Enhancing Postoperative Evaluation of Presbyopia Corrections: Correlation of Visual Curve Indices with Vision-Related Quality of Life

Background/Objectives: The aim of this study was to evaluate the correlation between the visual curve (ViC) and Area of the Curve (AoC) indices and the subjective perception of vision-related quality of life in patients who had undergone pseudophakic presbyopia correction. The central hypothesis was that AoC indices would show stronger correlations with vision-specific quality-of-life measures than single-point visual acuity (VA) assessments. Methods: A total of 100 patients who underwent bilateral pseudophakic presbyopia correction at the University Hospital of Alexandroupolis, Greece, were included in the study. Six months following surgery, visual acuity was assessed at nine distances using the DDART tool. The AoC was calculated using VA data from four, five, six, and nine distances, and further categorized into Near Vision AoC (AoCN) and Distance Vision AoC (AoCD). Participants also completed the NEI-VFQ-25 questionnaire to evaluate their subjective vision-related quality of life. Results: Statistically significant correlations were observed between AoC values and NEI-VFQ-25 total scores (r = 0.668–0.682, p < 0.001), near activity subscale scores (r = 0.656–0.686, p < 0.001), and distance activity subscale scores (r = 0.733–0.758, p < 0.001). In all analyses, the AoC indices derived from ViC demonstrated stronger correlations with quality-of-life scores than those observed with AoC-derived DCT and single VA measurements, even when the AoC was computed using only four measurement points. Conclusions: The AoC metric is a superior indicator of vision-specific quality of life compared to isolated VA measurements. AoC effectively captures the multifaceted nature of functional vision following presbyopia correction

Development and Validation of the First Smart TV-Based Visual Acuity Test: A Prospective Study

(1) Background: While smartphones are among the primary devices used in telemedical applications, smart TV healthcare apps are not prevalent despite smart TVs’ penetrance in home settings. The present study’s objective was to develop and validate the first smart TV-based visual acuity (VA) test (Democritus Digital Visual Acuity Test (DDiVAT)) that allows a reliable VA self-assessment. (2) Methods: This is a prospective validation study. DDiVAT introduces several advanced features for reliable VA self-testing; among them: automatic calibration, voice recognition, voice guidance, automatic calculation of VA indexes, and a smart TV-based messaging system. Normal and low vision participants were included in the validation. DDiVAT VA results (VADDiVAT) were compared against the ones from: (a) the gold-standard conventional ETDRS (VAETDRS), and, (b) an independent ophthalmologist who monitored the self-examination testing (VARES). Comparisons were performed by noninferiority test (set at 2.5-letters) and intraclass correlation coefficients (ICCs). DDiVAT’s test-retest reliability was assessed within a 15-day time-window. (3) Results: A total of 300 participants (185 and 115 with normal and low vision, respectively) responded to ETDRS and DDiVAT. Mean difference in letters was −0.05 for VAETDRS–VARES, 0.62 for VARES–VADDiVAT, and 0.67 for VAETDRS–VADDiVAT, significantly lower than the 2.5 letter noninferiority margin. ICCs indicated an excellent level of agreement, collectively and for each group (0.922-0.996). All displayed letters in DDiVAT presented a similar difficulty. The overall accuracy of the voice recognition service was 96.01%. ICC for VADDiVAT test-retest was 0.957. (4) Conclusions: The proposed DDiVAT presented non-significant VA differences with the ETDRS, suggesting that it can be used for accurate VA self-assessment in telemedical settings, both for normal and low-vision patients