Anna Sulley1, Kathrine Osborn Lorenz2, James S Wolffsohn3, Graeme Young4. 1. Johnson & Johnson Vision Care Companies, Wokingham, UK. Electronic address: asulley1@its.jnj.com. 2. Johnson & Johnson Vision Care, Inc, Jacksonville, FL, USA. 3. Aston University, Birmingham, UK. 4. Aston University, Birmingham, UK; Visioncare Research Ltd, Farnham, UK.
Abstract
PUROSE: To calculate theoretical fitting success rates (SR) for a range of typical soft contact lens (SCL) designs using a mathematical model. METHOD: A spreadsheet mathematical model was used to calculate fitting SR for various SCL designs. Designs were evaluated using ocular topography data from 163 subjects. The model calculated SR based on acceptable edge strain (within range 0-6%) and horizontal diameter overlap (range 0.2-1.2mm). Where lenses had multiple base curves (BCs), eyes unsuccessful with the steeper BC were tested with the flatter BC and aggregate SR calculated. Calculations were based on typical, current, hydrogel and silicone hydrogel SCLs and allowed for appropriate on-eye shrinkage (1.0-2.3%). Theoretical results were compared with those from actual clinical trials. RESULTS: Theoretical success rates for one-BC lenses ranged from 60.7% (95% CI 7.2%) to 90.2% (95% CI 3.7%). With two-BC designs, most combinations showed a SR increase with a second BC (84.0%-90.2%). However, one of the two-BC combinations showed only negligible increase with a second BC (72.4%-73.0%). For designs with lower SR, the greatest contributor to failure was inadequate lens diameter. For a given design, differences in shrinkage (i.e. on-eye bulk dehydration) had a significant effect on success rate. In comparison with historical clinical data, there was a positive correlation between small lens fitting prevalence and discomfort reports (r=+0.95, P=<0.001) with a poor correlation between theoretical and actual tight/loose fittings. CONCLUSIONS: Mathematical modelling is a useful method for testing SCL design combinations. The results suggest that judicious choice of additional fittings can expand the range of fitting success.
PUROSE: To calculate theoretical fitting success rates (SR) for a range of typical soft contact lens (SCL) designs using a mathematical model. METHOD: A spreadsheet mathematical model was used to calculate fitting SR for various SCL designs. Designs were evaluated using ocular topography data from 163 subjects. The model calculated SR based on acceptable edge strain (within range 0-6%) and horizontal diameter overlap (range 0.2-1.2mm). Where lenses had multiple base curves (BCs), eyes unsuccessful with the steeper BC were tested with the flatter BC and aggregate SR calculated. Calculations were based on typical, current, hydrogel and silicone hydrogel SCLs and allowed for appropriate on-eye shrinkage (1.0-2.3%). Theoretical results were compared with those from actual clinical trials. RESULTS: Theoretical success rates for one-BC lenses ranged from 60.7% (95% CI 7.2%) to 90.2% (95% CI 3.7%). With two-BC designs, most combinations showed a SR increase with a second BC (84.0%-90.2%). However, one of the two-BC combinations showed only negligible increase with a second BC (72.4%-73.0%). For designs with lower SR, the greatest contributor to failure was inadequate lens diameter. For a given design, differences in shrinkage (i.e. on-eye bulk dehydration) had a significant effect on success rate. In comparison with historical clinical data, there was a positive correlation between small lens fitting prevalence and discomfort reports (r=+0.95, P=<0.001) with a poor correlation between theoretical and actual tight/loose fittings. CONCLUSIONS: Mathematical modelling is a useful method for testing SCL design combinations. The results suggest that judicious choice of additional fittings can expand the range of fitting success.
Authors: Tamsin Doll; Joshua Moore; Ahmad H Shihab; Bernardo T Lopes; Ashkan Eliasy; Osama Maklad; Richard Wu; Lynn White; Steve Jones; Ahmed Elsheikh; Ahmed Abass Journal: PLoS One Date: 2020-11-25 Impact factor: 3.240