Psychotic symptoms (SP) in major depressive disorder (MDD) portend greater severity and adverse outcomes. The triglyceride–glucose (TyG) index, a pragmatic surrogate of insulin resistance, may be informative for SP risk, but evidence within MDD remains limited. In a cross-sectional cohort of first-episode, drug-naïve MDD outpatients (N = 1,718), the study outcome was defined as PANSS-defined psychotic symptom burden, operationalized as a PANSS positive subscale score ≥ 15, rather than as a DSM-IV diagnosis of MDD with psychotic features. Continuous predictors were z-standardized. Multivariable logistic regression estimated adjusted associations between TyG and SP while controlling for sex, age, illness duration, BMI, SBP, DBP, HAMD, and HAMA. Stratified models examined sex and onset-age differences. Exploratory indirect-effect analysis was performed using a product-of-coefficients approach with 5,000 nonparametric bootstrap resamples to estimate confidence intervals for indirect associations; because all variables were measured at baseline, these models were used to quantify statistical indirect associations rather than to infer temporal or causal pathways. SP prevalence was 9.9

BACKGROUND:The advantages of lithium in treating bipolar disorder (BD) are inconsistent with a declining trend in lithium prescriptions worldwide. Understanding lithium prescription patterns and serum concentrations could improve lithium clinical practices. METHODS:This multicentre study used latent variable analysis to explore lithium prescription patterns and changing trends in lithium serum concentrations. A regression model was used to identify their underlying associated factors. RESULTS:High- and low-dose prescription patterns were discovered in patients with mania and bipolar depression (BD-D), respectively. Patients with BD-D tended to receive lower lithium dosages. Lithium combination therapy was mainstream for BD. Factors associated with prescription patterns differed between patients with mania and BD-D. The lithium concentration-to-dose (C/D) ratio initially decreased but then increased. The final lithium serum concentration was mainly associated with dose titration. CONCLUSIONS:In this study, lower lithium dosage combined with second-generation antipsychotics is commonly used in the treatment of BD, and lithium prescription patterns fail to follow the guideline recommendations for BD. There are episode-specific factors associated with lithium prescriptions. A non-linear trend in the C/D ratio appears to be one of the factors contributing to lithium delay effects. Adjusting the lithium dosage is a direct way to change its serum concentration. Key PointsLower lithium dosage combined with SGAs is commonly used in the treatment of BD, and lithium prescription patterns fail to follow the guideline recommendations for BD.Factors associated with lithium prescription patterns differed between patients with mania and BD-D.In the context of a standardised lithium dosage (1 g), lithium plasma levels initially decrease before gradually increasing, which appears to be one of the factors contributing to lithium delay effects.

Systemic inflammation has been increasingly implicated in the pathogenesis of depressive symptoms. The inflammatory burden index (IBI), which integrates C-reactive protein (CRP) and the neutrophil-to-lymphocyte ratio (NLR), provides a composite measure of systemic inflammation. This study aimed to examine the association between IBI and depressive symptoms in a nationally representative sample of U.S. adults, with particular focus on potential threshold effects. Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9), with scores ≥10 indicating clinically relevant depressive symptoms. Because the PHQ-9 captures symptom severity rather than a clinician-diagnosed depressive disorder, we consistently use the term ‘depressive symptoms’ throughout to denote the PHQ-9–defined outcome. Multivariable logistic regression, generalised additive models, and segmented (two-piecewise) logistic regression were used to evaluate associations. Each one-unit increase in ln-IBI was associated with slightly higher odds of depressive symptoms (weighted OR = 1.07; 95

Sex differences in lithium-associated efficacy and adverse events have been well studied in bipolar disorder. Exploring variations in lithium concentrations between sexes may offer potential explanations. This multicenter, real-world, observational study, which was based on therapeutic monitoring data, was conducted at six Chinese hospitals. Sex differences in lithium concentrations and potential affecting factors were explored using the generalized estimating equation and multiple linear regression analysis, respectively. A total of 525 bipolar patients were included, comprising 328 patients diagnosed with mania or mania with depressive features and 197 with bipolar depression. There were 398 females and 127 males, including 79 patients aged 13–17 years. The median final lithium dosage of all the subjects was 0.9 g per day, with an average final concentration of 0.68 mmol/L. The lithium concentration was relatively stable in the context of a fixed dosage. In patients with mania or mixed features, lithium concentrations in females were significantly higher than those in males when a fixed lithium dosage was administered. This phenomenon was not observed in patients with bipolar depression. The number of factors influencing lithium concentrations was greater for males with mania or mixed features than for females, which was not observed between males and females with bipolar depression. The therapeutic lithium concentrations of bipolar male and female patients in real-world clinical practice were lower than the guideline-recommended ranges. In patients with manic or mixed features, females have a greater propensity for lithium accumulation than males do, and lithium concentrations are more likely to be affected by internal and external changes in males than in females. Therefore, the potential risk of toxicity and the stability of lithium concentrations are key points in females and males on lithium therapy, respectively.

