Development of predictive model for post-stroke depression at discharge based on decision tree algorithm: A multi-center hospital-based cohort study.

OBJECTIVE: Post-stroke depression (PSD) is one of the most common and severe neuropsychological sequelae after stroke. Using a prediction model composed of multiple predictors may be more beneficial than verifying the predictive performance of any single predictor. The primary objective of this study was to construct practical prediction tools for PSD at discharge utilizing a decision tree (DT) algorithm. METHODS: A multi-center prospective cohort study was conducted from May 2018 to October 2019 and stroke patients within seven days of onset were consecutively recruited. The independent predictors of PSD at discharge were identified through multivariate logistic regression with backward elimination. Classification and regression tree (CART) algorithm was employed as the DT model's splitting method. RESULTS: A total of 876 stroke patients who were discharged from the neurology departments of three large general Class A tertiary hospitals in Wuhan were eligible for analysis. Firstly, we divided these 876 patients into PSD and non-PSD groups, history of coronary heart disease (OR = 1.835; 95 % CI, 1.106-3.046; P = 0.019), length of hospital stay (OR = 1.040; 95 % CI, 1.013-1.069; P = 0.001), NIHSS score (OR = 1.124; 95 % CI, 1.052-1.201; P = 0.001), and Mini mental state examination (MMSE) score (OR = 0.935; 95 % CI, 0.893-0.978; P = 0.004) were significant predictors. The subgroup analysis results have shown that hemorrhagic stroke, history of hypertension and higher modified Rankin Scale score (mRS) score were associated with PSD at discharge in the young adult stroke patients. CONCLUSIONS: Several predictors of PSD at discharge were identified and convenient DT models were constructed to facilitate clinical decision-making.

Genome-Wide Mendelian Randomization Identifies Ferroptosis-Related Drug Targets for Alzheimer's Disease.

Background: Alzheimer's disease (AD) currently lacks effective disease-modifying treatments. Recent research suggests that ferroptosis could be a potential therapeutic target. Mendelian randomization (MR) is a widely used method for identifying novel therapeutic targets. Objective: Employ genetic information to evaluate the causal impact of ferroptosis-related genes on the risk of AD. Methods: 564 ferroptosis-related genes were obtained from FerrDb. We derived genetic instrumental variables for these genes using four brain quantitative trait loci (QTL) and two blood QTL datasets. Summary-data-based Mendelian randomization (SMR) and two-sample MR methods were applied to estimate the causal effects of ferroptosis-related genes on AD. Using extern transcriptomic datasets and triple-transgenic mouse model of AD (3xTg-AD) to further validate the gene targets identified by the MR analysis. Results: We identified 17 potential AD risk gene targets from GTEx, 13 from PsychENCODE, and 22 from BrainMeta (SMR p < 0.05 and HEIDI test p > 0.05). Six overlapping ferroptosis-related genes associated with AD were identified, which could serve as potential therapeutic targets (PEX10, CDC25A, EGFR, DLD, LIG3, and TRIB3). Additionally, we further pinpointed risk genes or proteins at the blood tissue and pQTL levels. Notably, EGFR demonstrated significant dysregulation in the extern transcriptomic datasets and 3xTg-AD models. Conclusions: This study provides genetic evidence supporting the potential therapeutic benefits of targeting the six druggable genes for AD treatment, especially for EGFR (validated by transcriptome and 3xTg-AD), which could be useful for prioritizing AD drug development in the field of ferroptosis.

The Effects of a Complex Interactive Multimodal Intervention on Personalized Stress Management Among Health Care Workers in China: Nonrandomized Controlled Study.

