Comparison of Toric Intraocular Lens Calculations Between the IOLMaster 700 and Pentacam AXL
Bibliographic record
Abstract
Abstract Purpose: To compare toric IOL suggestions for power, toric, and IOL alignment between the IOLMaster 700 and Pentacam AXL. Methods: This single-center retrospective chart review analyzed the charts of 62 patients (n=93 eyes) who underwent cataract surgery with a toric IOL between January and April 2022. For all patients, preoperative biometry was measured using both the IOLMaster 700 and Pentacam AXL, followed by IOL calculations performed on the Barrett Toric Online Calculator. The suggested IOL power and toric were defined as spherical equivalent power and toric power closest to plano and minimal residual astigmatism, respectively. Surgeons used lens suggestions as per IOLMaster 700 measurements, with Pentacam AXL being used as a confirmatory test. Patients with a history of laser refractive surgery, corneal disease, or in whom cataract density precluded measurements with either device were excluded. The outcome measures compared between devices were power, toric, and alignment suggestions. Results: Power suggestions were within ± 0.5D in 94% of the eyes, and were identical in 54%. Toric suggestions differed by ±1 toric step in 100% of eyes, and were identical in 67%. IOL alignment suggestions, however, were slightly more variable and differed by ± 5º in 38-55% of eyes. At one-month post-op, the mean absolute error in spherical equivalent was nearly identical between devices. Conclusion: Our results show that IOLMaster 700 and Pentacam AXL show generally similar TORIC calculations with respect to spherical equivalent and suggested toric power. Small differences in alignment axis are frequent between the two devices and warrant further study.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".