Glaucomatous Visual Field Progression with Frequency-Doubling Technology and Standard Automated Perimetry in a Longitudinal Prospective Study
Bibliographic record
Abstract
PURPOSE: To compare frequency-doubling technology (FDT) perimetry with standard automated perimetry (SAP) for detecting glaucomatous visual field progression in a longitudinal prospective study. METHODS: One eye of patients with open-angle glaucoma was tested every 6 months with both FDT and SAP. A minimum of 6 examinations with each perimetric technique was required for inclusion. Visual field progression was determined by two methods: glaucoma change probability (GCP) analysis and linear regression analysis (LRA). For GCP, several criteria for progression were used. The number of locations required to classify progression with FDT compared with SAP, respectively, was 1:2 (least conservative), 1:3, 2:3, 2:4, 2:6, 2:7, 3:6, 3:7, and 3:10 (most conservative). The number of consecutive examinations required to confirm progression was 2-of-3, 2-of-2, and 3-of-3. For LRA, the progression criterion was any significant decline in mean threshold sensitivity over time in each of the following three visual field subdivisions: (1) all test locations, (2) locations in the central 10 degrees and the superior and inferior hemifields, and (3) locations in each quadrant. Using these criteria, the proportion of patients classified as showing progression with each perimetric technique was calculated and, in the case of progression with both, the differences in time to progression were determined. RESULTS: Sixty-five patients were followed for a median of 3.5 years (median number of examinations, 9). For the least conservative GCP criterion, 32 (49%) patients were found to have progressing visual fields with FDT and 32 (49%) patients with SAP. Only 16 (25%) patients showed progression with both methods, and in most of those patients, FDT identified progression before SAP (median, 12 months earlier). The majority of GCP progression criteria (15/27), classified more patients as showing progression with FDT than with SAP. Contrary to this, more patients showed progression with SAP than FDT, when analysed with LRA; e.g., using quadrant LRA 20 (31%) patients showed progression with FDT, 23 (35%) with SAP, and only 10 (15%) with both. CONCLUSIONS: FDT perimetry detected glaucomatous visual field progression. However, the proportion of patients who showed progression with both FDT and SAP was small, possibly indicating that the two techniques identify different subgroups of patients. Using GCP, more patients showed progression with FDT than with SAP, yet the opposite occurred using LRA. As there is no independent qualifier of progression, FDT and SAP progression rates vary depending on the method of analysis and the criterion used.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".