The Effect of Attention on Fixation Stability During Dynamic Fixation Testing in Stargardt Disease
Notice bibliographique
Résumé
•The authors show that fixation stability in Stargardt disease is dependent on attention.•More unstable fixation is associated with higher variability of measurements.•Fixation stability may be associated with specific autofluorescence features.•Eyes with unstable fixation can keep steady fixation for a limited duration.•Drops in fixation stability are associated with eccentric fixation or multiple preferred retinal loci. PurposeSensitive, reproducible visual function biomarkers are necessary to evaluate the efficacy of emerging treatments for Stargardt disease type 1 in clinical trials. We previously demonstrated that fixation stability may serve as a secondary outcome parameter for visual function loss. However, the test duration and protocol have an unknown effect on the assessment of fixation stability. Here, we hypothesize that separate fixation testing with a single target is different from combined fixation testing using the same target with simultaneous perimetry testing.DesignInternational, multicenter, prospective, cross-sectional study.MethodsMicroperimetry data from the international, multicenter, prospective Progression of Atrophy Secondary to Stargardt Disease (ProgStar, NCT01977846) study were analyzed. Patients underwent various types of fixation testing including static testing and dynamic testing, and a duration-corrected dynamic test was generated (30sEpoch).ResultsA total of 437 eyes from 235 patients were included (mean age, 33.8 ± 15.1 years; 55.3% female). The mean 1SD-BCEA (bivariate contour ellipse area), which is the smallest ellipse encompassing 1 standard deviation of all fixation events, was smaller for the static fixation test compared to the 30sEpoch (4.5 ± 6.9 deg2 vs 5.3 ± 7.0 deg2; P = .02) and the number of points within both the 2-degree and 4-degree circles was larger (P < .0001).ConclusionsOur results suggest that differences in static and dynamic assessment of fixation stability are dependent not only on different test durations but also on the testing protocol of a single fixation target vs fixation target plus simultaneous perimetry testing and provide information on the conduct of fixation testing for clinical trials. Sensitive, reproducible visual function biomarkers are necessary to evaluate the efficacy of emerging treatments for Stargardt disease type 1 in clinical trials. We previously demonstrated that fixation stability may serve as a secondary outcome parameter for visual function loss. However, the test duration and protocol have an unknown effect on the assessment of fixation stability. Here, we hypothesize that separate fixation testing with a single target is different from combined fixation testing using the same target with simultaneous perimetry testing. International, multicenter, prospective, cross-sectional study. Microperimetry data from the international, multicenter, prospective Progression of Atrophy Secondary to Stargardt Disease (ProgStar, NCT01977846) study were analyzed. Patients underwent various types of fixation testing including static testing and dynamic testing, and a duration-corrected dynamic test was generated (30sEpoch). A total of 437 eyes from 235 patients were included (mean age, 33.8 ± 15.1 years; 55.3% female). The mean 1SD-BCEA (bivariate contour ellipse area), which is the smallest ellipse encompassing 1 standard deviation of all fixation events, was smaller for the static fixation test compared to the 30sEpoch (4.5 ± 6.9 deg2 vs 5.3 ± 7.0 deg2; P = .02) and the number of points within both the 2-degree and 4-degree circles was larger (P < .0001). Our results suggest that differences in static and dynamic assessment of fixation stability are dependent not only on different test durations but also on the testing protocol of a single fixation target vs fixation target plus simultaneous perimetry testing and provide information on the conduct of fixation testing for clinical trials.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».