BACKGROUND: Health care workers (HCWs) frequently face multiple stressors at work, particularly those working night shifts. HCWs who have experienced distress may find it difficult to adopt stress management approaches, even if they are aware of the effects of stress and coping processes. Therefore, an individualized intervention may be required to assist distressed HCWs in bridging the "knowledge-practice" gap in stress management and effectively alleviating stress symptoms. OBJECTIVE: The main objective of this research was to compare the effects of a complex interactive multimodal intervention (CIMI) to self-guided stress management interventions on stress symptoms of distressed HCWs, as measured by physiological (heart rate variability), psychological (perceived stress, mental distress, and subjective happiness), and sleep disorder (fatigue and sleepiness) indicators. METHODS: We conducted a nonrandomized, controlled study in 2 Chinese general hospitals. The participants in this study were 245 HCWs who fulfilled at least 1 of the 3 dimensions on the Depression, Anxiety, and Stress Scale. All eligible individuals were required to complete a questionnaire and wear a 24-hour Holter device to determine the physiological signs of stress as indexed by heart rate variability at both baseline and after the intervention. The CIMI group received a 12-week online intervention with 4 components-mobile stress management instruction, a web-based WeChat social network, personalized feedback, and a nurse coach, whereas the control group simply received a self-guided intervention. RESULTS: After a 12-week intervention, the Perceived Stress Scale (PSS) scores reduced significantly in the CIMI group (mean difference [MD] -5.31, 95% CI -6.26 to -4.37; P<.001) compared to the baseline levels. The changes in PSS scores before and after the intervention exhibited a significant difference between the CIMI and control groups (d=-0.64; MD -4.03, 95% CI -5.91 to -2.14; P<.001), and the effect was medium. In terms of physiological measures, both the control group (MD -9.56, 95% CI -16.9 to -2.2; P=.01) and the CIMI group (MD -8.45, 95% CI -12.68 to -4.22; P<.001) demonstrated a significant decrease in the standard deviation of normal-to-normal intervals (SDNN) within the normal clinical range; however, there were no significant differences between the 2 groups (d=0.03; MD 1.11, 95% CI -7.38 to 9.59; P=.80). CONCLUSIONS: The CIMI was an effective intervention for improving sleep disorders, as well as parts of the psychological stress measures in distressed HCWs. The findings provide objective evidence for developing a mobile stress management intervention that is adaptable and accessible to distressed HCWs, but its long-term effects should be investigated in future research. TRIAL REGISTRATION: ClinicalTrials.gov NCT05239065; https://clinicaltrials.gov/ct2/show/NCT05239065.

Polysomnography and Neuropsychological Analysis of Patients With Post-Traumatic Stress Disorder Two Years After the COVID-19 Pandemic in Wuhan.

OBJECTIVE: We used polysomnography (PSG) monitoring and neuropsychological scales to explore the characteristics of coronavirus disease-2019 (COVID-19) patients diagnosed with post-traumatic stress disorder (PTSD) in Wuhan, two years after the onset of the COVID-19 pandemic. METHODS: A total of 42 patients in the Sleep Medicine Center were diagnosed with insomnia between December 2021 and May 2022; they were divided into the PTSD group (patients with PTSD diagnosed with insomnia after COVID-19 infection) and the non-PTSD group (patients with insomnia without PTSD). A healthy control group was simultaneously included. RESULTS: The PTSD group was more significant than the non-PTSD group in partial manifestations of sleep disorders, neuropsychological clinical symptoms, and partial PSG data. Patients with different COVID-19 subtypes showed significant differences in the course of disease, sleep disorders, neuropsychological clinical symptoms, relevant scale scores, and PSG data analysis. CONCLUSION: The emotional anxiety and depression of COVID-19 patients diagnosed with PTSD two years after the COVID-19 pandemic in Wuhan are more significant, and will not be self-alleviated with the passage of time. It is necessary to continue to pay attention to the PTSD symptoms and sleep psychology of COVID-19 infected patients, and take appropriate measures. Patients with severe and critical COVID-19 have more severe sleep and mental disorders, and there is a significant correlation between the duration of the disease and the severity of mental and mental disorders and sleep disorders after recovery.

Clinical features, polysomnography, and genetics association study of restless legs syndrome in clinic based Chinese patients: A multicenter observational study.

STUDY OBJECTIVES: To systemically describe the clinical features, polysomnography (PSG) finding, laboratory tests and single-nucleotide polymorphisms (SNPs) in a clinic based Chinese primary restless legs syndrome (RLS) population. METHODS: This observational study, conducted from January 2020 to October 2021 across 22 sleep labs in China, recruited 771 patients diagnosed with RLS following the 2014 RLSSG criteria. Clinical data, PSG testing, and laboratory examination and SNPs of patients with RLS were collected. A total of 32 SNPs in 24 loci were replicated using the Asian Screening Array chip, employing data from the Han Chinese Genomes Initiative as controls. RESULTS: In this study with 771 RLS patients, 645 had primary RLS, and 617 has DNA available for SNP study. Among the 645 primary RLS, 59.7% were women. 33% had a family history of RLS, with stronger familial influence in early-onset cases. Clinical evaluations showed 10.4% had discomfort in body parts other than legs. PSG showed that 57.1% of RLS patients had periodic leg movement index (PLMI) of >5/h and 39.1% had PLMI >15/h, respectively; 73.8% of RLS patients had an Apnea-Hypopnea Index (AHI) > 5/h, and 45.3% had an AHI >15/h. The laboratory examinations revealed serum ferritin levels <75 ng/ml in 31.6%, and transferrin saturation (TSAT) of <45% in 88.7% of RLS patients. Seven new SNPs in 5 genes showed a significant allelic association with Chinese primary RLS, with one previously reported (BTBD9) and four new findings (TOX3, PRMT6, DCDC2C, NOS1). CONCLUSIONS: Chinese RLS patients has specific characters in many aspects. A high family history with RLS not only indicates strong genetic influence, but also reminds us to consider the familial effect in the epidemiological study. Newly developed sequencing technique with large samples remains to be done.

