Ocular involvement in newly diagnosed pediatric leukemia: A systematic review and meta‐analysis
Bibliographic record
Abstract
ABSTRACT Importance Ocular involvement in pediatric leukemia is often under‐recognized, especially in asymptomatic cases. Prevalence estimates of childhood leukemic ophthalmopathy range from 0.32% to 71%, depending on the study design and population. Objective To determine the prevalence and describe the nature of ocular involvement in newly diagnosed pediatric leukemia through systematic review and meta‐analysis. Methods A comprehensive search of MEDLINE, Embase, Cochrane, and Web of Science databases was conducted up to July 2024. Studies reporting on ocular involvement at diagnosis in children aged 18 years or younger with leukemia were included. Cases of relapsed disease were excluded as were those receiving concurrent treatment. A random effects meta‐analysis using an inverse‐variance restricted maximum likelihood approach was performed for prevalence estimates. Results Fourteen studies involving 2989 pediatric leukemia patients were included. The overall pooled prevalence of ocular involvement at diagnosis was 20.32% (95%CI = 9.88%–33.08%). The prevalence of asymptomatic ocular involvement was higher at 23.90% (95%CI = 10.27%–40.63%) compared to 14.75% (95%CI = 0.00%–45.31%) for symptomatic involvement alone. High heterogeneity (I2 = 97.7%) was observed across studies, likely driven by differences in study design and populations. Interpretation Ocular involvement in newly diagnosed pediatric leukemia is more common than previously understood, particularly for asymptomatic cases. Current practices of selective ophthalmic assessment may miss a number of early‐stage ocular manifestations, emphasizing the need for all newly diagnosed patients to be screened for ophthalmic involvement at the time of diagnosis.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.028 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".