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Introduction: The transplantation of highly sensitized patients remains a major obstacle. Immunized patients wait longer for a transplant if not prioritized, and if transplanted, their transplant outcome is worse. Case Presentation: We report a successful AB0- and HLA-incompatible living donor kidney transplantation in a 35-year-old female patient with systemic lupus erythematosus (SLE) and antiphospholipid syndrome. The patient had a positive T- and B-cell complement-dependent cytotoxicity (CDC) crossmatch and previous graft loss due to renal vein thrombosis. We treated the patient with intravenous immunoglobulins, rituximab, horse anti-thymocyte globulin, daratumumab, and imlifidase, besides standard immunosuppression. All IgG antibodies were sensitive to imlifidase treatment. Besides donor-specific HLA antibodies, anti-dsDNA antibodies and antiphospholipid antibodies were cleaved. The patient initially had delayed graft function. Two kidney biopsies (day 7 and day 14) revealed acute tubular necrosis without signs of HLA antibody-mediated rejection. On posttransplant day 30, hemodialysis was stopped, and creatinine levels declined over the next weeks to a baseline creatinine of about 1.7 mg/dL after 12 months. Conclusion: In this case, a novel multimodal treatment strategy including daratumumab and imlifidase enabled successful kidney transplantation for a highly immunized patient with antiphospholipid antibodies.
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OBJECTIVES: To assess the feasibility of long-term muscle monitoring, we implemented an AI-guided segmentation approach on clinically indicated Computed Tomography (CT) examinations conducted throughout the hospitalization period of patients admitted to the intensive care unit (ICU) with acute pancreatitis (AP). In addition, we aimed to investigate the potential of muscle monitoring for early detection of patients at nutritional risk and those experiencing adverse outcomes. This cohort served as a model for potential integration into clinical practice. MATERIALS: Retrospective cohort study including 100 patients suffering from AP that underwent a minimum of three CT scans during hospitalization, totaling 749 assessments. Sequential segmentation of psoas muscle area (PMA) was performed and was relative muscle loss per day for the entire monitoring period, as well as for the interval between each consecutive scan was calculated. Subgroup and outcome analyses were performed including ANOVA. Discriminatory power of muscle decay rates was evaluated using ROC analysis. RESULTS: Monitoring PMA decay revealed significant long-term losses of 48.20% throughout the hospitalization period, with an average daily decline of 0.98%. Loss rates diverged significantly between survival groups, with 1.34% PMA decay per day among non-survivors vs. 0.74% in survivors. Overweight patients exhibited significantly higher total PMA losses (52.53 vs. 42.91%; p = 0.02) and average PMA loss per day (of 1.13 vs. 0.80%; p = 0.039). The first and the maximum decay rate, in average available after 6.16 and 17.03 days after ICU admission, showed convincing discriminatory power for survival in ROC analysis (AUC 0.607 and 0.718). Both thresholds for maximum loss (at 3.23% decay per day) and for the initial loss rate (at 1.98% per day) proved to be significant predictors of mortality. CONCLUSIONS: The innovative AI-based PMA segmentation method proved robust and effortless, enabling the first comprehensive assessment of muscle wasting in a large cohort of intensive care pancreatitis patients. Findings revealed significant muscle wasting (48.20% on average), particularly notable in overweight individuals. Higher rates of initial and maximum muscle loss, detectable early, correlated strongly with survival. Integrating this tool into routine clinical practice will enable continuous muscle status tracking and early identification of those at risk for unfavorable outcomes.