Effects of chronotype on sleep, mood and cardiovascular circadian rhythms in rotating night shift medical workers.

PURPOSE: Whether chronotype affects the health outcomes of night shift work populations is unknown. This study aimed to assess the influence of different chronotypes in the rotating night shift population on sleep status, mood, blood pressure (BP), and heart rate variability (HRV), as well as the circadian rhythm of BP and HRV. METHODS: A total of 208 rotating night shift workers were included. All participants completed structured questionnaires to assess chronotype, mood and sleep status. During their daily lives outside of the night shift, they underwent 24-hour Holter electrocardiogram monitoring and 24-hour ambulatory blood pressure monitoring. Day-time and night-time BP and BP dipping were obtained. Day-time and night-time HRV values (SDNN, RMSSD, LF, HF, LF nu, SD1, SD2 and SD2/SD1) were calculated and fitted to the cosine period curve. Three circandian parameters (mesor, amplitude and acrophase) were extracted to quantify the circadian rhythm of the HRV indices. RESULTS: Among all three groups, E-type showed more fatigue and sleepiness. In addition, E-type showed blunted diastolic BP dipping. Notably, E-type showed association with higher RMSSD, LF, HF and SD1 in the night time, and higher mesors of RMSSD and LF and amplitude of SD2/SD1 in circadian analysis. CONCLUSION: Chronotype is a factor affecting fatigue, sleepiness and cardiovascular circadian rhythms of rotating night shift workers. Chronotype should be taken into consideration for managing night-shift rotation to promote occupational health.

Sleep-phasic heart rate variability predicts stress severity: Building a machine learning-based stress prediction model.

We propose a novel approach for predicting stress severity by measuring sleep phasic heart rate variability (HRV) using a smart device. This device can potentially be applied for stress self-screening in large populations. Using a Holter electrocardiogram (ECG) and a Huawei smart device, we conducted 24-h dual recordings of 159 medical workers working regular shifts. Based on photoplethysmography (PPG) and accelerometer signals acquired by the Huawei smart device, we sorted episodes of cyclic alternating pattern (CAP; unstable sleep), non-cyclic alternating pattern (NCAP; stable sleep), wakefulness, and rapid eye movement (REM) sleep based on cardiopulmonary coupling (CPC) algorithms. We further calculated the HRV indices during NCAP, CAP and REM sleep episodes using both the Holter ECG and smart-device PPG signals. We later developed a machine learning model to predict stress severity based only on the smart device data obtained from the participants along with a clinical evaluation of emotion and stress conditions. Sleep phasic HRV indices predict individual stress severity with better performance in CAP or REM sleep than in NCAP. Using the smart device data only, the optimal machine learning-based stress prediction model exhibited accuracy of 80.3 %, sensitivity 87.2 %, and 63.9 % for specificity. Sleep phasic heart rate variability can be accurately evaluated using a smart device and subsequently can be used for stress predication.

Association of intra-shift nap duration with heart rate variability in medical night shift workers.

