Global Prevalence of Severe Neonatal Jaundice among Hospital Admissions: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Evidence regarding the adverse burden of severe neonatal jaundice (SNJ) in hospitalized neonates in resource-constrained settings is sparse. We attempted to determine the prevalence of SNJ, described using clinical outcome markers, in all World Health Organization (WHO) regions in the world. Data were sourced from Ovid Medline, Ovid Embase, Cochrane Library, African Journals Online, and Global Index Medicus. Hospital-based studies, including the total number of neonatal admissions with at least one clinical outcome marker of SNJ, defined as acute bilirubin encephalopathy (ABE), exchange blood transfusions (EBT), jaundice-related death, or abnormal brainstem audio-evoked response (aBAER), were independently reviewed for inclusion in this meta-analysis. Of 84 articles, 64 (76.19%) were from low- and lower-middle-income countries (LMICs), and 14.26% of the represented neonates with jaundice in these studies had SNJ. The prevelance of SNJ among all admitted neonates varied across WHO regions, ranging from 0.73 to 3.34%. Among all neonatal admissions, SNJ clinical outcome markers for EBT ranged from 0.74 to 3.81%, with the highest percentage observed in the African and South-East Asian regions; ABE ranged from 0.16 to 2.75%, with the highest percentages observed in the African and Eastern Mediterranean regions; and jaundice-related deaths ranged from 0 to 1.49%, with the highest percentage observed in the African and Eastern Mediterranean regions. Among the cohort of neonates with jaundice, the prevalence of SNJ ranged from 8.31 to 31.49%, with the highest percentage observed in the African region; EBT ranged from 9.76 to 28.97%, with the highest percentages reported for the African region; ABE was highest in the Eastern Mediterranean (22.73%) and African regions (14.51%). Jaundice-related deaths were 13.02%, 7.52%, 2.01% and 0.07%, respectively, in the Eastern Mediterranean, African, South-East Asian and European regions, with none reported in the Americas. aBAER numbers were too small, and the Western Pacific region was represented by only one study, limiting the ability to make regional comparisons. The global burden of SNJ in hospitalized neonates remains high, causing substantial, preventable morbidity and mortality especially in LMICs.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.035 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".