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Background: Understanding the association of peripheral inflammation and post-stroke depressive symptomology (PSDS) might provide further insights into the complex etiological mechanism of organic depression. However, studies focusing on the longitudinal patterns of PSDS were limited and it remained unclear whether peripheral inflammation influences the occurrence and development of PSDS., Methods: A total of 427 prospectively enrolled and followed ischemic stroke patients were included in the analytical sample. Depressive symptomology was assessed on four occasions during 1 year after ischemic stroke. Peripheral inflammatory proteins on admission and repeated measures of peripheral immune markers in three stages were collected. Latent class growth analysis (LCGA) was employed to delineate group-based trajectories of peripheral immune markers and PSDS. Multinomial regression was performed to investigate the association of peripheral inflammation with PSDS trajectories., Results: Four distinct trajectories of PSDS were identified: stable-low (n = 237, 55.5 %), high-remitting (n = 120, 28.1 %), late-onset (n = 44, 10.3 %), and high-persistent (n = 26, 6.1 %) PSDS trajectories. The elevation of peripheral fibrinogen on admission increased the risk of high-persistent PSDS in patients with early high PSDS. Additionally, chronic elevation of innate immune levels might not only increase the risk of high-persistent PSDS in patients with early high PSDS but also increase the risk of late-onset PSDS in patients without early high PSDS. The elevation of adaptive immune levels in the convalescence of ischemic stroke may contribute to the remission of early high PSDS., Conclusions: Peripheral immunity could influence the development of PSDS, and this influence might have temporal heterogeneity. These results might provide vital clues for the inflammation hypothesis of PSD., Competing Interests: Declaration of competing interest All authors declare that they have no conflicts of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Poststroke cognitive impairment (PSCI) is highly prevalent in stroke survivors and correlated with unfavorable clinical outcomes. This study aimed to identify the neural substrate of PSCI using atlas-based disconnectome analysis and assess the value of disconnection score, a baseline measure for stroke-induced structural disconnection, in PSCI prediction., Methods: A multicenter prospective cohort of 676 first-ever patients with acute ischemic stroke was enrolled from 3 independent hospitals in China. Sociodemographic, clinical, and neuroimaging data were collected at acute stage of stroke. Cognitive assessment was performed at 3 months after stroke. Voxel-wise and tract-wise disconnectome analysis were performed to uncover the strategic structural disconnection pattern for global PSCI. Disconnection score was calculated for each participant in leave-one-dataset-out cross-validation. Multivariable logistic regression was performed for the association between disconnection score and PSCI. Prediction models with and without disconnection score were developed, cross-validated, and compared in terms of discrimination and goodness-of-fit., Results: Compared with lesions of non-PSCI, those of PSCI were more likely to have fiber connections with left prefrontal cortex and left deep structures (thalamus and basal ganglia). Disconnection score could predict the risk and severity of PSCI during cross-validation, and was independently associated with PSCI after controlling for all baseline covariates (odds ratio, 1.38 [95% CI, 1.17-1.64]; P <0.001). Incorporating disconnection score into a reference model with 6 known predictors resulted in significant improvement in both discrimination and goodness-of-fit throughout cross-validation., Conclusions: A strategic structural disconnection pattern centered on left prefrontal cortex, thalamus, and basal ganglia is identified for global PSCI using indirect disconnectome analysis. The baseline disconnection score is independently predictive of PSCI and has significant incremental value to preexisting sociodemographic, clinical, and neuroimaging predictors., Registration: URL: http://www.chictr.org.cn/enIndex.aspx; Unique identifier: ChiCTR-ROC-17013993.

