Peripheral inflammation and trajectories of depressive symptomology after ischemic stroke: A prospective cohort study.

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.

Longitudinal relationships between depressive symptoms and cognitive function after stroke: A cross-lagged panel design.

OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Depressive symptom dimensions predict the treatment effect of repetitive transcranial magnetic stimulation for post-stroke depression.

OBJECTIVE: Repetitive transcranial magnetic stimulation (rTMS) has attracted considerable attention because of its non-invasiveness, minimal side effects, and treatment efficacy. Despite an adequate duration of rTMS treatment, some patients with post-stroke depression (PSD) do not achieve full symptom response or remission. METHODS: This was a prospective randomized controlled trial. Participants receiving rTMS were randomly assigned to the ventromedial prefrontal cortex (VMPFC), left dorsolateral prefrontal cortex (DLPFC), or contralateral motor area (M1) groups in a ratio of 1:1:1. Enrollment assessments and data collection were performed in weeks 0, 2, 4, and 8. The impact of depressive symptom dimensions on treatment outcomes were tested using a linear mixed-effects model fitted with maximum likelihood. Univariate analysis of variance (ANOVA) and back-testing were used to analyze the differences between the groups. RESULTS: In total, 276 patients were included in the analysis. Comparisons across groups showed that 17-item Hamilton Rating Scale for Depression (HAMD-17) scores of the DLPFC group significantly differed from those of the VMPFC and M1 groups at 2, 4, and 8 weeks after treatment (p < 0.05). A higher observed mood score (ß = -0.44, 95% confidence interval [CI]: -0.85-0.04, p = 0.030) could predict a greater improvement in depressive symptoms in the DLPFC group. Higher neurovegetative scores (ß = 0.60, 95% CI: 0.25-0.96, p = 0.001) could predict less improvement of depressive symptoms in the DLPFC group. CONCLUSION: Stimulation of the left DLPFC by high-frequency rTMS (HF-rTMS) could significantly improve depressive symptoms in the subacute period of subcortical ischemic stroke, and the dimension of depressive symptoms at admission might predict the treatment effect.

Incremental Value of Stroke-Induced Structural Disconnection in Predicting Global Cognitive Impairment After Stroke.

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.

Nomogram including indirect bilirubin for the prediction of post-stroke depression at 3 months after mild acute ischemic stroke onset.

Background: Post-stroke depression (PSD) has been proven to be associated with stroke severity. Thus, we hypothesized that the prevalence of PSD would be lower in patients with mild stroke. We aim to explore predictors of depression at 3 months after mild acute ischemic stroke (MAIS) onset and to develop a practical and convenient prediction model for the early identification of patients at high risk. Methods: A total of 519 patients with MAIS were consecutively recruited from three hospitals in Wuhan city, Hubei province. MAIS was defined as a National Institute of Health Stroke Scale (NIHSS) score of ≤5 at admission. Meeting the DSM-V diagnostic criteria and a 17-item Hamilton Rating Scale for Depression (HAMD-17) score of >7 at their 3-month follow-up were considered the primary outcomes. A multivariable logistic regression model was used to determine the factors adjusted for potential confounders, and all independent predictors were brought into the construction of a nomogram to predict PSD. Results: The prevalence of PSD is up to 32% at 3 months after MAIS onset. After adjusting for potential confounders, indirect bilirubin (p = 0.029), physical activity (p = 0.001), smoking (p = 0.025), hospitalization days (p = 0.014), neuroticism (p < 0.001), and MMSE (p < 0.001) remained independently and significantly related with PSD. The concordance index (C-index) of the nomogram jointly constructed by the aforementioned six factors was 0.723 (95% CI: 0.678-0.768). Conclusion: The prevalence of PSD seems equally high even if the ischemic stroke is mild, which calls for great concern from clinicians. In addition, our study found that a higher level of indirect bilirubin can lower the risk of PSD. This finding may provide a potential new approach to PSD treatment. Furthermore, the nomogram including bilirubin is convenient and practical to predict PSD after MAIS onset.

