Balu H. Athreya

Ocular involvement in children with localised scleroderma: A multi-centre study

Background: Most of the available documentation in the literature on ocular involvement in localised scleroderma (LS) are descriptions of single cases in adult patients. This article reports the frequency and specific features of ocular involvement in a large cohort of children with juvenile LS (JLS). Methods: Data from a large, multi-centre, multinational study of children with LS were used to collect and analyse specific information on ocular involvement. Results: 24 out of 750 patients (3.2%) revealed a significant ocular involvement. 16 were female and 8 male. 16 patients (66.7%) had scleroderma “en coup de sabre” (ECDS) of the face, 5 (20.8%) had the linear subtype, 2 (8.3%) had generalised morphea (GM) and one (4.2%) had plaque morphea (PM). Of the 24 patients with eye involvement, 10 patients (41.7%) reported adnexa (eyelids and eyelashes) abnormalities, 7 (29.2%) anterior segment inflammation (5 anterior uveitis, 2 episcleritis) and 3 central nervous system-related abnormalities. 4 patients presented single findings such as paralytic strabismus (1), pseudopapilloedema (1) and refractive errors (2). Other extracutaneous manifestations were detected in a significantly higher number of patients with ocular involvement and were mostly neurological. Conclusion: Ocular abnormalities are not unusual in patients with JLS, especially in the ECDS subtype. They are frequently associated with other internal organ involvement, particularly the central nervous system (CNS). Careful ophthalmic monitoring is recommended for every patient with JLS, but is mandatory in those with skin lesions on the face and/or concomitant CNS involvement.

Computer-assisted Diagnosis of Pediatric Rheumatic Diseases

Objective. AI/RHEUM is a multimedia expert system developed originally to assist in the diagnosis of rheumatic diseases in adults. In the present study we evaluated the usefulness of a modified version of this diagnostic decision support system in diagnosing childhood rheumatic diseases. Methodology. AI/RHEUM was modified by the addition of 5 new diseases to the knowledge base of the system. Criteria tables for each of the diseases included in the knowledge base were modified to suit the needs of children. The modified system was tested on 94 consecutive children seen in a pediatric rheumatology clinic. Results. AI/RHEUM made the correct diagnosis in 92% of the cases when the diagnosis was available in the knowledge base of the system. It was also shown to be effective in the education of pediatric trainees through its multimedia features. Conclusions. AI/RHEUM is an expert system that may be helpful to the nonspecialist as a diagnostic decision support system and as an educational tool.