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STEPWISE DIAGNOSTIC PATHWAY FOR SUSPECTED MULTIPLE SCLEROSIS: AN AUXILIARY ALGORITHM FOR PRACTICING PHYSICIANS
Aliyev R.R.


DOI: 10.61775/2413-3302.v1i43.17


SUMMARY
Early diagnosis of multiple sclerosis (MS) is of major clinical importance for timely initiation of disease-modifying treatment and reduction of disability risk. Because the clinical onset of MS is heterogeneous, practicing physicians need a structured approach to symptoms suggestive of demyelinating disease. The aim of this article is to present an auxiliary diagnostic pathway for suspected MS, summarizing the stages of initial clinical assessment, neuroimaging, diagnostic supportive evaluation according to the 2024 revision of the McDonald criteria, and exclusion of alternative diagnoses. The article also includes a comparison of symptom profiles during the first and second suspected attacks based on clinical data of MS patients observed during 2013–2022. The comparison showed that, during the second attack, the frequency of visual disturbances, bulbar symptoms, and cerebellar symptoms decreased, whereas speech disturbances and pelvic organ dysfunction became more frequent. No statistically significant change was observed for motor and sensory disturbances. These findings support the importance of assessing not only current clinical manifestations, but also previous neurological episodes and the temporal evolution of symptoms when MS is suspected. The proposed stepwise diagnostic pathway is based on evaluation of the typicality of clinical signs, interpretation of Magnetic Resonance Imaging findings in relation to the clinical presentation, staged use of additional paraclinical investigations, and exclusion of alternative diagnoses. This approach may help practicing physicians recognize suspected MS in a timely manner, avoid premature diagnosis in atypical cases, and refer patients for appropriate specialized neurological assessment.
Keywords: multiple sclerosis, clinical onset, relapse, diagnostic pathway, McDonald 2024, magnetic resonance imaging


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