Amsler grid test for detection of advanced glaucoma in Ethiopia
Bibliographic record
Abstract
OBJECTIVE: This study was done to determine the validity of amsler grid test black on white (BOW), as well as white on black (WOB) for identifying central visual field (VF) defects in patients with advanced glaucoma. DESIGN: Prospective study. PARTICIPANTS: We prospectively included 100 consecutive eyes of 88 adult patients with advanced glaucoma and 100 eyes of 100 normal individuals. We used a lottery method to choose the side of the eye for the control groups. METHODS: All participants had reliable Humphrey 10-2 Swedish Interactive Threshold Algorithm (SITA) standard VF. Both the BOW and WOB amsler grid tests were done for each group. Sensitivity, specificity, and positive and negative predictive values of the amsler grid scotoma area were calculated with the 10-2 VF as the reference standard. RESULTS: The mean ± standard deviation (SD) of age and the 10-2 VF mean deviation (MD) of advanced glaucoma eyes were 59.8 ± 11.8 (range 34-84) years and -19.94 ± 9.8(range -34.98--0.52) respectively. Among 108 eyes with normal 10-2 VF test, 103 had a normal BOW amsler grid test and 5 had an abnormal BOW test. Among 92 eyes with an abnormal 10-2 VF test, 74 had an abnormal and 18 had normal BOW amsler grid test. Sensitivity, specificity, and positive and negative predictive values of the BOW amsler grid test were 80.4%, 95.4%, 93% and 85.1% respectively whereas that of the WOB amsler grid test were 71.7%, 95.4%, 93% and 72.8% respectively. CONCLUSION: The sensitivity and specificity of both BOW and WOB amsler grid tests were high in detecting VF defects in advanced glaucoma.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".