Characteristics of Dimensional Psychopathology in Suicidal Patients With Major Psychiatric Disorders and Its Association With the Length of Hospital Stay: Algorithm Validation Study

The interaction network and potential clinical effectiveness of dimensional psychopathology phenotyping based on EMR: a Bayesian network approach

The current DSM-oriented diagnostic paradigm has introduced the issue of heterogeneity, as it fails to account for the identification of the neurological processes underlying mental illnesses, which affects the precision of treatment. The Research Domain Criteria (RDoC) framework serves as a recognized approach to addressing this heterogeneity, and several assessment and translation techniques have been proposed. Among these methods, transforming RDoC scores from electronic medical records (EMR) using Natural Language Processing (NLP) has emerged as a suitable technique, demonstrating clinical effectiveness. Numerous studies have sought to use RDoC to understand the Diagnostic and Statistical Manual of Mental Disorders (DSM) categories from a qualified perspective, but few studies have examined the distribution variations and interaction characteristics of RDoC within various DSM categories through retrospective analyses. Therefore, we employed unsupervised learning to translate five domains of eRDoC scores derived from electronic medical records (EMR) of patients diagnosed with Major Depressive Disorder (MDD), Schizophrenia (SCZ), and Bipolar Disorder (BD) at West China Hospital between 2008 and 2021. The distribution characteristics, interaction networks, and potential clinical effectiveness of RDoC domains were analyzed. Using non-parametric statistical tests, we found that MDD had the highest score in Negative Valence System (NVS) (4.1, p < 0.001), while BD exhibited the highest score in Positive Valence System (PVS) score (4.9, p < 0.001) and Arousal System (AS) (4.4, p < 0.001). SCZ demonstrated the highest scores in Cognitive Systems (CS) (5.8, p < 0.001) and Social Processes Systems (SPS) (4.6, p < 0.001). Through Bayesian network (BN) analysis, we identified relatively consistent interaction relationships among various RDoC domains (NVS → AS, NVS → CS, NVS → PVS, as well as CS → SPS; parameter range = 0.156 to 0.635, p < 0.001). Lastly, using logistic regression and Cox proportional hazards models, we demonstrated that AS was significantly associated with the length of hospital stay (-0.21, p < 0.05) and 30-day readmission risk (adjusted odds ratio [aOR] = 0.91, 95% confidence interval [CI] 0.91-0.99) to some extent. In conclusion, we suggest that the eRDoC characteristics varied in different DSM. By Bayesian Network, we found NVS and CS might be potential source in interacting with other system. Furthermore, CS, SPS and AS were associated with the length of stay and 30-days readmission, making them effective for predicting prognosis of psychiatric disorders.

Association between psychiatric symptoms with multiple peripheral blood sample test: a 10-year retrospective study

Background

Psychiatric illness is thought to be a brain somatic crosstalk disorder. However, the existing phenomenology-based Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) diagnostic framework overlooks various dimensions other than symptoms. In this study, we investigated the associations between peripheral blood test indexes with various symptom levels of major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) to explore the availability of peripheral blood test indexes.

Methods

We extracted cases diagnosed with MDD, BD, and SCZ at West China Hospital from 2009 to 2021, translated their main complaints into Research Domain Criteria (RDoC) symptom severity scores using nature language processing (NLP), and collected their detailed psychiatric symptoms and peripheral blood test results. Then, generalized linear models were performed between seven types of peripheral blood test values with their transformed RDoC scores and detailed symptom information adjusted for age, gender, smoking, and alcohol history.

Results

Several inflammatory-related indexes were strongly associated with the negative valence system (NVS) domain (basophil percentage adjusted β = 0.275, lymphocyte percentage adjusted β = 0.271, monocyte percentage adjusted β = 0.223, neutrophil percentage adjusted β = -0.310, neutrophil count adjusted β = -0.301, glucose adjusted β = -0.287, leukocyte count adjusted β = -0.244, NLR adjusted β = -0.229, and total protein adjusted β = -0.170), the positive valence system (PVS) domain (monocyte percentage adjusted β = 0.228, basophil count adjusted β = 0.176, and glutamyl transpeptidase adjusted β = 0.171), and a wide range of mood, reward, and psychomotor symptoms. In addition, glucose, urea, urate, cystatin C, and albumin showed considerable associations with multiple symptoms. In addition, based on the direction of associations and the similarity of symptoms in terms of RDoC thinking, it is suggested that "positive" mood symptoms like mania and irritability and "negative" mood symptoms like depression and anxiety might be on a continuum considering their opposite relationships with similar blood indexes.

