Serum multi-trace elements and post-stroke cognitive impairment: a prospective observational cohort study

Abstract

Post-stroke cognitive impairment (PSCI) significantly affects stroke survivors. Identifying modifiable risk factors for PSCI is essential. Serum multi-trace elements are crucial for neurological function but vary in concentration among older adults. It remains unclear whether increasing multi-trace elements can reduce the incidence of PSCI. We investigated the associations between baseline serum multi-trace elements and PSCI. The Montreal Cognitive Assessment defined PSCI. We used logistic regression analyses to evaluate the association between serum multi-trace elements and PSCI. Subsequently, we assessed the associations between serum multi-trace elements and three different cognitive domains using the Kruskal-Wallis test. We further evaluated improvements in the predictive ability of serum multi-trace elements. Finally, 626 patients (mean age: 62.85 ± 7.54 years) were followed up for a median of 1.2 years. Lower concentrations of serum iron (odds ratio [OR] = 2.498, 95% confidence interval [CI]: 1.505-4.145) and zinc (OR = 2.015, 95% CI: 1.233-3.293) were associated with a higher PSCI risk. Higher concentrations of serum iron (OR = 0.368, 95% CI: 0.227-0.595) and magnesium (OR = 0.273, 95% CI: 0.164-0.454), along with lower concentrations of serum copper (OR = 0.544, 95% CI: 0.34-0.872), were significantly correlated with a lower PSCI risk. Cognitive impairments varied across multi-trace elements. Serum iron affected wider cognition, while magnesium and copper levels were strongly associated with language and executive function. Adding serum multi-trace elements to the conventional model improved PSCI risk reclassification (area under curve: 0.676-0.718). Multi-trace elements may influence PSCI progression. This study was registered with the Chinese Clinical Trial Registry (URL: https://www.chictr.org.cn/ ; unique identifier: ChiCTR1900022675).

Fig. 1. Grouping flowchart of the study participants.

AIS acute ischemic stroke, PSCI post-stroke cognitive impairment. PSNCI post-stroke non-cognitive impairment.

Fig. 2. Association of serum iron and zinc quintiles with PSCI risk.

Incidence rates, odds ratios (ORs), and 95% confidence intervals (CIs) of PSCI by quintiles (Q1, Q2, Q3, Q4, Q5) of serum iron A and zinc B in T1. Iron (μmol/L): Q1 = 0.7–8.0; Q2 = 8.1–9.5; Q3 = 9.6–10.2; Q4 = 10.2–11.3; Q5 = 11.3–12.3; Zinc (μmol/L): Q1 = 3.9–10.0; Q2 = 10.1–10.6; Q3 = 10.6–11.0; Q4 = 11.0–11.4; Q5 = 11.4–11.6. PSCI post-stroke cognitive impairment.

Fig. 3. Cognitive performance across multi-trace elements in PSCI patients.

Cognitive impairment features in PSCI by serum concentrations of iron A, magnesium B, zinc C, and copper D. Auditory verbal learning test (AVLT, delayed free recall and recognition tests), Boston Naming Test (BNT), animal fluency test (AFT), and Shape Trails Test (STT, A & B). PSCI post-stroke cognitive impairment. *P < 0.05, **P < 0.01, ***P < 0.001.

Fig. 4. Receiver operator characteristic (ROC) curves for prediction of post-stroke cognitive impairment (PSCI).

The green curve represents the conventional model, including age, sex, body mass index (kg/m²), smoking status, drinking status, and vascular risk factors (hypertension, diabetes mellitus, hyperlipidemia, previous stroke, coronary artery disease, and atrial fibrillation). The blue curve represents the conventional model + multi-trace elements. AUC area under the curve.