Stem cell-based interventions for the prevention and treatment of germinal matrix-intraventricular haemorrhage in preterm infants
Bibliographic record
Abstract
BACKGROUND: Germinal matrix-intraventricular haemorrhage (GMH-IVH) remains a substantial issue in neonatal intensive care units worldwide. Current therapies to prevent or treat GMH-IVH are limited. Stem cell-based therapies offer a potential therapeutic approach to repair, restore, and/or regenerate injured brain tissue. These preclinical findings have now culminated in ongoing human neonatal studies. OBJECTIVES: To determine the benefits and harms of stem cell-based interventions for prevention or treatment of germinal matrix-intraventricular haemorrhage (GM-IVH) in preterm infants. SEARCH METHODS: We used the standard search strategy of Cochrane Neonatal to search the Cochrane Central Register of Controlled Trials (CENTRAL; 2019, Issue 1), in the Cochrane Library; MEDLINE via PubMed (1966 to 7 January 2019); Embase (1980 to 7 January 2019); and the Cumulative Index to Nursing and Allied Health Literature (CINAHL) (1982 to 7 January 2019). We also searched clinical trials databases, conference proceedings, and reference lists of retrieved articles for randomised controlled trials and quasi-randomised trials. SELECTION CRITERIA: We attempted to identify randomised controlled trials, quasi-randomised controlled trials, and cluster trials comparing (1) stem cell-based interventions versus control; (2) mesenchymal stromal cells (MSCs) of type or source versus MSCs of other type or source; (3) stem cell-based interventions other than MSCs of type or source versus stem cell-based interventions other than MSCs of other type or source; or (4) MSCs versus stem cell-based interventions other than MSCs. For prevention studies, we included extremely preterm infants (less than 28 weeks' gestation), 24 hours of age or less, without ultrasound diagnosis of GM-IVH; for treatment studies, we included preterm infants (less than 37 weeks' gestation), of any postnatal age, with ultrasound diagnosis of GM-IVH. DATA COLLECTION AND ANALYSIS: For each of the included trials, two review authors independently planned to extract data (e.g. number of participants, birth weight, gestational age, type and source of MSCs, other stem cell-based interventions) and assess the risk of bias (e.g. adequacy of randomisation, blinding, completeness of follow-up). Primary outcomes considered in this review are all-cause neonatal mortality, major neurodevelopmental disability, GM-IVH, and extension of pre-existing non-severe GM-IVH. We planned to use the GRADE approach to assess the quality of evidence. MAIN RESULTS: Our search strategy yielded 769 references. We did not find any completed studies for inclusion. One randomised controlled trial is currently registered and ongoing. Five phase 1 trials are described in the excluded studies. AUTHORS' CONCLUSIONS: Currently no evidence is available to show the benefits or harms of stem cell-based interventions for treatment or prevention of GM-IVH in preterm infants.
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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 | 0.009 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".