Psychopathological network for early-onset post-stroke depression symptoms.

BACKGROUND: Post-stroke depression (PSD) can be conceptualized as a complex network where PSD symptoms (PSDS) interact with each other. The neural mechanism of PSD and interactions among PSDS remain to be elucidated. This study aimed to investigate the neuroanatomical substrates of, as well as the interactions between, individual PSDS to better understand the pathogenesis of early-onset PSD. METHODS: A total of 861 first-ever stroke patients admitted within 7 days poststroke were consecutively recruited from three independent hospitals in China. Sociodemographic, clinical and neuroimaging data were collected upon admission. PSDS assessment with Hamilton Depression Rating Scale was performed at 2 weeks after stroke. Thirteen PSDS were included to develop a psychopathological network in which central symptoms (i.e. symptoms most strongly correlated with other PSDS) were identified. Voxel-based lesion-symptom mapping (VLSM) was performed to uncover the lesion locations associated with overall PSDS severity and severities of individual PSDS, in order to test the hypothesis that strategic lesion locations for central symptoms could significantly contribute to higher overall PSDS severity. RESULTS: Depressed mood, Psychiatric anxiety and Loss of interest in work and activities were identified as central PSDS at the early stage of stroke in our relatively stable PSDS network. Lesions in bilateral (especially the right) basal ganglia and capsular regions were found significantly associated with higher overall PSDS severity. Most of the above regions were also correlated with higher severities of 3 central PSDS. The other 10 PSDS could not be mapped to any certain brain region. CONCLUSIONS: There are stable interactions among early-onset PSDS with Depressed mood, Psychiatric anxiety and Loss of interest as central symptoms. The strategic lesion locations for central symptoms may indirectly induce other PSDS via the symptom network, resulting in higher overall PSDS severity. TRIAL REGISTRATION: URL: http://www.chictr.org.cn/enIndex.aspx ; Unique identifier: ChiCTR-ROC-17013993.

Explore the influencing factors and construct random forest models of post-stroke depression at 3 months in males and females.

BACKGROUND: Post-stroke depression (PSD) is one of the most common neuropsychiatric complications after stroke. The occurrence, development and prognosis of PSD have long been different between males and females. The main purpose of this study was to explore the influencing factors of PSD at 3 months in males and females, and construct random forest (RF) models to rank the influencing factors. METHODS: This is a prospective multicenter cohort study (Registration number: ChiCTR-ROC-17013993). Stroke patients hospitalized in the department of Neurology of three hospitals in Wuhan were enrolled from May 2018 to August 2019. Scale assessments were performed 24 hours after admission and 3 months after stroke onset. Binary logistic regression analysis was used for univariate and multivariate (stepwise backward method) analysis, when p was less than 0.05, the difference between groups was considered statistically significant. Lastly, the RF models were constructed according to the results of multivariate regression analysis. RESULTS: This study found that several baseline variables were associated with PSD at 3 months in males and females. RF model ranked them as stroke severity (OR [odds ratio] =1.17, p < 0.001, 95%CI [confidence interval]:1.11-1.24), neuroticism dimension (OR = 1.06, p = 0.002, 95%CI:1.02-1.10), physical exercise (OR = 0.62, p = 0.007, 95%CI:0.44-0.88), sleeping time < 5 h (OR = 1.91, p = 0.006, 95% CI:1.20-3.04) and atrial fibrillation (OR = 4.18, p = 0.012, 95%CI:1.38-12.68) in males. In females, RF model ranked them as psychological resilience (OR = 0.98, p = 0.015, 95%CI:0.96-1.00), ability of daily living (OR = 0.98, p = 0.001, 95%CI:0.97-0.99), neuroticism dimension (OR = 1.11, p = 0.002, 95%CI:1.04-1.18) and subjective support (OR = 1.11, p < 0.001, 95%CI:1.05-1.78). CONCLUSION: The study found influencing factors of PSD at 3 months were different in males and females, and construct RF models to rank them according to their importance. This suggests that clinicians should focus their interventions on sex-specific influencing factors in order to improve the prognosis of PSD patients. TRIAL REGISTRATION: ChiCTR-ROC-17013993.