Limitations

The cross-sectional design, limited symptoms record, and high proportion of missing values in some other peripheral blood indexes limited our findings.

Conclusion

The proportion of high inflammatory indexes in SCZ was relatively high, but in terms of mean values, SCZ, BD, and MDD did not differ significantly. Inflammatory response showed a strong correlation with NVS, PVS, and a range of psychiatric symptoms especially mood symptoms, psychomotor symptoms, and cognitive abilities.

Hospital Length of Stay and Associated Factors in Adult Patients with Depression in Germany: A Cross-Sectional Study

Objective: The aim of the present study was to evaluate the hospital length of stay (LoS) and its associated factors among adult patients hospitalized with depression in Germany. Methods: This cross-sectional study included all adults (≥18 years) hospitalized with depression from January 2019 to December 2023 treated in 36 hospitals across Germany. The primary outcome was patients' hospital LoS in days. The associations between age, sex, depression severity, co-diagnoses, hospital, and hospital LoS were analyzed using hierarchical multivariable linear regression models. Results: A total of 6579 patients (mean age 46.6 ± 17.7 years) with 8965 hospitalizations for depression were available. The mean hospital LoS was 35.2 days. Severe depression (+4.9 days) was associated with a longer hospital LoS, with moderate depression as the reference. Older age was positively associated with a longer hospital LoS. Vitamin D deficiency (+9 days), lipid metabolism disorders (+8 days), obesity (+8 days), sleep disorders (+7 days), and reaction to severe stress and adjustment disorders (+5 days) were also significantly associated with hospital LoS. Conclusions: In patients with depression, higher depression severity, advanced age, vitamin D deficiency, lipid metabolism disorders, obesity, sleep disorders, reactions to severe stress, and adjustment disorders were associated with a longer hospital LoS. Addressing these factors through comprehensive and integrated care strategies could help optimize hospitalization duration and improve overall patient outcomes.

Factors related to the length of stay for major depressive disorder patients in China: A real-world retrospective study

Background

As numerous patients with depression have to be hospitalized because of various reasons, the demand far exceeds the limited bed count in the psychiatry department. Controlling the length of stay (LOS) of the patient is gradually being considered an effective method to alleviate this problem. Given the lack of statistical evidence of the LOS of patients with major depressive disorder (MDD) in China and the strain on the limited psychiatric resources, the purpose of our study was to investigate the LOS of patients with MDD among in-patient samples and to analyze related factors of the LOS in China by building a regression model.

Method

The data were exported from the electronic medical record system. A total of three categories of independent variables were enrolled in our study, namely, demographic, clinical, and biochemical. Univariate analysis and binominal regression analysis were applied comprehensively to find the factors related to the LOS among MDD samples. The discrimination accuracy of the model was evaluated by the receiver operating characteristic (ROC) analysis. ROC analysis indicated that the discrimination accuracy of our model was acceptable (AUC = 0.790, 95% CI = 0.714–0.865, P < 0.001).

Result

A total of 254 patients were finally brought into analysis after filtering. Regression analysis indicated that abnormal LDL was the only risk factor of long LOS (OR = 3.352, 95% CI = 1.087–10.337, P = 0.035) among all the kinds of variables. Notably, in the statistically irrelevant factors of the LOS, the category of anti-depressant drugs [serotonin–norepinephrine reuptake inhibitor (SNRI) or selective serotonin reuptake inhibitor (SSRI)] prescribed to patients with MDD was not associated statistically with the LOS, which was against our initial hypothesis that the LOS of patients with MDD treated with SNRI would vary from that of the patients treated with SSRI.

Conclusion

Up to our knowledge, our research is the first study to show the potential factors related to the LOS from various domains, especially biochemical indexes, and the effect of drugs, among clinical patients with MDD in China. Our results could provide a theoretical reference for efficient psychiatry hospitalization management and prioritization of allocating medical resources. Future studies are required for updating independent variables which are potentially related to the LOS and verifying existing results in a larger sample.