2 resultados para Metaphors on Vision

em Universidade Complutense de Madrid


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The article addresses the analysis of time images furnished by a qualitative research made in Spain on the relations of working time and family/personal time. The analysis focuses on three widespread time metaphors used in day-to-day speeches by social agents. The first one is the metaphor of time as resource for action. Its value is equally economical, moral and political. Used in different context of action, it may mean something that can be either invested, donated generously to others, appropriated for caring for oneself, or spent without purpose with others. The second metaphor represents time as an external environment to which action must adapt. This metaphor shows many variants that represent time as a dynamic/static, repetitive/innovative, ordered/chaotic environment. In this external environment, the agents must resolve the problems of temporal embeddedness, hierarchy and synchronization of their actions. The third metaphor shows time as a horizon of action intentionality where the agents try to construct the meaning of their action and identity. Within this horizon the construction of a significant narrative connecting past and present experiences with future expectations is possible.

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Purpose: The purpose of this study was to develop and validate a multivariate predictive model to detect glaucoma by using a combination of retinal nerve fiber layer (RNFL), retinal ganglion cell-inner plexiform (GCIPL), and optic disc parameters measured using spectral-domain optical coherence tomography (OCT). Methods: Five hundred eyes from 500 participants and 187 eyes of another 187 participants were included in the study and validation groups, respectively. Patients with glaucoma were classified in five groups based on visual field damage. Sensitivity and specificity of all glaucoma OCT parameters were analyzed. Receiver operating characteristic curves (ROC) and areas under the ROC (AUC) were compared. Three predictive multivariate models (quantitative, qualitative, and combined) that used a combination of the best OCT parameters were constructed. A diagnostic calculator was created using the combined multivariate model. Results: The best AUC parameters were: inferior RNFL, average RNFL, vertical cup/disc ratio, minimal GCIPL, and inferior-temporal GCIPL. Comparisons among the parameters did not show that the GCIPL parameters were better than those of the RNFL in early and advanced glaucoma. The highest AUC was in the combined predictive model (0.937; 95% confidence interval, 0.911–0.957) and was significantly (P = 0.0001) higher than the other isolated parameters considered in early and advanced glaucoma. The validation group displayed similar results to those of the study group. Conclusions: Best GCIPL, RNFL, and optic disc parameters showed a similar ability to detect glaucoma. The combined predictive formula improved the glaucoma detection compared to the best isolated parameters evaluated. The diagnostic calculator obtained good classification from participants in both the study and validation groups.