Objective: The present study represents one of the largest series of pediatric multiple sclerosis (PedMS) in Western Balkan region. This is the first study aimed to evaluate the characteristics of PedMS in the Serbian population. Methods: This retrospective study on 54 PedMS, aged 7–17 years, was performed at the Clinic of Neurology and Psychiatry for Children and Youth in Belgrade, Serbia, a tertiary center for the diagnosis and treatment of children with neurological and psychiatric diseases. Results: Female to male ratio was 37 (68.5%): 17 (31.5%). Family history of MS was noted in 9.3% and autoimmune diseases in 24.1% patients. Co-occurring migraine was in 7,4%. Monofocal onset of disease was present in 77.8% patients. The most common initial symptoms were optic neuritis (37%), sensory disturbances (31.5%), motor deficit (24.1%), cerebellar (18.5%) and brainstem lesions (16.7%), pain (9.3%), acute disseminated encephalomyelitis like symptoms (1.9%), and hearing loss (3.7%). Visual evoked potentials were pathological in 75.9% of patients. Oligoclonal bands were positive in 68.5% of patients. Magnetic resonance imaging showed periventricular (94.4%), infratentorial (77.8%), juxtacortical and cortical changes (55.6%) and changes in the cervical spinal cord (33.3%). The median EDSS score was 2.0. Conclusion: Our cohort significantly differs from the literature data regarding more frequent occurrence of optic neuritis, hearing loss as a first symptom, the relapsing-remitting course of the disease, higher proportion of early onset of disease, presence of co-occurring migraine and the frequent occurrence of epilepsy and other autoimmune diseases in the family.

Neuroretinitis due to Bartonella henselae infection is a rare cause of vision loss in children. Two pediatric cases of acute unilateral vision loss accompanied by edema of the optic nerve on fundoscopic examination are presented. Severe causes of vision loss were excluded. During the course of the disease, macular stellate exudates emerged on control fundoscopic examinations, and diagnosis of neuroretinitis was made. A causative agent was confirmed by serologic examination, as high titers of IgM and IgG antibodies to Bartonella henselae were detected. Both patients significantly recovered after oral antibiotic treatment.

Depressive disorders significantly impact individuals worldwide, including children and adolescents. Despite their widespread occurrence, early and precise diagnosis of depressive disorders remains a complex and challenging task, particularly in younger populations. This study proposes a novel machine learning framework leveraging kinematic handwriting analysis to enhance the detection of psychomotor disturbances indicative of psychomotor retardation in youths with depression. The handwriting data were acquired from 20 youths with depression and 20 healthy controls. All participants completed a simple repetitive handwriting task: continuous writing of the small cursive Latin letter “l”. Segmentation of the handwriting data into individual “Letters” was conducted, and 177 kinematic features were extracted and analyzed. Statistical methods were used to identify significant features. After recursive feature elimination, classification was achieved through machine learning algorithms: logistic regression, support vector machine, and random forest. After the identification of 40 significant features, logistic regression, utilizing an optimal three-feature subset, achieved the highest accuracy in classifying individual letters of 76.7% and the highest accuracy in classifying subjects of 82.5%. The feature selection process revealed that velocity-related features were most effective in distinguishing patients with depression from controls, expectedly reflecting a slowdown in psychomotor functioning among the patients. The findings demonstrate that kinematic handwriting analysis, when combined with machine learning techniques, offers a promising tool to support objective recognition of psychomotor speed, providing insight into psychomotor retardation in youth with depression.