Poststroke depression (PSD) is a common complication of stroke. Brain network disruptions caused by stroke are potential biological determinants of PSD but their conclusive roles are unavailable. Our study aimed to identify the strategic structural disconnection (SDC) pattern for PSD at three months poststroke and assess the predictive value of SDC information. Our prospective cohort of 697 first-ever acute ischemic stroke patients were recruited from three hospitals in central China. Sociodemographic, clinical, psychological and neuroimaging data were collected at baseline and depression status was assessed at three months poststroke. Voxel-based disconnection-symptom mapping found that SDCs involving bilateral temporal white matter and posterior corpus callosum, as well as white matter next to bilateral prefrontal cortex and posterior parietal cortex, were associated with PSD. This PSD-specific SDC pattern was used to derive SDC scores for all participants. SDC score was an independent predictor of PSD after adjusting for all imaging and clinical-sociodemographic-psychological covariates (odds ratio, 1.25; 95% confidence interval, 1.07, 1.48; P = 0.006). Split-half replication showed the stability and generalizability of above results. When added to the clinical-sociodemographic-psychological prediction model, SDC score significantly improved the model performance and ranked the highest in terms of predictor importance. In conclusion, a strategic SDC pattern involving multiple lobes bilaterally is identified for PSD at 3 months poststroke. The SDC score is an independent predictor of PSD and may improve the predictive performance of the clinical-sociodemographic-psychological prediction model, providing new evidence for the brain-behavior mechanism and biopsychosocial theory of PSD., (© 2022. The Author(s).)

Background: Post-stroke depression (PSD) is the most common neuropsychiatric complication after stroke, seriously affecting the quality of survivors' life. As one of the important causes of PSD, neuroendocrine mechanism has been widely studied in recent years. The main objective of this study was to investigate the relationship between adrenocorticotropic hormone (ACTH) on admission and PSD at 3 months., Methods: This is a hospital-based prospective cohort study, which was conducted at three independent hospitals (Tongji Hospital, Wuhan First Hospital and Wuhan Central Hospital) between August 2018 and June 2019. A total of 768 ischemic stroke patients were finally eligible for analysis and categorized into equal tertiles according to the distribution of ACTH and the number of patients. The χ 2 -test, Mann-Whitney U -test and Kruskal-Wallis test were used to check for statistical significance. And restricted cubic spline (RCS) regression model was used to explore the non-linear relationship between continuous ACTH levels and PSD at 3 months., Results: The optimal cut-off points of ACTH were as follows: (T1) 0.32-20.55 pg/mL, (T2) 20.56-39.79 pg/mL, (T3) 39.80-143.40 pg/mL. A total of 305 patients (39.7%) were diagnosed as PSD at 3 months follow-up. Significant differences were found between the PSD and non-PSD groups in ACTH concentration (P = 0.001). After adjustment for all conventional confounders, the odds ratios of PSD were 1.735 (95% CI = 1.176-2.560, P = 0.005) for the highest tertile of ACTH and 1.496 (95% CI = 1.019-2.194, P = 0.040) for the middle tertile of ACTH, as compared with the lowest tertile. In multiple-adjusted RCS regression, continuous ACTH showed saturation effect relation with PSD risk after 31.02 pg/mL (P for nonlinear = 0.0143)., Conclusion: Higher ACTH level on admission is a significant and independent biomarker to predict the development of PSD at 3 months follow-up. Besides, saturation effect was revealed even if the underlying mechanism is unclear. For stroke patients, doctors should pay attention to the baseline ACTH for screening high-risk PSD in clinical practice., Competing Interests: The authors report no conflicts of interest for this work nor concerning the materials or methods used in this study nor the findings specified in this paper., (© 2022 Wang et al.)