Background and aim Suicide is nearly always associated with underlying mental disorders. Risk factors for suicide attempts (SAs) in patients with bipolar disorder (BD) misdiagnosed with major depressive disorder (MDD) remain unelucidated. This study was to evaluate the prevalence and clinical risk factors of SAs in Chinese patients with BD misdiagnosed with MDD. Methods A total of 1487 patients with MDD from 13 mental health institutions in China were enrolled. Mini International Neuropsychiatric Interview (MINI) was used to identify patients with BD who are misdiagnosed as MDD. The general sociodemographic and clinical data of the patients were collected and MINI suicide module was used to identify patients with SAs in these misdiagnosed patients. Results In China, 20.6% of patients with BD were incorrectly diagnosed as having MDD. Among these misdiagnosed patients, 26.5% had attempted suicide. These patients tended to be older, had a higher number of hospitalizations, and were more likely to experience frequent and seasonal depressive episodes with atypical features, psychotic symptoms, and suicidal thoughts. Frequent depressive episodes and suicidal thoughts during depression were identified as independent risk factors for SAs. Additionally, significant sociodemographic and clinical differences were found between individuals misdiagnosed with MDD in BD and patients with MDD who have attempted suicide. Conclusions This study highlights the importance of accurate diagnosis in individuals with BD and provide valuable insights for the targeted identification and intervention of individuals with BD misdiagnosed as having MDD and those with genuine MDD, particularly in relation to suicidal behavior.

Background: The age of onset (AOO) is a key factor for heterogeneity in major depressive disorder (MDD). Looking at the effect of AOO on symptomatology may improve clinical outcomes. This study aims to examine whether and how AOO affects symptomatology using a machine learning approach and latent profile analysis (LPA). Methods: The study enrolled 915 participants diagnosed with MDD from eight hospitals across China. Depressive symptoms were assessed using the 17-item Hamilton Depression Rating Scale. The relationship between symp-tom profiles and AOO was explored using Random Forest. The effect of AOO on symptom clusters and subtypes was investigated using multiple linear regression and LPA. A continuous AOO indicator was used to conduct the analyses.Results: Based on the Random Forest, symptom profiles were closely associated with AOO. The regression model showed that the severity of neurovegetative symptoms was positively associated with AOO (beta = 0.18, p < 0.001), and the severity of cognitive-behavioral symptoms was negatively associated with AOO (beta =-0.12, p < 0.001). LPA demonstrated that the subgroups characterized by suicide and guilt had earlier onset of depression. The subgroup with the lowest global severity of depression had the latest onset.Limitations: AOO was recalled retrospectively. The relative scarcity of participants with childhood and adoles-cence onset depression.Conclusions: AOO has an important impact on symptomatology. The findings may enhance clinical evaluations for MDD and assist clinicians in promoting earlier detection and individualized care in vulnerable individuals.

