Efficacy of mesenchymal stromal cells in preclinical models of necrotizing enterocolitis: a systematic review protocol
Bibliographic record
Abstract
Introduction: Necrotizing enterocolitis is an acute inflammatory disease of the intestine that can lead to necrosis and bowel perforation. It is a severe complication of preterm birth. It’s mortality rate is up to 50% and survival after necrotizing enterocolitis leads to long-term complications. The current treatment is supportive and includes bowel rest and decompression and antibiotics. Thus, new treatments are necessary to reduce mortality and morbidity. Mesenchymal stromal cells are known to have anti-inflammatory properties and might be a promising option for treatment. Here we present a protocol for a systematic review with the aim to explore the efficacy of cell therapies with mesenchymal stromal cells in animal models of necrotizing enterocolitis. The primary outcome is histological signs of necrotizing enterocolitis. Additional outcomes include survival, bowel perforation, gut permeability, gut motility, levels of inflammatory markers, cytokine levels and adverse events. Methods: We will conduct a systematic search of MEDLINE, Embase, and Web of Science databases. The retrieved records will be screened individually by two investigators. We will include all preclinical in vivo animal models of experimentally induced necrotizing enterocolitis that evaluate the efficacy of mesenchymal stromal cells or other cell therapy treatments. Outcome data will be extracted from each article and risk of bias assessment performed. Funnel plots and SYRCLE’s risk of bias tool for animal studies will be used. Data will be reported as ratios, divided in predefined subgroups where relevant. Conclusions: This systematic review aims to examine the efficacy of mesenchymal stromal cells in preclinical models of necrotizing enterocolitis and whether there is sufficient evidence to support a clinical trial of efficacy and safety of the treatment with mesenchymal stromal cells in infants with necrotizing enterocolitis.
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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 | 0.051 | 0.071 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.021 | 0.016 |
| Bibliometrics | 0.014 | 0.011 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.050 | 0.005 |
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".