Purpose: Previous studies have shown that persistent post-stroke depression (PSD) was associated with unfavorable prognosis. The aim of this multicenter prospective study was to investigate the predictors associated with persistent PSD, develop a nomogram and validate its clinical usefulness by decision curve analysis (DCA)., Patients and Methods: A total of 875 acute ischemic stroke patients from four hospitals were consecutively recruited and completed 1-year follow-ups. Sociodemographic indicators, vascular risk factors, clinical information, serum biochemical indicators and cytokines were collected on admission. The functional outcome was assessed at 1 year after stroke. Persistent depression was defined as having a presentation of depression at each follow-up points and the depressive symptoms occurring persistently since the diagnosis of depression., Results: There were 513 patients who experienced PSD during the 1-year follow-up, the cumulative incidence of PSD within 1 year was 58.6%. Persistent PSD was recorded in 289 patients, of which 59 (20.4%) result in unfavorable outcomes. The risk factors of persistent PSD in 1 year after stroke were the Hamilton Depression Scale-17 items (HAMD-17) score at admission, serum direct bilirubin and free serum thyroxine (FT4) level and activated partial thromboplastin time (APTT). Nomogram conducted based on these factors has a C-index (± standard deviation) of 0.655 ± 0.039, and the DCA demonstrated that the nomogram had a favorable clinical utility., Conclusion: We found that persistent depression after stroke in the first-year time course after stroke was associated with HAMD-17 score at admission, lower serum direct bilirubin and FT4 level, and APTT. A nomogram was developed with advisable clinical usefulness in our study., Competing Interests: All authors declare no competing interests in the work., (© 2022 Lan et al.)

Background: Post-stroke depression (PSD) is the most common psychological consequence of stroke. Increased inflammatory markers resulting from ischemic stroke may played an important role in the pathogenesis of depressive symptomology. The present study was conducted to further elucidate the relationship between stroke severity, systemic low-grade inflammation and chronic phase post-stroke depressive symptomology (CP-PSDS)., Methods: A total of 897 stroke patients were consecutively recruited in this multicenter prospective cohort study and followed up for 1 year. The analytical sample consisted of 436 patients with ischemic stroke (23.4% female, median age = 57 years) from this cohort. Serum concentrations of inflammatory markers were measured in all 436 patients with ischemic stroke, from fasting morning venous blood samples on admission. Stroke severity was evaluated using the National Institutes of Health Stroke Scale (NIHSS) on admission and post-stroke depressive symptomology (PSDS) was evaluated by 17-item Hamilton Rating Scale for Depression (HRSD)., Results: In the fully adjusted models, we observed that 1) NIHSS (Model 2: β = 0.200, 95%CI, 0.057 ∼ 0.332), fibrinogen (Model 2: β = 0.828, 95%CI, 0.269 ∼ 1.435), white blood cell counts (WBC, model 2: β = 0.354, 95%CI, 0.122 ∼ 0.577) and neutrophil counts (Model 2: β = 0.401, 95%CI, 0.126 ∼ 0.655) can independently predict the CP-PSDS after ischemic stroke onset; 2) fibrinogen (Indirect effect = 0.027, 95%CI, 0.007 ∼ 0.063, 13.4% mediated), WBC (Indirect effect = 0.024, 95%CI, 0.005 ∼ 0.058, 11.8% mediated) and neutrophil counts (Indirect effect = 0.030, 95%CI, 0.006 ∼ 0.069, 14.8% mediated) could partially mediate the association between stroke severity and CP-PSDS, and 3) stroke severity might cause CP-PSDS partly through the chain-mediating role of both fibrinogen and neutrophil counts (chain mediated effect = 0.003, 95%CI, 0.000 ∼ 0.011, p = 0.025, 1.6% mediated)., Conclusions: Findings revealed that fibrinogen, WBC and neutrophil counts may be independent predictors of CP-PSDS and partial mediators of the relationship between stroke severity and CP-PSDS among patients with ischemic stroke. In addition, the chain mediating effect of fibrinogen and neutrophil counts might play an important role in the occurrence of CP-PSDS. However, no inflammatory markers were associated with CP-PSDS in females., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Purpose: Post-stroke depression (PSD) is one of the most common and severe psychological sequelae after stroke, negatively affecting the patient's functional outcome and quality of life. Rapidly measurable biomarkers to predict PSD are pivotal for the optimized care and allocation of healthcare resources. Lactic dehydrogenase (LDH) levels are increased in patients with central nervous system (CNS) disorders such as cerebral infarction and hypoxic–ischemic encephalopathy, which may