The Study Of Evaluation,Diagnostic Criteria,Risk Prediction,and Biomarkers For Post-stroke Depression

BackgroundPost-stroke depression(PSD)is a common mental problem after stroke with an approximately prevalence of 33%through lifespan.PSD not only exacerbates functional recovery but also seriously affects the cognitive and social functions.It brings heavy burden to individuals,families,and society due to high suicide rate and mortality.However,there is no specific evaluation scale for PSD.The diagnostic criteria and the pathogenesis are also unclear.Effective risk predictive model of PSD for early screening in high-risk populations is still absent.Therefore,establishing early prediction and reasonable diagnosis is the key measure to improve the prognosis of PSD.The evaluation of depression in the stroke patients generally relies on the scales.Hamilton depression rating scale(HDRS),which is an observer-rating scale,has been among the most widely used scales in the study of PSD,and it has been proved a reliable instrument.However,it should be conducted by experienced doctors or rehabilitation therapists in structural interview.The post-stroke depression rating scale(PSDRS)was specifically devised for post-stroke patients by Gainotti in 1997.It is consisted of 10 sections including catastrophic reaction and difficulty in emotional control with different subtypes.The lack of evidence base medicine research,disagreement on some of items,and high requirements for assessors limit its application by the clinical and scientific research of PSD patients.In addition,the diagnosis criteria of PSD are virtually unclear because there is no accurate description of this disease in three major diagnosis systems,including diagnostic and statistical manual of mental disorder,fourth edition(DSM-IV)by American psychiatry association,the international classification of disease,tenth edition(ICD-10)of the World Health Organization and Chinese classification of mental disorders,third version(CCMD-3).In previous studies,DSM and evaluation scale were often used as diagnostic criteria,so it brings the problem that whether it is suitable for PSD with MDD criteria in DSM.It might lead to misdiagnosis for PSD with the depressive symptoms and course.In hence,the establishment and improvement of the diagnostic criteria are crucial for early recognition and effective treatment.Previous studies find that the prevalence of PSD vary from 5%to 67%among all types of stroke patients.This variation is influenced by the diagnostic criteria,evaluation instruments,different time windows and heterogeneities in populations.Despite this broad range,a recently updated meat analysis raises that a overall 31%of stroke survivors developed PSD.Considering this high prevalence it is critical to establish an early prediction model.Several studies indicated that age,gender,education level,medical and psychiatric history,lesion location,and ability of daily life were associated with PSD.Other studies find that biological factors,stroke associated factors and social-psychological factors participant in the PSD.A meta-analysis by Hackett and his colleagues shows that physical disabilities,the severity of the stroke and cognitive impairment were associated with PSD.The updated data by these authors demonstrates that the PSD is related to depression history,nerve function defect in acute and recovery phase,but no relationship found with demographic factors.De Man-van Ginkel JM and his colleagues proposed a post-stroke depression prediction scale(DePreS)to assessing the risk of PSD in the first week after stroke showed a cut-off score of 2.Although this prediction model has a good predictive performance based on demographic and stroke-related predictors,the influences of socio-psychology factors and cognitive factors on PSD are little considered.So,the risk prediction model combination of demographic,clinical,socio-psychology and biological factors will largely improve the efficiency of forecasting and reduce the occurrence of PSD through close observation for high-risk populations.It is widely known that the etiology of PSD is heterogenous and complicated.However,the hypothesis of neurotrophic factors is important to explain the occurrence of this disease.The lack of neurotrophic factors in central and peripheral damages nerve regeneration and synaptic plastic.PSD as the most common psychiatric complication after stroke,it is found to be closely related to the factors of vascular endothelial growth factor(VEGF),placental growth factor(PIGF)and insulin-like growth factor(IGF-1)with vascular permeability and neuroprotection.Little study concerned these factors in PSD patients,and this study was aimed to explore the changes of these factors and its receptors in PSD patients.It will not only help to reveal the pathophysiology mechanism of PSD but also uncover valuable biomarkers for distinguishing PSD and major depressive disorder(MDD).The PSD patients,Non-PSD patients,MDD patients and normal control(NC)were recruited in our study.The demographic materials,neurological function,cognitive function,and socio-psychological factors were collected to establish the post-stroke depression scale(PSD-S),clear diagnostic criteria and risk predictive model.Then the levels of neurotrophic factors were detected to find the biological markers.Part 1 The establishment of the evaluation scale and the diagnostic criteria for PSD1.The development of a new post-stroke depression scale in Chinese population Objective:To distinguish patients with and without depression after stroke reliably,and this study proposes a new PSD-S.Methods:PSD-S was developed based on various depression scales and clinician experiences.,and the whole flow was like following:Firstly,55 items were collected after being analyzed,arranged and merged from 12 different depressive scales.Secondly,15 items were selected by 10 senior psychiatrists/neurologists according to their clinical experiences in our research group.Then,these items were emailed to the national experts to choose the common symptoms in depressive patients after stroke according to their clinical experiences.Replies were received from 65 chief doctors consisting of 39 