Recurrent early filter clotting during continuous veno-venous hemodialysis with regional citrate anticoagulation is linked to systemic thrombin generation and heparin induced thrombocytopenia type II: a retrospective analysis

OBJECTIVE: Regional citrate anticoagulation (RCA) for continuous renal replacement therapy (CRRT) is widely used and leads to an excellent clottingfree filter survival. Despite strict adherence to protocols, in some cases recurrent early filter-clotting occurs. The aim of this observational study was to evaluate the underlying causes and the efficacy of interventions in patients with early recurrent filter-clotting during RCA. METHODS: In a retrospective analysis of a cohort of 1183 patients treated with RCA-CRRT we detected 12 patients with early filter-clotting unrelated to protocol violation or any obvious technical or medical reason. RESULTS: All patients were systemically anticoagulated with low molecular weight or unfractionated heparin for at least 24h before initiation of Continuous Veno-Venous Hemodialysis with RCA (RCA-CVVHD). During RCA, all postfilter ionized calcium concentrations were in the target range (mean 0.33±0.05 mmol/L). At the time of the first clotting event, thrombocyte counts were 168±66/ nL. After the clotting events, the systemic anticoagulation was switched to argatroban in all patients. With systemic anticoagulation using argatroban filter lifetime of RCA-CVVHD increased significantly (p<0.001) and clotting-events decreased from 0.61 to 0.10 per 24h. All patients were tested for HIT and 5/12 (42%) had a positive test for hep-PF4-antibodies. Application of argatroban significantly reduced early filter-clotting both in HIT-positive patients as well as in HIT-negative patients. At the time of the first clotting event, no patient had clinical signs of thrombosis or thromboembolism. However, during follow up a thromboembolic event occurred in three patients. CONCLUSION: In patients with recurrent early filter-clotting despite strict adherence to the citrate protocol undetected HIT or other causes of thrombin activation may be present. Therefore, patients with recurrent early filter clotting in RCA-CVVHD should be screened for HIT or other conditions that may activate thrombin. A significant improvement of filter run-time can be achieved by systemic administration of a thrombin inhibitor both in patients with and without HIT

A time-resolved proteomic and prognostic map of COVID-19

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease

A time-resolved proteomic and prognostic map of COVID-19

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease