Age norms for grating acuity and contrast sensitivity in children using eye tracking technology.

KEY MESSAGES: Visual acuity is the most used method to assess visual function in children. Contrast sensitivity complements the information provided for visual acuity, but it is not commonly used in clinical practice. Digital devices are increasingly used as a method to evaluate visual function, due to multiple advantages. Testing with these devices can improve the evaluation of visual development in children from a few months of age. Visual acuity and contrast sensitivity tests, using eye tracking technology, are able to measure visual function in children across a wide range of ages, objectively, quickly and without need of an experienced examiner. PURPOSE: To report age-normative values for grating visual acuity and contrast sensitivity in healthy children using a digital device with eye tracking technology and to validate the grating acuity test. METHODS: In the first project of the study, we examined healthy children aged between 6 months and 7 years with normal ophthalmological assessment. Grating visual acuity (VA) and contrast sensitivity (CS) were assessed using a preferential gaze paradigm with a DIVE (Device for an Integral Visual Examination) assisted with eye tracking technology to provide age norms. For the validation project, we compared LEA grating test (LGT) with DIVE VA in a group of children aged between 6 months and 4 years with normal and abnormal visual development. RESULTS: Fifty-seven children (2.86 ± 1.55 years) were examined with DIVE VA test and 44 successfully completed DIVE CS test (3.06 ± 1.41 years). Both, VA and CS values increased with age, mainly along the first two years of life. Sixty-nine patients (1.34 ± 0.61 years) were included in the DIVE VA test validation. The mean difference between LGT and DIVE VA was - 1.05 ± 4.54 cpd with 95% limits of agreement (LoA) of - 9.95-7.84 cpd. Agreement between the two tests was higher in children younger than 1 year with a mean difference of - 0.19 ± 4.02 cpd. CONCLUSIONS: DIVE is an automatic, objective and reliable tool to assess several visual function parameters in children, and it has good agreement with classical VA tests, especially for the first stage of life.

Face recognition impairment in small for gestational age and preterm children.

BACKGROUND: Infants born prematurely or with low birth weight are at increased risk of visual perceptual impairment. Face recognition is a high-order visual ability important for social development, which has been rarely assessed in premature or low birth weight children. AIMS: To evaluate the influence of prematurity and low birth weight on face recognition skills. METHODS: Seventy-seven children were evaluated as part of a prospective cohort study. They were divided into premature and term birth cohorts. Children with a birth weight below the 10th centile were considered small for gestational age. All children underwent a full ophthalmologic assessment and evaluation of face recognition skills using the Facial Memory subtest from the Test of Memory and Learning. RESULTS: Premature infants scored worse on immediate face recognition compared to term infants. However, after adjusting for birth weight, prematurity was not associated with worse outcomes. Independent of gestational age, outcomes of low birth weight children were worse than those of appropriate birth weight children, for immediate face recognition (odds ratio [OR], 5.14; 95% confidence interval [CI], 1.32-21.74) and for face memory (OR, 4.48; 95% CI, 1.14-16.95). CONCLUSIONS: Being born small for gestational age is associated with suboptimal face recognition skills, even in children without major neurodevelopmental problems.

Effect of prematurity and low birth weight in visual abilities and school performance.

BACKGROUND: Prematurity and low birth weight are known risk factors for cognitive and developmental impairments, and school failure. Visual perceptual and visual motor skills seem to be among the most affected cognitive domains in these children. AIMS: To assess the influence of prematurity and low birth weight in visual cognitive skills and school performance. METHODS: We performed a prospective cohort study, which included 80 boys and girls in an age range from 5 to 13. Subjects were grouped by gestational age at birth (preterm, <37 weeks; term, 37-42 weeks) and birth weight (small for gestational age (SGA), <10th centile; appropriate weight for gestational age (AGA), ≥10th centile). Each child underwent full ophthalmologic assessment and standardized testing of visual cognitive abilities (Test of Visual Perceptual Skills and Test of Visual Analysis Skills). Parents completed a questionnaire on school performance in children. RESULTS: Figure-ground skill and visual motor integration were significantly decreased in the preterm birth group, compared with term control subjects (figure-ground: 45.7 vs 66.5, p=0.012; visual motor integration, TVAS: (9.9 vs 11.8, p=0.018), while outcomes of visual memory (29.0 vs 47.7, p=0.012), form constancy (33.3 vs 52.8, p=0.019), figure-ground (37.4 vs 65.6, p=0.001), and visual closure (43.7 vs 62.6 p=0.016) testing were lower in the SGA (vs AGA) group. Visual cognitive difficulties corresponded with worse performance in mathematics (r=0.414, p=0.004) and reading (r=0.343, p=0.018). CONCLUSION: Specific patterns of visual perceptual and visual motor deficits are displayed by children born preterm or SGA, which hinder mathematics and reading performance.

