AimTo evaluate visual impairment (VI) in children with cerebral palsy (CP).MethodsThis population-based study included 419 children from the Surveillance of Cerebral Palsy in Europe (SCPE) C28 RCP-HR – Register of Cerebral Palsy of Croatia born 2003-2008. Vision in children with CP (according to SCPE) was classified as normal or impaired, with the subcategory of severe VI. The proportion of children with VI was assessed in groups with different CP type/subtype, gross and fine motor function, and gestational age (GA).ResultsA total of 266 children had some degree of VI (266/400; 66.5%), 134 had normal vision, and data on VI were unknown for 19 children. Severe VI was present in 44 children (44/400; 11%). The proportion of children with VI and severe VI increased with the Gross Motor Function Classification System and Bimanual Fine Motor Function levels. Children with bilateral spastic CP had the highest frequency of severe VI (14.9%). The percentage of severe VI in children with bilateral spastic CP was 53.8% in the group born <28 weeks of GA, 13.3% in the group born 28-31 weeks of GA, 11.1% in the group born 32-36 weeks of GA, and 24.4% in the group born >36 weeks of GA (λ2 = 4.95; df = 6; P < 0.001).ConclusionChildren with CP have a high prevalence of VI and severe VI, which is increasing with the level of motor impairment. Severe VI is significantly more common in children with bilateral spastic CP, especially among extremely premature infants.
The aim of this population-based study was to evaluate the characteristics of cerebral palsy (CP) in relation to the predominant pattern of the magnetic resonance imaging Classification System (mriCS) that was analogously applied to the neonatal/early infant cranial ultrasound (CuS). The study included children born during the 2004-2007 period from the Croatian part (C28 rCP-hr) of the Surveillance of Cerebral Palsy in europe (SCPe) CP register. motor functions, accompanying impairments and brain mri were evaluated in 227 children, 185 of which also had CuS. Concerning CP types, 56% of children had bilateral spastic, 34% unilateral spastic, 9% dyskinetic and 1% ataxic CP type. gross motor function Classification System (gmfCS) revealed that 62.05% had mild (gmfCS i-iii) and 37.85% had severe motor impairment (gmfCS iv-v). CuS showed white matter injury in 60%, gray matter injury in 12%, maldevelopments in 8%, miscellaneous changes in 14%, while 6% were normal; mri showed significant agreement (κ=0.675, p<0.001). neuroimaging findings of maldevelopments and predominant gray matter injury were associated with more severe CP, but 7% of children with CP had normal mri. As we found very good agreement between CuS and mri findings, CuS is recommended in children at an increased risk of CP if mri is not available.
A case of persistent fetal palmar grasping of the umbilical cord in a 23-year-old primigravida is described. Palmar grasping was detected with three-dimensional ultrasound examination after cardiotocographically recorded fetal bradyarrhythmia. Because of acute fetal hypoxia, urgent Misgav-Ladach cesarean section was performed to deliver a hypotrophic female newborn, 2,120 g/43 cm, Apgar score 4/7, pH 7.29. No other pathology was found during the procedure. The postoperative course proceeded uneventfully and the early neonatal neurological status and neurosonographic findings were normal.
Watermark, Tensiometer and Time Domain Reflectometry (TDR) are commonly used soil water sensors in irrigation practice whose performance depends on soil type, depth and growing conditions. Here, the results of sensor performance evaluation in different soil depths as well as the field and laboratory testing in silty clay loamy soil are presented. Gravimetric soil moisture samples were taken from sensor installation depths (10, 20, 30 and 45 cm) and used as reference Soil Water Content (SWC). The measurements varied significantly (p < 0.05) across the monitoring depths. On average across the soil depths, there was a strong negative linear relationship between Watermark (r = −0.91) and TDR (r = 0.94), and a moderate negative (r = −0.75) linear relationship between SWC and Tensiometer. In general, Watermark and Tensiometer measured SWC with great accuracy in the range of readily available water, generated larger Mean Difference (MD) than TDR and overestimated SWC, while TDR underestimated SWC. Overall, laboratory testing reduced the root mean square error (RMSE, Watermark = 1.2, Tensiometer = 2.6, TDR = 1.9) and Mean Average Error (MAE, Watermark = 0.9, Tensiometer = 2.04. TDR = 1.04) for all tested sensors.
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