Comparison of Worth Four Dots (W4D) and Bagolini Striated Lenses in adult suppression detection
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Suppression is an adaptive response in which visual information from one eye is inhibited to prevent visual conflict. This phenomenon is commonly observed in individuals with strabismus, anisometropia, or amblyopia. Clinically detecting suppression is essential for assessing binocular vision and conducting visual training. The Worth Four Dots (W4D) and Bagolini Striated Lenses (BAG) are widely used tools. However, empirical comparisons of their screening performance in large-scale clinical settings remain limited. METHODS: This single-center, prospective, cross-sectional study recruited participants aged ≥ 18 at the Yuan Dong Optometry Clinic in Chiayi, Taiwan. All participants underwent distance suppression measurements using the W4D and BAG following subjective refraction. The W4D was consistently conducted prior to the BAG. The agreement between the two tests was analyzed using cross-tabulation, Cohen’s kappa coefficient, and McNemar’s test. RESULTS: A total of 2280 participants were included in this study. The W4D identified suppression in 35 participants, while the BAG identified 26 participants. Among these, 22 participants were positive on both tests; 13 were positive only on the W4D, and 4 were positive only on the BAG. Cohen’s kappa coefficient was 0.72, indicating a good level of agreement between the two tests. However, McNemar’s test revealed a significant difference between the two tests (p = 0.049), with the W4D detecting more positive participants. CONCLUSION: This study demonstrated a significant difference in suppression detection between the W4D and BAG. In the absence of a gold standard, the W4D is recommended as a first-line screening tool due to its higher detection rate. Further confirmatory testing should be conducted when suppression is indicated.
Source: BMC Ophthalmology
Authors: Chieh-Yueh Lin, Guan-Cheng Lin, Kun-Shiang Chen, Li-Te Yin
Institution: Chung Hwa University of Medical Technology
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,990
OpenAlex ID: W4415156235
