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Objective The novel coronavirus disease 2019 (COVID-19) is a global public health emergency that has caused worldwide concern. The mental health of medical students under the COVID-19 epidemic has attracted much attention. This study aims to identify subgroups of medical students based on depression and anxiety and explore the influencing factors during the COVID-19 epidemic in China. Methods A total of 29,663 medical students were recruited during the epidemic of COVID-19 in China. Depression and anxiety symptoms were assessed using Patient Health Questionnaire 9 (PHQ9) and Generalized Anxiety Disorder 7 (GAD7) respectively. Latent class analysis was performed based on depression and anxiety symptoms in medical students. The latent class subtypes were compared using the chi-square test. Multinomial logistic regression was used to examine associations between identified classes and related factors. Results In this study, three distinct subgroups were identified, namely, the poor mental health group, the mild mental health group and the low symptoms group. The number of medical students in each class is 4325, 9321 and 16,017 respectively. The multinomial logistic regression results showed that compared with the low symptoms group, the factors influencing depression and anxiety in the poor mental health group and mild mental health group were sex, educational level, drinking, individual psychiatric disorders, family psychiatric disorders, knowledge of COVID-19, fear of being infected, and participate in mental health education on COVID-19. Conclusions Our findings suggested that latent class analysis can be used to categorize different medical students according to their depression and anxiety symptoms during the outbreak of COVID-19. The main factors influencing the poor mental health group and the mild mental health group are basic demographic characteristics, disease history, COVID-19 related factors and behavioural lifestyle. School administrative departments can carry out targeted psychological counseling according to different subgroups to promote the physical and mental health of medical students.

BACKGROUND: The purpose of this study was to explore the association between perceived stress and depression among medical students and the mediating role of insomnia in this relationship during the COVID-19 pandemic in China. METHODS: A cross-sectional survey was conducted from March to April 2020 in medical university. Levels of perceived stress, insomnia and depression were measured using Perceived Stress Scale (PSS), Insomnia Severity Index (ISI) and Patient Health Questionnaire 9 (PHQ-9). The descriptive analyses of the demographic characteristics and correlation analyses of the three variables were calculated. The significance of the mediation effect was obtained using a bootstrap approach with SPSS PROCESS macro. RESULTS: The mean age of medical students was 21.46 years (SD=2.50). Of these medical students, 10,185 (34.3%) were male and 19,478 (65.7%) were female. Perceived stress was significantly associated with depression (s=0.513, P

Bipolar disorder type II (BD-II) is linked to an increased suicidal risk. Since a prior suicide attempt (SA) is the single most important risk factor for sequent suicide, the elucidation of involved neural substrates is critical for its prevention. Therefore, we examined the spontaneous brain activity and its temporal variabilities in suicide attempters with bipolar II during a major depressive episode. In this cross-sectional study, 101 patients with BD-II, including 44 suicidal attempters and 57 non-attempters, and 60 non-psychiatric controls underwent a resting-state functional magnetic resonance imaging (fMRI). Participants were assessed with Hamilton Rating Scale for Depression (HAMD) and Nurses, Global Assessment of Suicide Risk (NGASR). The dynamics of low-frequency fluctuation (dALFF) was measured using sliding-window analysis and its correlation with suicidal risk was conducted using Pearson correlation. Compared to non-attempters, suicidal attempters showed an increase in brain activity and temporal dynamics in the anterior cingulate cortex (ACC). In addition, the temporal variabilities of ACC activity positively correlated with suicidal risk (R = 0.45, p = 0.004), while static ACC activity failed to (R = 0.08, p > 0.05). Our findings showed that an aberrant static ALFF and temporal variability could affect suicidal behavior in BD-II patients. However, temporal variability of neuronal activity was more sensitive than static amplitude in reflecting diathesis for suicide in BD-II. Dynamics of brain activity could be considered in developing neuromarkers for suicide prevention.

A kind of double-layer curved compound eye (DLCCE) inspired by natural compound eye was developed and fabricated in two-photon polymerization (TPP) technology to solve the existing problems, such as defocus at the edge, hard to miniaturize, assemble and detect. For each ommatidium, a corresponding modified microlens was designed to refract and focus the incident rays on the photoelectric detector. The diameter of the complete compound eye is $47.9~\mu \text{m}$ . It is integrated by 33 ommatidia with a diameter of $3.9~\mu \text{m}$ and possesses a theoretical FOV angle of 85°. What’s more, extra supports and through-holes were designed to promote to develop the unpolymerized photoresist within the fabricated structure. An imaging experiment was conducted to demonstrate the validity of developed compound eye comparing with the single-layer one. This work was expected to promote compound eyes to be applied in more imaging and sensing fields of microvision for their miniaturization, integration and optimization of optical system.

