Refractive changes and visual quality in patients with corneal edema after cataract surgery.

BACKGROUND: To assess visual quality and stabilization of refractive changes in corneal edema patients after cataract surgery, using visual acuity (VA) and contrast sensitivity measurements. METHODS: Sixty-one eyes were analysed, twenty-three with and thirty-eight without corneal edema. Uncorrected and corrected distance VA (UDVA and CDVA) were determined with an EDTRS chart, the contrast sensitivity function (CSF) under photopic and mesopic illumination conditions with a CVS-1000e chart, clinical refraction, and corneal topography. Measurements were taken preoperatively, 1-2 days, 1 and 3-months after surgery. Clinical refraction was converted to vector notation (M, J0, J45) and SPSS v26.0 was used for data analysis. RESULTS: An improvement of VA was observed through the postoperative period; changes between visits were significant for CDVA in both groups and for UDVA in the edema sample. Significant astigmatic changes (J0,J45) between visits were not observed, but M values showed a hyperopic tendency in the edema group and a myopic shift in the control group that did not change between visits, with statistically significant differences between groups. Controls had significantly better contrast sensitivity at high spatial frequencies. Under mesopic conditions, global contrast sensitivity losses were observed in the edema group, which improved between visits in the middle frequency range. CONCLUSION: Corneal edema patients had a significant reduction of CDVA, and frequency-selective sensitivity losses that evidence a visual quality loss. Clinical refraction may improve visual quality, but in edema patients these losses are related to corneal changes, which did not change at three months after surgery.

Blue-yellow deficiencies in young moderate smokers

Purpose: To evaluate whether tobacco affects color vision in young moderate smokers.MethodsChromatic mechanisms of 13 moderate smokers (10–20 cigarettes/day and at least 5 years smoking) and 17 non-smokers in the 18–35 age range were assessed with the Farnsworth-Munsell 100-hue (FM100h) test and short wavelength automated perimetry (SWAP).ResultsFM100h Total Error Scores (TES) were higher for smokers, and although differences were not significant (p = 0.14), a linear model with principal component analysis was able to explain 95% of the variance in TES and red-green partial error scores, though not in blue-yellow partial error scores (p = 0.07), using the number of years as smokers and the number of cigarettes/day as predictors. SWAP sensitivity values were globally worse (p = 0.002) for smokers (25.7 + 6.2 dB) than for non-smokers (26.7 + 6.2 dB). In the upper visual hemifield sensitivity, total deviation and pattern deviation values were worse for smokers (p < 0.001). Differences in mean defect and pattern standard deviation were not significant (p > 0.05 in both cases). The number of out-of-limits points in the total difference and pattern difference map were significantly larger for smokers. After correcting for multiple comparisons, only the differences in the upper visual hemifield were significant.ConclusionsThis pilot study suggests that even young moderate smokers show small sensitivity loss in the blue-yellow mechanism, it is statistically significant, restricted to the upper visual hemifield. This corresponds to a retinal region where literature reports a lower density of retinal ganglion cells and where, therefore, the chromatic mechanisms would be more fragile. (AU)

Blue-yellow deficiencies in young moderate smokers.

PURPOSE: To evaluate whether tobacco affects color vision in young moderate smokers. METHODS: Chromatic mechanisms of 13 moderate smokers (10-20 cigarettes/day and at least 5 years smoking) and 17 non-smokers in the 18-35 age range were assessed with the Farnsworth-Munsell 100-hue (FM100h) test and short wavelength automated perimetry (SWAP). RESULTS: FM100h Total Error Scores (TES) were higher for smokers, and although differences were not significant (p = 0.14), a linear model with principal component analysis was able to explain 95% of the variance in TES and red-green partial error scores, though not in blue-yellow partial error scores (p = 0.07), using the number of years as smokers and the number of cigarettes/day as predictors. SWAP sensitivity values were globally worse (p = 0.002) for smokers (25.7 + 6.2 dB) than for non-smokers (26.7 + 6.2 dB). In the upper visual hemifield sensitivity, total deviation and pattern deviation values were worse for smokers (p < 0.001). Differences in mean defect and pattern standard deviation were not significant (p > 0.05 in both cases). The number of out-of-limits points in the total difference and pattern difference map were significantly larger for smokers. After correcting for multiple comparisons, only the differences in the upper visual hemifield were significant. CONCLUSIONS: This pilot study suggests that even young moderate smokers show small sensitivity loss in the blue-yellow mechanism, it is statistically significant, restricted to the upper visual hemifield. This corresponds to a retinal region where literature reports a lower density of retinal ganglion cells and where, therefore, the chromatic mechanisms would be more fragile.