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The Use of New Hematological Markers in the Diagnosis of Alopecia Areata
Alopecia areata (AA) is a non-cicatricial inflammatory and autoimmune hair loss disease. In recent studies, it has been reported that hematological parameters can be used as oxidative stress markers in the diagnosis of many inflammatory diseases due to their low cost and widespread use. In this stud...
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Published in: | Dermatology practical & conceptual 2023-04, Vol.13 (2), p.e2023118 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that cite this one |
Online Access: | Get full text |
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Summary: | Alopecia areata (AA) is a non-cicatricial inflammatory and autoimmune hair loss disease. In recent studies, it has been reported that hematological parameters can be used as oxidative stress markers in the diagnosis of many inflammatory diseases due to their low cost and widespread use.
In this study, it was aimed to reveal the significant cut-off points of hematological inflammatory markers in AA that can guide clinicians in clinical practice and determine how many times they increase the risk of disease.
The present study is retrospective case-control type. Seventy patients with AA and seventy healthy controls were included in the study. The hematological parameters in both groups were evaluated retrospectively.
Hemoglobulin, monocyte, platelet, monocyte high-density lipoprotein cholesterol (HDL-C) ratio (MHR), monocyte lymphocyte ratio (MLR), platelet lymphocyte ratio (PLR) were high in patients with AA, while the number of lymphocytes was low. In ROC analysis, the optimal cut-off values for the diagnosis of AA were as follows: MLR 0.216, MHR 0.010, and PLR 111.715. In regression analysis, being above the following values of MLR 0.216, MHR 0.010, and PLR 111.715 increased the risk of developing AA by 6.3, 3.8, and 2.7 times, respectively.
It was seen that MHR and PLR, especially MLR, can significantly increase the risk of developing the disease in AA and can also be used as diagnostic markers. |
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ISSN: | 2160-9381 2160-9381 |
DOI: | 10.5826/dpc.1302a118 |