Structural disconnection-based prediction of poststroke depression.

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.

Neural Substrates of Poststroke Depression: Current Opinions and Methodology Trends.

Poststroke depression (PSD), affecting about one-third of stroke survivors, exerts significant impact on patients' functional outcome and mortality. Great efforts have been made since the 1970s to unravel the neuroanatomical substrate and the brain-behavior mechanism of PSD. Thanks to advances in neuroimaging and computational neuroscience in the past two decades, new techniques for uncovering the neural basis of symptoms or behavioral deficits caused by focal brain damage have been emerging. From the time of lesion analysis to the era of brain networks, our knowledge and understanding of the neural substrates for PSD are increasing. Pooled evidence from traditional lesion analysis, univariate or multivariate lesion-symptom mapping, regional structural and functional analyses, direct or indirect connectome analysis, and neuromodulation clinical trials for PSD, to some extent, echoes the frontal-limbic theory of depression. The neural substrates of PSD may be used for risk stratification and personalized therapeutic target identification in the future. In this review, we provide an update on the recent advances about the neural basis of PSD with the clinical implications and trends of methodology as the main features of interest.

Higher Concentration of Adrenocorticotropic Hormone Predicts Post-Stroke Depression.

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.

Nomogram for Persistent Post-Stroke Depression and Decision Curve Analysis.

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.

Blood biomarkers of post-stroke depression after minor stroke at three months in males and females.

BACKGROUND: Post-stroke depression (PSD) is one of the most common neuropsychiatric complications after stroke. Studies on the underlying mechanisms and biological markers of sex differences in PSD are of great significance, but there are still few such studies. Therefore, the main objective of this study was to investigate the association of biomarkers with PSD at 3 months after minor stroke in men and women. METHODS: This was a prospective multicenter cohort study that enrolled 530 patients with minor stroke (males, 415; females, 115). Demographic information and blood samples of patients were collected within 24 h of admission, and followed up at 3 months after stroke onset. PSD was defined as a depressive disorder due to another medical condition with depressive features, major depressive-like episode, or mixed-mood features according to the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-V). Univariate analysis was performed using the chi-square test, Mann-Whitney U test, or t-test. Partial least-squares discriminant analysis (PLS-DA) was used to distinguish between patients with and without PSD. Factors with variable importance for projection (VIP) > 1.0 were classified as the most important factors in the model segregation. RESULTS: The PLS-DA model mainly included component 1 and component 2 for males and females. For males, the model could explain 13% and 16.9% of the variables, respectively, and 29.9% of the variables in total; the most meaningful predictors were exercise habit and fibrinogen level. For females, the model could explain 15.7% and 10.5% of the variables, respectively, and 26.2% of the variables in total; the most meaningful predictors in the model were brain-derived neurotrophic factor (BDNF), magnesium and free T3. Fibrinogen was positively correlated with the Hamilton Depression Scale-17 items (HAMD-17) score. BDNF, magnesium, and free T3 levels were negatively correlated with the HAMD-17 score. CONCLUSIONS: This was a prospective cohort study. The most important markers found to be affecting PSD at 3 months were fibrinogen in males, and free T3, magnesium, and BDNF in females. TRIAL REGISTRATION: ChiCTR-ROC-17013993 .

Systemic low-grade inflammation and depressive symptomology at chronic phase of ischemic stroke: The chain mediating role of fibrinogen and neutrophil counts.

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: ß = 0.200, 95%CI, 0.057 ∼ 0.332), fibrinogen (Model 2: ß = 0.828, 95%CI, 0.269 ∼ 1.435), white blood cell counts (WBC, model 2: ß = 0.354, 95%CI, 0.122 ∼ 0.577) and neutrophil counts (Model 2: ß = 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.