Bipolar disorder (BD) is associated with a high risk of suicidality, and it is challenging to predict suicide attempts in clinical practice to date. Although structural and functional connectivity alterations from neuroimaging studies have been previously reported in BD with suicide attempts, little is known about how abnormal structural and functional connectivity relates to each other. Here, we hypothesize that structure connectivity constrains functional connectivity, and structural–functional coupling is a more sensitive biomarker to detect subtle brain abnormalities than any single modality in BD patients with a current major depressive episode who had attempted suicide. By investigating structural and resting-state fMRI connectivity, as well as their coupling among 191 BD depression patients with or without a history of suicide attempts and 113 healthy controls, we found that suicide attempters in BD depression patients showed significantly decreased central-temporal structural connectivity, increased frontal–temporal functional connectivity, along with decreased structural–functional coupling compared with non-suicide attempters. Crucially, the altered structural connectivity network predicted the abnormal functional connectivity network profile, and the structural–functional coupling was significantly correlated with suicide risk but not with depression or anxiety severity. Our findings suggest that the structural connectome is the key determinant of brain dysfunction, and structural–functional coupling could serve as a valuable trait-like biomarker for BD suicidal predication over and above the intramodality network connectivity. Such a measure can have clinical implications for early identification of suicide attempters with BD depression and inform strategies for prevention.

Objective Misdiagnosis of bipolar disorder (BD) as unipolar disorder (UD) may cause improper treatment strategy to be chosen, especially in the early stages of disease. The aim of this study was to characterize alterations in specific brain networks for depressed patients who transformed into BD (tBD) from UD. Method The module allegiance from resting-fMRI by applying a multilayer modular method was estimated in 99 patients (33 tBD, 33 BD, 33 UD) and 33 healthy controls (HC). A classification model was trained on tBD and UD patients. HC was used to explore the functional declination patterns of BD, tBD, and UD. Results Based on our classification model, difference mainly reflected in default-mode network (DMN). Compared with HC, both BD and tBD focused on the difference of somatomotor network (SMN), while UD on the abnormity of DMN. The patterns of brain network between patients with BD and tBD were well-overlapped, except for cognitive control network (CCN). Conclusion The functional declination of internal interaction in DMN was suggested to be useful for the identification of BD from UD in the early stage. The higher recruitment of DMN may predispose patients to depressive states, while higher recruitment of SMN makes them more sensitive to external stimuli and prone to mania. Furthermore, CCN may be a critical network for identifying different stages of BD, suggesting that the onset of mania in depressed patients is accompanied by CCN related cognitive impairments.

Background Major depressive disorder (MDD) is often accompanied with classic diurnal mood variation (DMV) symptoms. Patients with DMV symptoms feel a mood improvement and prefer activities at dusk or in the evening, which is consistent with the evening chronotype. Their neural alterations are unclear. In this study, we aimed to explore the neuropathological mechanisms underlying the circadian rhythm of mood and the association with chronotype in MDD. Methods A total of 126 depressed patients, including 48 with DMV, 78 without, and 67 age/gender-matched healthy controls (HC) were recruited and underwent a resting-state functional magnetic resonance imaging. Spontaneous neural activity was investigated using amplitude of low-frequency fluctuation (ALFF) and region of interest (ROI)-based functional connectivity (FC) analyses were conducted. The Morningness-Eveningness Questionnaire (MEQ) was utilized to evaluate participant chronotypes and Pearson correlations were calculated between altered ALFF/FC values and MEQ scores in patients with MDD. Results Compared with NMV, DMV group exhibited lower MEQ scores, and increased ALFF values in the right orbital superior frontal gyrus (oSFG). We observed that increased FC between the left suprachiasmatic nucleus (SCN) and supramarginal gyrus (SMG). ALFF in the oSFG and FC of rSCN-SMG were negatively correlated with MEQ scores. Limitation Some people's chronotypes information is missing. Conclusion Patients with DMV tended to be evening type and exhibited abnormal brain functions in frontal lobes. The synergistic changes between frontotemporal lobe, SCN-SMG maybe the characteristic of patients with DMV symptoms.

