Global incidence proportion of intraventricular haemorrhage of prematurity: a meta-analysis of studies published 2010–2020
Bibliographic record
Abstract
Objective To investigate differences and calculate pooled incidence of any intraventricular haemorrhage (IVH), severe IVH (Grade III/IV, sIVH) and ventriculoperitoneal shunt (VPS) placement in preterm infants across geographical, health and economic regions stratified by gestational age (GA). Design MEDLINE, Embase, CINAHL and Web of Science were searched between 2010 and 2020. Studies reporting rates of preterm infants with any IVH, sIVH and VPS by GA subgroup were included. Meta-regression was performed to determine subgroup differences between study designs and across United Nations geographical regions, WHO mortality strata and World Bank lending regions. Incidence of any IVH, sIVH and VPS by GA subgroups<25, <28, 28–31, 32–33 and 34–36 weeks were calculated using random-effects meta-analysis. Results Of 6273 publications, 97 met inclusion criteria. Incidence of any IVH (37 studies 87 993 patients) was: 44.7% (95% CI 40.9% to 48.5%) for GA <25 weeks, 34.3% (95% CI 31.2% to 37.6%) for GA <28 weeks, 17.4% (95% CI 13.8% to 21.6%) for GA 28–31 weeks, 11.3% (95% CI 7.3% to 17.0%) for GA32–33 weeks and 4.9% (95% CI 1.4% to 15.2%) for GA 34–36 weeks. Incidence of sIVH (49 studies 328 562 patients) was 23.7% (95% CI 20.9% to 26.7%) for GA <25 weeks, 15.0% (95% CI 13.1% to 17.2%) for GA <28 weeks, 4.6% (95% CI 3.5% to 6.1%) for GA 28–31 weeks, 3.3% (95% CI 2.1% to 5.1%) for GA 32–33 weeks and 1.8% (95% CI 1.2% to 2.8%) for GA 34–36 weeks. Europe had lower reported incidence of any IVH and sIVH relative to North America (p<0.05). Proportion of VPS across all GA groups was 8.4% (95% CI 4.7% to 14.7%) for any IVH and 17.2% (95% CI 12.2% to 26.2%) for sIVH. Heterogeneity was high (I 2 >90%) but 64%–85% of the variance was explained by GA and study inclusion criteria. Conclusions We report the first pooled estimates of IVH of prematurity by GA subgroup. There was high heterogeneity across studies suggesting a need for standardised incidence reporting guidelines.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".