Metabolic risk-factor clustering estimation in obese children

The purpose of this study was to apply the new approach for Metabolic IndividualRisk-factor And Clustering Estimation (MIRACLE) score in a group of Spanishobese children and adolescents and to describe its relationship with other metabolicrisk factors. 153 children with simple obesity were studied: 79 males and 74 females,mean age 11.2 ± 2.2. Obesity was defined when BMI was higher than the age and sexspecific equivalent to 30 kg/m2 in adults. MIRACLE score included: family history(early cardiovascular disease, type 2 diabetes, and hypertension), individual history(small for gestational age and ethnic origin), clinical features (BMI, waist circumference>90th percentile and blood pressure >95th percentile) and metabolic abnormalities(glucose intolerance or type 2 diabetes). It was assigned a value of 1 to “presence”and 0 to” absence” in every patient. The children were considered as having metabolicrisk when at least 5 items were present. Triglycerides, HDL-cholesterol,apolipoprotein B, apolipoprotein A1, glucose and HOMA index, were measured too.The most frequent clinical features of MIRACLE score were: excess waist circumference(95.4%) and hypertension (41.8%). Family history criteria were frequent(55.3% for type 2 diabetes, 39,1% for hypertension and 31.3% for early cardiovasculardisease). Individual risk factors were not frequent. Glucose intolerance wasdetected in 22.2% of the obese patients. A MIRACLE score >= 5 was found in 37.4%of the children studied, being associated with a significant risk of dyslipidemia(triglycerides, p=0.040; HDL-cholesterol, p=0.006; LDL-cholesterol p=0.038;apolipoprotein B, p=0.008) only in females. In conclusion, the MIRACLE score isuseful in order to detect metabolic risk in obese children but it seems necessary toimprove the score, by including other features of the metabolic syndrome like lipid profile or indirect indicators of insulin resistance (AU)

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Metabolic risk-factor clustering estimationin obese children

The purpose of this study was to apply the new approach for Metabolic IndividualRisk-factor And Clustering Estimation (MIRACLE) score in a group of Spanishobese children and adolescents and to describe its relationship with other metabolicrisk factors. 153 children with simple obesity were studied: 79 males and 74 females,mean age 11.2 ¡À 2.2. Obesity was defined when BMI was higher than the age and sexspecific equivalent to 30 kg/m2 in adults. MIRACLE score included: family history(early cardiovascular disease, type 2 diabetes, and hypertension), individual history(small for gestational age and ethnic origin), clinical features (BMI, waist circumference>90th percentile and blood pressure >95th percentile) and metabolic abnormalities(glucose intolerance or type 2 diabetes). It was assigned a value of 1 to ¡°presence¡±and 0 to¡± absence¡± in every patient. The children were considered as having metabolicrisk when at least 5 items were present. Triglycerides, HDL-cholesterol,apolipoprotein B, apolipoprotein A1, glucose and HOMA index, were measured too.The most frequent clinical features of MIRACLE score were: excess waist circumference(95.4%) and hypertension (41.8%). Family history criteria were frequent(55.3% for type 2 diabetes, 39,1% for hypertension and 31.3% for early cardiovasculardisease). Individual risk factors were not frequent. Glucose intolerance wasdetected in 22.2% of the obese patients. A MIRACLE score ¡Ý 5 was found in 37.4%of the children studied, being associated with a significant risk of dyslipidemia(triglycerides, p=0.040; HDL-cholesterol, p=0.006; LDL-cholesterol p=0.038;apolipoprotein B, p=0.008) only in females. In conclusion, the MIRACLE score isuseful in order to detect metabolic risk in obese children but it seems necessary toimprove the score, by including other features of the metabolic syndrome like lipidprofile or indirect indicators of insulin resistance (AU)

No disponible

Metabolic risk-factor clustering estimation in obese children.

The purpose of this study was to apply the new approach for Metabolic Individual Risk-factor And Clustering Estimation (MIRACLE) score in a group of Spanish obese children and adolescents and to describe its relationship with other metabolic risk factors. 153 children with simple obesity were studied: 79 males and 74 females, mean age 11.2 +/- 2.2. Obesity was defined when BMI was higher than the age and sex specific equivalent to 30 kg/m2 in adults. MIRACLE score included: family history (early cardiovascular disease, type 2 diabetes, and hypertension), individual history (small for gestational age and ethnic origin), clinical features (BMI, waist circumference > 90th percentile and blood pressure > 95th percentile) and metabolic abnormalities (glucose intolerance or type 2 diabetes). It was assigned a value of 1 to "presence" and 0 to" absence" in every patient. The children were considered as having metabolic risk when at least 5 items were present. Triglycerides, HDL-cholesterol, apolipoprotein B, apolipoprotein A1, glucose and HOMA index, were measured too. The most frequent clinical features of MIRACLE score were: excess waist circumference (95.4%) and hypertension (41.8%). Family history criteria were frequent (55.3% for type 2 diabetes, 39.1% for hypertension and 31.3% for early cardiovascular disease). Individual risk factors were not frequent. Glucose intolerance was detected in 22.2% of the obese patients. A MIRACLE score > or = 5 was found in 37.4% of the children studied, being associated with a significant risk of dyslipidemia (triglycerides, p = 0.040; HDL-cholesterol, p = 0.006; LDL-cholesterol p = 0.038; apolipoprotein B, p = 0.008) only in females. In conclusion, the MIRACLE score is useful in order to detect metabolic risk in obese children but it seems necessary to improve the score, by including other features of the metabolic syndrome like lipid profile or indirect indicators of insulin resistance.