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Stem cell-based interventions for the prevention and treatment of intraventricular haemorrhage and encephalopathy of prematurity in preterm infants

2023· review· en· W4320856590 on OpenAlexaff
Olga Romantsik, Alvaro Moreira, Bernard Thébaud, Ulrika Ådén, David Ley, Matteo Bruschettini

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2023
Typereview
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsStem Cell NetworkOttawa HospitalChildren's Hospital of Eastern OntarioUniversity of Ottawa
FundersLunds UniversitetMonash University
KeywordsMedicineMesenchymal stem cellStem-cell therapyStem cellPediatricsEncephalopathyInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Germinal matrix-intraventricular haemorrhage (GMH-IVH) and encephalopathy of prematurity (EoP) remain substantial issues in neonatal intensive care units worldwide. Current therapies to prevent or treat these conditions are limited. Stem cell-based therapies offer a potential therapeutic approach to repair, restore, or regenerate injured brain tissue. These preclinical findings have now culminated in ongoing human neonatal studies. This is an update of the 2019 review, which did not include EoP. OBJECTIVES: To evaluate the benefits and harms of stem cell-based interventions for prevention or treatment of GM-IVH and EoP in preterm infants. SEARCH METHODS: We used standard, extensive Cochrane search methods. The latest search was April 2022. SELECTION CRITERIA: We attempted to include 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 or EoP; for treatment studies, we included preterm infants (less than 37 weeks' gestation), of any postnatal age, with ultrasound diagnosis of GM-IVH or with EoP. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. Our primary outcomes were 1. all-cause neonatal mortality, 2. major neurodevelopmental disability, 3. GM-IVH, 4. EoP, and 5. extension of pre-existing non-severe GM-IVH or EoP. We planned to use GRADE to assess certainty of evidence for each outcome. MAIN RESULTS: We identified no studies that met our inclusion criteria. Three studies are currently registered and ongoing. Phase 1 trials are described in the 'Excluded studies' section. AUTHORS' CONCLUSIONS: No evidence is currently available to evaluate the benefits and harms of stem cell-based interventions for treatment or prevention of GM-IVH or EoP in preterm infants. We identified three ongoing studies, with a sample size range from 20 to 200. In two studies, autologous cord blood mononuclear cells will be administered to extremely preterm infants via the intravenous route; in one, intracerebroventricular injection of MSCs will be administered to preterm infants up to 34 weeks' gestational age.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.030
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0070.006
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0130.001

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.

Opus teacher head0.140
GPT teacher head0.396
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations5
Published2023
Admission routes1
Has abstractyes

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