Age-related macular degeneration (AMD) is of increasing concern given the ageing population, and the associated economic and social burdens. Vision-related quality-of-life (QoL) is arguably one of the most important factors in the management of those with AMD. Consequently, there is a clear need for an understanding of the clinical outcomes that influence vision-related QoL in order to inform management strategies. The principle aim of the studies described herein was to determine the factors that predict vision-related QoL in those with AMD, over 1 year. Experimental procedures were undertaken at baseline (n=52 individuals with AMD) and repeated after 1 year (n=32 individuals with AMD). These included: visual acuity, contrast sensitivity, reading speed, microperimetry, optical coherence tomography and fundus photography. A questionnaire interview included assessment of vision-related QoL (Impact of Visual Impairment questionnaire), health status (EQ-5D), level of depressive symptoms (PHQ-9) and well-being (Warwick-Edinburgh Well-Being Scale). At baseline, the optimum multiple regression model accounted for 41% of the variance in vision-related QoL and included Mean Total Deviation or Mean Sensitivity with level of depressive symptoms. After 1 year, the optimum model to predict change in vision-related QoL accounted for 43% of the variance and included baseline contrast sensitivity and change in health status and reading speed. The most clinically useful measures of visual function, in identifying those with a reduced QoL or those at risk of a reduced QoL were contrast sensitivity, microperimetry, and reading speed. These outcomes may allow a better understanding of vision-related QoL if they were adopted in a clinical setting. In conclusion, the studies provide sufficient evidence to encourage a review of the clinical outcome measures most relevant to vision-related QoL.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:738351 |
| Date | January 2017 |
| Creators | Cassels, Nicola |
| Publisher | Cardiff University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://orca.cf.ac.uk/109189/ |
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