Comparison of clinical features and inflammatory factors between patients with bipolar depression and unipolar depression

Background To compare the differences in clinical features and inflammatory factors of unipolar depression and bipolar depression, and to explore potential clinical features and peripheral blood biological markers are used to distinguish unipolar depression and bipolar depression. And to further build a prediction model. Methods The inpatients of Shanghai Mental Health Center from June 2022 to June 2024 were selected as the study objects. According to the diagnosis of hospitalization records, 274 cases were divided into unipolar depression group and 128 cases were bipolar depression group. A total of 128 patients were enrolled in each of the two groups by the propensity score matching method. The demographic data, clinical characteristics and biological indicators of the two groups were compared. Biological markers include neutrophil/lymphocyte ratio (NLR), monocyte/lymphocyte ratio (MLR), platelet/lymphocyte ratio (PLR), C-reactive protein (CRP), serum triodothyronine (T3), thyroxin (T4), free thyroid hormone (fT3, fT4), and thyroid stimulating hormone (TSH) ), complement 3(C3), complement 4(C4), immunoglobulin A(IgA), immunoglobulin G(IgG), immunoglobulin M(IgM). Binomial Logistic regression analysis was used to control confounding factors to explore the predictors of bipolar depression. Receiver operating characteristic (ROC) curve was used to analyze the predictive value of clinical features and biological indicators in bipolar depression. Results There were statistical differences in life events (χ ²  = 15.397, P  = 0.000), CRP (Z = 6.717, P  = 0.000), TSH (Z = 1.988, P  = 0.047), C3 (Z = 5.682, P  = 0.000), C4 (Z = 4.216, P  = 0.000), IgM (Z = 2.304, P  = 0.021) between unipolar depression group and bipolar depression group. Logistic regression analysis showed that life events (OR = 4.552, 95%Cl = 2.238∼9.257), CRP (OR = 13.886, 95%Cl = 5.290∼36.452), IgM (OR = 0.561, 95%Cl = 0.325∼0.970) were associated with bipolar depression. ROC curve analysis showed that the AUC of Logistic regression model predicting bipolar depression was 0.806, with a sensitivity of 61.7%, and a specificity of 85.9%. Conclusions Compared with unipolar depression, no life events, higher levels of CRP and lower levels of IgM were related factors of bipolar depression, and the combined diagnosis model is more effective to distinguish unipolar depression from bipolar depression.