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Background Acute kidney injury (AKI) has been reported after CAR-T cells, but available data are limited. We sought to describe the incidence of AKI in a cohort of patients hospitalized in the intensive care unit (ICU) following CAR-T cell reinjection, identify the primary factors linked to the onset of AKI, and ascertain the key determinants associated with kidney outcomes and mortality. Methods We retrospectively analyzed 119 patients hospitalized in ICU after CAR-T cell therapy between 2017 and 2023. Factors associated with AKI, mortality, and kidney sequelae were identified using multivariate analyses. Results Of the 119 patients, 41 patients fulfilled diagnostic criteria of AKI (34%). By multivariate analysis, grade ≥3 cytokine release syndrome (CRS) [OR = 1.20 CI95% (1.01–1.43)] and elevated lactate dehydrogenase (LDH) levels at admission [OR = 1.44 CI95% (1.04–1.99)] were significantly associated with the occurrence of AKI during ICU stay. AKI KDIGO ≥2 was an independent risk factor for hospital mortality [OR = 1.50 (1.22–1.85), P < 0.001]. Nine out of 12 (75%) and 6/9 (67%) patients who had experienced AKI and survived had chronic kidney disease (CKD) at 6 months and 1 year, respectively. We did not identify any specific factor associated with kidney recovery. Conclusion AKI may occur in ICU patients receiving CAR-T cell therapy, especially those who experience CRS and exhibit elevated LDH levels. Early recognition of AKI is of utmost importance as it substantially compromises survival in these patients. Future studies should aim to elucidate the underlying pathophysiological mechanisms of AKI in this context and pinpoint predictive factors for long-term risks of CKD. [ABSTRACT FROM AUTHOR]

Hyperviscosity syndrome (HVS) is a rare complication of newly diagnosed multiple myeloma (NDMM) related to high tumour burden. Studies about the prognosis of HVS in modern-era therapy for NDMM are missing. We investigated a retrospective cohort study of NDMM with HVS between 2011- 2021. Thirty-nine NDMM patients with HVS were included. HVS presentation was heterogeneous, with asymptomatic, mild, and neurological forms in 23%, 59%, and 18% of cases, respectively. No thrombosis or major bleeding was observed. Therapeutic plasma exchanges were used in 92% of patients, which were effective and well tolerated. No rebound effect was observed. All patients except one had at least one CRAB criterion. Most of the patients received bortezomib and high-dose steroids (95%) associated with an immunomodulatory drug (43%) or alkylating agents (42%). HVS in NDMM patients had dismal overall survival matched to multiple myeloma patient controls (without HVS) in our center (median: 3.6 vs. 7.7 years, p=0.01), as confirmed by multivariate analysis. Early deaths (in the first two months) occurred in 21% of older patients (>65 years). HVS in NDMM patients is a rare but life-threatening complication associated with high lethality in older patients and be a potential dismal prognosis factor in the modern treatment era. [ABSTRACT FROM AUTHOR]

Objectives: Although some prognostic factors for COVID-19 were consistently identified across the studies, differences were found for other factors that could be due to the characteristics of the study populations and the variables incorporated into the statistical model. We aimed to a priori identify specific patient profiles and then assess their association with the outcomes in COVID-19 patients with respiratory symptoms admitted specifically to hospital wards. Methods: We conducted a retrospective single-center study from February 2020 to April 2020. A non-supervised cluster analysis was first used to detect patient profiles based on characteristics at admission of 220 consecutive patients admitted to our institution. Then, we assessed the prognostic value using Cox regression analyses to predict survival. Results: Three clusters were identified, with 47 patients in cluster 1, 87 in cluster 2, and 86 in cluster 3; the presentation of the patients differed among the clusters. Cluster 1 mostly included sexagenarian patients with active malignancies who were admitted early after the onset of COVID-19. Cluster 2 included the oldest patients, who were generally overweight and had hypertension and renal insufficiency, while cluster 3 included the youngest patients, who had gastrointestinal symptoms and delayed admission. Sixty-day survival rates were 74.3%, 50.6% and 96.5% in clusters 1, 2, and 3, respectively. This was confirmed by the multivariable Cox analyses that showed the prognostic value of these patterns. Conclusion: The cluster approach seems appropriate and pragmatic for the early identification of patient profiles that could help physicians segregate patients according to their prognosis. [ABSTRACT FROM AUTHOR]

Immunoglobulin G (IgG) metabolism has received much attention in the literature for two reasons: (i) IgG homeostasis is regulated by the neonatal Fc receptor (FcRn), by a pH-dependent and saturable recycling process, which presents an interesting biological system; (ii) the IgG-FcRn interaction may be exploitable as a means for extending the plasma half-life of therapeutic monoclonal antibodies, which are primarily IgG-based. A less-studied problem is the importance of endogenous IgG metabolism in IgG multiple myeloma. In multiple myeloma, quantification of serum monoclonal immunoglobulin plays an important role in diagnosis, monitoring and response assessment. In order to investigate the dynamics of IgG in this setting, a mathematical model characterizing the metabolism of endogenous IgG in humans is required. A number of authors have proposed a two-compartment nonlinear model of IgG metabolism in which saturable recycling is described using Michaelis-Menten kinetics; however it may be difficult to estimate the model parameters from the limited experimental data that are available. The purpose of this study is to analyse the model alongside the available data from experiments in humans and estimate the model parameters. In order to achieve this aim we linearize the model and use several methods of model and parameter validation: stability analysis, structural identifiability analysis, and sensitivity analysis based on traditional sensitivity functions and generalized sensitivity functions.We find that allmodel parameters are identifiable, structurally and taking into account parameter correlations, when several types of model output are used for parameter estimation. Based on these analyses we estimate parameter values from the limited available data and compare them with previously published parameter values. Finally we show how the model can be applied in future studies of treatment effectiveness in IgG multiple myeloma with simulations of serum monoclonal IgG responses during treatment. [ABSTRACT FROM AUTHOR]