Napping during night shifts effectively reduces disease risk and improves work performance, but few studies have investigated the association between napping and physiological changes, particularly in off-duty daily lives. Changes in the autonomic nervous system precede diseases like cardiovascular disease, diabetes, and obesity. Heart rate variability is a good indicator of autonomic nervous system. This study aimed to investigate the link between night shift nap durations and heart rate variability indices in the daily lives of medical workers. As indicators of chronic and long-term alterations, the circadian patterns of heart rate variability indices were evaluated. We recruited 146 medical workers with regular night shifts and divided them into four groups based on their self-reported nap durations. Heart rate variability circadian parameters (midline-estimating statistic of rhythm, amplitude, and acrophase) were obtained by obtaining 24-h electrocardiogram on a day without night shifts, plotting the data of the heart rate variability indices as a function of time, and fitting them into periodic cosine curves. Using clinical scales, depression, anxiety, stress, fatigue, and sleepiness were assessed. Linear regression analysis revealed a positive relationship between 61-120-min naps and 24-h, daytime, and night-time heart rate variability indices, and the parasympathetic activity oscillation amplitude (indexed by high-frequency power, the square root of the mean of the sum of squares of differences between adjacent normal intervals, standard deviation of short-term R-R-interval variability) within one circadian cycle. This study indicated that napping for 61-120 min during night shifts could benefit medical workers' health, providing physiological evidence to promote nap management.

The needle in the haystack: Identifying and validating common genes of depression, insomnia, and inflammation.

BACKGROUND: Insomnia, inflammation, and depression are often co-occurring conditions. The mechanisms underlying these conditions remain unclear. MATERIALS AND METHODS: We collected microarray datasets of depression and insomnia from GEO and analyzed them for differentially expressed genes (DEGs). We then overlapped the DEGs with a list of inflammatory response-related genes to identify genes associated with all three conditions. We next performed analyses of enrichment analyses, KEGG mapping, and protein-protein interaction to identify hub genes. Furthermore, we established a depression rat model with inflammation and insomnia to validate the potential genes. At last, a two-sample Mendelian randomization (MR) study was conducted to confirm the association of identified target genes with depression outcomes. RESULTS: We obtained 32 common DEGs associated with the depression, insomnia and inflammatory, and found that the PI3K-AKT signaling pathway might be involved in the inflammatory response in insomnia and depression. CREB1, CYBB, FYN, and CCR5 were identified as targets for the next validation. In model rats, the CCR5 and PI3K-AKT pathways were significantly up-regulated, while the model group exhibited significantly lower hippocampal p-CREB protein expression. The MR study suggested a potential causal relationship between CREB1 and the risk of depression (OR = 1.11, p = 0.013). LIMITATIONS: The identified potential genes and pathways require further laboratory and clinical evidence verification. CONCLUSION: We identified four potential inflammatory related-genes (CREB1, CYBB, FYN, and CCR5). CREB1 may be a potential inflammatory response-related biomarker and drug target for depression and insomnia, as validated by the followed rat model and MR study.

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.

Complex interactive multimodal intervention to improve personalized stress management among healthcare workers in China: A knowledge translation protocol.

Objectives: Numerous stress management interventions have been implemented in the workplace, but few are adapted to the healthcare setting. Due to the nature of their jobs, healthcare workers (HCWs) may find it difficult to adopt recommended stress management strategies. We present the protocol for a 12-week personalized stress management intervention among HCWs to change their behavior as well as improve physiological/psychological outcomes. Methods: It is a pragmatic quasi-experimental study involving stressed HCWs from two general hospitals in Wuhan, China. The intervention group will receive a complex interactive multimodal intervention, including advanced education via mobile connection, participation in a web-based social network, tailored feedback, and the support of a nurse coach, while the control group will engage in self-guided stress management. Results: The primary outcome is centered on behavioral measures, namely improvements in stress management practice frequency after a 12-week intervention. The secondary outcomes are the changes in stress-related physiological indices (i.e. high frequency variability and normalized unit assessed by Holter) and psychological indicators (scores on the Perceived Stress Scale and Depression, Anxiety, Stress Scale) following 12 weeks of treatment. Conclusion: The knowledge translation intervention builds on a body of work defining the role of individualized instruction and feedback intervention, as well as group intervention through WeChat social network and personalized coaching. We believe this novel intervention will help HCWs promote their stress management awareness and skills, and ultimately benefit their long-term health. Trial Registration: ClinicalTrials.gov., NCT05239065. Registered 14 February 2022-Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT05239065.

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.

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.

Correlation of Circadian Rhythms of Heart Rate Variability Indices with Stress, Mood, and Sleep Status in Female Medical Workers with Night Shifts.

