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Sökning: WFRF:(Kosieradzki M)

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  • Kwiatkowski, A., et al. (författare)
  • Chlamydia pneumoniae infection: an additional factor for chronic allograft rejection.
  • 2006
  • Ingår i: Transplantation Proceedings. - : Elsevier BV. - 0041-1345. ; 38:1, s. 108-111
  • Tidskriftsartikel (refereegranskat)abstract
    • Introduction Chronic rejection (CHR) of organ allografts, one of the most significant problems in modern transplantation, is not fully understood. This study sought to evaluate the influence of selected parameters on late kidney transplant function. Patients and Method The studied group consisted of eighty-six patients who received allogeneic transplants between 1988 and 1999 for leukocyte Chlamydia pneumoniae–DNA, immunoglobulin (Ig)A/IgG anti–C pneumoniae, blood lipids, ischemic damage in the donor and during organ preservation, HLA mismatch, and acute rejection episodes. Results Eighty-six patients were segregated as 26 patients (30%) with histologically proven chronic graft rejection (CHR[+]) and 59 patients (70%) without (CHR[−]). The presence of C pneumoniae–DNA in peripheral blood leukocytes was significantly more frequent in CHR(+) than CHR(−) group (46% vs 20%). Patients with leukocytes positive for C pneumoniae–DNA more frequently (50%) had CHR than patients negative for C pneumoniae–DNA (22%). CHR(+) patients showed significantly lower HDL levels (47 mg/dL vs 58 mg/dL) and higher triglyceride levels (193 mg/dL vs 148 mg/dL). To study the cumulative effect of differences between the CHR(+) and CHR(−) groups, we applied a multiple binary logistic regression analysis. An econometric model enabled us to calculate the probability of CHR for a given patient taking into account covariates chosen by means of stepwise selection: the presence of C pneumoniae–DNA in blood leukocytes, the use of continuous pulsatile perfusion in hypothermia, myocardial infarction occurrence, and triglyceride concentrations. Conclusion The presence of C pneumoniae–DNA in peripheral blood leukocytes increased the risk of CHR, which may be predicted by a multifactor analysis of chosen parameters.
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