Abstract Background Psychotic symptoms are prevalent in patients with bipolar disorder (BD). However, nearly all previous studies on differences in sociodemographic and clinical factors between patients with (BD P +) and without (BD P-) psychotic symptoms were conducted in Western populations, and limited information is known in China. Method A total of 555 patients with BD from seven centers across China were recruited. A standardized procedure was used to collect patients’ sociodemographic and clinical characteristics. The patients were divided into BD P + or BD P- groups based on the presence of lifetime psychotic symptoms. Mann–Whitney U test or chi-square test was used to analyze differences in sociodemographic and clinical factors between patients with BD P + and BD P-. Multiple logistic regression analysis was conducted to explore factors that were independently correlated with psychotic symptoms in BD. All the above analyses were re-conducted after the patients were divided into BD I and BD II group according to their types of diagnosis. Results A total of 35 patients refused to participate, and the remaining 520 patients were included in the analyses. Compared with patients with BD P-, those with BD P + were more likely to be diagnosed with BD I and mania/hypomania/mixed polarity in the first mood episode. Moreover, they were more likely to be misdiagnosed as schizophrenia than major depressive disorder, were hospitalized more often, used antidepressants less frequently, and used more antipsychotics and mood stabilizers. Multivariate analyses revealed that diagnosis of BD I, more frequent misdiagnosis as schizophrenia and other mental disorders, less frequent misdiagnosis as major depressive disorder, more frequent lifetime suicidal behavior, more frequent hospitalizations, less frequent use of antidepressants, more frequent use of antipsychotics and mood stabilizers were independently correlated with psychotic symptoms in BD. After dividing the patients into BD I and BD II groups, we observed notable differences in sociodemographic and clinical factors, as well as clinicodemographic correlates of psychotic features between the two groups. Conclusions Differences in clinical factors between patients with BD P + and BD P- showed cross-cultural consistency, but results on the clinicodemographic correlates of psychotic features were not. Notable differences between patients with BD I and BD II were found. Future work exploring the psychotic features of BD needs to take types of diagnosis and cultural differences into consideration. Trial registration This study was first registered on the website of the ClinicalTrials.gov ( https://clinicaltrials.gov/ ) on 18/01/2013. Its registration number is NCT01770704.

AimAppraise the clinical features and influencing factors of the hospitalization times and length of stay in bipolar disorder (BD) patients.MethodsThis is a multicenter, observational, cohort study of patients diagnosed of type I or type II bipolar disorder. Five hundred twenty outpatients in seven hospitals from six cities in China were recruited from February 2013 to June 2014 and followed up using a continuous sampling pattern. The research included a retrospective period of 12 months and the prospective period of 9 months. The demographic and clinical features of the patients were collected. The influencing factors that could affect the length of stay (number of days spent in the hospital in the prospective period) were analyzed by poisson's regression and the hospitalization times (times of hospitalization in the prospective and retrospective period) was analyzed by general linear model. The selected variables included gender, age, years of education, occupational status, residence status, family history of mental disease, comorbid substance abuse, comorbid anxiety disorder, times of suicide (total suicide times that occurred in the retrospective and prospective period), polarity of the first mood episode, and BD type(I/II).ResultsPoisson's regression analysis showed that suicide times [Incidence Rate Ratio (IRR) = 1.20, p < 0.001], use of antipsychotic (IRR = 0.62, p = 0.011), and use of antidepressant (IRR = 0.56, p < 0.001) were correlated to more hospitalization times. Linear regression analysis showed that BD type II (β = 0.28, p = 0.005) and unemployment (β = 0.16, p = 0.039) which might mean longer duration of depression and poor function were correlated to longer length of stay. However, patients who experienced more suicide times (β = −0.21, p = 0.007) tended to have a shorter length of stay.ConclusionOverall, better management of the depressive episode and functional rehabilitation may help to reduce the length of stay. BD patients with more hospitalization times were characterized by higher risk of suicide and complex polypharmacy. Patients at high risk of suicide tended to have inadequate therapy and poor compliance, which should be assessed and treated adequately during hospitalization.Clinical trial registrationwww.ClinicalTrials.gov, Identifier: NCT01770704.

Abstract Background: Telomere shortening has been considered a potential biological marker related to disease susceptibility and aging in psychiatric disorders. However, the relationship between telomere length and bipolar disorder (BD-I and BD-II) is uncertain. Moreover, whether telomere shortening is an independent factor of cognitive impairment in BD patients is still inconclusive. Methods: We explore telomere length and cognitive function in patients with bipolar disorder and the relationship between them. We enrolled three groups (35 patients with euthymic BD-I, 18 with euthymic BD-II, and 37 healthy controls). Telomere length was measured by fluorescent quantitative polymerase chain reaction (q-PCR), and cognitive function was evaluated by the MATRICS Consensus Cognitive Battery (MCCB). SPSS 24.0 was used for statistical analysis. Results: The telomere length of euthymic patients with BD-I and BD-II was shorter than that of healthy controls. Telomere length was not significantly different between BD-I and BD-II. Patients with BD-I and BD-II showed poor cognitive function compared to healthy controls. In the three groups, no correlation was detected with telomere length orcognitive function. The duration of illness (DI) was negatively correlated with reasoning and problem solving in BD-I. Nevertheless, the duration of untreated illness (DUI) showed a negative correlation with visual learning performance. Conclusions: This study provides preliminary evidence that shortenedtelomere length is a potential biomarker for BD-I and BD-II. However, the cognitive deficit in BD has no correlation with shortened telomere length.

