Several cases of acute necrotizing encephalopathy (ANE) with influenza A (H1N1) have been reported to date. The prognosis of ANE associated with H1N1 is variable; some cases resulted in severe neurologic complication, whereas other cases were fatal. Reports mostly focused on the diagnosis of ANE with H1N1 infection, rather than functional recovery. We report a case of ANE with H1N1 infection in a 4-year-old Korean girl who rapidly developed fever, seizure, and altered mentality, as well as had neurologic sequelae of ataxia, intentional tremor, strabismus, and dysarthria. Brain magnetic resonance imaging showed lesions in the bilateral thalami, pons, and left basal ganglia. To our knowledge, this is the first report of ANE caused by H1N1 infection and its long-term functional recovery in Korea.
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To investigate the reliability of inspection-based classification of sagittal gait patterns in children with bilateral spastic cerebral palsy (CP).
Video clip recordings of gait patterns and sagittal kinematic data obtained by a computerized motion analysis system from 91 patients with bilateral spastic CP were reviewed. The abnormal gait patterns were classified into 4 groups using the method described by Rodda et al. Visual observation-based classification (visual classification) was compared with classification by 3D analysis-based methods (3D classification). The reliabilities of visual classifications made by an experienced physician and a trainee physician were analyzed.
The consistency of inspection-based gait classification using kinematic data analysis was demonstrated by an experienced physician (Kappa coefficient (k)=0.67, p<0.001). However, the consistency was low for the trainee physician (k=0.37, p<0.001). Group III (apparent equinus) was commonly confused with group IV (crouch gait) by the trainee physician, resulting in lower agreement for those two evaluation groups than for other patterns. Video observation showed low reliability in comparisons made between the experienced and the trainee physician (k=0.37, p<0.001).
There was substantial agreement of gait classification between video observation and kinematic data analysis by the experienced physician, but not by the trainee physician. Low reliability was also demonstrated for inspection-based gait classification.
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