Infection, Inflammation, and Poststroke Cognitive Impairment

Red blood cell distribution width to albumin ratio (RAR) is associated with low cognitive performance in American older adults: NHANES 2011-2014

BACKGROUND

The red blood cell distribution width to albumin ratio (RAR) is a novel comprehensive biomarker of inflammation and nutrition, which has emerged as a reliable prognostic indicator for adverse outcomes and mortality in patients with various diseases. However, the association between RAR and low cognitive performance in older adults remains unclear. This study aims to investigate the relationship between RAR and low cognitive performance among older adults in the United States.

METHODS

This study, a retrospective analysis, included 2,765 participants aged 60 years and older from the National Health and Nutrition Examination Survey (NHANES) conducted between 2011 and 2014. Low cognitive performance was assessed using word learning subset from the Consortium to Establish a Registry for Alzheimer's Disease (CERAD), the Digit Symbol Substitution Test (DSST), and the Animal Fluency Test (AFT). Low cognitive performance was defined as scores below the lowest quartile in each cognitive test. The association between RAR and low cognitive performance was evaluated using weighted multivariable logistic regression, restricted cubic splines (RCS), and subgroup analyses.

RESULTS

After adjusting for all potential confounders, RAR was independently and linearly positively associated with both low DSST performance and low AFT performance. Specifically, compared to participants in the first quartile of RAR, those in the fourth quartile had adjusted ORs (95% CIs) of 1.81 (1.03, 3.20) for low DSST performance and 1.68 (1.05, 2.67) for low AFT performance. Subgroup analysis did not reveal significant interactions between stratification variables.

CONCLUSION

RAR is significantly linearly positively associated with low cognitive performance. Maintaining a lower RAR may be a crucial strategy for mitigating the risk of cognitive decline in the elderly population.

Research progress on the mechanism and markers of metabolic disorders in the occurrence and development of cognitive dysfunction after ischemic stroke

Post-stroke cognitive impairment (PSCI) is a common complication following a stroke that significantly affects patients' quality of life and rehabilitation outcomes. It also imposes a heavy economic burden. There is an urgent need to better understand the pathophysiology and pathogenesis of PSCI, as well as to identify markers that can predict PSCI early in the clinical stage, facilitating early prevention, monitoring, and treatment. Although the mechanisms underlying PSCI are complex and multifaceted, involving factors such as atherosclerosis and neuroinflammation, metabolic disorders also play a critical role. This article primarily reviews the relationship between metabolic disorders of the three major nutrients-sugar, fat, and protein-and the development of cognitive dysfunction following ischemic stroke (IS). It aims to elucidate how these metabolic disturbances contribute to cognitive dysfunction post-stroke and to explore potential metabolic biomarkers for PSCI. We believe that this review will offer new insights into the early identification, treatment, and prognostic assessment of PSCI.

Domain-specific cognitive impairments, mood and quality of life 6 months after stroke

PURPOSE

To identify which acute and 6-month domain-specific cognitive impairments impact mood, participation, and stroke-related quality of life 6 months post-stroke.

MATERIALS AND METHODS

A prospective cohort of 430 stroke survivors completed the Oxford Cognitive Screen (OCS) acutely and 6 months post-stroke. Participants completed the Stroke Impact Scale (SIS) and Hospital Depression and Anxiety Scale (HADS) at 6 months. Multivariable regression analyses assessed whether severity of, and domain-specific, cognitive impairment acutely and at 6 months was associated with composite 6-month SIS scores, each SIS subscale, and HADS scores.

RESULTS

Increased severity of acute and 6-month cognitive impairment was associated with lower 6-month SIS composite scores independent of age, sex, education years, and stroke severity (both p < 0.001). Domain-specific impairments in memory (p < 0.001) and attention (p = 0.002) acutely, and language (p < 0.001), memory (p = 0.001) and number processing (p = 0.006) at 6 months showed the strongest associations with worse SIS composite scores. Severity of acute and 6-month cognitive impairment was associated with poorer functioning in each SIS subscale, and greater levels of depression (acute p = 0.021, 6-months p < 0.001), but not anxiety (p = 0.174, p = 0.129).

