Test-retest reliability and the agreement of the Thai BQ and the Thai ESS were evaluated using Cohen's kappa coefficient.

RESULTS

Factor analysis identified 4 main factors: Factor 1-Snoring behaviour; Factor 2-Sleepiness during driving; Factor 3-Daytime fatigue; and Factor 4-Hypertension or obesity. Cronbach's alpha coefficient was 0.77 (95% confidence interval (CI) = 0.69-0.83) and Cohen's kappa coefficient was 0.86 (95% CI = 0.74-0.98) in the Thai BQ. Cronbach's alpha coefficient was 0.59 (95% CI = 0.45-0.70) and the Cohen's kappa coefficient was 0.81 (95% CI = 0.60-1.00) in the Thai ESS. The agreement between the Thai ESS and the Thai BQ was fair.

CONCLUSIONS

The Thai BQ is a valid and reliable tool to screen for OSA in stroke patients. As factor analysis revealed 4 factors in contrast to the 3 factors in the original BQ, further modification of the Thai BQ is required.

Guidelines for the prevention of stroke in patients with stroke and transient ischemic attack: a guideline for healthcare professionals from the American Heart Association/American Stroke Association

The aim of this updated guideline is to provide comprehensive and timely evidence-based recommendations on the prevention of future stroke among survivors of ischemic stroke or transient ischemic attack. The guideline is addressed to all clinicians who manage secondary prevention for these patients. Evidence-based recommendations are provided for control of risk factors, intervention for vascular obstruction, antithrombotic therapy for cardioembolism, and antiplatelet therapy for noncardioembolic stroke. Recommendations are also provided for the prevention of recurrent stroke in a variety of specific circumstances, including aortic arch atherosclerosis, arterial dissection, patent foramen ovale, hyperhomocysteinemia, hypercoagulable states, antiphospholipid antibody syndrome, sickle cell disease, cerebral venous sinus thrombosis, and pregnancy. Special sections address use of antithrombotic and anticoagulation therapy after an intracranial hemorrhage and implementation of guidelines.

Predictive value of Berlin Questionnaire and Epworth Sleepiness Scale for obstructive sleep apnea in a sleep clinic population

INTRODUCTION

The Berlin Questionnaire (BQ) and Epworth Sleepiness Scale (ESS) are two of the widely used screening instruments for subjects suffering from sleep disorders.

OBJECTIVES

To determine the predictive accuracy of the BQ and ESS in the subjects who were admitted to our sleep clinic, using overnight polysomnography as the 'gold standard'.

METHODS

The BQ and ESS were performed to 1450 subjects hospitalized in our sleep clinic for polysomnographic evaluation.

RESULTS

One thousand two hundred thirty of 1450 subjects (84.8%) had apnea-hypopnea index (AHI) ≥ 5, and 70.5% of them were classified as being at high risk of sleep apnea with BQ and 45.9% of them were classified as having excessive daytime sleepiness with ESS. Being in the high-risk group with the self-reported, BQ predicted an AHI ≥ 5 with a sensitivity of 0.73 and a specificity of 0.44, vs a sensitivity of 0.46 and a specificity of 0.60 with the self-reported ESS. Sensitivity of BQ (0.80) was highest when we selected the cut-off value of AHI as 30. When we evaluated the predictive accuracy of BQ and ESS together, specificity of both instruments as 0.72 at AHI cut-off value of 5 was found. AHIs were significantly correlated with the scores in each category and the total scores of BQ (P < 0.0001).

CONCLUSIONS

The BQ is a poor predictor of obstructive sleep apnea (OSA) in subjects admitted to our sleep clinic. BQ and ESS together may be used to detect patients with low risk for OSA.

Can a prediction model combining self-reported symptoms, sociodemographic and clinical features serve as a reliable first screening method for sleep apnea syndrome in patients with stroke?

OBJECTIVE

To determine whether a prediction model combining self-reported symptoms, sociodemographic and clinical parameters could serve as a reliable first screening method in a step-by-step diagnostic approach to sleep apnea syndrome (SAS) in stroke rehabilitation.

DESIGN

Retrospective study.

SETTING

Rehabilitation center.

PARTICIPANTS

Consecutive sample of patients with stroke (N=620) admitted between May 2007 and July 2012. Of these, 533 patients underwent SAS screening. In total, 438 patients met the inclusion and exclusion criteria.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

We administered an SAS questionnaire consisting of self-reported symptoms and sociodemographic and clinical parameters. We performed nocturnal oximetry to determine the oxygen desaturation index (ODI). We classified patients with an ODI ≥15 as having a high likelihood of SAS. We built a prediction model using backward multivariate logistic regression and evaluated diagnostic accuracy using receiver operating characteristic analysis. We calculated sensitivity, specificity, and predictive values for different probability cutoffs.

