Strokes and their relationship with sleep and sleep disorders

Prevalence, contributing factors, and economic implications of strokes among older adults: a study of North-East India

Stroke is a significant cause of mortality and disability in India, with its economic impact on the rise. This study aims to investigate the prevalence and factors associated with stroke among the elderly population in seven north-eastern states of India and its economic consequences. Data from the initial phase of the Longitudinal Ageing Study in India (2017-2018) were utilized, and bivariate and multivariate analyses were done. Stroke prevalence (1.53%) was notable among both genders, with approximately 1% in females and 2.3% in males. Individuals with low physical activity, higher socio-economic status, and unemployment faced a higher risk of stroke. Females exhibited a 60% lower likelihood [AOR 0.40; (CI 0.250-0.627)] of stroke compared to males and hypertension was a significant risk factor. Stroke patients incur up to INR 50,000 of financial burden, with a considerable proportion facing disability in comprehension and speech. The economic burden of stroke-related hospitalization was significantly high, emphasizing the need for government-funded health insurance to cover stroke-related medications and reducing out-of-pocket expenses for patients seeking treatment in healthcare facilities. The study highlights the urgency for better schemes to address the growing threat of strokes in the north-eastern parts of India for comprehensively tackling this public health challenge.

Post-stroke depression in Vietnamese patients is associated with decreased sleep quality and increased fatigue: a one-institution cross-sectional analysis

PURPOSE

This study aimed to determine the prevalence of post-stroke depression (PSD) during the first year and its associated factors, especially focusing on sleep quality and fatigue severity.

METHODS

A cross-sectional study was conducted among stroke patients in Vietnam's National Geriatric Hospital. Data were collected by using standardized questionnaires for interviewing and evaluating patients at the research site. Several covariables were presented including demographics, stroke-related characteristics, activities of daily living, post-stroke fatigue, and sleep quality (Pittsburgh Sleep Quality Index [PSQI] scale). PSD was assessed as an outcome variable through the Patient Health Questionnaire-9 scale. To summarize sociodemographic and clinical variables, descriptive statistics were performed. A logistic regression model was used to explore the factors related to PSD.

RESULTS

Of 157 patients with stroke, mean age 73.1 (± 9.6), PSD was present in 60 patients (38%). The global score and all PSQI components of participants with PSD showed worse levels than those without depression. Furthermore, the prevalence of PSD was higher in patients with low IADL scores and functional disability at high levels. In the multivariate logistic regression analysis, the patients with PSD showed higher Fatigue Severity Scale (FSS) scores (OR = 4.11; 95% CI = 1.39; 12.19) and higher scores in two domains of the PSQI scale including subjective sleep quality (OR = 3.03; 95% CI = 1.21; 7.58) and sleep disturbance (OR = 5.22; 95% CI = 1.33; 20.47).

CONCLUSION

There is a significant prevalence of depression following stroke. Furthermore, post-stroke fatigue and two PSQI scale components (subjective sleep quality and sleep disturbance) were shown to be associated with PSD. This finding may guide early screening and intervention strategies to address depression following stroke.

The associations of BMI, chronic conditions and lifestyle factors with insomnia symptoms among older adults in India

Background

The aim of the study was to estimate the prevalence of insomnia symptoms and to examine the associations of body mass index (BMI), chronic diseases, and lifestyle factors with self-reported insomnia symptoms among older people in India.

Methods

We conducted a cross-sectional study using data from the baseline wave of the Longitudinal Ageing Study in India (LASI) that was collected during 2017–18. A sample of 31,358 older adults aged 60 and above was included in the analyses. Descriptive statistics and bivariate and multivariable analyses were performed to obtain the results.

Results

In this study, insomnia symptoms were reported by around 36 percent of older adults aged 60 and above. After controlling for socio-demographic factors, insomnia symptoms were positively associated with the risk of being underweight [AOR: 1.289, CI: 1.211–1.372] and negatively associated with obesity/overweight [AOR: 0.928, CI: 0.872–0.990] as compared to older adults with normal BMI. The odds of insomnia symptoms were higher among those who reported the following chronic conditions, i.e., hypertension [AOR:1.356, CI:1.278–1.438], diabetes [AOR:1.160, CI:1.074–1.254], chronic lung diseases [AOR:1.485, CI:1.351–1.632], bone-related diseases [AOR:1.561, CI:1.458–1.670] and any psychiatric disorders [AOR:1.761, CI:1.495–2.074]. In addition, older adults who were physically active [AOR: 0.850, CI:0.804–0.900] were less likely to report insomnia symptoms.

Conclusions

The study suggests a high prevalence of insomnia symptoms among the older population in India. Early identification of the signs of insomnia in older population is crucial, as is timely treatment for any kind of sleep problems. In addition, nutrition-based interventions and individual disease-specific management programs may help minimize the stressful situations in later life and develop a good night’s sleep for the older population.

Can exercise training promote better sleep and reduced fatigue in people with chronic stroke? A systematic review

Poor sleep and chronic fatigue are common in people with chronic stroke (i.e. ≥ 6 months post-stroke). Exercise training is a viable, low-cost therapy for promoting sleep and reducing fatigue; however, the effects of exercise on sleep and fatigue in people with chronic stroke are unclear. Thus, we conducted a systematic review ascertaining the effects of exercise on sleep and fatigue in people with chronic stroke. We systematically searched EMBASE, MEDLINE, AgeLine, the Cochrane Database of Systematic Reviews, CINAHL, SPORTDiscus, SCOPUS, and reference lists of relevant reviews for articles that examined the effects of exercise on sleep or fatigue in chronic stroke. Search results were limited to adults ≥ 18 years, randomized controlled trials, non-randomized trials, and pre-post studies, which were published in English and examined the effects of exercise on sleep or fatigue in people with chronic stroke. We extracted study characteristics and information on the measurement of sleep and fatigue, and assessed study quality and risk of bias using the CONSORT criteria and Cochrane risk-of-bias tool, respectively. We found two studies that examined the effects of exercise on sleep, and two that examined the effects of exercise on fatigue. All studies reported positive effects of exercise training on sleep and fatigue; however, there were concerns of bias and study quality in all studies. There is preliminary evidence that exercise promotes sleep and reduces fatigue in people with chronic stroke; however, the extent to which exercise impacts these health parameters is unclear.

