The estimation of excessive daytime sleepiness in post-stroke patients - a polysomnographic study

Presence of Self-Reported Sleep Alterations After Stroke and Their Relationship With Disability: A Longitudinal Study

BACKGROUND

Sleep disorders have a prevalence of 30% to 70% in post-stroke individuals. The presence of sleep disorders and poor sleep quality after stroke can affect important functions and lead to worse outcomes. However, most studies are restricted to the acute post-stroke stage only.

OBJECTIVE

To investigate the frequency of self-reported sleep alterations in a sample of chronic stroke individuals and to identify which self-reported sleep alterations were associated with disability.

METHODS

Prospective exploratory study. Self-reported sleep alterations were measured by the Pittsburgh Sleep Quality Index, Insomnia Severity Index, Epworth Sleepiness Scale, and STOP-Bang Questionnaire. The dependent variable was measured 3 years after the first contact by the Modified Rankin Scale (mRS). Step-wise multiple linear regression analysis was employed to identify which sleep alterations were associated with disability.

RESULTS

Sixty-five individuals with stroke participated. About 67.7% of participants had poor sleep quality, 52.4% reported insomnia symptoms, 33.9% reported excessive daytime sleepiness, and 80.0% were classified as intermediate or high risk for obstructive sleep apnea. Only risk for obstructive sleep apnea was significantly associated with disability and explained 5% of the variance in the mRS scores.

CONCLUSION

Self-reported sleep alterations had a considerable frequency in a sample of chronic stroke individuals. The risk of obstructive sleep apnea was associated with disability in the chronic stage of stroke. Sleep alterations must be considered and evaluated in the rehabilitation process even after a long period since the stroke onset.

Stroke: What's Sleep Got to Do With It?

SUMMARY

Ischemic strokes most often occur between 6 am and 12 am after awakening from sleep but up to 30% occur during sleep. Wake-up strokes (WUS) are new focal neurological deficit(s) persisting for ≥ 24 hours attributable to an ischemic event present on patient awakening. Obstructive sleep apnea (OSA) is a major risk factor for WUS because it compounds the instability of the morning environment and increases the likelihood of cardiovascular events, including hypertension, atrial fibrillation, right-to-left shunts, and stroke. Circadian-driven alterations in structural, homeostatic, and serological factors also predispose to WUS. Also, WUS patients are often not considered candidates for time-dependent intravenous thrombolysis therapy because of an uncertain onset time. However, using the tissue clock (positive diffusion weighted imaging-negative fluid-attenuated inversion recovery mismatch) dates the WUS as 3 to 4.5 hours old and permits consideration for intravenous thrombolysis and if needed mechanical thrombectomy. Given the high prevalence of moderate/severe OSA in stroke patients and its impact on stroke outcomes, screening with overnight pulse oximetry and home sleep apnea test is needed. Treating OSA poststroke remains challenging. Polysomnographic changes in sleep architecture following acute/subacute stroke may also impact upon stroke outcome.

Independent Association Between Oxygen Desaturation Index and Cardiovascular Disease in Non-Sleepy Sleep-Disordered Breathing Subtype: A Chinese Community-Based Study

PURPOSE

Non-sleepy sleep-disordered breathing (SDB) is increasingly recognized as an important clinical subtype. The association between non-sleepy SDB and cardiovascular disease (CVD) is not well understood. Our objectives were to investigate the relationship between non-sleepy SDB and CVD and determine which nocturnal hypoxia parameter most strongly reflects this association in a large community population.

PATIENTS AND METHODS

Cross-sectional data from 3626 randomly-selected Chinese community-dwelling participants who underwent overnight type IV sleep monitoring were analyzed. Parameters of nocturnal hypoxemia were extracted from sleep monitoring devices, including mean nocturnal oxygen saturation, lowest oxygen saturation, oxygen desaturation index (ODI), and time with oxygen saturation <90%. An ODI ≥7.0 events/h was considered to signify SDB. An Epworth Sleepiness Scale score of 10 or less indicated no sleepiness.

RESULTS

The SDB rate was 30.7% (1114/3626), of which 96.5% (1075/1114) were considered the non-sleepy SDB subtype. ODI, typical nocturnal intermittent hypoxia indicator for SDB, was independently related to CVD, regardless of whether excessive daytime sleepiness was present. After adjusting for confounders, ODI most strongly reflected the association between non-sleepy SDB and CVD (OR:1.023; 95% CI:1.003-1.043). We observed a nonlinear association between ODI and the prevalence of CVD, where the likelihood of CVD increased with ODI≥10 events/h and a markedly increasing trend was observed with ODI ≥20 events/h (reference ODI = 7.0 events/h). Metabolic parameters, Pittsburgh Sleep Quality Index, and inflammatory marker did not mediate the association between ODI and CVD in the non-sleepy SDB subtype.

CONCLUSION

In the Chinese community-dwelling population, non-sleepy SDB was highly prevalent. ODI, an easily extracted indicator from a type IV sleep monitor, most strongly reflected the association between non-sleepy SDB and CVD.

Bed Sensor Technology for Objective Sleep Monitoring Within the Clinical Rehabilitation Setting: Observational Feasibility Study

Background

Since adequate sleep is essential for optimal inpatient rehabilitation, there is an increased interest in sleep assessment. Unobtrusive, contactless, portable bed sensors show great potential for objective sleep analysis.

Objective

The aim of this study was to investigate the feasibility of a bed sensor for continuous sleep monitoring overnight in a clinical rehabilitation center.

Methods

Patients with incomplete spinal cord injury (iSCI) or stroke were monitored overnight for a 1-week period during their in-hospital rehabilitation using the Emfit QS bed sensor. Feasibility was examined based on missing measurement nights, coverage percentages, and missing periods of heart rate (HR) and respiratory rate (RR). Furthermore, descriptive data of sleep-related parameters (nocturnal HR, RR, movement activity, and bed exits) were reported.

Results

In total, 24 participants (12 iSCI, 12 stroke) were measured. Of the 132 nights, 5 (3.8%) missed sensor data due to Wi-Fi (2), slipping away (1), or unknown (2) errors. Coverage percentages of HR and RR were 97% and 93% for iSCI and 99% and 97% for stroke participants. Two-thirds of the missing HR and RR periods had a short duration of ≤120 seconds. Patients with an iSCI had an average nocturnal HR of 72 (SD 13) beats per minute (bpm), RR of 16 (SD 3) cycles per minute (cpm), and movement activity of 239 (SD 116) activity points, and had 86 reported and 84 recorded bed exits. Patients with a stroke had an average nocturnal HR of 61 (SD 8) bpm, RR of 15 (SD 1) cpm, and movement activity of 136 (SD 49) activity points, and 42 reported and 57 recorded bed exits. Patients with an iSCI had significantly higher nocturnal HR (t₁₈=−2.1, P=.04) and movement activity (t₁₈=−1.2, P=.02) compared to stroke patients. Furthermore, there was a difference between self-reported and recorded bed exits per night in 26% and 38% of the nights for iSCI and stroke patients, respectively.

Conclusions

It is feasible to implement the bed sensor for continuous sleep monitoring in the clinical rehabilitation setting. This study provides a good foundation for further bed sensor development addressing sleep types and sleep disorders to optimize care for rehabilitants.