Reevaluating the association between chorioamnionitis and cerebellar hemorrhage: A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Chorioamnionitis is a recognized risk factor for intraventricular hemorrhage and white matter injury in preterm infants. However, its association with cerebellar hemorrhage (CBH) remains controversial with conflicting evidence in the literature. To clarify this relationship, we conducted a systematic review and meta‐analysis examining the association between chorioamnionitis and CBH. PubMed/MEDLINE, EMBASE, and the Cochrane Library were searched for articles from their inception to December 2024 by two independent reviewers. Studies that compared infants with CBH to those without, while also reporting maternal history of chorioamnionitis, were included in the analysis. Studies without adequate information about the control group were excluded. The Newcastle–Ottawa scale was used to assess the risk of bias in the studies included. A random‐effects model was used to calculate the pooled odds ratio and 95% confidence interval. Out of 261 studies screened, 7 studies were included, reaching a total of 1216 infants with 331 with documented chorioamnionitis. Meta‐analysis findings demonstrated that chorioamnionitis exposure was significantly associated with an increased risk of CBH (OR 1.71, 95% CI: 1.25–2.35). Notably, prior meta‐analyses did not establish a significant link between chorioamnionitis and CBH. Findings suggest that more recent studies may be detecting an association, warranting further investigation into the potential pathophysiological mechanisms and confounding factors influencing this relationship. Systematic Review Registration: PROSPERO identifier: CRD42024626144
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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 | 0.016 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.034 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".