Rapid eye movement (REM) sleep microarchitecture is altered in patients with wake-up ischemic stroke: A polysomnographic study

It is well established that certain alteration of sleep disorders occur in patients with wake-up stroke (WUS) such as sleep disordered breathing, periodic limb movements and sleep duration. However, the data are lacking about the microarchitecture of different sleep stages among those patients.

Aim of work

To compare the polysomnographic microarchitecture of rapid eye movement (REM) sleep between WUS and daytime stroke (DTS).

Methods

A cross-sectional polysomnographic study was conducted on 20 patients with WUS and 20 patients with DTS, with analysis of REM sleep microarchitecture in specific.

Results

Patients with WUS had significantly shorter REM stage (11.76 ± 5.48% in WUS versus 16.59 ± 5.33% in DTS, P = 0.008), longer early morning REM was (25.70 ± 13.13 min in WUS versus 4.15 ± 4.69 min in DTS, P=<0.001), higher apnea-hypopnea index (AHI) during REM (6.29 ± 10.18 in WUS versus 1.10 ± 4.57 in DTS, P = 0.009), and lower mean Oxygen saturation during REM (92.70 ± 3.63 WUS versus 95.45 ± 1.35 DTS, P = 0.012). The OR of early morning REM duration was 1.8 (CI 1.099–3.130, p = 0.021) for WUS.

Conclusion

The microarchitecture of REM sleep is disrupted in patients with wake-up stroke.

⁃

The polysomnographic parameters are significantly different between patients with daytime stroke (DTS) and wake-up stroke (WUS).

⁃

Patients with WUS have longer stage 2 and shorter REM stage.

⁃

The REM microarchitecture is disrupted among patients with WUS e.g. early morning REM duration in comparison to patients with daytime stroke (DTS).

⁃

The distruption was in the form of shorter REM percentage to total sleep time, higher sleep apnea hypopnea index (AHI) during REM sleep, lower oxygen saturation during REM sleep and longer early morning REM duration.

⁃

Periodic limb movement (PLM) index, and PLM-related arousals are higher among DTS.

Contribution of sleep quality to fatigue following a stroke: a cross-sectional study

BACKGROUND

The prevalence of fatigue and sleep disturbances is high in stroke populations. Sleep quality can be targeted by interventions to alleviate fatigue following a stroke. This study aimed to determine the prevalence of fatigue and poor sleep quality, and to quantify the contribution of sleep quality to fatigue following a stroke, in chronic (≥1 year) stroke survivors.

METHODS

A cross-sectional design was adopted. A total of 112 stroke survivors (mean age ± standard deviation [year], 64.18 ± 5.77) at 6.08 ± 4.80 years post-stroke completed this study. All participants were assessed using the Fatigue Assessment Scale, the Pittsburgh Sleep Quality Index, the Visual Analogue Scale-Pain, the Fugl-Meyer Assessment of the upper and lower extremities, the 5-Time Sit-To-Stand Test, the Epworth Sleepiness Scale, the Frenchay Activities Index, the Life-Space Assessment, the Community Integration Measure, and the Multidimensional Scale of Perceived Social Support. Pearson and partial correlation coefficients were used to examine the correlation between fatigue and other variables. A multiple linear regression (the forced entry method) was performed to quantify the independent contribution of sleep quality to prediction of fatigue.

RESULTS

Of the 112 participants, 52.7% reported experiencing fatigue and 64.3% reported poor sleep quality. Sleep quality could independently account for 5.9% of the variance in fatigue scores after a stroke.

CONCLUSIONS

There is a high prevalence of fatigue and poor sleep quality in Chinese stroke survivors. Sleep quality is an independent predictor of fatigue in those living in the community who have survived a stroke for a year or longer.

Connection between sleeping patterns and cognitive deterioration in women with Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) causes symptoms such as dementia, memory loss, disorientation, and even aggressiveness, and is more common in women than in men. AD may also manifest itself in changes in sleep patterns. However, the relationship between AD (in all stages) and bedtime behavior has not been thoroughly investigated.

METHODS

In a prospective, cross-sectional survey, we evaluated 74 women categorized in two different stages of cognitive decline associated with AD (mild and severe) along with 37 women with no cognitive decline who served as controls. We obtained demographic and medical information such as age, health status, and medication, as well as psychiatrically confirmed staging of AD. We also collected actigraphy data for several nights in a row with a medical grade wristband using a 3-axis accelerometer and solid-state on-board memory. These data served as parameters for a clustering machine learning (ML) algorithm.

RESULTS

The ML process was able to unsupervisedly identify 85% of the participants according to their pre-assigned degree of dementia. When the clustering was carried out in a binary fashion (i.e., only taking into account healthy members vs. severely affected AD patients), it was possible to correctly classify 91% of the cases.

CONCLUSIONS

This study revealed a strong connection between the severity of the intellectual decline and the features distilled from actigraphically derived sleep parameters.