Letter to the Editor: Advancing predictive psychiatry in perinatal care: The imperative of multidimensional modeling for postpartum anxiety following preeclampsia

Table 1 Evolution of predictive indicators for postpartum anxiety in high-risk obstetric populations

Model generation	Typical predictors	Theoretical focus	Key limitation	Exemplary study (AUC)1
First (psychosocial)	Past anxiety/depression, low social support, low income, low resilience	Psychosocial stress and vulnerability	Neglects biological context of medical comorbidities	AUC approximately 0.72[3]
Second (obstetric-biological)	Pregnancy complications (PE, GDM), biomarker levels (Hct, CRP), delivery trauma	Specific disease pathophysiology and stress	Often cross-sectional or single-center; biomarkers may be proximal	AUC = 0.908[4]
Third (integrated multi-omics)	Polygenic risk scores, epigenetic markers (DNA methylation), proteomic/metabolomic profiles, neuroimaging data	Systems biology and neurodevelopment	Costly, complex analysis, requires large cohorts; clinical feasibility low	Emerging studies (e.g., integration of PRS for depression)[14]
Trend	Increasing dimensionality, moving from readily available to mechanistic biomarkers, integrating data types

¹Area under the curve values are study-specific and reflect performance under original conditions; they are not directly comparable across studies due to differences in populations, outcome definitions, timing, and modeling methods.

PE: Preeclampsia; GDM: Gestational diabetes mellitus; Hct: Hematocrit; CRP: C-reactive protein; PRS: Polygenic risk score; AUC: Area under the curve.