Objective: Alcohol use disorder (AUD) is a serious issue worldwide and frequently co-occurs with depression. However, the quality of life (QOL) of AUD patients with and without depression is not well studied in the Chinese Han population. The aim of this study was to investigate QOL and its correlates in AUD patients with and without depression in China.Methods: Five hundred and fifteen psychiatric patients diagnosed with AUD were recruited. All these patients completed the Beck Depression Inventory (BDI) to assess depression, the Medical Outcome Study 36-Item Short Form Health Survey (SF-36) to evaluate QOL and the Alcohol Use Disorders Identification Test (AUDIT) to measure the severity of drinking.Results: Compared with AUD patients without depression, those with depression had a lower QOL in all eight domains of the SF-36 (all P < 0.001), but were more willing to have alcohol-related treatment (P < 0.05). Negative correlations were noted between (i) the BDI total score and all eight domains of the SF-36 (all P < 0.001); and (ii) between the AUDIT total score and six domains of the SF-36 (all P < 0.05).Conclusions: Depression impairs QOL in patients with AUD in China. Early intervention in comorbid depression to improve QOL is needed.

Bipolar II disorder (BD-II) major depression episode is highly associated with suicidality, and objective neural biomarkers could be key elements to assist in early prevention and intervention. This study aimed to integrate altered brain functionality in the frontolimbic system and machine learning techniques to classify suicidal BD-II patients and predict suicidality risk at the individual level. A cohort of 169 participants were enrolled, including 43 BD-II depression patients with at least one suicide attempt during a current depressive episode (SA), 62 BD-II depression patients without a history of attempted suicide (NSA), and 64 demographically matched healthy controls (HCs). We compared resting-state functional connectivity (rsFC) in the frontolimbic system among the three groups and explored the correlation between abnormal rsFCs and the level of suicide risk (assessed using the Nurses' Global Assessment of Suicide Risk, NGASR) in SA patients. Then, we applied support vector machines (SVMs) to classify SA vs. NSA in BD-II patients and predicted the risk of suicidality. SA patients showed significantly decreased frontolimbic rsFCs compared to NSA patients. The left amygdala-right middle frontal gyrus (orbital part) rsFC was negatively correlated with NGASR in the SA group, but not the severity of depressive or anxiety symptoms. Using frontolimbic rsFCs as features, the SVMs obtained an overall 84% classification accuracy in distinguishing SA and NSA. A significant correlation was observed between the SVMs-predicted NGASR and clinical assessed NGASR (r = 0.51, p = 0.001). Our results demonstrated that decreased rsFCs in the frontolimbic system might be critical objective features of suicidality in BD-II patients, and could be useful for objective prediction of suicidality risk in individuals.

Background: Depressive symptoms are common among psychiatric patients with alcohol dependence (AD). However, the prevalence and clinical correlates of comorbid depressive symptoms are less well studied in Chinese Han patients. Methods: In this hospital-based survey, we recruited 378 psychiatric patients diagnosed with AD according to the Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition (DSM-IV). All patients completed the Beck Depression Inventory (BDI) to evaluate depressive symptoms and the Alcohol Use Disorders Identification Test (AUDIT) to assess the severity of drinking. Results: Compared to patients without depressive symptoms, 48.9% (185/378) of the patients with comorbid depressive symptoms were younger, had a more unstable marital status, had a higher AUDIT total score, and had a higher adverse consequences subscore (all P

Diurnal mood variation (DMV), a common symptom of major depressive disorder (MDD), is associated with circadian related genes and dysregulation of the suprachiasmatic nucleus (SCN). Previous research confirmed that the RORA gene is involved in the regulation of circadian rhythms. In this study, we hypothesized that polymorphisms of RORA may affect DMV symptoms of MDD through functional changes in the SCN. A total of 208 patients diagnosed with depression and 120 control subjects were enrolled and underwent a resting-state functional magnetic resonance imaging (rs-fMRI). Blood samples were collected and genotyping of 9 RORA gene SNPs were performed using next-generation sequencing technology. Patients were categorized as an AA genotype or C allele carriers based on RORA rs72752802 polymorphism. SCN-seed functional connectivity (FC) was compared between the two groups and correlation with severity of DMV was analyzed. Finally, a mediation analysis was performed to further determine FC intermediary effects. We observed that rs72752802 was significantly associated with patients' DMV symptoms. C allele carriers of rs72752802 showed significantly decreased FC between the right SCN and right superior temporal gyrus (rSTG). This was also correlated with DMV symptoms. In addition, the rs72752802 SNP influenced DMV symptoms through intermediary effects of SCN-rSTG connectivity. The study presented here provides a neurological and genetic basis for understanding depressed patients experiencing DMV.