CONCLUSIONS

Both acute and 6-month domain-specific cognitive impairments, particularly in memory, were found to negatively impact overall functional and mood outcomes 6 months post-stroke.

A systematic review and meta-analysis show a decreasing prevalence of post-stroke infections

BACKGROUND

Infection is a common complication in the acute phase after stroke; a systematic review in 2011 reported a post-stroke infection prevalence of 30%. Despite the plethora of primary data on post-stroke infections in recent times, a systematic review that synthesizes the data to provide comprehensive information to guide preventive, control, and management efforts is yet to be undertaken. This systematic review, therefore, aimed at bridging this gap by describing the epidemiology of post-stroke infections including the global prevalence and the associated mortality rates.

METHODOLOGY

A comprehensive search was conducted in PubMed, SCOPUS, and Web of Science resulting in 2210 studies, of which 73 studies covering 32,109,574 stoke patients were included in the systematic review. Prevalence data on defined post-stroke infections were extracted for analysis in RStudio version 4.3.3.

RESULTS

The pooled prevalence of post-stroke infections and mortality rates were 9.14% and 15.91% respectively. The prevalence of post-stroke infections was highest for pneumonia (12.4%), followed by urinary tract infection (8.31%). Geographically, the prevalence of post-stroke infections for the various continents were Europe (10.41%), Africa (10.22%), South America (8.83%), North America (8.15%), Asia (8.09%), and Australia (7.88%). Common etiological agents of post-stroke infections included multidrug-resistant organisms particularly, Carbapenem-resistant Klebsiella pneumoniae (15.4-31.8%), Methicillin-resistant Staphylococcus aureus (9.8-15.4%), and Carbapenem-resistant Acinetobacter baumannii (38.5%).

CONCLUSION

This systematic review indicates about a 3-fold decline in the global prevalence of post-stroke infections in the last decade. Pneumonia is the most common post-stroke infection. Europe and Africa have the highest prevalence of post-stroke infections.

Exploring the therapeutic potential of sγPNA-141: Pharmacodynamics and mechanistic insights during ischemic stroke recovery

MicroRNA-141-3p plays a detrimental role in the pathology of ischemic stroke, presenting a new target for stroke treatment. This study introduces and validates a novel class of peptide nucleic acid (PNA)-based miR-141-3p inhibitors known as serine gamma PNA-141 (sγPNA-141) for ischemic stroke treatment. After synthesis, physicochemical characterization, and nanoparticle encapsulation of sγPNA-141, we compared its safety and efficacy with traditional phosphorothioate- and regular PNA-based anti-miR-141-3p (PNA-141) in vitro, followed by detailed in vivo and ex vivo efficacy testing of sγPNA-141 for treating ischemic stroke using a mouse model. sγPNA-141 demonstrated higher affinity and specificity toward miR-141-3p, and when applied post-stroke, demonstrated decreased brain damage, enhanced neuroprotective proteins, reduced tissue atrophy, swift improvement in functional deficits, and improvement in learning and memory during long-term recovery. Overall, our data show sγPNA-141 has neuroprotective and neuro-rehabilitative effects during stroke recovery. Furthermore, we demonstrated sγPNA-141's effects are mediated by the TGF-β-SMAD2/3 pathway. In summary, the present findings suggest that sγPNA-141 could be a potentially novel and effective therapeutic modality for the treatment of ischemic stroke.

Factors Influencing Poststroke Cognitive Dysfunction: Cross-Sectional Analysis

BACKGROUND

Poststroke cognitive impairment (PSCI) is a common and debilitating complication that affects stroke survivors, impacting memory, attention, and executive function. Despite its prevalence, the factors contributing to PSCI remain unclear, with limited insights into how demographic and clinical variables influence cognitive outcomes.

