Decoding Fatigue in Systemic Lupus Erythematosus with Artificial Intelligence: Hematologic or Inflammatory Factors?

    March 2026 in “ Oral Presentations
    Alexandru Garaiman, Ciprian Jurcuț, Camelia Badea, Simona Cariola, Razvan Ionescu, M. Bojinca, Cristian Baicusi, Alina Dima
    Studysummary This study identified hemoglobin level as the strongest biological predictor of fatigue in systemic lupus erythematosus patients, highlighting its association with disease activity and systemic inflammation.
    Our plain-language summary. Not medical advice or a treatment recommendation. Consult a qualified healthcare professional before changing treatment. Full disclaimer
    This study investigated the predictors of fatigue in 144 patients with systemic lupus erythematosus (SLE) using a random forest model. Hemoglobin level was identified as the most significant predictor of fatigue, with a threshold of 12.5 g/dL indicating increased fatigue risk. Other factors such as SLAM score, erythrocyte sedimentation rate, SLEDAI, and SLICC index also contributed to fatigue, though to a lesser extent. The model's predictive accuracy was reflected in an area under the ROC curve of 76.9%. The study highlights the importance of hematologic status, disease activity, and systemic inflammation in SLE-related fatigue.
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