The Validity of Screening For Open-angle Glaucoma in High-risk Populations With Single-test Screening Mode Frequency Doubling Technology Perimetry (FDT)
Bibliographic record
Abstract
PURPOSE: To evaluate whether a single frequency doubling perimetry (FDT) test is a valid screening tool to detect open-angle glaucoma (OAG) in high-risk populations. PATIENTS AND METHODS: All participants underwent frequency doubling Technology perimetry (FDT C-20-5 algorithm, Carl Zeiss Meditec Inc, Dublin, CA) and complete ophthalmic examination. FDT printouts were classified according to Iwasaki and Patel protocols. Gold-standard was clinical diagnosis of glaucomatous optic nerve damage. MAIN OUTCOME MEASURES: Sensitivity, specificity, positive predictive value, negative predictive value, positive, and negative likelihood ratios of a single-test screening FDT. RESULTS: Data of 445 right eyes and 408 left eyes of participants were analyzed. On the basis of clinical diagnosis, 19 right eyes (4.3%) and 20 left eyes (4.9%) had glaucoma. Depending on the gold standard used, the range of sensitivity was between 40.7% and 78.9%, 66% and 70% for specificity, 7.7% and 25.2% for positive predictive value, 82.3% and 98.6% for negative predictive value, 1.25 and 2.37 for positive likelihood ratio, and 0.32 and 0.87 for negative likelihood ratio. The κ coefficient of agreement between the FDT classifications as described by Iwasaki et al and Patel et al was 0.936 in right eyes and 0.935 in left eyes. CONCLUSIONS: The sensitivity and specificity of a single reliable screening FDT test were low. Thus, a single screening FDT test in even a high-risk population has poor validity and steps should be taken to better define the target population before testing, and enhance the FDT screening strategy.
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How this classification was reachedexpand
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".