6,653 research outputs found

    Clinical use of immunosuppressants

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    Intraoperative blood transfusions in highly alloimmunized patients undergoing orthotopic liver transplantation.

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    Intraoperative blood requirements were analyzed in patients undergoing primary orthotopic liver transplantation and divided into two groups on the basis of panel reactive antibody of pretransplant serum measured by lymphocytotoxicity testing. One group of highly sensitized patients (n = 25) had PRA values of over 70% and the second group of patients (n = 26) had 0% PRA values and were considered nonsensitized. During the transplant procedure, the 70% PRA group received considerably greater quantities of blood products than the 0% PRA group--namely, red blood cells: 21.1 +/- 3.7 vs. 9.8 +/- 0.8 units (P = 0.002), and platelets: 17.7 +/- 3.2 vs. 7.5 +/- 1.5 units (P = 0.003). Similar differences were observed for fresh frozen plasma and cryoprecipitate. Despite the larger infusion of platelets, the blood platelet counts in the 70% PRA group were lower postoperatively than preoperatively. Twenty patients in the 70% PRA group received platelet transfusions, and their mean platelet count dropped from 95,050 +/- 11,537 preoperatively to 67,750 +/- 8,228 postoperatively (P = 0.028). In contrast, nearly identical preoperative (84,058 +/- 17,297) and postoperative (85,647 +/- 12,445) platelet counts were observed in the 17 0% PRA patients who were transfused intraoperatively with platelets. Prothrombin time, activated partial thromboplastin time, and fibrinogen levels showed no significant differences between both groups. These data demonstrate that lymphocytotoxic antibody screening of liver transplant candidates is useful in identifying patients with increased risk of bleeding problems and who will require large quantities of blood during the transplant operation

    Intraoperative blood transfusion requirements and deficient hemostasis in highly alloimmunized patients undergoing liver transplantation

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    During orthopic liver transplantation (OLT) a large transfusion of different blood components is frequently necessary. From 1981 to 1985 at the University Health Center in Pittsburgh, 4,318 units of RBCs and 4,788 units of platelets were administered during 366 OLT performed in adults. This results in a mean of 25 units of RBCs and 30 units of platelets per operation. The majority of adult liver transplant patients receive multiple transfusions of whole blood and/or blood components during their pretransplant course because of complications relating to their original disease. The exposure of these patients to different antigens from random donors facilitates the development of alloimmunization. The heightened alloimmune state can be identified by preoperative values of panel reacting antibodies (PRA). Since platelets possess the HLA antigens of donor specificity, platelets may function as the target of host antibodies, resulting in platelet alteration and subsequent dysfunction. Thus, the effect of alloimmunization on platelet function may be one of the factors responsible for significant blood loss after large transfusions of different blood components. In this retrospective study we compared blood loss and platelet transfusion during OLT with preoperative alloimmunization against random donor antigens, indicated by PRA values

    The application of statistical network models in disease research

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    This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.Host social structure is fundamental to how infections spread and persist, and so the statistical modelling of static and dynamic social networks provides an invaluable tool to parameterise realistic epidemiological models. We present a practical guide to the application of network modelling frameworks for hypothesis testing related to social interactions and epidemiology, illustrating some approaches with worked examples using data from a population of wild European badgers Meles meles naturally infected with bovine tuberculosis. Different empirical network datasets generate particular statistical issues related to non-independence and sampling constraints. We therefore discuss the strengths and weaknesses of modelling approaches for different types of network data and for answering different questions relating to disease transmission. We argue that statistical modelling frameworks designed specifically for network analysis offer great potential in directly relating network structure to infection. They have the potential to be powerful tools in analysing empirical contact data used in epidemiological studies, but remain untested for use in networks of spatio-temporal associations. As a result, we argue that developments in the statistical analysis of empirical contact data are critical given the ready availability of dynamic network data from bio-logging studies. Furthermore, we encourage improved integration of statistical network approaches into epidemiological research to facilitate the generation of novel modelling frameworks and help extend our understanding of disease transmission in natural populations.M.J.S. is funded by a NERC standard grant (NE/M004546/1) awarded to R.A.M., D.P.C., D.J.H. and M.B., with the APHA team at Woodchester Park, UK (lead scientist is R.J.D.) as project partners

    Social structure contains epidemics and regulates individual roles in disease transmission in a group-living mammal

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    This is the final version. Available from Wiley via the DOI in this record. Data accessibility: The original weighted adjacency matrix for the high‐density population of European badgers, as well as code used for simulating networks and disease simulations can be found online https://doi.org/10.5061/dryad.49n3878.Population structure is critical to infectious disease transmission. As a result, theoretical and empirical contact network models of infectious disease spread are increasingly providing valuable insights into wildlife epidemiology. Analyzing an exceptionally detailed dataset on contact structure within a high-density population of European badgers Meles meles, we show that a modular contact network produced by spatially structured stable social groups, lead to smaller epidemics, particularly for infections with intermediate transmissibility. The key advance is that we identify considerable variation among individuals in their role in disease spread, with these new insights made possible by the detail in the badger dataset. Furthermore, the important impacts on epidemiology are found even though the modularity of the Badger network is much lower than the threshold that previous work suggested was necessary. These findings reveal the importance of stable social group structure for disease dynamics with important management implications for socially structured populations.Natural Environment Research Council (NERC
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