Comparison of Two-Year Clinical and Patient-Reported Outcome Measures Between Acrysof IQ and Clareon PanOptix Multifocal Intraocular Lenses
Bibliographic record
Abstract
PURPOSE: To compare the 2-year clinical and patient-reported outcome measures of PanOptix multifocal intraocular lenses (MIOLs) based on the lens material. DESIGN: Retrospective matched cohort study. METHODS: A comparison between patients who had undergone bilateral operation with Acrysof IQ versus Clareon PanOptix MIOLs was done by 1-to-1 matching of age, axial length, mean keratometry, and corneal astigmatism. A total of 122 eyes of 122 patients in each group were studied. Main outcome measures analyzed included uncorrected near visual acuity (UNVA) and uncorrected distance visual acuity (UDVA), prediction error in spherical equivalent and postoperative refraction stability, glistening, subsurface nano-glistening (SSNG), Nd:YAG laser posterior capsulotomy rates, the area under the log contrast sensitivity function (AULCSF) under photopic and mesopic conditions, Strehl ratio, and area ratio. Patient-reported outcome measures such as dysphotopsia and modified spectacle-independent Visual Function Index (VF)-14 questionnaire scores were collected at 2 years. RESULTS: Throughout the study period, comparable UNVA, UDVA, and refractive stability were observed between the groups, except for better UNVA among eyes with Clareon than among eyes with Acrysof IQ at 2 years (0.00 ± 0.02 vs 0.02 ± 0.04, P < .001). Clareon implantation resulted in better photopic (1.47 ± 0.19 vs 1.38 ± 0.21 logCWeber units; P < .001), and mesopic (1.16 ± 0.22 vs 1.06 ± 0.19 logCWeber units; P < .001) AULCSF, lower prevalence of glistening (0% vs 88%, P < .001) and SSNG (0% vs 26%, P < .001) and cumulative Nd:YAG laser capsulotomy rates (hazard ratio = 0.632; 95% CI = 0.482-0.830, P < .001) when compared to those with Acrysof IQ. No differences were observed in the incidence of clinically significant glare or halos, but the incidence of starburst (5% vs 16%, P = .002) tended to favor Clareon over Acrysof IQ. Modified VF-14 questionnaire scores were greater for Clareon than Acrysof IQ (93.4 ± 10.3 vs 90.4 ± 13.6 points, P < 0.001). A multivariable regression analysis showed that patient age (beta = -0.394, P < .001; beta = -0.352, P < .001) and glistening grade (beta = -0.163, P = .010; beta = -0.232, P < .001) remained significantly associated with the photopic and mesopic AULCSF, respectively. Furthermore, higher glistening grade (r = -0.144, P = .003; beta = -1.771, P = .001 when age and sex adjusted) were associated with worse modified VF-14 questionnaire scores. CONCLUSIONS: Clareon PanOptix outperformed Acrysof IQ PanOptix in visual quality and spectacle-independent visual function, potentially resulting from a lower prevalence of glistening.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".