Purpose: Heart rate variability (HRV) indices have been used as stress indicators. Rare studies investigated the associations of circadian rhythms of the HRV indices with the stress, mood, and sleep conditions in populations under stress. Methods: In total 257 female participants (203 shift workers and 54 non-shift workers) were included. All the participants completed a structured questionnaire to assess the stress, mood, and sleep conditions and performed 24-hour Holter electrocardiogram monitoring on the day away from shifts. Using epochs of 1-min or 5-min beat-to-beat intervals, the HRV indices (SDNN, RMSSD, LF, HF, LF/HF, and LFnu, SD1, SD2, SD1/SD2) were plotted as a function of time and fitted into cosine periodic curves, respectively. Three mathematical parameters based on the cosine periodic curves were extracted, MESOR (M, overall averages of the cosine curve), amplitude (A, amplitude of the peak of the cosine curve), and acrophase (θ, latency to the peak) to quantify the circadian rhythms of the HRV indices. Multivariable linear regression models were used to reveal the associations of these parameters with the clinical assessments of stress, mood, or sleep conditions, as well as with the 24-h averages of the HRV indices. Results: The parameters M and A of SDNN, RMSSD, LF, and HF, and θ of LF/HF and LFnu significantly differ between shift and non-shift workers. The parameter θ of LF/HF positively correlates with the severity of stress and anxiety. The parameter A of LF/HF and LFnu also positively correlates with daytime sleepiness and sleep fragmentation. In addition, the parameters M and A instead of θ of SDNN, RMSSD, LF, LF/HF, and LFnu significantly correlate with the 24-h averages of HRV indices. Conclusion: The circadian rhythms of the HRV indices over 24 hours can, to some extent, predict the severity of stress, emotion and sleep conditions in female populations under stress.

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.

Clinical study of double anti-platelet therapy combined with different doses of statin in the treatment of acute cerebral infarction complicated with microhemorrhage.

OBJECTIVE: To assess the clinical effect and safety of double anti-platelet therapy combined with different doses of statins for acute cerebral infarction complicated with microhemorrhage. METHODS: A total of 312 patients who had acute cerebral infarction complicated with microhemorrhage in our hospital were randomly allocated into two groups: the experimental group (n=164) and group for control (n=148). Those in the group for experiment received dual antiplatelet rosuvastatin tablets (20 mg QN), while the control group received dual antiplatelet rosuvastatin tablets (10 mg QN). After 30 days of treatment, blood biochemistry and brain magnetic resonance imaging were performed to record the serum lipid levels, liver transaminase, inflammatory and oxidative stress indicators and other biochemical indicators as well as the number of cerebral microhemorrhage foci. RESULTS: Serum lipids in both groups after intervention were decreased compared to those without intervention (P < 0.05). Furthermore, after receiving the intervention, the HCY and inflammatory indicators (such as hs-CRP) of the two groups were improved compared to before intervention (P < 0.05). The safety index (Aspartate aminotransferase (AST), Alanine aminotransferase (ALT), Creatine kinase (CK), creatinine (Cr)) had no statistically significant difference than those without intervention in the two groups (P > 0.05). CONCLUSION: Rosuvastatin can effectively regulate blood lipids and Hcy levels in patients with acute cerebral infarction and microbleeds, and it can reduce blood lipids and inflammation; furthermore, high dose rosuvastatin has better improvement effects and higher safety in a shorter period time.

Development and Validation of 3-Month Major Post-Stroke Depression Prediction Nomogram After Acute Ischemic Stroke Onset.

PURPOSE: The early detection of major post-stroke depression (PSD) is essential to optimize patient care. A major PSD prediction tool needs to be developed and validated for early screening of major PSD patients. PATIENTS AND METHODS: A total of 639 acute ischemic stroke (AIS) patients from three hospitals were consecutively recruited and completed a 3-month follow-up. Sociodemographic, clinical and laboratory test data were collected on admission. With major depression criteria being met in the DSM-V, 17-item Hamilton Rating Scale For Depression (HRSD) score ≥17 at 3 months after stroke onset was regarded as the primary endpoint. Multiple imputation was used to substitute the missing values and multivariable logistic regression model was fitted to determine associated factors with a bootstrap backward selection process. The nomogram was constructed based on the regression coefficients of the associated factors. Performance of the nomogram was assessed by discrimination (C-statistics) and calibration curve. RESULTS: A total of 7.04% (45/639) of patients were diagnosed with major PSD at 3 months. The final logistic regression model included age, baseline NIHSS and mRS scores, educational level, calcium-phosphorus product, history of hypertension and atrial fibrillation. The model had acceptable discrimination, based on a C-statistic of 0.81 (95% CI, 0.791-0.829), with 71.1% sensitivity and 78.6% specificity. We also transformed the model to a nomogram, an easy-to-use clinical tool which could be used to facilitate the early screening of major PSD patients at 3 months. CONCLUSION: We identified several associated factors of major PSD at 3 months and constructed a convenient nomogram to guide follow-up and aid accurate prognostic assessment.

