Blood tests to rule out mimics of multiple sclerosis should consider which infections?

Blood tests to rule out mimics of multiple sclerosis should consider which infections?

• A. Lyme disease, HIV, and syphilis
• B. Tuberculosis alone
• C. Hepatitis B only
• D. Malaria

Answer: (A)

When evaluating suspected multiple sclerosis, it’s crucial to check for infections that can mimic CNS demyelination. Lyme disease, HIV, and syphilis can all cause CNS involvement with symptoms and imaging findings that resemble MS, so testing for these infections helps distinguish true MS from other causes. Neuroborreliosis from Lyme can present with meningitis, radiculopathy, or cranial neuropathies and MS-like lesions on MRI. HIV can produce CNS demyelination and neurocognitive changes, or predispose to opportunistic infections that imitate MS. Neurosyphilis from syphilis can cause meningitis, tabes dorsalis, and other neurologic signs that resemble MS. Including these tests in the workup helps avoid misdiagnosis and ensures appropriate treatment. Tuberculosis, hepatitis B, or malaria can affect the CNS but are not as classic and routine MS mimics in most diagnostic algorithms.

When evaluating suspected multiple sclerosis, it’s crucial to check for infections that can mimic CNS demyelination. Lyme disease, HIV, and syphilis can all cause CNS involvement with symptoms and imaging findings that resemble MS, so testing for these infections helps distinguish true MS from other causes. Neuroborreliosis from Lyme can present with meningitis, radiculopathy, or cranial neuropathies and MS-like lesions on MRI. HIV can produce CNS demyelination and neurocognitive changes, or predispose to opportunistic infections that imitate MS. Neurosyphilis from syphilis can cause meningitis, tabes dorsalis, and other neurologic signs that resemble MS. Including these tests in the workup helps avoid misdiagnosis and ensures appropriate treatment. Tuberculosis, hepatitis B, or malaria can affect the CNS but are not as classic and routine MS mimics in most diagnostic algorithms.