Bibliographic record
Abstract
<div> Purpose To evaluate the corneal biomechanical properties of phacoemulsification in the treatment of cataract patients. Methods Pertinent studies were searched in PubMed, EMBASE, Web of Science and clinicaltrials.gov., as of November 05, 2024. The reference lists of related published reviews were included as well. This meta-analysis was performed with Stata Software and Review Manager, we used mean difference (MD) to evaluate the statistical consequence, using I<sup>2</sup> statistic to assess the heterogeneity. Subgroup analysis were performed under the occurrences of high heterogeneity. We used eleven items to describe the characteristics of included studies, publication bias was performed with Egger’s test. The quality assessment were evaluated with 3 items by Newcastle-Ottawa Scale (NOS) items. Results Thirteen eligible studies were identified for data synthesis and assessment. According to the result of meta-analysis, the central corneal thickness(CCT) (MD = 10.50, 95% CI: [5.01, 15.98]; P<0.05) and intraocular pressure(IOPg)(MD = -0.73, 95% CI: [-1.26, -0.19]; P<0.05) of cataract patients after phacoemulsification was significantly higher than the control groups. The values of corneal hysteresis(CH) (MD = -0.43, 95% CI: [-0.62, -0.23]; P<0.05) and corneal resistance factor(CRF) (MD = -0.49, 95% CI: [-0.64, -0.33]; P<0.05) after phacoemulsification surgery were statistically lower than the control groups. While the values of IOPcc did not show statistically different (MD = -0.13, 95% CI: [-0.67, 0.41]; P = 0.64). Conclusion Included data analysis indicated that the values of CCT, CH, CRF and IOPg showed statistical change in cataract patients after phacoemulsification surgeries compared with control groups. There is a correlation between corneal biomechanics and phacoemulsification surgeries. </div>
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.255 | 0.003 |
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; both teacher heads agree on what is shown here.
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".