Early distinction of bipolar disorder (BD) from major depressive disorder (MDD) is difficult since no tools are available to estimate the risk of BD. In this study, we aimed to develop and validate a model of oxidative stress injury for predicting BD. Data were collected from 1252 BD and 1359 MDD patients, including 64 MDD patients identified as converting to BD from 2009 through 2018. 30 variables from a randomly-selected subsample of 1827 (70%) patients were used to develop the model, including age, sex, oxidative stress markers (uric acid, bilirubin, albumin, and prealbumin), sex hormones, cytokines, thyroid and liver function, and glycolipid metabolism. Univariate analyses and the Least Absolute Shrinkage and Selection Operator were applied for data dimension reduction and variable selection. Multivariable logistic regression was used to construct a model for predicting bipolar disorder by oxidative stress biomarkers (BIOS) on a nomogram. Internal validation was assessed in the remaining 784 patients (30%), and independent external validation was done with data from 3797 matched patients from five other hospitals in China. 10 predictors, mainly oxidative stress markers, were shown on the nomogram. The BIOS model showed good discrimination in the training sample, with an AUC of 75.1% (95% CI: 72.9%-77.3%), sensitivity of 0.66, and specificity of 0.73. The discrimination was good both in internal validation (AUC 72.1%, 68.6%-75.6%) and external validation (AUC 65.7%, 63.9%-67.5%). In this study, we developed a nomogram centered on oxidative stress injury, which could help in the individualized prediction of BD. For better real-world practice, a set of measurements, especially on oxidative stress markers, should be emphasized using big data in psychiatry.

Objective: To investigate the prevalence of psychotic depression and the differences in sociodemographic and clinical characteristics and prescription patterns of psychotropic medications between patients with psychotic depression (PD) and patients with nonpsychotic depression (NPD) in China. Methods: We conducted a cross-sectional study in 13 major psychiatric hospitals or the psychiatric units of general hospitals in China from September 1, 2010, to February 28, 2011. PD was defined according to the psychotic disorder section of the Mini International Neuropsychiatric Interview (MINI). The sociodemographic and clinical characteristics and the prescription patterns of psychotropic medications were compared between the PD and NPD groups. Multivariate logistic regression analysis was used to investigate factors associated with an increased likelihood of PD. Results: Among 1172 MDD patients, the prevalence of psychotic features was 9.2% in the present study. The logistic regression analysis indicated that unmarried (OR = 2.08, p < 0.001), frequent depressive episodes (OR = 2.10, p = 0.020), depressive episodes with suicidal ideation and attempts (OR = 1.91, p = 0.004), and patients who were prescribed any antipsychotics (OR = 2.94, p < 0.001) were associated with psychotic features in patients with MDD. Limitations: Cross-sectional design, retrospective recall of some data Conclusion: The prevalence of PD is high in China, and there were some differences in demographic and clinical characteristics between patients with PD and patients with NPD. Clinicians should regularly assess psychotic symptoms and consider intensive treatment and close monitoring when treating subjects with PD.

BACKGROUND:Patients with bipolar disorder (BD) show deficits of facial emotion processing even in the euthymic phase. However, the large-scale functional brain network mechanism underlying the emotional deficit of BD remains unclear. Specifically, it is of importance to understand how the task-modulated functional connectivity (FC) was alternated over distributed brain networks in BD.METHODS:In this study, we analyzed functional MRI data of a face-matching task from 29 euthymic BD patients and 29 healthy controls (HC), and performed whole-brain psychophysiological interaction (PPI) analysis to obtain task-modulated FC. Abnormal FC patterns were identified through support vector machine-based classification. The topological organization of task-modulated FC networks was estimated by the graph theoretical analysis and compared between BD and HC.RESULTS:BD exhibited widely distributed aberrant task-modulated FC patterns not only in core neurocognitive intrinsic brain networks (the fronto-parietal, cingulo-opercular, and default mode networks), but also in the cerebellum and primary processing networks (sensorimotor and visual). Furthermore, the local efficiency of the frontal-parietal network was significantly increased in BD.LIMITATIONS:The modest sample size. Only face pictures with negative emotion were used. Only unidirectional task-modulated FC was investigated.CONCLUSIONS:BD patients showed a widely distributed aberrant task-modulated FC pattern. Particularly, the fronto-parietal network, as one of the core neurocognitive intrinsic brain networks, was the primary network that demonstrated changes of both FC strength and local efficiency in BD. These findings on the task-modulated FC between these intrinsic brain networks might be considered an endophenotype of the BD condition persistent in the euthymic state.

