ABSTRACT
OBJECTIVE: To study the prevalence of Macrophage Activation Syndrome (MAS) in children with Kawasaki disease (KD) and to devise a classification tree for predicting MAS in early KD based on easily available clinical and laboratory information using artificial intelligence (AI) technology. METHODS: A prospective cross-sectional observational study was conducted (March 2020 - October 2021) during which hospitalized children aged 1-18 years with KD were consecutively enrolled. Those with positive RTPCR test or IgM/IgG serology for COVID-19 were excluded. The clinical and laboratory profiles of children with and without MAS were studied. A multivariable logistic regression (LR) model was developed utilizing backward elimination method to determine the relationship between select candidate predictor variables and MAS in patients with KD. A classification tree was created based on these using artificial intelligence algorithms. RESULTS: Sixty-two children were diagnosed with KD during the study period, of these, 42 children with KD were included; 14 (33.3 %) were diagnosed with MAS. The median (IQR) duration of fever (days) was significantly more in MAS than those without MAS [7 (5, 15) vs 5 (5, 9), P < 0.05]. Serum albumin (g/dL) was significantly lower in those with MAS [2.3 (2.2, 2.7) vs 2.8 (2.3, 3.1), P = 0.03]. The classification tree constructed by the AI-based algorithm predicted that in children with KD who had myocardial dysfunction, serum albumin ≤ 2.8 g/dL and fever > 6 days duration at admission had increased likelihood of developing MAS. In children without myocardial dysfunction, alanine transaminase (ALT) levels > 70 U/L and fever > 5 days were equally predictive of MAS. CONCLUSION: Nearly one-third of the children with KD had MAS. Clinicians should consider screening all children with KD for MAS at admission. A classification tree based on the presence of myocardial dysfunction, duration of fever > 6 days, ALT levels and hypoalbuminemia can identify MAS in the course of KD.
ABSTRACT
Background: Subacute sclerosing panencephalitis is a progressive devastating condition due to persistence of mutant measles virus, affecting children and adolescents, characterised by myoclonus, seizures, and neuropsychiatric issues. Movement disorders apart from myoclonus are reportedly uncommon. We aimed to describe frequency and proportion of movement disorders among children with subacute sclerosing panencephalitis, hypothesizing that these occur more frequently than previously reported. Methods: In this cross-sectional study, we enrolled children with subacute sclerosing panencephalitis between 1 month and 18 years of age who fulfilled the diagnosis of subacute sclerosing panencephalitis as per modified Dyken criteria, and examined them for movement disorders. We also assessed their clinical profile and disease severity via Jabbour staging and modified Rankin Scale score. We compared demographic, clinical, and laboratory features of children with and without movement disorders. Results: We enrolled 50 children (36 males; 72%) (age range 1.5-14 years). Of these, 28 (56%) had movement disorders. Among movement disorders, the most frequent was myoclonus (92%), followed by ataxia (9; 18%), chorea-athetosis (7; 14%), dystonia (6; 12%), tremor (4; 8%), repetitive behavior (4; 8%), and parkinsonism (3; 6%). Movement disorders were the presenting feature of subacute sclerosing panencephalitis among 7 children. There were no significant differences in clinical or laboratory features among children with and without movement disorders. Conclusions: Movement disorders were frequent in subacute sclerosing panencephalitis. Hyperkinetic disorders were dominant. Dystonia and chorea-athetosis occurred more commonly among nonmyoclonus movement disorders. Movement disorders may manifest even in earlier stages of subacute sclerosing panencephalitis and may be the heralding feature. Recognition of these features is important to plan management and reduce morbidity.