RESULTS

Thirty-one percent of patients had a high likelihood of SAS. The prediction model consisted of the following variables: sex, age, body mass index, and self-reported apneas and falling asleep during daytime. The diagnostic accuracy was .76. Using a low probability cutoff (0.1), the model was very sensitive (95%) but not specific (21%). At a high cutoff (0.6), the specificity increased to 97%, but the sensitivity dropped to 24%. A cutoff of 0.3 yielded almost equal sensitivity and specificity of 72% and 69%, respectively. Depending on the cutoff, positive predictive values ranged from 35% to 75%.

CONCLUSIONS

The prediction model shows acceptable diagnostic accuracy for a high likelihood of SAS. Therefore, we conclude that the prediction model can serve as a reasonable first screening method in a stepped diagnostic approach to SAS in stroke rehabilitation.

Association of sleep apnea with clinically silent microvascular brain tissue changes in acute cerebral ischemia

The aim of this study was to determine the importance of sleep apnea in relation to clinically silent microvascular brain tissue changes in patients with acute cerebral ischemia. Patients with acute cerebral ischemia prospectively underwent nocturnal respiratory polygraphy within 5 days from symptom-onset. Sleep apnea was defined as apnea-hypopnea-index (AHI) ≥5/h. Experienced readers blinded to clinical and sleep-related data reviewed brain computed tomography and magnetic resonance imaging scans for leukoaraiosis and chronic lacunar infarctions. Ischemic lesions were considered clinically silent when patients did not recall associated stroke-like symptoms. Functional outcome was assessed with modified Rankin Scale at discharge, 6 and 12 months. Fifty-one of 56 (91 %) patients had sleep apnea of any degree. Patients with moderate-to-severe leukoaraiosis (Wahlund score ≥5) were found to have higher mean AHI than those with none or mild leukoaraiosis (34.4 vs. 12.8/h, p < 0.001). Moderate-to-severe sleep apnea (AHI ≥15/h) was found to be an independent predictor of moderate-to-severe leukoaraiosis (adjusted OR 6.03, 95 % CI 1.76-20.6, p = 0.0042) and of moderate-to-severe leukoaraiosis associated with clinically silent chronic lacunar infarctions (adjusted OR 10.5, 95 % CI 2.19-50.6, p = 0.003). The higher the Wahlund score and the AHI, the more likely unfavorable functional outcome resulted over time (p = 0.0373). In acute cerebral ischemia, sleep apnea is associated with clinically silent microvascular brain tissue changes and may negatively influence functional outcome. Routine sleep apnea screening and further investigation of possible long-term effects of non-invasive ventilatory treatment of sleep apnea appear warranted in this at-risk population.

Agreement between stroke patients and family members for ascertaining pre-stroke risk for sleep apnea

BACKGROUND

Ascertaining self-reported information about the risk for pre-stroke obstructive sleep apnea (OSA) in the acute stroke period is challenging as many stroke patients have deficits that hinder communication. We examined agreement between stroke patients without communication limitations and family members (proxy) in the pre-stroke risk for OSA.

METHODS

Patient-proxy pairs (n=42) were interviewed independently as part of the Brain Attack Surveillance in Corpus Christi (BASIC) Project from May 2010 to April 2011. The Berlin questionnaire was used to measure a high risk for OSA defined as the presence of at least two of the following conditions: (1) snoring behaviors/witnessed apneas, (2) daytime sleepiness, and (3) hypertension or obesity. Patient-proxy agreement was assessed using a κ coefficient.

RESULTS

Forty-three percent of patients self-identified as being at high risk for sleep apnea, and 45% of proxies identified patients as high risk. Patient-proxy agreement for high risk for pre-stroke OSA was fair (κ=0.28) with better agreement for spouses and children proxies (κ=0.38) than for other family members. Agreement also was fair for most individual questions.

CONCLUSIONS

Spouse and child proxy use of the Berlin questionnaire may be an option to assess a patient's pre-stroke likelihood of sleep apnea. Whereas prospective studies of incident stroke in patients with and without objectively confirmed sleep apnea would require formidable resources, our results suggest that an alternative strategy may involve proxy use of the Berlin questionnaire in a retrospective study design.

Predictive factors of subjective sleep quality and insomnia complaint in patients with stroke: implications for clinical practice

The complaints regarding sleep problems have not been well identified after a stroke. The aim of this study was to investigate the predictive factors of sleep quality and insomnia complaints in patients with stroke. A total of 70 subjects, 40 patients (57 ± 7 years) and 30 healthy controls (52 ± 6 years) assessed by the Pittsburgh Sleep Quality Index (PSQI) and the Sleep Habits Questionnaire took part in the study. The data were analyzed using the chi-square test, the Student's t-test and logistic regression analysis. On average, the patients showed poor sleep quality (patients: 6.3 ± 3.5; controls: 3.9 ± 2.2; p= 0.002) and insomnia complaint was the most prevalent (patients: 37.5%; controls: 6.7%; p= 0.007). The absence of insomnia complaint (OR= 0.120; 95%CI= 0.017-0.873; p= 0.036) and the decreased latency of sleep (OR= 0.120; 95%CI= 0.017-0.873; p= 0.036) were the protective factors of sleep quality. Female sex (OR= 11.098; 95%CI= 1.167-105.559; p= 0.036) and fragmented sleep (OR= 32.040; 95%CI= 3.236-317.261; p= 0.003) were the risk factors for insomnia complaint. We suggest that complaints of poor sleep quality and insomnia should be given priority assessment during clinical diagnosis of sleep disorders in stroke.

