A clinical assessment of visual performance of combining the TECNIS<sup>&reg;</sup>&nbsp;Symfony&nbsp;Extended Range of Vision IOL (ZXR00) with the +3.25 D TECNIS Multifocal 1-piece IOL (ZLB00) in subjects undergoing bilateral cataract extraction
Bibliographic record
Abstract
PURPOSE: Symfony intraocular lens (IOL) with a TECNIS Multifocal (MF) low-add IOL (+3.25) to enable a patient to be less dependent on corrective lenses. SETTING: Clinic in Canada. DESIGN: Single-center, prospective, open-label. MATERIALS AND METHODS: Fifty patients were enrolled for bilateral surgery. Patients were implanted with TECNIS Symfony Extended Range of Focus lens in the dominant eye, and TECNIS low-add +3.25 MF IOL in the non-dominant eye. Patients were ≥18 years of age and had best-corrected visual acuity >20/30 in both eyes, pupil size >3.5 mm, and <1.5 D of corneal astigmatism. Patients were evaluated preoperatively, operatively, and postoperatively on Day 1, Day 7, Month 1, and Month 3. Postoperative evaluations at Month 3 were completed by 32 of 50 patients enrolled, and included distance, intermediate and near visual acuity (VA), and subjective outcomes. RESULTS: Three months postoperatively, binocular results without correction revealed 97% (29/30) of patients had distance VA of 20/20 or better, 97% (29/30) had intermediate VA of 20/25 or better, and 94% (28/30) had near VA of 20/25 or better. At Month 3, the majority of patients reported "none" for visual symptoms of glare (30/30, 100%), halo (29/30, 96.6%), starbursts (29/30), or other - blur (30/30, 100%). CONCLUSION: Three months postoperatively, the combination of the increased depth of focus of the TECNIS Symfony IOL with a TECNIS MF low-add (+3.25) IOL may provide excellent uncorrected VA at near, intermediate, and far distances with minimal ocular symptoms.
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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 | 0.001 | 0.002 |
| 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) | 0.002 | 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".