Trifocal and extended depth of focus intraocular lenses – comparative analysis
Bibliographic record
Abstract
Aim of the study: Comparative analysis of trifocal and extended depth of focus (EDoF) lenses, taking into account visual acuity (VA) at different distances, contrast sensitivity (CS), defocus curve, spectacle independence, reading speed and the presence of photic phenomena, and assessment of patient satisfaction.Methodology: Review of scientific papers and articles on high technology lenses found in PubMed, American Academy of Ophthalmology, ESCRS databases and own observations.Results: Regarding VA, the studies we analyzed showed significantly better uncorrected (UNVA) and corrected near visual acuity (CNVA) for trifocal than EDoF lenses, while the EDoFs showed slightly better results for uncorrected distance visual acuity (UDVA), uncorrected (UIVA) and corrected intermediated visual acuity (CIVA).CS in most of articles showed no significant differences, only a few presented a slightly better results in EDoF group.Analysis of defocus curve shows that trifocal lenses exhibit better close-range vision acuity compared to EDoF of intraocular lenses (IOLs).Most of authors summarize the patient-assessed incidence and severity of dysphotopsia as low and statistically insignificant in both groups of lenses (range is < 1% to 25%).Spectacle independence for near vision was observed for both types of lenses, but slightly better for trifocal IOLs than EDoF IOLs (87% vs. 79.83%).The differences in reading speed were not statistically significant.Patients' satisfaction was high for both lenses and all of them will choose the same lens again.Conclusion: Visual function results are very good and comparable for both analyzed types of IOLs.However trifocal lenses presented better near vision, but EDoF IOLs had a slightly lower frequency and severity of dysphotopsia.The significant superiority of the EDoF lenses over the trifocals is not proven.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".