psychiatrists and 26 neurologists.The PSD-S consisted of 8 items which were most selected by more than half experts after statistics.158 stroke patients who were able to finish PSD-S and HDRS were recruited.Cronbach a,Spearman rank coefficient,and Kruskal-Wallis test were used to examine reliability,internal consistency and discriminate validity respectively.Then the receiver operating characteristic(ROC)curve was used to determine the ability of scale and categorized scales to the range of depression.Finally,the factors of the PSD-S were classified by average clustering analysis.Results:The Cronbach a of PSD-S was 0.797 indicted a good reliability.The Spearman correlation coefficient between PSD-S and HDRS was 0.822(P<0.001)showed an excellent congruent validity.The discriminate validity displayed the significant difference between patients with and without depression(P<0.001).6/24 was set to be the cut-off value by ROC analysis.Moreover,the different severity was distinguished by the value 6/24 and 15/24.Conclusions:PSD-S is a valid,reliable and specific tool for evaluating post-stroke depression patients and can be conveniently utilized.2.The establishment of diagnostic criteria for PSD in Chinese stroke survivors Objective:PSD is the most common complication of stroke.However,there is a wide range from stroke and traditional PSD.This study is aimed to propose the new conception of the stroke patients with depression and then make them to receive reasonable diagnosis and treatment.Methods:We firstly put forward the opinions that the general PSD should be divided into post-stroke depressive disorder(PSDD)and post-stroke depression symptoms(PSDS)according to Diagnostic and Statistical Manual of Mental Disorder-fifth edition(DSM-5)and ZhongDa diagnostic criteria of PSDS-first edition(ZD-1/PSDS)respectively.The ZD-1/PSDS was established based on the suggestions of 65 Chinese chief doctors considering that the symptoms of PSDS might be different from PSDD and the duration of DSM-5 was too strict.Then 166 stroke inpatients were recruited and conducted with the diagnosis and the classification of PSD to verify the new concept.Results:24(14.46%)and 80(48.19%)stroke patients were diagnosed as PSDD and PSDS according to individual diagnosis criteria.Moreover,the patients meet the diagnostic criteria of PSDD should meet the criteria of PSDS first.The distribution frequencies of depressive symptoms were different,which suggested there might be discrepant depressive symptoms between PSDS and PSDD.Conclusions:The present study proposes new opinions about the classification and diagnosis of depression in stroke survivors.The definition and criteria of PSDS are beneficial to explore phenomenological consistency and provide useful information for early recognition and appropriate interventions.Part 2 The study of risk prediction model for PSD in Chinese stroke survivorsObjective:Biological and psychology factors have been identified as the risk factors for PSD,but little is known about the strength of these predictive factors of PSD.Additionally,few study considered the socio-psychological factors.We aimed to develop a clinical and comprehensive prediction model for clinical identification and early prevention of PSD.Methods:A total of 562 participants were recruited,including 226 PSD patients and 336 Non-PSD patients.Multivariate logistic regression was used to extract the risk factors and then construct the risk prediction model for PSD.A decision tree was used to convert the logistic model to a visible model for early recognition of PSD.The ROC was used to evaluate the performance of the model.Results:Six significant predictors were found with the multivariate logistic regression method,including the history of brain cerebral infarction and five socio-psychological factors,which were Eysenck personality questionnaire with neuroticism stability(EPQ_N),life event scale(LES),the Snaith-Hamilton pleasure scale(SHARPS),20 items Toronto alexithymia scale(TAS-20)and social support rating scale(SSRS).The logistic model was converted into a tree model with the decision tree,generated 11 evaluation rules.The areas under the curve(AUC)for the logistic model and the tree model were separately 0.845 and 0.843(P<0.05).The accuracies of the two models were 0.75 and 0.78 respectively.Conclusions:This study constructed a risk prediction model for the PSD and generated the predictive criteria.The model indicated the socio-psychological factors were important to identify the risk of PSD and would contribute to post-stroke rehabilitation.Part 3 The study of neurotrophic factors protein and mRNA expression in PSD patientsObjective:Previous studies suggest that neurotrophic factors participate in the development of stroke and depression.So we investigated the utility of these biomarkers as predictive and distinguish model for PSD.Methods:159 individuals including PSD,Non-PSD,MDD and NC groups were recruited to examine the protein and mRNA expression levels of VEGF,vascular endothelial growth factor receptors(VEGFR2),PIGF,IGF-1 and insulin-like growth factor receptors(IGF-1R).The chi-square test was used to evaluate the categorical variable while nonparametric test and one-way analysis of variance were applied to continuous variables of general characteristics,clinical and biological changes.In order to explore the predictive and distinguish the role of these factors in PSD,discriminant analysis and ROC curve were calculated.Results:The four groups had statistical differences in these neurotrophic factors(all P<0.05)except VEGF concentration and IGF-1R mRNA(P=0.776,P=0.102 respectively).We identified these mRNA expression and protein analytes with the general predictive performance for PSD and Non-PSD groups(AUC:0.805,95%CI,0.704-0.907,P<0.001).Importantly,there is an excellent predictive performance(AUC:0.984,95%CI,0.964-1.000,P<0.001)to differentiate PSD patients from MDD patients.Conclusions:This was the first study to explore the alterations of neurotrophic factors family in PSD patients,and the results intriguingly demonstrated that the combination of protein and mRNA expression of biological factors could be used as a predictive and discriminant model for PSD.