A Systematic Review and Meta-Analysis of Animal Studies Testing Intra-Arterial Chilled Infusates After Ischemic Stroke
Bibliographic record
Abstract
Background: As not all ischemic stroke patients benefit from currently available treatments, there is considerable need for neuroprotective co-therapies. Therapeutic hypothermia is one such co-therapy, but numerous issues have hampered its clinical use (e.g., pneumonia risk with whole-body cooling). Some problems may be avoided with brain-specific methods, such as intra-arterial selective cooling infusion (IA-SCI) into the arteries supplying the ischemic tissue. Objective: Our research question was about the efficacy of IA-SCI in animal middle cerebral artery occlusion models. We hypothesized that IA-SCI would be beneficial, but translationally-relevant study elements may be missing (e.g., aged animals). Methods: We completed a systematic review of the PubMed database following the PRISMA guidelines on May 21, 2020 for animal studies that administered IA-SCI in the peri-reperfusion period and assessed infarct volume, behavior (primary meta-analytic endpoints), edema, or blood-brain barrier injury (secondary endpoints). Our search terms included: “focal ischemia” and related terms, “IA-SCI” and related terms, and “animal” and related terms. Nineteen studies met inclusion criteria. We adapted a methodological quality scale from 0 to 12 for experimental design assessment (e.g., use of blinding/randomization, a priori sample size calculations). Results: Studies were relatively homogenous (e.g., all studies used young, healthy animals). Some experimental design elements, such as blinding, were common whereas others, such as sample size calculations, were infrequent (median methodological quality score: 5; range: 2–7). Our analyses revealed that IA-SCI provides benefit on all endpoints (mean normalized infarct volume reduction = 23.67%; 95% CI: 19.21–28.12; mean normalized behavioral improvement = 35.56%; 95% CI: 25.91–45.20; mean standardized edema reduction = 0.95; 95% CI: 0.56–1.34). Unfortunately, blood-brain barrier assessments were uncommon and could not be analyzed. However, there was substantial statistical heterogeneity and relatively few studies. Therefore, exploration of heterogeneity via meta-regression using saline infusion parameters, study quality, and ischemic duration was inconclusive. Conclusion: Despite convincing evidence of benefit in ischemic stroke models, additional studies are required to determine the scope of benefit, especially when considering additional elements (e.g., dosing characteristics). As there is interest in using this treatment alongside current ischemic stroke therapies, more relevant animal studies will be critical to inform patient studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.050 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.028 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".