Objective To investigate the application value of serum lithium level in predicting relapse within 12 months after lithium maintenance therapy in patients with bipolar disorder (BD).

Methods Clinical data of BD patients who received lithium maintenance therapy and were followed up for at least 12 months in Sanya Second People's Hospital from January 1, 2018 to December 31, 2023 were retrospectively collected. Patients were divided into relapse and non-relapse groups according to whether BD relapsed within 12 months. Logistic regression was used to analyze the influencing factors of relapse within 12 months, and receiver operating characteristic (ROC) curves and the area under the curve (AUC) were used to evaluate the predictive value of these factors.

Results A total of 200 BD patients were included, with 80 cases in the relapse group and 120 cases in the non-relapse group. Multivariate Logistic regression analysis showed that increased number of previous episodes [OR=2.549, 95%CI (1.533, 4.239), P < 0.001] and elevated thyroid-stimulating hormone (TSH) level [OR=2.295, 95%CI (1.349,3.905), P=0.002] were independent risk factors for BD relapse, whereas elevated serum lithium level [OR=0.019, 95%CI (0.004, 0.087), P < 0.001] was a protective factor for BD relapse. ROC curve analysis showed that serum lithium level, number of previous episodes, and TSH level all had good predictive ability, with AUC values of 0.951, 0.833, and 0.729, respectively. The multivariable model integrating these indicators showed the optimal predictive performance [AUC=0.977, 95%CI (0.961, 0.993)].

Conclusion Serum lithium level, TSH level, and the number of previous episodes are key factors affecting relapse risk after lithium maintenance therapy in BD patients. Maintaining serum lithium level at ≥ 0.602 mmol/L can significantly reduce relapse risk. The multifactorial prediction model established by combining thyroid function and disease course information has excellent discriminative ability, and may provide a basis for early clinical identification of high-risk patients and formulation of individualized maintenance regimens.

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