Increased CD64 expression on polymorphonuclear neutrophils indicates infectious complications following solid organ transplantation

Grey, Daniel J. R.; Sack, Ulrich; Scholz, Markus; Knaack, Heike; Stephan, Frank; Oppel, Christoph; Luderer, Daniel; Fangmann, J.; Emmrich, Frank; Kamprad, Manja

doi:10.1002/cyto.a.21049

Cited by 9 publications

(16 citation statements)

References 64 publications

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“…The performance of the models was assessed by calculating the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Statistical analysis was performed using SPSS version 22.0 (SPSS, Inc., Chicago, IL, USA). A P-value of < 0.05 was considered to be statistically significant.…”

Section: Discussionmentioning

confidence: 99%

The Study of the Association between Immune Monitoring and Pneumonia in Kidney Transplant Recipients Through Machine Learning Models

Peng

Gong

Han

et al. 2020

Preprint

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Background: Kidney transplantation is the optimal treatment to cure the patients with end-stage renal disease (ESRD). However, the infectious complication, especially pneumonia, is the main cause of mortality in the early stage. Immune monitoring by relevant biomarkers provides direct evidence of immune status. We aimed to study the association between immune monitoring and pneumonia in kidney transplant patients through machine learning models. Methods: A total of 146 patients receiving the immune monitoring panel in our center, including 46 pneumonia recipients and 100 stable recipients, were retrospectively reviewed to develop the models. All the models were validated by external data containing 10 pneumonia recipients and 32 stable recipients. The immune monitoring panel consisted of the percentages and absolute cell counts of CD3+CD4+ T cells, CD3+CD8+ T cells, CD19+ B cells and natural killer (NK) cells, and median fluorescence intensity (MFI) of human leukocyte antigen (HLA)-DR on monocytes and CD64 on neutrophils. The machine learning models of support vector machine (SVM), logistic regression (LR), multi-layer perceptron (MLP) and random forest (RF) were applied for analysis.Results: The pneumonia and stable groups showed significant difference in cell counts of each subpopulation and MFI of monocyte HLA-DR and neutrophil CD64. The SVM model by monocyte HLA-DR (MFI), neutrophil CD64 (MFI), CD8+ T cells (cells/μl), NK cells (cell/μl) and TBNK (T cells, B cells and NK cells, cells/μl) had the best performance with the average area under the curve (AUC) of 0.940. The RF model best predicted the patients who would progress into severe pneumonia, with the average AUC of 0.760. All the models had good performance validated by external data.Conclusions: The immune monitoring panel was tightly associated with pneumonia in kidney transplant recipients. The models developed by machine learning techniques identified patients at risk and predicted the prognosis. Based on the results of immune monitoring, better individualized therapy might be achieved.

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Section: Discussionmentioning

confidence: 99%

The Study of the Association between Immune Monitoring and Pneumonia in Kidney Transplant Recipients Through Machine Learning Models

Peng

Gong

Han

et al. 2020

Preprint

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“…Given that the neutrophil is the major cellular component of acute response to infection, the CD64 expression by neutrophil granulocytes has also been shown to be a useful parameter for diagnostic evaluation of suspect postoperative complications in transplanted patients [6]; the high diagnostic value for infectious complications shown in other studies is not influenced by immunosuppression in this population. The use of CD64 expression by neutrophil granulocytes as an infection marker also in the postoperative course of transplanted patients should allow early determination of further treatment already within 24 hours without waiting for the definitive microbiologic culture results [9].…”

Section: Clinical Indicationmentioning

confidence: 98%

“…Given that the neutrophil is the major cellular component of acute response to infection, the detection of molecular changes of neutrophil granulocytes' activation could provide a rapid and sensitive indicator of a systemic inflammatory response (1,2,(9)(10)(11)14). Diagnostic use of a quantitative flow cytometric assay for expression strength of CD64 by neutrophil granulocytes as an in vitro indicator of neutrophil granulocytes' activation seems to be a valuable marker as an additional utility in the evaluation of patients with suspected acute inflammation or infection (1,3 CD64 expression by neutrophil granulocytes has also been shown to be a useful parameter for diagnostic evaluation of suspect postoperative complications in transplanted patients (6); the high diagnostic value for infectious complications shown in other studies is not influenced by immunosuppression in this population. The use of CD64 expression by neutrophil granulocytes as an infection marker also in the postoperative course of transplanted patients should allow early determination of further treatment already within 24 h without waiting for the definitive microbiologic culture results (9).…”

Section: Clinical Indicationmentioning

confidence: 99%

“…In comparison to various other parameters including C-reactive protein (CRP), CD64 expression by neutrophil granulocytes has a very good performance as summarized in Ref. [6) and it is shown there for transplanted patients in detail. Regarding procalcitonin, at least in preterm children, CD64 is even better than procalcitonin (PCT) (17).…”

Section: Clinical Indicationmentioning

confidence: 99%

“…Expression of the Fc receptor CD64 on their surface has been shown to correlate with complications in sepsis [1][2][3], infectious diseases [4;5], and even in solid organ transplanted patients [6].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

CD64 expression by neutrophil granulocytes

Sack

2015

Cytometry Part B Clinical

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Monocytes and macrophages in flow: an ESCCA initiative on advanced analyses of monocyte lineage using flow cytometry

Lambert

Preijers

Demirel

et al. 2015

Cytometry Part B Clinical

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In April 2013, a symposium was organized to highlight different aspects of differentiation and activation of the monocyte-macrophage lineage as analyzed on the flow cytometer. Characterization of this lineage requires knowledge of the maturation process from their progenitors that are present in bone marrow up to the mature monocytic cells in peripheral blood, because each monocytic lineage cell with an aberrant phenotype refers to the corresponding maturation stage. A standardized quantitative analysis will facilitate the monitoring of the pathological processes and the clinical features, such as the outcome of treatment. However, changes in marker expression by variation in intensity, asynchronism, and lineage infidelity must be considered. The dynamics of normal marker expressions in early differentiation stages, e.g. molecules like HLA II, CD64 or CD14, give rise to a hypothesis on their possible role in monocyte ontogeny. Besides their usual role in tissue homeostasis, mature macrophages may also play a similar role in hematopoiesis. This meeting highlighted the large potential of flow cytometric tools available for monitoring of all these aspects in the monocytic and macrophage cell lineage. © 2015 International Clinical Cytometry Society.

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Increased CD64 expression on polymorphonuclear neutrophils indicates infectious complications following solid organ transplantation

Cited by 9 publications

References 64 publications

The Study of the Association between Immune Monitoring and Pneumonia in Kidney Transplant Recipients Through Machine Learning Models

The Study of the Association between Immune Monitoring and Pneumonia in Kidney Transplant Recipients Through Machine Learning Models

CD64 expression by neutrophil granulocytes

Monocytes and macrophages in flow: an ESCCA initiative on advanced analyses of monocyte lineage using flow cytometry

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