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Myopia is a worldwide major public concern, aside from the visual disturbance needing optical correction, myopia may be associated with open angle glaucoma, retinal detachment and myopic maculopathy. The higher the myopia the higher the risk for retinal associated comorbidities, and the axial length is the more important measure to estimate risk of visual impairment. Recently a formula to predict axial length using spherical equivalent and keratometry was proposed, with the intention of categorizing the risk of visual impairment with Tideman et al. classification. PURPOSE: To evaluate the accuracy of an axial length prediction formula in a Colombian population 8-17 years old. METHODS: Children from MIOPUR study with optical biometer axial length measure (AL), manifest refraction and keratometry were included in the analysis. Predicted axial length (PAL) was calculated with the prediction formula. A Bland-Altman assessment was conducted, and the concordance correlation coefficient was measured. Proposed classification of AL to establish risk of visual loss was used with measured AL and with PAL. The percentage of eyes misclassified was then established. RESULTS: A total of 2129 eyes were included in the analysis. Mean difference of axial length (actual AL minus PAL) was -0.516 mm (-1.559 mm - 0.528 mm). Concordance correlation coefficient (CCC) of 0.656 (IC95 0.636-0.675) was found between the real AL and PAL. PAL differed from measured AL by 1 mm or more in 16.58 %, and by 2 mm or more, in 0.61 % of the eyes. In myopic eyes, PAL was in average 0.426 mm longer than the AL actually measured with CCC of 0.714 (IC95 0.666-0.761). PAL differed from measured AL by 1 mm or more in 21.92 %, and by 2 mm or more, in 0.45 % of the myopic eyes. The study revealed that 15.03 % of all eyes, and 29.81 % of myopic eyes, were misclassified when PAL was used. CONCLUSIONS: The proposed axial length prediction formula was not accurate, and it did not adequately classify risk of visual impairment in myopic eyes in a group of Colombian children. We consider that it is not possible to predict the axial length based only on optometric data, such as the corneal radius of curvature and the spherical equivalent. This is very possibly related to the variability of crystalline lens power within a population.

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La inteligencia artificial tiene el potencial de transformar la forma en que se brinda la atención médica. Puede respaldar mejoras en los resultados y aumentar la productividad y la eficiencia de la prestación de los servicios. En servicios de las diferentes especialidades los avances realizados a nivel hardware deben desarrollarse en paralelo con los métodos de aprendizaje automático, aspectos que la inteligencia artificial contribuye para promover un cambio de paradigma significativo en las más diversas áreas de la medicina. Es importante en la educación médica como eje para el conocimiento y en la toma de decisiones que pueden mejorar el desempeño de los profesionales. Los estudiantes de medicina de nueva generación pueden adaptarse perfectamente a los nuevos métodos digitalizados en un contexto médico globalizado, incluida la inteligencia artificial. Por ello es importante tener como objetivos a implementar en los planes de estudio e introducir programas educativos representativos de esta tecnología. Es fundamental que todas las áreas del Sistema de Salud tengan confianza en los sistemas informáticos específicamente en el aprendizaje profundo, no solo por la información concreta y objetiva que de él se deriva sino también por la posibilidad de predecir eventos futuros, brindando alta certeza en cuanto al diagnóstico y tratamiento de enfermedades.

Artificial intelligence has the potential to transform the way healthcare is delivered. You can support improved results and increase the productivity and efficiency of service delivery. In the services of the different specialties, the advances made at the hardware level must be developed in parallel with the methods of machine learning, aspects that artificial intelligence contributes to promote a significant paradigm shift in the most diverse areas of medicine. It is important in medical education as an axis for knowledge and in making decisions that can improve the performance of professionals. New generation medical students can perfectly adapt to new digitized methods in a globalized medical context, including artificial intelligence. For this reason, it is important to have as objectives to be implemented in the study plans and to introduce educational programs that are representative of this technology. It is essential that all areas of the Health System have confidence in computer systems specifically in deep learning, not only because of the concrete and objective information that is derived from it but also because of the possibility of predicting future events, providing high certainty regarding to the diagnosis and treatment of diseases.

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Previous research has suggested multiple factor structures for the 12-item General Health Questionnaire (GHQ-12), with contradictory evidence arising across different studies on the validity of these models. In the present research, it was hypothesized that these inconsistent findings were due to the interaction of 3 main methodological factors: ambiguous response categories in the negative items, multiple scoring schemes, and inappropriate estimation methods. Using confirmatory factor analysis with appropriate estimation methods and scores obtained from a large (n = 27,674) representative Spanish sample, we tested this hypothesis by evaluating the fit and predictive validities of 4 GHQ-12 factor models-unidimensional, Hankins' (2008a) response bias model, Andrich and Van Schoubroeck's (1989) 2-factor model, and Graetz's (1991) 3-factor model-across 3 scoring methods: standard, corrected, and Likert. In addition, the impact of method effects on the reliability of the global GHQ-12 scores was also evaluated. The combined results of this study support the view that the GHQ-12 is a unidimensional measure that contains spurious multidimensionality under certain scoring schemes (corrected and Likert) as a result of ambiguous response categories in the negative items. Therefore, it is suggested that the items be scored using the standard method and that only a global score be derived from the instrument.

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The presence of a corneal flap is a hallmark of laser in situ keratomileusis (LASIK), which offers advantages in terms of speed of visual recovery; however, it also carries the risk of postoperative flap displacement. We conducted a retrospective review of all consecutive eyes on which LASIK was performed by one single surgeon at an ophthalmological institute in Colombia between May 2005 and January 2011, looking for eyes that required flap repositioning. Demographic data, preoperative refraction, hinge position, and visual outcomes following flap repositioning were evaluated. A literature review on the subject was also conducted. We found 37 eyes on which flap repositioning was performed-12 eyes (32.4 %) with subluxation and 25 eyes (67.6 %) with folds; 21 eyes (56.8 %) had a temporal hinge and 16 eyes (43.2 %) had a superior hinge. With regard to the total number of eyes on which LASIK was performed (2,595), the overall incidence was 1.4 %. Sixteen out of 2,093 eyes (0.8 %) with a superior hinge and 21 out of 502 eyes (4.2 %) with a temporal hinge had flap-related postoperative complications (p < 0.00). A final best-corrected visual acuity (BCVA) between 20/20 and 20/25 was found in 75.7 % and a final BCVA between 20/30 and 20/40 was found in 21.6 %. Only one eye had less than 20/40 (previous amblyopia). From the eight eyes with a BCVA between 20/30 and 20/40, three had residual microstriae and one had corneal haze. Six eyes (16.2 %) lost two or more lines of BCVA. Flap subluxation or folds requiring flap repositioning were significantly more frequent when a temporal hinge was used.

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