4 The Association Between Pro-Inflammatory Cytokines and C-Reactive Protein and the Cognitive and Neurological Outcome in Stroke Survivors: A Systematic Review
Bibliographic record
Abstract
Objective: Childhood ischemic and hemorrhagic stroke is often associated with neuropsychological and cognitive deficits. Stroke induces an inflammatory response in the central and peripheral nervous systems. High levels of inflammatory markers in the plasma have been associated with poorer cognitive outcomes. The role of inflammation in neurological prognosis of stroke has been studied previously; however, there is a limited understanding of the association between inflammatory markers and neuropsychological outcome post-stroke. The present review examined the existing literature on the association between inflammatory markers and post-stroke functioning. Participants and Methods: Data bases (PsycINFO, PubMed, Web of Science, and Ovid) were reviewed in October 2020. Articles were restricted to English-language literature. Articles were included regardless of recruitment setting, number of strokes, mechanism of stroke, timing of blood collection and outcome assessment. The articles focused on patients with stroke (between the ages of 0 to 95), measured post-stroke outcome by neurological and cognitive outcome measures (i.e., it included findings on any aspect of cognition such as memory, information processing, or attention), and on pro-inflammatory cytokines and c-reactive proteins as measures of inflammation. The systematic literature search retrieved 954 articles to review against inclusion criteria. Descriptive statistics were performed using IBM SPSS 27.0 Statistics Software. Results: A total of 18 articles were included in this review. The population age ranged from 21 to 95, and, when reported (n=17), mean participant age was 66.31. Among stroke patient populations, ischemic stroke was most researched (n=15). The most widely investigated biomarkers were CRP (n=9), IL-6 (n=8), TNF- a (n=7), IL-1 b (n=5), and IL-10 (n=5). The time of initial blood collection ranged from on admission to within 3 months poststroke. Equal number of studies used both neurological and cognitive tests (n=7), or only neurological (n=7), 2 studies only used cognitive tests, and one study used all three types of measures. The most commonly used cognitive test was the Mini Mental State Examination, MMSE (n=7). The next commonly used cognitive test was the Montreal Cognitive Assessment (MoCA), (n=4). Only two studies used a comprehensive neuropsychological battery. Conclusions: There is a lack of research into diverse stroke populations. All the studies examined the association between inflammatory markers and the post-stroke outcomes in adult populations and mostly in patients with ischemic stroke. The lack of research on pediatric and young adult stroke represents a significant gap in understanding predictors of neurological and cognitive outcomes. Further, the review revealed a lack of comprehensive neurocognitive assessment post stroke, with most studies measuring neuropsychological outcome using brief cognitive instruments. Our findings highlight a critical need for addressing the above gaps to help elucidate the role of inflammatory markers in the neuropsychological prognosis of stroke in younger populations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".