Pathologic basis of antibody-mediated organ transplant rejection: from pathogenesis to diagnosis.

PURPOSE OF REVIEW: Although antibody-mediated rejection of clinical organ transplants has been recognized more than a half-century ago, our understanding of its pathological/clinical phenotypes has dramatically increased over the past decade. This review highlights the pathological/clinical spectrum of ABMR and discusses its microscopic pathology in relationship with pathogenesis. RECENT FINDINGS: Newly recognized pathological manifestations of ABMR are: (1) C4d-negative active ABMR, which cannot be definitely diagnosed by current diagnostic systems and often remains underdetected. Novel molecular diagnostic tests can fill this diagnostic gap but these new tests are yet to be prepared for routine application; (2) antibody-mediated vascular rejection, which is misclassified by the current Banff Classification, is therefore inadequately treated and has a high risk for transplant failure; and (3) subclinical (insidious) microvascular inflammation, which can be with or without complement activation, predicts progression to chronic rejection, transplant dysfunction, and failure. SUMMARY: A major progress has been made in understanding of ABMR of clinical transplants in the last 5 years. New pathology types of ABMR are not appropriately classified and updates to the Banff diagnostic criteria are required. Better diagnosis would help develop effective antiantibody treatment strategies and improve long-term outcomes for patients.

Within-individual hematocrit variations and self-monitoring of blood glucose.

Many self-monitoring of blood glucose (SMBG) systems have generated artefactually increased glucose results in low-hematocrit patients (e.g., intensive care unit and renal failure patients); conversely, these devices could produce artefactually decreased glucose results in high-hematocrit patients (e.g., neonates). The introduction of hematocrit-independent SMBG systems permits more accurate testing in anemic or polycythemic individuals. In this issue of Journal of Diabetes Science and Technology, Ramljak and coauthors have created glucose bias graphs for 19 common SMBG devices and declared certain systems to be optimally accurate because of insensitivity to hematocrit variation over a broad hematocrit range. Luckily, the average within-individual variation of hematocrit is low (between 2.9 and 3.3%). As such, a larger spectrum of SMBG devices can be regarded as optimally hematocrit independent.