Purposes: This study aimed to analyze the predictive ability of the complete blood count and derived inflammatory indicators for BD patients with different states to identify potential biomarkers.
Methods: We collected the data of BD in-patients from January 2021 to March 2023. The complete blood count and derived inflammatory indicators were computed by univariate analysis, logistic regression analysis, and receiver operating characteristic (ROC) curve analysis.
Results: In terms of BD patients, the levels of MON (p<0.0001), hs-CRP ( = 0.018), and NLR ( = 0.002) were independent risk factors in logistic regression analysis, as well as the cut-off values were 0.405 10/L, 2.600 mg/L, and 2.321, respectively. Regarding BD-M patients, the levels of MON (<0.0001), hs-CRP ( = 0.012), and NLR ( = 0.002) were predictors in logistic regression analysis, and the cut-off values were, respectively, 0.505 10/L, 2.600 mg/L, and 2.620. Additionally, the levels of NLR ( = 0.006) and MHR (<0.0001) were important indicators for BD-D and the cut-off values were 1.735 and 0.487, respectively. Furthermore, our findings showed that the level of MON ( = 0.001) was related to BD-mixed and the cut-off value was 0.340 10/L. Notably, MON+hs-CRP + NLR, MON+hs-CRP + NLR, and NLR + MHR had the highest diagnostic accuracy to predict BD, BD-M, and BD-D patients, respectively.
Conclusion: Our findings showed that distinct inflammatory indicators were closely associated with BD and its different states. Additionally, we also identified their cut-off values and optimal combined predictive indicators in different states of BD, helping us improve diagnostic accuracy and better assess them to manage early targeted interventions.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10354814 | PMC |
http://dx.doi.org/10.3389/fpsyt.2023.1219151 | DOI Listing |
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