ArticleAmerican journal of medicine open2026
Clinical Correlates of Hospital Admission in Adult SLE Patients Presenting to the Emergency Department.
Article in American journal of medicine open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
4 authors.
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Abstract
Introduction: Systemic lupus erythematosus (SLE) is a multisystem autoimmune disease frequently requiring emergency care. However, limited data exist on factors influencing hospital admission from the emergency department (ED) in this population. Methods: We performed a retrospective analysis of adult SLE-related ED visits in the 2022 Nationwide Emergency Department Sample (NEDS). All analyses incorporated NEDS discharge weights to produce nationally representative estimates. Logistic regression analyses were used to identify factors associated with ED-to-hospital admission in adult SLE patients. Results: Of the weight total of 376,776 SLE-related ED visits, 37.7% resulted in hospital admission. Infections, cardiovascular, and renal complications were the most common admitting diagnoses. The strongest associations with hospital admission included bloodstream infection due to central venous catheter (OR 532.10), sepsis (OR 94.65), myocardial infarction (OR 18.27), hypertensive emergency (OR 14.33), combined kidney heart disease (OR 14.26), and acute kidney failure (OR 9.05). Additionally, increasing age and Asian/Pacific Islander race were associated with higher odds of admission, while female sex was associated with lower odds. Conclusion: Over one-third of ED visits for SLE patients result in hospitalization, primarily driven by high-acuity conditions. These findings highlight key clinical and demographic factors associated with admission and can inform ED triage decisions and care algorithms for this complex population.
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