OBJECTIVE

This study investigates the incidence of cognitive impairment in patients with stroke and examines key demographic and clinical factors, such as age, gender, and education level, which contribute to cognitive decline. The aim is to provide a deeper understanding of PSCI to inform early intervention strategies for improving patient outcomes.

METHODS

A cross-sectional study was conducted on 305 patients with ischemic stroke admitted to Zhongda Hospital, Southeast University, from January 2019 to September 2022. Cognitive function was assessed using the Mini-Mental State Examination (MMSE) within 72 hours of hospital admission. Demographic information, including age, gender, and education level, were collected. Statistical analyses were performed using chi-square tests, independent t tests, and multivariate regression to assess the relationship between cognitive function and key variables. Pearson correlation analysis explored associations among age, education, and MMSE scores.

RESULTS

Among the 305 patients with stroke, 16.7% (n=51) were diagnosed with cognitive impairment based on MMSE scores. The prevalence of cognitive impairment was slightly higher in males (17.6%, n=159) than females (15.8%, n=146), but this difference was not statistically significant. A strong negative correlation was found between MMSE scores and age (r=-0.32; P<.01), indicating that older patients had lower cognitive function. Education level showed a positive correlation with MMSE scores (r=0.41; P<.01), with patients with higher educational attainment demonstrating better cognitive outcomes. Cognitive function showed a marked decline in patients older than 60 years, particularly in domains such as memory, attention, and language skills.

CONCLUSIONS

This study confirms that age and education are significant factors in determining cognitive outcomes after stroke. The results align with existing literature showing that cognitive function declines with age, while higher educational attainment serves as a protective factor. The findings suggest that individuals with greater cognitive reserve, often linked to higher education, are better equipped to cope with the impact of brain injury. However, the study's reliance on MMSE may have limited its ability to detect domain-specific impairments. Future studies should consider using more sensitive cognitive tools, such as the Montreal Cognitive Assessment (MoCA), to provide a more comprehensive evaluation of PSCI. Cognitive impairment is prevalent among stroke survivors, with age and education level being key factors influencing outcomes. These findings underscore the importance of early detection and targeted interventions to mitigate cognitive decline. Further research with larger samples and more sensitive cognitive assessments is needed to fully understand PSCI and improve rehabilitation strategies for patients with stroke.

Impact of Pre-Stroke Frailty on Outcome Three Years after Acute Stroke: The Nor-COAST Study

INTRODUCTION

We aimed to explore the predictive value of pre-stroke frailty index (FI) on functional dependency and mortality 3 years after stroke.

METHODS

Based on the Rockwood 36-item FI score, we calculated the pre-stroke FI from medical conditions recorded at baseline in the multicenter prospective Nor-COAST study 2015-2017. Participants with a FI score and a modified Rankin scale (mRS) 0-6 3 years post-stroke were included in this study. We used logistic regression analysis with unfavorable mRS (over 2 vs. 0-2) at 3 years, or dead within 3 years, as dependent variable, and frailty and pre-stroke mRS, one at a time, and simultaneously, as predictors. The analyses were carried out unadjusted and adjusted for the following variables one at a time: Age, sex, years of education, stroke severity at admission, infections treated with antibiotics and stroke progression. We report odds ratio (OR) per 0.10 increase in FI.

RESULTS

At baseline, the 609 included patients had mean age 72.8 (standard deviation [SD] 11.8), 261 (43%) were females, and had a FI mean score of 0.16 (SD 0.12), range 0-0.69. During 3 years, 138 (23%) had died. Both the FI, and pre-stroke mRS, were strong predictors for unfavorable mRS (OR 4.1 and 2.7) and dead within 3 years (OR 2.2 and 1.7). Only adjusting for age affected the result. The OR for pre-stroke mRS decreased relatively more than the OR for FI when entered as predictors simultaneously.

CONCLUSIONS

FI is a stronger predictor than premorbid mRS for prognostication after stroke.