Diagnostic value of screening instruments for identifying obstructive sleep apnea in kidney failure

BACKGROUND

Patients with chronic kidney disease (CKD) and end-stage renal disease (ESRD) have a high prevalence of obstructive sleep apnea (OSA) that can have significant clinical implications. An accurate clinical screening tool for OSA that identifies patients for further diagnostic testing would assist in the identification of this comorbidity. The Berlin Questionnaire (BQ), Adjusted Neck Circumference (ANC), and STOP-BANG questionnaire are 3 such instruments that have been validated in patients with normal kidney function.

OBJECTIVE

The objective of this study was to determine the validity of these screening instruments in patients with CKD and ESRD, using overnight cardiopulmonary monitoring to diagnose OSA.

METHODS

One hundred seventy-two patients were recruited from nephrology clinics and hemodialysis units (CKD: n = 109; ESRD: n = 63). All patients completed the BQ, ANC, STOP-BANG, and overnight cardiopulmonary monitoring to diagnose OSA (respiratory disturbance index [RDI] ≥ 15). Sensitivity, specificity, positive and negative predictive values, and accuracy were calculated for the BQ, ANC, and STOP-BANG.

RESULTS

Obstructive sleep apnea was present in 41 CKD patients (38%) and 32 ESRD patients (51%). All screening instruments had satisfactory sensitivity (56% to 94%) but poor specificity (29% to 77%) and low accuracy (51% to 69%) in both CKD and ESRD patients with RDI ≥ 15. Using an RDI ≥ 30 yielded similar results.

CONCLUSIONS

Current screening questionnaires do not accurately identify patients at high risk for OSA or rule out the presence of OSA in patients with CKD and ESRD. Consequently, objective monitoring during sleep is required to reliably identify sleep apnea in these patient populations.

Arterial hypertension and obstructive sleep apnoea syndrome: treatment resistance and the role of autonomic dysfunction

Aim. To study the role of obstructive sleep apnoea syndrome (OSAS) in the development of treatment resistance in patients with arterial hypertension (AH). To assess the effects of autonomic nervous system (ANS) dysfunction, as one of the potential pathophysiological mechanisms of inadequate blood pressure (BP) reduction in patients with AH and OSAS. Material and methods. The study included 365 ambulatory AH patients: 194 with OSAS and 161 with resistance to antihypertensive therapy after 6-15 months. The 24-hour BP monitoring (BPM) and 24-hour cardio-respiratory monitoring of electrocardiogram (ECG), with heart rate variability (HRV) analysis, were performed. Results. Among patients with AH and OSAS, most individuals had low antihypertensive therapy compliance. All parameters of 24-hour BPM in this group were lower than in OSAS-free hypertensives, and this difference was more pronounced in patients with lower treatment compliance, particularly for pulse BP and HR. HRV parameters correlated with apnoea-hypopnoea index (AHI) and BP levels during 24-hour BPM. However, in multivariate analyses, these correlations were observed only for HRV parameters and AHI. Conclusion. In AH patients, OSAS aggravates the clinical course of the disease. ANS dysfunction could be one of the mechanisms underlying the development of antihypertensive treatment resistance.

Sleepiness, fatigue, and risk of obstructive sleep apnea using the STOP-BANG questionnaire in multiple sclerosis: a pilot study

PURPOSE

This study aims: (1) to identify patients with multiple sclerosis (MS) who are at high risk for obstructive sleep apnea (OSA) by utilizing the STOP-BANG questionnaire and (2) to evaluate the relationship between OSA risk as determined by the STOP-BANG questionnaire and self-reported sleepiness and fatigue using the Epworth Sleepiness Scale (ESS) and the Fatigue Severity Scale (FSS), respectively.

METHODS

A total of 120 consecutive patients presenting to the UC Davis Neurology MS Clinic were invited to participate in an anonymous survey. The exclusion criteria were: age <18 years, indefinite MS diagnosis, or incomplete survey.

RESULTS

There were 103 subjects included in our study: 42% of subjects (n = 43) met the criteria for high-risk OSA, 69% of subjects (n = 71) screened high for fatigue (FSS ≥ 4), but only 24 subjects (23%) screened high for excessive daytime sleepiness (ESS > 10). In males, 44% of the variation in ESS scores and 63% in FSS scores were explained by the STOP-BANG components. However, only 17% of the variation in ESS scores and 15% of the variation in FSS scores was explained by the STOP-BANG components in females.

CONCLUSIONS

Over 40% of MS patients were identified as high risk for OSA based on the STOP-BANG questionnaire. The STOP-BANG questionnaire offers clinicians an efficient and objective tool for improving detection of OSA risk in MS patients.