Accuracy of user-adjusted axial length measurements with optical biometry in eyes having combined phacovitrectomy for macular-off rhegmatogenous retinal detachment
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Bibliographic record
Abstract
PURPOSE: To evaluate the accuracy of user-adjusted axial length (AL) measured by optical biometry for intraocular lens (IOL) calculations in eyes having combined phacovitrectomy for macula-off rhegmatogenous retinal detachment (RRD). SETTING: Ophthalmology Department, Calderdale Royal Hospital, Halifax, United Kingdom. DESIGN: Retrospective case series. METHODS: Consecutive eyes having phacovitrectomy for macula-off RRD were evaluated. The ALs were measured using optical biometry with user adjustment to identify a posterior peak corresponding to the eye's AL and ultrasound (US). These were compared with each other and with the postoperative optical biometry and analyzed for accuracy as an indication of the eye's AL. RESULTS: The study comprised 22 eyes of 22 patients. There was no statistically significant difference between the mean AL measurements derived from user-adjusted optical biometry and US AL (P = .964). The user-adjusted optical biometry was not statistically significantly different from the postoperative optical biometry (P = .242). Compared with the postoperative optical biometry, the IOL power was within ±0.5 diopter in 12 (92%) of 13 cases (95% confidence interval [CI], 77.8 to 100.0) for user-adjusted optical biometry and in 10 (77%) of 13 cases (95% CI, 54.0 to 99.8) for US measurements. CONCLUSIONS: User-adjusted optical biometry could be used as an alternative method for measuring AL in macula-off RRD with combined phacovitrectomy. However, optical biometry would require assessment of agreement with US AL in cases in which a posterior peak is not easily identifiable. User-adjusted optical biometry might outperform US AL when calculating IOL power; however, a larger study should be performed to confirm this. FINANCIAL DISCLOSURE: None of the authors has a financial or proprietary interest in any material or method mentioned.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 it