Meta-analysis of clinical efficacy of intraocular lens incarceration in the treatment of pediatric cataract
Bibliographic record
Abstract
AIM:To systematically compare and evaluate the clinical efficacy of intraocular lens(IOL)incarceration and non-incarceration in pediatric cataract.METHODS: Literatures were searched from domestic and foreign databases such as PubMed, Embase, Cochrane Library, Wanfang, and CNKI, and the paper editions of relevant journals were consulted as well. The retrieval period of literature was from January 2000 to January 2021. The screened literatures were evaluated and extracted by two experienced researchers. After performing the evaluation guidelines of Cochrane collaboration and the Newcastle-Ottawa Scale(NOS), the Rev Man 5.4 software was applicated to complete the Meta-analysis.RESULTS:Seven references(328 eyes)were involved in this analysis. The results of the Meta-analysis showed that the two groups had statistically significant differences in best corrected visual acuity(BCVA)>0.5 eyes(RR=2.00, 95%CI: 1.18-3.37, P=0.01), IOL shift(RR=0.28, 95%CI: 0.17-0.46, P<0.00001)and mild or above opacification of the visual axis(RR=0.35, 95%CI: 0.19-0.65, P=0.0007)after surgery. However, there was no significant difference in the occurrence of posterior synechia(RR=0.67, 95%CI: 0.10-4.33, P=0.67)and very mild opacification of the visual axis(RR=1.05, 95%CI: 0.64-1.73, P=0.84).CONCLUSION:IOL incarceration in the treatment of pediatric cataract can significantly improve postoperative BCVA, reduce occurrence of IOL shift and prevent mild or above opacification of the visual axis, which has more advantages in overall clinical efficacy. But more high quality prospective studies should be still required for further analysis.
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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 | 0.017 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.049 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".