Joint Effect of Rapid Kidney Function Decline and Depressive Symptom Trajectories on New-onset Stroke: A Prospective Study Based on the CHARLS Cohort

Technical Summary: Joint Effect of Rapid Kidney Function Decline and Depressive Symptom Trajectories on New-onset Stroke

Problem Statement
Stroke remains a leading cause of global disability and mortality, with a significant "residual risk" persisting despite the management of conventional cardiovascular risk factors. Current literature suggests that static baseline measurements (e.g., a single eGFR value or baseline depression status) fail to capture the dynamic, progressive nature of microvascular injury and psychological deterioration that may precede cerebrovascular events. Furthermore, while chronic kidney disease (CKD) and depression are independently linked to stroke, the synergistic impact of their concurrent longitudinal trajectories—specifically rapid kidney function decline (RKFD) and increasing depressive symptoms (IDS)—on incident stroke risk remains poorly understood. Existing prediction models often overlook these dynamic "brain-kidney-psychological" interactions, limiting their utility for early risk stratification.

Methodology
This prospective study utilized data from the China Health and Retirement Longitudinal Study (CHARLS), a nationally representative cohort of Chinese adults aged ≥45 years.

• Population: The final analysis included 5,452 participants who were free of stroke at baseline (2011–2012) and had complete data for renal function and depressive symptoms. Participants with baseline eGFR <60 mL/min/1.73 m² or pre-existing stroke were excluded.
• Exposure Definition:
  • Rapid Kidney Function Decline (RKFD): Defined as an annual estimated glomerular filtration rate (eGFR) decline of ≥3 mL/min/1.73 m² between 2012 and 2015.
  • Increasing Depressive Symptoms (IDS): Defined as an increase of ≥3 points in the 10-item Center for Epidemiologic Studies Depression Scale (CES-D-10) score between 2012 and 2015.
• Outcome: Incident stroke was identified via self-reported physician diagnosis during 2018 or 2020 follow-ups.
• Statistical Analysis: The study employed multivariate logistic regression to assess independent and joint associations, adjusting for demographics, lifestyle factors, cardiometabolic conditions, and biomarkers (CRP, uric acid). Restricted cubic spline (RCS) analysis evaluated dose-response relationships. Interaction effects were tested using multiplicative terms, and subgroup analyses were conducted across various strata (e.g., sex, baseline depression, uric acid levels). Predictive performance was evaluated using AUC, Akaike Information Criterion (AIC), and Decision Curve Analysis (DCA).

Key Results

• Incidence: During the follow-up period, 445 participants (8.2%) developed incident stroke.
• Independent Associations:
  • IDS: Showed a robust, independent association with increased stroke risk (Adjusted OR = 1.53, 95% CI: 1.23–1.88).
  • RKFD: Demonstrated a positive but borderline significant association with stroke risk after full adjustment (Adjusted OR = 1.22, 95% CI: 0.98–1.53, P = 0.081).
• Joint Effect: Participants with concurrent RKFD and IDS exhibited the highest risk of stroke (Adjusted OR = 2.08, 95% CI: 1.49–2.90), indicating a significant synergistic effect compared to those with neither condition. The risk was significantly elevated even in the "IDS-only" group (OR = 1.38), whereas "RKFD-only" did not reach statistical significance.
• Stratified Findings: The synergistic effect was particularly pronounced in specific subgroups:
  • Women: OR = 2.37 (95% CI: 1.52–3.68).
  • Participants without baseline depression: OR = 2.36 (95% CI: 1.57–3.55).
  • Individuals with hyperuricemia: OR = 2.45 (95% CI: 1.58–3.79).
• Predictive Utility: Incorporating RKFD and IDS into a stroke risk prediction model significantly improved discrimination (AUC) and clinical net benefit compared to models based solely on traditional risk factors.

Significance and Claims
The authors claim that this study provides new evidence supporting a transition from "static screening" to "dynamic monitoring" in stroke prevention. Key contributions include:

1. Dynamic Trajectories: Demonstrating that the progression of renal dysfunction and depressive symptoms, rather than just baseline status, are critical predictors of stroke risk.
2. Synergistic Interaction: Establishing that the co-occurrence of RKFD and IDS creates a "body-mind" interaction network that more than doubles stroke risk, suggesting shared pathophysiological mechanisms such as systemic inflammation, neuroendocrine dysregulation (HPA axis), and endothelial dysfunction.
3. Clinical Application: The study proposes that integrating these dynamic indicators into clinical practice can enhance early risk identification, particularly for vulnerable subgroups like women and those with hyperuricemia. The development of a nomogram incorporating these factors offers a tool for individualized risk estimation.
4. Preventive Strategy: The findings support an integrated management approach where patients with worsening depressive symptoms receive closer renal and vascular surveillance, and those with rapid kidney decline undergo routine psychological evaluation.

The paper concludes that while observational in nature and limited by self-reported stroke data, the results highlight the necessity of monitoring longitudinal changes in both renal and psychological health to address the residual risk of stroke in aging populations.