The risk of stroke-related pneumonia: a systematic review of peripheral immunodepression markers
Bibliographic record
Abstract
Ischemic stroke (IS)-associated pneumonia is a leading cause of mortality after stroke, driven by peripheral immune imbalance. This systematic review evaluates immunosuppression markers associated with pneumonia following IS in clinical studies. Following PRISMA guidelines, we searched PubMed/MEDLINE, EMBASE, and LILACS databases until March 2024. Inclusion criteria comprised clinical studies assessing IS-related immunosuppression and pneumonia, excluding in vitro and animal studies. Study quality was assessed using the Newcastle-Ottawa Scale. A total of 32 studies met the inclusion criteria, analyzing 1,833 post-stroke patients. Findings indicate that increased interleukin-6 (IL-6), interleukin-10 (IL-10), and C-reactive protein (CRP) levels, alongside decreased repulsive guidance molecule A (RGM-A), are early indicators of post-stroke pneumonia. Meta-analysis was not conducted due to heterogeneity in study methodologies and populations. Elevated IL-6, IL-10, and CRP levels, along with reduced RGM-A, are associated with post-stroke pneumonia, emphasizing the role of immune dysregulation in its pathophysiology. Despite promising findings, further studies with standardized detection techniques are needed to enhance diagnostic accuracy and improve patient prognosis. The variability in study methodologies presents a limitation to drawing definitive conclusions. Registration: PROSPERO CRD42024543108.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".