be related to the occurrence of PSD in acute ischemic stroke (AIS) patients. This study aimed to investigate whether LDH levels on admission are associated with PSD at discharge. Patients and Methods: A multicenter prospective cohort study was conducted, including all consecutive AIS patients within 7 days after symptom onset from May 2018 to October 2019. According to the distribution of LDH and the number of patients, patients were divided into equal tertiles. PSD was evaluated by DSM-V criteria and the 17-item Hamilton Rating Scale for Depression (HRSD-17) at discharge. Results: A total of 518 AIS patients were included. The optimal cut-off points of LDH were: lowest tertile (T1) 102– 159/L, middle tertile (T2) 160– 189 U/L, and upper tertile (T3) 190– 520 U/L. A total of 249 patients (48.07%) were diagnosed with PSD at discharge. After adjusting for potential confounding factors, the odds ratio of T3 PSD was 1.698 (95% CI, 1.070– 2.694, P=0.025), compared with T1. Conclusion: In summary, LDH serum levels on admission are associated with PSD at discharge. Clinicians should pay more attention to the baseline LDH level in screening for PSD at discharge. [ABSTRACT FROM AUTHOR]

Background: Fasting C-peptide (FCP) has been shown to play an important role in the pathophysiology of mood disorders including depression and schizophrenia, but it is unknown whether it also predicts post-stroke depression (PSD). This study examined the association between FCP and PSD at 6 months after acute ischemic-stroke onset among Chinese subjects.Methods: A total of 656 stroke patients were consecutively recruited from three hospitals of Wuhan city, Hubei province. Clinical and laboratory data were collected on admission. PSD status was evaluated by DSM-V criteria and 17-item Hamilton Rating Scale for Depression (HAMD-17) at 6 months after acute ischemic stroke. The χ2-test, Mann-Whitney U-test, and t-test were used to check for statistical significance. Multivariate logistic regression model was used to explore independent predictor of PSD.Results: In the univariate analysis, significant differences were found between the PSD and non-PSD groups in terms of FCP level (p = 0.009). After multivariate adjustments, FCP remained a significant independent predictor of PSD, with an adjusted odds ratio of 1.179 (95%CI: 1.040-1.337, p = 0.010).Conclusions: Higher FCP levels on admission were found to be associated with PSD at 6 months after acute ischemic-stroke onset. For stroke patients, doctors should pay attention to the baseline FCP for screening high-risk PSD in clinical practice. [ABSTRACT FROM AUTHOR]

Stroke is a leading cause of mortality and disability. This study aimed to investigate the temporal and directional relationships between post-stroke depressive symptoms and cognitive impairment using a cross-lagged panel design. Depressive symptoms and cognitive impairment are two common post-stroke complications. However, the precise underlying mechanism remains unclear despite their close relationship. Therefore, elucidating the causal relationship between these two issues is of great clinical significance for improving the poor prognosis of stroke. This study employed a hospital-based multicenter prospective cohort design. A total of 610 patients with ischemic stroke were eligible. Depressive symptoms (measured using the seventeen-item Hamilton Rating Scale for Depression) and cognitive function (measured using the Montreal Cognitive Assessment) were assessed at baseline and the 12-month follow-up. Spearman's correlation was used to examine the correlation between cognitive function and depressive symptoms. Additionally, a cross-lagged panel analysis was employed to elucidate the causal relationship between these factors after adjusting for potential covariates. The results of a four-iteration cross-lagged panel analysis substantiated a bidirectional relationship between post-stroke depressive symptoms and cognitive function over time. Specifically, higher scores for early depressive symptoms were associated with lower scores for later cognitive function; additionally, higher baseline cognitive function scores were associated with lower depressive symptom scores at a later point. This study establishes a reciprocally causal long-term relationship between depressive symptoms and cognitive function after an ischemic stroke. Therefore, interventions aimed at improving cognitive function and ameliorating depressive symptoms may positively affect both cognition and mood. Trial registration: ChiCTR-ROC-17013993. • Cognitive impairment and depressive symptoms after stroke are closely related. • The relationship between depressive symptoms and cognitive function is reciprocal. • Improving both depressive symptoms and cognitive function benefits patients. [ABSTRACT FROM AUTHOR]