Longitudinal Changes of Fixation Stability and Location Within 24 Months in Stargardt Disease: ProgStar Report No. 16
Bibliographic record
Abstract
Objective: Stargardt Disease type 1 (STGD1) is the most common macular dystrophy. The assessment of fixation describes an important dimension of visual function but there is limited data on its progression over time. We present longitudinal changes and investigate its usefulness for clinical trials.Design: International, multicenter, prospective cohort studyParticipants and Main Outcome Measures: A total of 239 individuals with genetically confirmed STGD1 (≥ 1 disease-causing ABCA4 variant). We determined the fixation stability (FS) using the bivariate contour ellipse area (1 SD-BCEA) and fixation location (FL) using the eccentricity of fixation from the fovea during 5 study visits every 6 months.Results: At baseline, 239 patients (105 males, 44 %) and 459 eyes with a median age of 32 years were included. The baseline mean log BCEA was 0.70 ± 1.41 log deg2Tanna P Strauss RW Fujinami K Michaelides M. Stargardt disease: clinical features, molecular genetics, animal models and therapeutic options.Br J Ophthalmol. 2017; 101: 25-30Crossref PubMed Scopus (138) Google Scholar and the mean FL was 6.25 ± 4.40 deg. Although the mean log BCEA did not monotonically increase from visit to visit, the overall yearly increase in log BCEA was 0.124 log deg2Tanna P Strauss RW Fujinami K Michaelides M. Stargardt disease: clinical features, molecular genetics, animal models and therapeutic options.Br J Ophthalmol. 2017; 101: 25-30Crossref PubMed Scopus (138) Google Scholar (95% CI, 0.063-0.185). The rate of change was not different between the two years but increased faster in eyes without flecks outside of the vascular arcades and depended on baseline log BCEA. FL did not change statistically significantly over time.Conclusion and relevance: Fixation parameters are unlikely to be sensitive outcome measures for clinical trials in STGD1 but they may provide useful ancillary information in selected cases to longitudinally describe and understand an eye's visual function.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".