在双相障碍中,混合状态是一种常见的情感发作类型,对其药物治疗需要得到临床足够重视.本文回顾了2017～2021年相关的指南/推荐/建议,对成年人混合状态急性期的药物治疗进行综述.

BACKGROUND:Dynamic functional connectivity (dFC) based on resting-state fMRI has attracted interest in the field of bipolar disorder (BD), because dFC can better capture the evolving processes of emotion and cognition, which are typically impaired in BD. However, previous dFC studies of BD have typically focused on specific seed brain regions or specific functional brain networks, and they have ignored global dynamic information interaction in the whole brain. This study is aimed to reveal aberrant and interpretable whole-brain dFC patterns of BD.METHODS:The resting-state fMRI data collected from 35 euthymic BD patients and 30 healthy people. We developed a new dFC inference pipeline, including the sliding-window method, k-means clustering, a new permutation with zero-inflated Poisson regression method, and a similarity analysis for interpretable states, to examine the different patterns of dFC states between BD patients and healthy participants.RESULTS:BD patients had significantly more frequent transitions between two specific dFC states, which were respectively close to high-level cognitive networks and low-level sensory networks, than healthy controls (p < 0.05, FDR).LIMITATIONS:The size of samples and other BD types need to be expanded to validate the results of this study. Possible confounding effect of medication.CONCLUSIONS:This study detected aberrant dFC pattern of BD, which indicated the increased lability of the processes of cognition and emotion in BD, and this finding could improve our understanding of the neuropathological mechanism of BD.

双相障碍(Bipolar disorder,BD)是一类常见的精神障碍,其病因与发病机制尚不明确.近年来有证据表明神经免疫系统可能参与了BD的病理过程,BD涉及免疫细胞的激活和中枢神经系统炎症物质的释放,但其内在联系尚不完全清楚.BD患者外周的C-反应蛋白以及促炎细胞因子(如:白介素-1、干扰素-γ、白介素-6、肿瘤坏死因子-α)和抑炎细胞因子(如:白介素-4、白介素-10、转化生长因子-β)水平存在异常改变,但在不同性别、情感状态和疾病阶段下相关标志物水平具有明显差异,另外体重、合并症以及药物治疗也会影响到相关标志物的水平.明确神经免疫在BD的发病机制中的作用对BD的临床诊断和预后以及预测药物疗效具有潜在价值.

Abstract Objectives This study aims to explore the reliability, validity, and feasibility of Clinically Useful Depression Outcome Scale (CUDOS) in screening mixed features in patients diagnosed with mania. Methods A total of 109 patients with (hypo‐) manic episode were recruited. The reliability of Chinese version of CUDOS (CUDOS‐C) were analyzed with Cronbach's alpha and intraclass correlation coefficient (ICC). Spearman correlation coefficient was used to analyze the validity by comparing the correlation between CUDOS‐C and Patient Health Questionnaire‐9 (PHQ‐9), 32‐item Hypomania Checklist (HCL‐32). The score of MINI (hypo‐) manic episode with mixed features—DSM‐5 Module—Chinese version(MINI‐M‐C) ≥ 2 was considered as the gold standard of mixed features, and the receiver operating characteristic (ROC) curve analysis was used to calculate the optimal cut‐off values of CUDOS‐C score. Results The Cronbach's alpha value of CUDOS‐C was 0.898, and the ICC of CUDOS‐C test‐retest was 0.880 (95% CI: 0.812‐0.923, p < .05).The CUDOS‐C score was significantly correlated with PHQ‐9 score (r = 0.893, p = .000), but not with HCL‐32 score(r = 0.088, p = .364).The area under ROC curve was 0.909 (95% CI: 0.855 to 0.963, p < .001) for CUDOS‐C identifying mixed features in mania. The optimal cut‐off value was 11 with a sensitivity of 0.854 and a specificity of 0.868. The CUDOS‐C (score ≥ 12) identified 40.4% of the patients with mixed features, which was higher than those diagnosed by clinicians (18.3%) and screened using MINI‐M‐C (37.6%). Conclusions The results indicate the CUDOS‐C is a reliable and valid self‐administered questionnaire for assessing depressive symptoms and screening patients with mixed mania.

