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https://hdl.handle.net/11499/52786
Title: | A comprehensive investigation of novel and traditional inflammatory and metabolic markers as predictive indicators in psoriasis | Authors: | Metin, Zuhal Tur, Kagan Durmaz, Koray Akogül, Serkan Akca, Hanife M. M. Imren, Işıl G. Demir, Nazime B. O. Ozkoca, Defne |
Keywords: | C-Reactive-Protein Vitamin-D Uric-Acid Risk Resistance Severity Health |
Publisher: | Wiley | Abstract: | Background Psoriasis is a chronic inflammatory and papulosquamous dermatological disorder. While previous studies have discussed certain inflammatory markers for diagnosing and monitoring psoriasis, there is an absence of comprehensive research encompassing both novel and traditional inflammatory markers, as well as metabolic markers, in relation to psoriasis. Methods A total of 209 individuals participated, including 54 psoriasis patients and 155 controls. Psoriasis Area Severity Index (PASI) was calculated for the patient group. Potential predictive markers for psoriasis were identified: Uric acid/HDL ratio (UHR), D-dimer/albumin ratio (DAR), fibrinogen/albumin ratio (FAR), erythrocyte sedimentation rate, CRP, WBC, HOMA-IR, and vitamin D levels. Differences between groups and correlations with PASI and each other were analyzed using the Mann-Whitney U test and Spearman correlation coefficient. Results The results indicate that the patient group exhibited statistically significantly higher levels of UHR, FAR, CRP, WBC, and HOMA-IR. Upon analyzing the correlations between PASI and the identified markers, statistically significant positive correlation with WBC and negative correlation with vitamin D were observed. The correlations of PASI with other markers did not reach statistical significance. It should be underlined that our study was conducted in a predominantly mild-to-moderate patient population. Conclusions The absence of specificity of these markers for psoriasis limits their practical application. However, the development of new objective measures by using them in combination with specific data such as PASI will provide significant benefits in terms of disease diagnosis, follow-up, and treatment. | URI: | https://doi.org/10.1111/ijd.16813 https://hdl.handle.net/11499/52786 |
ISSN: | 0011-9059 1365-4632 |
Appears in Collections: | Fen Fakültesi Koleksiyonu PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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