Vital-affective symptom connectivity during electroconvulsive therapy distinguishes depression remission outcomes: A cross-lagged panel network study

Abstract Background Electroconvulsive therapy (ECT) is effective for depression, but symptom dynamics during treatment remain unclear. Network approaches may clarify symptom relations and identify patterns linked to remission. Objective Examining symptom dynamics during ECT using temporal network modeling and comparing baseline and temporal symptom networks between remitters and non-remitters. Methods Using the Dutch ECT Cohort (N = 857, unipolar/bipolar depression), we examined seven harmonized symptoms from the Hamilton Depression Rating Scale (HDRS-17) and Montgomery–Åsberg Depression Rating Scale (MADRS) over the first five weeks of treatment. We estimated baseline networks using partial correlations and temporal networks using Cross-Lagged Panel Network analysis, which quantified each symptom's in-prediction and out-prediction. Between remitters (N=413) and non-remitters (N=379), baseline networks were compared using the Network Comparison Test, while temporal networks were compared via network density, Jaccard overlap, and edge correlations. Results In the full sample (65.2% female, mean age 61.3 ± 15.5 years), suicidal thoughts exerted the strongest influence on other symptoms (i.e., highest out-prediction). Baseline networks did not differ by outcome, but temporal networks did: remitters showed greater density than non-remitters (χ² = 8.20, p < 0.01), with low overlap in edges (Jaccard = 0.25), and non-significant edge-weight correlations (r = 0.16; p=0.46) between groups. Remitters displayed integrated affective-vital symptom connections, while non-remitters showed fragmented subnetworks. Conclusions Reductions in suicidal thoughts preceded broader symptom improvements, suggesting this symptom warrants monitoring. Remitters showed coordinated symptom reduction where affective and vital symptoms reinforced each other, while non-remitters showed independent reduction. These findings provide insights into symptom dynamics during ECT.