Introduction: Unequal retinal image size (RIS) or aniseikonia is usually related with anisometropia. Higher differences of RIS may manifest symptoms such as dizziness, headache or disorientation. In worst case might cause suppression that leads to amblyopia. Current study aims to evaluate the consistency of aniseikonia measurement in Smart Optometry smartphone application among myopic, hyperopic, and astigmatic simulated anisometropia and real anisometropia groups. Methods: Fifteen real anisometropes (refractive error; -0.50 until -6.00 diopters; D) and fifteen emmetropes (refractive error: -0.25 until +0.50D) were recruited. Real anisometropes wore their habitual spectacle correction while each emmetropes were fitted using soft contact lenses of +4.00DS, -4.00DS and -4.00DC with base curve 8.6 and total diameter 14.2mm in random order to mimic myopic-, hyperopic- and astigmatic-anisometropia before testing. Participants with any ocular disease and binocular vision problem were excluded. The consistency of aniseikonia measurement was determined in two visits, separated by at least 24-hour interval. Three repetitive measurements were taken in each visit. Results: Independent t-test and paired t-test showed that real and simulated anisometropia gave insignificant aniseikonia percentage, p>0.05. ICC findings revealed moderate-to-good agreement for all simulated and real groups. Bland Altman analysis between two visits exhibited good agreement among all simulated group; myopic (mean difference 0.2047; 95%CI:-1.1386-1.549), hyperopic (mean difference 0.2200; 95%CI:-0.9286-1.3686) and astigmatic (mean difference 0.2533; 95%CI:-0.7114-1.2180). Real anisometropes demonstrated good agreement with bias value of 0.2247(95%CI:-0.9162-1.3656) using Bland Altman plot. Conclusion: Smart Optometry application provides consistent measurement of aniseikonia regardless any types of anisometropia.

Introduction: Short-term fasting may influence intraocular pressure (IOP) due to alteration of fluid (total body water; TBW, and water intake) and fat (total body fat; TBF). This study aimed: i) to compare IOP values within and between, fasting and non-fasting periods; and ii) to assess the association between IOP and, TBW and TBF. Methods: Thirty healthy participants aged 21.8±1.1 years were assessed on two different periods (fasting vs. non-fasting). During each period, the IOP, TBW and TBF values were assessed for four times (morning, afternoon, evening, late-evening). The IOP was measured using AccuPen® tonopen, while TBW and TBF were assessed by using a Tanita body composition analyser. Results: During fasting, the IOP value in the afternoon (14.53±2.33 mmHg) was significantly higher than in the evening (12.43±2.73 mmHg, p=0.009) and late-evening (12.60±2.44 mmHg, p=0.003). No significant difference in IOP was observed during non-fasting period. The mean of IOP in the evening was significantly lower during fasting compared to non-fasting (12.43±2.73 mmHg vs 13.75±2.53 mmHg, p=0.044). The IOP and TBW were negatively correlated (r=-0.268; p=0.011) during non-fasting and showed no association during fasting period. There was no significant correlation between IOP and TBF during both fasting and non-fasting periods. Conclusion: IOP reduction during short-term fasting, together with the no association with TBF and TBW suggested that IOP is an independent factor that reduces during fasting in healthy population.