Objective The physiological mechanism of suicide attempt (SA) in bipolar II disorder (BD-II) remains only partially understood. The study seeks to identify the dysfunction pattern in suicide brain for BD-II patients. Methods Graph theory was utilized to explore topological properties at whole-brain, module and region levels based on resting-state functional MRI (rs-fMRI) data, which acquired from 38 un-medicated BD-II patients with at least one SA, 60 none SA (NSA) patients and 69 healthy controls (HCs). Finally, the correlation relationship between graph metrics and clinical variables were estimated. Results Compared with NSA patients and HCs, the functional connectivity strength between limbic/sub-cortical (LIMB/SubC) and frontoparietal network (FPN) were significantly weakened. Nodal strength in left head of caudate nucleus (HCN), raphe nucleus (RN), right nucleus accumbens (NAcc), right subgenual anterior cingulate cortex (sgACC) and nodal efficiency in right sgACC, right HCN for SA patients were significantly reduced relative to NSA and HCs. In particular, nodal strength in RN and nodal efficiency in right sgACC showed a significant negative correlation with Nurses’ Global Assessment of Suicide Risk (NGASR) scores. Limitations This is a single-mode cross-sectional study, the results were not verified by multi-center data. Conclusions The abnormal disrupted FC between LIMB/SubC and FPN is associated with SA in BD-II patients, which increased the susceptibility of suicide. Especially, the dysfunction in RN and right sgACC predict a higher suicide risk in BD-II patients.The results can help us to understand the suicide mechanism and early judgment of suicidal behaviors for BD-II patients.

Although structural and functional brain abnormalities have been observed in depressed suicide attempters (DS), structural deficits and functional impairments together with their relationship in DS remain unclear. To clarify this issue, we aimed to examine the differences in gray matter (GM) alteration, corresponding functional connectivity (FC) change, and their relationship between DS and depressed non-suicide attempters (NDS). Sixty-eight DS, 119 NDS and 103 healthy controls were enrolled and subjected to magnetic resonance imaging scans. The patients were evaluated using the 17-item Hamilton Rating Scale for Depression (HRSD) and Nurses' Global Assessment of Suicide Risk (NGASR) scale. Both voxel-based morphometry and resting-state FC analyses were performed based on functional and structural imaging data. Compared with NDS, the DS group showed reduced GM volume in the right inferior frontal orbital gyrus (IFOG) and left caudate (CAU) but increased GM volume in the left calcarine fissure, weaker negative right IFOG-left rectus gyrus (REG) FC, and weaker positive right IFOG-left inferior parietal lobule (IPL) FC. In DS, the GM volume of the right IFOG and left CAU was negatively correlated with NGASR and HRSD scores, respectively; the right IFOG-left IPL FC was negatively correlated with cognitive factor scores; and the GM volume of the right IFOG was positively correlated with IFOG-REG and IFOG-IPL FC. Our findings indicate that structural deficit with its related functional alterations in brain circuits converged in right IFOG centralized pathways and may play a central role in suicidal behaviors in depression.

Background The fundamental pathophysiology of major depressive disorder (MDD) could be characterized by functional brain networks which tightly and dynamically connect into groups as communities, making the flexible brain possible to external multifarious demands. We aim to scrutinize what brain dynamics go awry in MDD and antidepressants effects on multi-dimensional symptoms. Methods Thirty-five patients and thirty-five controls underwent resting-state functional magnetic resonance imaging (MRI). Patients were scanned before and after 8 or 12 weeks of pharmacotherapy. Group independent component analysis decomposed resting-state images to instinct networks and networks' integrated flexibility was calculated. Network flexibility between patients at baseline and after therapy were compared. Results All patients completed the clinical trial and MRI scans. Following antidepressants treatment, we found significant normalization of reduced network flexibility in default mode network (DMN) and cognitive control network (CCN) of MDD patients. Selectively significant correlations between network flexibility and multi-dimensional symptoms such as anxiety/somatization and hysteresis factor were also found. Conclusions “Hypoflexible” CCN may involve in anxiety syndrome. Low flexibility in DMN may be indicative of hysteresis. These suggest an important pathophysiology of depressive manifestation of MDD. The antidepressant-induced normalization of the “hypoflexibility” suggests a selective pathway through which antidepressants may alleviate symptoms in depression.

