CLINICAL-ALGORITHMIC APPROACHES TO THE DIAGNOSIS OF LATENT AND ATYPICAL FORMS OF SCABIES IN CHILDREN

Abstract

 Introduction: Scabies, caused by the mite Sarcoptes scabiei var. hominis, remains a significant public health issue globally, particularly affecting children. While classic presentations are readily identifiable, latent and atypical forms pose considerable diagnostic challenges, leading to delayed treatment, increased morbidity, and continued transmission. This study aims to develop and propose a structured clinical-algorithmic approach to enhance the diagnostic accuracy of these challenging scabies presentations in the pediatric population. Methods: A comprehensive literature review was conducted using PubMed, Scopus, and Google Scholar databases to identify studies related to atypical scabies, scabies in infants, diagnostic methods, and clinical guidelines published between 2000 and 2025. Based on the synthesized evidence and analysis of prototypical clinical scenarios, a step-by-step diagnostic algorithm was developed. The algorithm integrates epidemiological data, clinical manifestations (both classic and atypical), and modern diagnostic tools like dermoscopy. Results: The developed algorithm stratifies the diagnostic process based on the initial clinical suspicion. It guides the clinician from initial assessment (pruritus characteristics, contact history) through a detailed physical examination focused on subtle and location-specific signs in different pediatric age groups. Key decision points include the presence of eczematous, nodular, or bullous lesions, and involvement of atypical sites such as the scalp, face, palms, and soles. The algorithm incorporates dermoscopy ("delta wing jet" sign) as a crucial second-line investigation and skin scraping for microscopy as a confirmatory test. A scoring system is proposed to aid in decision-making for empirical treatment in cases with high clinical suspicion but negative microscopy. Discussion: Atypical presentations of scabies in children are often misdiagnosed as eczema, impetigo, or allergic reactions, primarily due to the unique immunological responses of children and the frequent use of topical steroids (scabies incognito). The proposed algorithm provides a systematic framework that minimizes diagnostic errors by encouraging clinicians to consider scabies in a wider range of dermatological presentations. Its implementation can lead to earlier diagnosis and treatment, thereby reducing complications like secondary bacterial infections and preventing outbreaks in families and communities. The algorithm's utility lies in its structured approach, which is particularly valuable for primary care physicians and pediatricians who may be less familiar with atypical dermatoses. Conclusion: The diagnosis of latent and atypical scabies in children requires a high index of suspicion and a systematic approach. The proposed clinical algorithm serves as a practical tool to improve diagnostic accuracy, ensure timely management, and control the spread of this common but often-overlooked infestation.