Delayed Diagnosis of Poems Syndrome, How AI Tools Can Enhance Diagnostic Accuracy

Polyneuropathy, organomegaly, endocrinopathy, monoclonal plasma cell disorder, and skin changes (POEMS) syndrome is a rare multisystem disorder often misdiagnosed due to its wide-ranging manifestations and clinical overlap with common medical conditions. We present a case of a 76-year-old male who initially presented with bilateral lower extremity oedema and fatigue. Despite multiple specialist evaluations and worsening symptoms with characteristic clinical features, including peripheral neuropathy, thrombocytosis, and sclerotic bone lesions, POEMS syndrome was not investigated until the haematology service saw the patient during his hospitalization. Earlier evaluations prior to hospitalization revealed an IgG lambda monoclonal protein, splenomegaly, papilledema, and an elevated vascular endothelial growth factor (VEGF) level of 10,999 pg/ml, confirming the diagnosis of POEMS syndrome. This case underscores the importance of early identification of markers related to POEMS syndrome. The patient's presentation also fulfilled the PEST acronym (which stands for papilledema, extravascular volume overload, sclerotic bone lesions, and thrombocytosis), a helpful clinical reminder for internists. Due to his poor functional status and age, he was ineligible for an autologous stem cell transplant and was treated with a combination of daratumumab, lenalidomide, and dexamethasone. After 4 months of treatment, he showed significant clinical improvement and a greater than 50% reduction in VEGF levels. This case illustrates the diagnostic challenges of POEMS syndrome and the important role internists can play in early recognition. Prompt VEGF testing, investigation with artificial intelligence tools, and inclusion of POEMS syndrome in the differential can reduce unnecessary consultations and healthcare costs, while enabling timely therapy.

When a patient has a constellation of symptoms including peripheral neuropathy and monoclonal gammopathy, POEMS syndrome needs to be added to the working diagnoses.Common cognitive biases may delay diagnosis of a rare disease such as POEMS syndrome, leading to adverse clinical outcomes and increased healthcare costs.Earlier screening of the patient's symptoms via artificial intelligence tools could have prompted an appropriate diagnosis and combat common cognitive biases.