Background: The treatment outcomes of the depression remain unsatisfactory. The timely selection of the optimal treatment at early-stage is a critical issue. Despite of significant findings in neuroimaging biomarkers, few studies included neuroimaging assessments in early-phases of treatment and a single biomarker is hard to guide personal treatment selection. Thus, a data-driven approach combined with functional circuits and clinical symptom was applied to predict effective treatment selection by identifying treatment-related subgroups. Methods: Our study was a naturalistic study and 489 participants were enrolled from three sites. We identified symptom-guided brain connectome subgroups and built an early-stage treatment prediction model in the discovery dataset (n=228). Subgroups were compared in the aspects of effective intervention, symptomatic improvement, demographics, brain connectomes and clinical symptoms. Notably, we employed two independent datasets (n=89) to externally validate model. New patients' effective intervention was then expected to be consistent with the pre-defined subgroup. Results: Three subgroups with distinct treatment recommendations emerged: (1) an SSRIs-oriented subgroup with more symptomatic improvements of apathy. (2) a physiotherapy-oriented subgroup with high improvement of suicide symptom. (3) an SNRI-oriented subgroup, unique decreased interactions within salience network (SN), between SN and cognition control network, together with the high baseline depressive severity. Specially, our model had a high sensitivity of 83.6% in improvement prediction, with an overall accuracy of 69.7%. Furthermore, our model was more effective for SSRIs prediction with 87.5% accuracy. Conclusion: Our study offers guidance of multiple treatment strategies in early-stage treatment and extrapolates neuroimaging findings to 'real-world' practice. Funding Statement: The work was supported by the National Natural Science Foundation of China [grant numbers: 81871066，81571639]; Jiangsu Provincial Medical Innovation Team of the Project of Invigorating Health Care through Science, Technology and Education [grant number: CXTDC2016004]; Jiangsu Provincial key research and development program [grant number: BE2018609]. Declaration of Interests: The authors state that they have no conflict of interest with the content of this article. Ethics Approval Statement: A complete description of the study was informed to all subjects and written informed consents were obtained from all participants as approved by the Research Ethics Review Board of the Affiliated Brain Hospital of Nanjing Medical University, Nanjing Drum Tower Hospital and Peking University Sixth Hospital.

Major depressive disorder (MDD) is associated with a heavy disease burden due to the difficulty in diagnosing the disorder and the uncertainty of treatment outcomes. Previous studies have demonstrated the value of functional connectivity (FC) between the dorsolateral prefrontal cortex (DLPFC) and the subgenual anterior cingulate cortex (sgACC) in the identification of MDD and the prediction of antidepressant efficacy. In the present study, we aimed to investigate whether FC is helpful in discriminating patients from healthy controls and in predicting treatment outcome.Seventy-six medication-free patients with MDD and 28 healthy controls were enrolled in the study. Magnetoencephalography (MEG) and the Hamilton Rating Score for Depression (HRSD-17) were administered at baseline. Then, the HRSD-17 was assessed weekly until each patient met the remission criteria, defined as a total HRSD-17 score ≤ 7. Time-dependent Cox regression analysis was used to evaluate the association between FC and the incidence of remission.Healthy controls and MDD patients had opposite FC patterns; this may be helpful for identifying MDD (AUC = 0.8, p 0.001, sensitivity 85.7%, specificity 67.9%). Alpha connectivity between the DLPFC and sgACC (HR 1.858, 95%CI 1.013-3.408, p = 0.045) was found to be an independent factor associated with better final antidepressant outcome.This study was conducted in a small sample of subjects. Further, the direction of regulation between the DLPFC and sgACC was not considered.FC may help identify depression and may be related to the severity of depressive symptoms and predict the efficacy of antidepressant treatment.

