Three-Dimensional Heads-Up vs. Standard Operating Microscope for Cataract Surgery: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: The surgical time duration, the postoperative best-corrected visual acuity (BCVA), and the incidence rate of intraoperative complications, alongside the vision and posturing parameters, were estimated by systematic review and meta-analysis to compare the three-dimensional (3D) heads-up visualization system (HUVS) and standard operating microscope (SOM) in cataract surgery. METHODS: A literature search was conducted using PubMed, Embase, and Scopus on 26 June 2022. The weighted mean difference (WMD) was used to present postoperative BCVA and the mean surgical time duration, whereas the risk ratio (RR) was used to present the incidence rate of intraoperative complications. Publication bias was evaluated with Egger's test. The Cochrane Collaboration's Tool for randomized clinical trials, the methodological index for non-randomized, and the Newcastle-Ottawa Scale were used to assess the risk of bias. The research has been registered with the PROSPERO database (identifier, CRD42022339186). RESULTS: In the meta-analysis of five studies with 1021 participants, the pooled weighted mean difference (WMD) of the postoperative BCVA showed no significant difference between patients who underwent HUVS versus SOM cataract surgery (WMD = -0.01, 95% confidence interval (CI): -0.01 -0.02). In the meta-analysis of nine studies with 5505 participants, the pooled WMD of mean surgical time duration revealed no significant difference between patients who underwent HUVS versus SOM cataract surgery (WMD = 0.17, 95% CI: -0.43-0.76). In the meta-analysis of nine studies with 8609 participants, the pooled risk RR associated with intraoperative complications was 1.00 (95% CI, 1.00-1.01). CONCLUSIONS: 3D HUVS and SOM provide comparable surgical time duration, postoperative BCVA, and incidence rate of intraoperative complications.
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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 | 0.016 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.048 |
| Bibliometrics | 0.006 | 0.007 |
| 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) | 0.003 | 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".