Background: : A useful scale for identification of mixed features in major depressive episodes (MDE) patients is urgent in China. This study aimed to evaluate the reliability and validity of the Chinese version of the Clinically Useful Depression Outcome Scale supplemented with questions for the DSM-5 mixed features specifier (ChineseCUDOS-M) in MDE patients. Methods: : A total of 152 MDE patients were recruited and assessed using Chinese-CUDOS-M, Patient Health Questionnaire-9 (PHQ-9) and 32-item Hypomania Checklist (HCL-32). Principal component analysis (PCA) and exploratory factor analysis (EFA) were conducted. The predictive validity was calculated by the area under the receiver operating characteristic curve (AUROC). Results: : The Cronbach's alpha of Chinese-CUDOS-M was 0.85. PCA showed three common factors with eigenvalue greater than 1; the eigenvalue of factor I was 4.96, with 38.1% of variance explanation. ChineseCUDOS-M depression subscale was associated with PHQ-9 (r = 0.83, p<0.01), and manic subscale was associated with HCL-32 (r = 0.73, p< 0.01). AUROC of the Chinese-CUDOS-M for patients with mixed depression was 0.90 (95%CI: 0.85-0.95), with a cut-off value of 7, sensitivity of 0.95, and specificity of 0.73. Furthermore, AUROC was 0.88 in patients with major depressive disorder (MDD), with a cut-off value of 7, sensitivity of 0.96, and specificity of 0.71. AUROC was 0.92 in bipolar disorder (BD) depression patients, with a cut-off value of 9, sensitivity of 0.89, and specificity of 0.87. Conclusion: : Our study shows that the Chinese-CUDOS-M can identify mixed features in both MDD and BD depression with satisfactory reliability and validity.

Background: Early identification of bipolar disorder (BD) from major depressive disorder (MDD) is difficult since no tools available to estimate the risk of BD. This study aimed to develop and validate a model of oxidative stress injury for predicting BD. Methods: Data of 1,252 BD and 1,359 MDD patients were collected, including 64 MDD patients who were identified as converting to BD from 2009 through 2018. 30 variables from a randomly selected subsample of 1,827 (70%) patients were used to develop the model, including age, sex, oxidative stress markers (uric acid, bilirubin, albumin, prealbumin), sex hormones, cytokines, thyroid and liver function, glycolipid metabolism, etc. Univariate analyses and the Least Absolute Shrinkage and Selection Operator (LASSO) were applied for data dimension reduction and variable selection. Multivariable logistic regression was used to construct BIOS model on nomogram. Internal validation assessed in the remaining 784 patients (30%), and independent external validation done by 3,797 matched patients from five other hospitals in China. Results: 10 predictors, mainly the oxidative stress markers, were shown on nomogram. BIOS model showed good discrimination in the training sample, with AUC of 75.1% (95% CI: 72.9%~77.3%), sensitivity of 0.66, and specificity of 0.73. The discrimination was well both at internal validation (AUC 72.1%, 68.6~75.6%) and external validation (AUC 65.7%, 63.9~67.5%). Conclusion: A nomogram centered on oxidative stress injury could help individualized prediction of BD. For better real-world practice, a set of measurements especially on oxidative stress markers should be emphasized using big data in psychiatry. Funding: China Key R&D Program (2016YFC1307100), the NSFC (81930033, 81771465, 91232719), SMHC-CRC (CRC2018DSJ01-1), and the Innovative Research Team of High-level Local Universities in Shanghai. Declaration of Interest: None to declare. Ethical Approval: The study was registered at International Clinical Trials Registry Platform with the number of NCT03949218. Ethical issue was approved by the SMHC Institution Review Board (IRB, number of 2019-15R) and the informed consent requirement was omitted according to relevant research.