Pre-existing Comorbidity Burden and Patient Perceived Stroke Impact

Improving physical movement during stroke rehabilitation: investigating associations between sleep measured by wearable actigraphy technology, fatigue, and key biomarkers

BACKGROUND

Sleep disturbance and fatigue are common in individuals undergoing inpatient rehabilitation following stroke. Understanding the relationships between sleep, fatigue, motor performance, and key biomarkers of inflammation and neuroplasticity could provide valuable insight into stroke recovery, possibly leading to personalized rehabilitation strategies. This study aimed to investigate the influence of sleep quality on motor function following stroke utilizing wearable technology to obtain objective sleep measurements. Additionally, we aimed to determine if there were relationships between sleep, fatigue, and motor function. Lastly, the study aimed to determine if salivary biomarkers of stress, inflammation, and neuroplasticity were associated with motor function or fatigue post-stroke.

METHODS

Eighteen individuals who experienced a stroke and were undergoing inpatient rehabilitation participated in a cross-sectional observational study. Following consent, participants completed questionnaires to assess sleep patterns, fatigue, and quality of life. Objective sleep was measured throughout one night using the wearable Philips Actiwatch. Upper limb motor performance was assessed on the following day and saliva was collected for biomarker analysis. Correlation analyses were performed to assess the relationships between variables.

RESULTS

Participants reported poor sleep quality, frequent awakenings, and difficulties falling asleep following stroke. We identified a significant negative relationship between fatigue severity and both sleep quality (r=-0.539, p = 0.021) and participants experience of awakening from sleep (r=-0.656, p = 0.003). A significant positive relationship was found between grip strength on the non-hemiplegic limb and salivary gene expression of Brain-derived Neurotrophic Factor (r = 0.606, p = 0.028), as well as a significant negative relationship between grip strength on the hemiplegic side and salivary gene expression of C-reactive Protein (r=-0.556, p = 0.048).

CONCLUSION

The findings of this study emphasize the importance of considering sleep quality, fatigue, and biomarkers in stroke rehabilitation to optimize recovery and that interventions may need to be tailored to the individual. Future longitudinal studies are required to explore these relationships over time. Integrating wearable technology for sleep and biomarker analysis can enhance monitoring and prediction of outcomes following stroke, ultimately improving rehabilitation strategies and patient outcomes.

Comorbidity and outcomes among hospitalized patients with stroke: a nationwide inpatient analysis

Objective

We aimed to characterize healthcare utilization and comorbidity outcomes among hospitalized elderly stroke patients using a nationally representative dataset in the United States.

Methods

Using the 2019 National Inpatient Sample, patients aged 65 years or older with and without comorbidities who were hospitalized for acute stroke were identified using the International Classification of Diseases, Tenth Revision, Clinical Modification codes. Patient comorbidities were identified with the use of the Elixhauser Comorbidity Index. The prevalence of comorbidities, in-hospital mortality, length of stay, and total hospital costs were analyzed for these patients.

Results

Within 451,945 patients (mean age 78 years, 54.1% women, 73.7% white), we observed that more than 90% of patients had a minimum of two comorbidities. The median number of comorbidities was 4.0 (IQR 3.0-6.0). There was significant variation in the prevalence rate of comorbidities. The five most common comorbidities were uncomplicated hypertension (55.4%), paralysis (40.1%), congestive heart failure (39.8%), various neurological illnesses (38.3%), and complex hypertension (32.5%). After adjusting for patient- and hospital-level characteristics, a statistically significant association was observed between comorbidities and various adverse outcomes. Specifically, comorbidities were found to be significantly associated with an increased risk of inpatient mortality (odds ratio: 1.09; 95% CI: 1.08-1.11; P < 0.001), a longer duration of hospitalization (0.68 days; 95% CI: 0.66-0.71; P < 0.001), and higher total cost ($1,874.9; 95% CI: 1,774.6-1,975.2; P < 0.001).

Conclusion

This national data suggests that comorbidity is common among hospitalized older stroke patients and substantially increases the healthcare burden and inpatient mortality in the United States. These findings underscore the integration of comorbidity management into the care of older stroke patients.

Examining the Associations between Post-Stroke Cognitive Function and Common Comorbid Conditions among Stroke Survivors

A considerable complication for stroke survivors is the subsequent development of cognitive decline or dementia. In this study, the relationship between the inflammation-centered comorbidity burden on post-stroke cognitive function among community-dwelling stroke survivors capable of independent living was examined. Data for this secondary analysis were collected from stroke survivors (n = 97) participating in a randomized clinical trial. Participants provided baseline responses, regarding cognitive function (mini-mental status exam, MMSE; Montreal cognitive assessment, MoCA), history of stroke comorbid conditions, and the Stroke Prognosis Instrument-II (SPI-II), an index of stroke comorbidity and recurrent stroke risk within the next two years. Relationships and differences between groups were tested for significance using Spearman's correlation, Kruskal-Wallis, or Mann-Whitney U tests. Most stroke survivors (69%) had multiple comorbidities. Total SPI-II scores were negatively correlated to both MoCA and MMSE scores (r = -0.25, p = 0.01; r = -0.22, p = 0.03, respectively), and differences in MoCA scores among SPI-II risk groups (low, medium, high) were evident (p = 0.05). In contrast, there were no differences in MoCA or MMSE scores when comorbid conditions were examined individually. Lastly, no gender differences were evident in cognitive assessments. Our data support the premise that comorbidity's burden impacts post-stroke cognitive decline, more than a single comorbid condition. Inflammation may be an important component of this comorbidity burden. Future studies that operationalize this concept will better illuminate the complex phenomenon of post-stroke cognitive decline for improved clinical rehabilitation modalities.