Background: Sleep disturbances, such as early wakening, are frequently observed in patients with major depressive disorder (MDD). The suprachiasmatic nuclei (SCN), which controls circadian rhythm, is innervated by the raphe nucleus, a region where Tryptophan hydroxylase-2 (TPH-2) gene is primarily expressed. Although TPH-2 is often implicated in the pathophysiology of depression, few studies have applied a genetic and imaging technique to investigate the mechanism of early wakening symptom in MDD. We hypothesized that TPH-2 variants could influence the function of SCN in MDD patients with early wakening symptom. Methods: One hundred and eighty five MDD patients (62 patients without early wakening and 123 patients with early wakening) and 64 healthy controls participated in this study. Blood samples were collected and genotyping of rs4290270, rs4570625, rs11178998, rs7305115, rs41317118, and rs17110747 were performed by next-generation sequencing (NGS) technology. Logistic regression model was employed for genetic data analysis using the PLINK software. Based on the allele type, rs4290270, which was significant in the early wakening MDD group, participants were categorized into two groups (A allele and T carrier). All patients underwent whole brain resting-state functional magnetic resonance imaging (rs-fMRI) scanning and a voxel-wise functional connectivity comparison was performed between the groups. Results: rs4290270 was significantly linked to MDD patients who exhibited early wakening symptom. The functional connectivities of the right SCN with the right fusiform gyrus and right middle frontal gyrus were increased in the T carrier group compared to the A allele group. In addition, the functional connectivities of the left SCN with the right lingual gyrus and left calcarine sulcus were decreased in the T carrier group compared to the A allele group. Conclusion: These findings suggested that the TPH-2 gene variant, rs4290270, affected the circadian regulating function of SCN. The altered functional connectivities, observed between the SCN and right fusiform gyrus, right middle frontal gyrus, the right lingual gyrus and left calcarine sulcus, could highlight the neural mechanism by which SCN induces sleep-related circadian disruption in T carrier MDD patients. Hence, rs4290270 could potentially serve as a reliable biomarker to identify MDD patients with early wakening symptom.

Objective Skeletal muscle atrophy induced by hypoxia on the plateau will lead to the decrease of muscle strength and the degeneration of athletic ability. Resistance training is an efficient method to stimulate the growth of muscle and improve protein synthesis. Akt-FoxO1 (Fork head box protein 1) pathway plays a significant role in the regulation of skeletal muscle protein degradation. However, it is not clear whether resistance training could prevent skeletal muscle atrophy induced by hypoxia and what is the regulation role of Akt-FoxO1 pathway. This study built a rat model that resistance training inhibited the skeletal muscle atrophy induced by hypoxia and explore the variation of Akt, FoxO1, Murf and Atrogin-1. Methods 40 male 8-week-old Sprague-Dawley (SD) rats were divided into 4 groups randomly: control group (C), resistance training group (R), hypoxia group (H) and hypoxia resistance training group (HR). H and HR group were placed into simulated 4000m altitude (12.4%, O2%) and R and HR group received ladder resistance training. Their incremental load is calculated by using average body weight. After 4 weeks intervention of hypoxia and resistance training, body composition, wet weight of skeletal muscle (soleus, musculus gastrocnemius,extensor digitorum longus and muscelus biceps brachii) and skeletal muscle cross-sectional area (CSA) were measured. The expression of Akt, FoxO1, Murf and Atrogin-1 were detected by Western blot and RT-PCR.Moreover,immunofluorescence technique was used to locate the phosphorylation of FoxO1. Results The lean body mass of HR group was significantly higher than H group (P

Objective To determine the prevalence, associated factors and treatment status of alcohol use disorders (AUDs) in psychiatric patients in China. Methods We asked 24,379 consecutive patients aged ≥18years who presented at the psychiatric departments in eight hospitals in 2013 whether they had consumed alcoholic beverages in the previous month. Of the 2964 (12.2%) patients who answered yes and were then screened with the Alcohol Use Disorders Identification Test (AUDIT), 1304 (5.3%) screened positive (AUDIT≥7) and, based on DSM-IV criteria, were diagnosed with AUDs by psychiatrists. The treatments prescribed for them were also recorded. Logistic regression was used to identify AUDs associated factors. Results The prevalence of AUDs was 2.4% (95% CI: 2.2–2.6%). None of the patients diagnosed with AUDs had got medical treatment for preventing relapse. The risk factors for AUDs were middle-aged or elderly (OR=1.86, 95% CI: 1.23–2.80), and consuming beverages with high degree of alcohol content (OR=2.92, 95% CI: 2.11–4.06). Conclusions The prevalence of AUDs in psychiatric patients in China was not high, but the rate of treatment was dramatically low, indicating the serious neglect of AUDs. Our study suggests an urgent need to improve the situation of unmet need for treatment of psychiatric patients with AUDs.