A Rescue Technique for Vertical Diplopia After Toric Lens Use in Patients With Keratoconus
Bibliographic record
Abstract
PURPOSE: To describe a patient with irregular astigmatism who developed highly symptomatic monocular vertical diplopia after receiving a toric intraocular lens (IOL) at the time of surgery. METHODS: Data collected for this case report included pre-operative and postoperative uncorrected distance visual acuity (UDVA), corrected distance visual acuity, refraction, mean keratometry, topographic astigmatism, and pachymetry. RESULTS: The patient's vertical diplopia was corrected safely. UDVA improved from 20/40 to 20/20, refraction improved from −0.50 −1.00 × 155° to −1.00 −0.87 × 160°, and mean keratometry changed from 45.18 to 45.08 diopters (D). Topographic astigmatism changed from −1.02 D @ 165° to −1.30 D @ 170°, and central pachymetry decreased from 506 to 491 µm. CONCLUSIONS: Monocular vertical diplopia after toric lens implantation in a patient with keratoconus may be corrected with lens exchange for a non-toric lens and subsequent SmartSurfACE photorefractive keratectomy (SCHWIND eyetech-solutions). [ Journal of Refractive Surgery Case Reports. 2022;2(3):e60–e62.]
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".