A Comparative Study on the Psychological Health of Frontline Health Workers in Wuhan Under and After the Lockdown.

Background: The coronavirus disease-2019 (COVID-19) outbreak and a 3-month lockdown of Wuhan may have had a long-term impact on the mental health of frontline healthcare workers (HWs). However, there is still a lack of comparative studies on the mental health of front-line HWs in the initial phase of the lockdown and 1 month after the lifting of the lockdown. Methods: We recruited 1717 HWs during the initial phase of the lockdown and 2214 HWs 1 month after the lifting of the lockdown, and their baseline characteristics and psychiatric health in these two phases were compared. Furthermore, Pearson's Chi-square test and multivariate logistic regression analysis were used to determine the possible risk factors associated with depressive symptoms in the front-line HWs. Results: Compared with the initial phase of the lockdown, the proportion of HWs with anxiety symptoms and stress decreased, while the proportion of HWs with depressive symptoms increased a month after the lifting of the lockdown. Male sex, exercise habit, comorbidities, and having family members or relatives with suspected or confirmed COVID-19 infection were significantly related to the increased incidence of depressive symptoms during the initial phase of the lockdown. Comorbidities, negative effect of media coverage, working >4 days a week, lower annual household income, and deteriorating relationships with family members were associated with depressive symptoms a month after the lifting of the lockdown. Conclusion: The increased proportion of HWs with depressive symptoms 1 month after the lifting of the lockdown suggested that mental health of front-line HWs should be a top-priority issue, not only during, but also after the pandemic.

[Observation of therapeutic effect on coronavirus disease 2019 with insomnia in treatment with baduanjin and auricular point sticking therapy].

OBJECTIVE: To compare the clinical therapeutic effect on coronavirus disease 2019 (COVID-19) with insomnia between the combined treatment of baduanjin and auricular point sticking therapy and the medication with oral estazolam on the base of the conventional treatment. METHODS: A total of 90 patients with COVID-19 accompanied with insomnia were randomly divided into an observation group (45 cases, 3 cases dropped off) and a control group (45 cases). In the observation group, baduanjin, a traditional Chinese fitness activity, was practiced everyday. Besides, auricular point sticking therapy was exerted at ear-shenmen (TF 4), subcortex (AT 4), heart (CO 15), occiput (AT 3), etc. These auricular points were pressed and kneaded three times a day, 30 s at each point each time, consecutively for 12 days. In the control group, estazolam tablets were prescribed for oral administration, 1 mg, once daily, consecutively for 12 days. Before and after treatment, the score of Pittsburgh sleep quality index (PSQI), the score of self-rating anxiety scale (SAS), the score of self-rating depression scale (SDS) and the score of symptoms in traditional Chinese medicine (TCM) were observed in the two groups and the clinical therapeutic effect was evaluated. RESULTS: After treatment, the scores of every item and the total scores in PSQI were all reduced as compared with those before treatment in the two groups (P<0.01). The scores of sleep time and sleep efficiency in the observation group were lower than those in the control group after treatment (P<0.05). SAS scores and SDS scores in the observation group and SAS score in the control group after treatment were all reduced as compared with those before treatment (P<0.01), and SDS score in the observation group was lower than that in the control group (P<0.01). After treatment, in the observation group, the score of each of the symptoms of TCM, i.e. unsound sleep, irritability and hot temper, profuse sputum and sticky feeling in the mouth, bitter taste in the mouth and foul breath, abdominal distention and poor appetite, as well as lassitude was reduced as compared with that before treatment successively (P<0.01), and the scores aforementioned (excepted for the unsound sleep) in the observation group were all lower than the control group (P<0.05). The total effective rates were 83.3% (35/42) in the observation group and 84.4% (38/45) in the control group, without statistical difference in comparison (P>0.05). CONCLUSION: The combined treatment of baduanjin and auricular point sticking therapy improves sleep quality, the conditions of anxiety and depression and the symptoms in TCM for patients of COVID-19 with insomnia. The therapeutic effect of this combined treatment is better than the oral administration of estazolam.

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.