Higher Serum Lactic Dehydrogenase is Associated with Post-Stroke Depression at Discharge.

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.

Higher fasting C-peptide is associated with post-stroke depression: a multicenter prospective cohort study.

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.

Artificial neural network and decision tree models of post-stroke depression at 3 months after stroke in patients with BMI ≥ 24.

OBJECTIVE: Previous studies have shown that excess weight (including obesity and overweight) can increase the risk of cardiovascular, cerebrovascular and other diseases, but there is no study on the incidence of post-stroke depression (PSD) and related factors in patients with excessive weight. The main purpose of this study was to find related factors of PSD at 3 months after stroke in patients with excessive weight and construct artificial neural network (ANN) and decision tree (DT) models. METHODS: This is a prospective multicenter cohort study (Registration number: ChiCTR-ROC-17013993). Five hundred and three stroke patients with Body Mass Index(BMI) ≥ 24 were included in this study. The diagnostic criteria of PSD is according to the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-V) diagnostic criteria for depression due to other medical conditions and the HAMD-17 scores > 7 at 3 months after stroke was used as the primary endpoint. The χ2 test, Mann-Whitney U test or t-test were used to check for statistical significance. RESULTS: Our study found that sleeping time < 5 h, CHD, physical exercise, BI score, N dimension(EPQ) and subjective support(SSRS) were associated with PSD in patients with excessive weight. Physical exercise(odd ratio [OR] = 0.49, p = 0.001, 95%CI [confidence interval]: 0.32-0.75) and BI score(OR = 0.99, p < 0.001, 95%CI: 0.98-0.99) were protective factors; sleeping time < 5 h(OR = 2.86, p < 0.001, 95%CI: 1.62-5.04), CHD(OR = 2.18, p = 0.018, 95%CI: 1.14-4.15), N dimension(OR = 1.08, p = 0.001, 95%CI: 1.03-1.13) and subjective support(OR = 1.04, p = 0.022, 95%CI: 1.01-1.07) were risk factors. CONCLUSION: This study found several factors related to the occurrence of PSD at 3 months in patients with excessive weight. Meanwhile, ANN and DT models were constructed for clinicians to use.

Psycho-social factors associated with high depressive symptomatology in female adolescents and gender difference in adolescent depression: an epidemiological survey in China's Hubei Province.

BACKGROUND: Exploring etiological clues to adolescent depression, especially in female adolescents, might be helpful to improve the social environment of female adolescents. The aim at this study is to explore psycho-social factors of female adolescents with high depressive symptomatology and gender differences in depressive symptoms among Chinese adolescents. METHOD: We examined 4100 adolescents from Wuhan city and Jianli county via a cross-sectional study. Depressive symptomatology was screened through the Chinese version of Center for Epidemiology Studies Depression Scale. Multivariate logistic regression was performed to explore the factors related to high depressive symptomatology in female and male adolescents, respectively. RESULTS: The prevalence of high depressive symptomatology in female and male were 38.9 and 30.2% respectively. The psycho-social factors of high depressive symptomatology in female adolescents were age (Adjusted odds ratio [aOR] = 1.201, 95% confidence interval [CI], 1.076 ~ 1.341), single parent family (aOR = 2.004, 95%CI, 1.448 ~ 2.772) and fathers' education level (compared to primary school and below, [Junior middle school, aOR = 0.641, 95%CI, 0.439 ~ 0.934; Senior middle school, aOR = 0.603, 95%CI, 0.410 ~ 0.888; College degree and above, aOR = 0.639, 95%CI, 0.437 ~ 0.936]). CONCLUSION: Fathers' education level was associated with high depressive symptomatology in female adolescents. Female adolescents whose father with primary school education or below deserves more attention. Further epidemiologic researches need to be conducted to explore the different risk factors between female and male adolescents in China.