Hamilton scale and MADRS are interchangeable in meta-analyses but can disagree at trial level

Impact of dementia-landscaped therapy garden on psychological well-being- A pilot study

Non-pharmacological interventions are increasingly recognized as first-line therapies for managing dementia symptoms alongside pharmacologic strategies. Among these, therapy gardens and horticultural interventions have emerged as promising adjunctive approaches. This pilot study aimed to evaluate the effects of a six-month dementia-friendly therapy garden intervention on psychological well-being, specifically depression levels, and to determine whether baseline dementia severity predicts treatment success. The study was conducted in a real-world setting, with a final sample of 28 dementia patients. Unlike previous studies, this intervention incorporated multimodal stimulation, including sensory, motor, and cognitive elements. Results indicated a significant reduction in depression, as measured by the Montgomery-Åsberg Depression Rating Scale (MADRS) after six months of intervention (p <.05). However, depression scores assessed using the Hamilton Depression Rating Scale (HAM-D) showed only a trend toward improvement but did not reach statistical significance. No improvements were observed at the three-month mark, suggesting that sustained engagement is necessary for measurable benefits. Cognitive function, as assessed by dementia severity, did not show significant improvement, and dementia severity at baseline was not a significant predictor of treatment response. These findings underscore the potential of dementia-friendly therapy gardens to provide meaningful psychological benefits by significantly reducing depression over time. Notably, even individuals with more advanced dementia benefited, challenging the prevailing notion that non-pharmacological interventions are primarily effective in early disease stages. These results highlight the need for further research on the long-term effects and mechanisms underlying garden-based interventions in dementia care.

Predictors of Cognitive Decline in Alzheimer's Disease: A Longitudinal Bayesian Analysis

Background and Objectives: Alzheimer's disease (AD) is a progressive neurodegenerative condition that significantly affects cognitive, emotional, and functional abilities in older adults. This study aimed to explore how demographic, clinical, and psychological factors influence the progression of cognitive decline in patients diagnosed with AD. Materials and Methods: A total of 101 patients were evaluated retrospectively and followed longitudinally at three different time points, using standardized instruments, including the MMSE, Reisberg's GDS, clock-drawing test, MADRS, and Hamilton depression scale. Statistical methods included non-parametric tests, mixed-effect modeling, and Bayesian analysis. Results: Most patients were older women from rural areas, predominantly in moderate-to-severe stages of AD. Age showed a significant association with cognitive decline (p < 0.05), and depression-particularly in moderate and severe forms-was strongly linked to lower MMSE scores (p < 0.001). Over 70% of the participants had some degree of depression. The clock-drawing test highlighted visuospatial impairments, consistent with everyday functional loss. Although donepezil and memantine combinations appeared to be more frequently prescribed, no treatment showed a statistically significant advantage, and confidence interval overlaps suggest caution in interpreting differences between therapies. Longitudinal models confirmed a progressive and accelerated decline, with inter-individual variability becoming more pronounced in later stages. Although comorbidities, such as hypertension and diabetes, were frequent, they did not show a statistically significant effect on MMSE scores in this cohort. Conclusions: Age and depression appear to play central roles in the pace of cognitive deterioration in AD. Given the limited efficacy of most current therapies, these findings highlight the need for earlier intervention and a more personalized, integrated approach-combining cognitive care, psychiatric support, and comorbidity management-to better meet the needs of patients with AD.

How to Determine a Therapeutic Reference Range for a Psychotropic Drug Systematically? Recommendations of the TDM Task Force of the AGNP

BACKGROUND

Therapeutic drug monitoring (TDM) is essential for controlling pharmacogenetic and pharmacokinetic variations and for optimizing pharmacotherapy. However, its value is often underestimated because of nonsystematic recommendations for target ranges in the literature. The purpose of this study was to emphasize transparency and systematization in the forthcoming Updates to the Arbeitsgemeinschaft für Neuropsychopharmakologie und Pharmakopsychiatrie (AGNP)-TDM Consensus Guidelines.

METHODS

Here, a stepwise method for determining therapeutic reference ranges (TRRs) in psychiatry is introduced. By using various data types, a multidimensional approach for establishing a range is presented. The data types were classified based on how effectively they supported the target ranges. This method was demonstrated for 3 drugs commonly used in psychiatry (aripiprazole, olanzapine, and escitalopram).

RESULTS

Despite the methodological shortcomings in published concentration-effect studies, the approach used here enabled the determination of reference ranges by combining multiple types of data. The lower limit of the TRR is ideally derived from studies that link blood drug concentrations to clinical effectiveness, particularly symptom-specific responses, after fixed-dose treatment. The upper limit depends on the concentrations associated with adverse reactions or maximal response. Thresholds can be estimated using receiver operating characteristic analyses. Preliminary thresholds were derived from responder concentration data or from expected drug concentrations under approved doses. Positron emission tomography studies were used to further validate these ranges.

CONCLUSIONS

This study proposed a new standard for determining the TRR of psychotropic drugs, thereby enhancing their clinical utility and validity. Adjusting blood levels to these ranges should improve response rates and medication tolerance.

Correlates of higher anxiety scores reported by women admitted for elective caesarean section

Background

An elective caesarean section (CS) has been associated with high anxiety scores, and there are associations between higher anxiety scores and younger age, primigravidae, higher educational level, and previous experience with anaesthesia. In this study, the aim is to measure anxiety scores associated with an elective CS using two measuring scales and identify women's characteristics and obstetrics variables that are associated with higher scores.

Methods

A cross-sectional study was conducted between Nov 15, 2019 and Nov 15, 2020. Women were included if they were 18 years of age or more, had viable pregnancies, and were admitted for an elective CS. Anxiety scores were measured on admission using the visual analogue scale for anxiety (VASA) and then the State-Trait Anxiety Inventory (STAI-Y). Associated factors were studied using logistic regression analyses.

Results

Three hundred women were recruited. Means (SD) for the participant's age and gestation age were 30.5 (5.7) years and 37.6 (1.4) weeks, respectively. Additionally, 29.3% of the participants having a CS were primigravidae and 62.3% were for maternal indications. Furthermore, 55%, 59%, and 61% of the women had scores above the means of VASA and STAI-S components 1 and 2, respectively.Variables that showed statistically significant associations with higher anxiety scores were that the woman's age was 25-34, the CS was for foetal indications, the choice of anaesthesia was general, and the source of information for the choice of anaesthesia was a layperson.

Conclusion

Higher anxiety scores are prevalent among women admitted for an elective CS. STAI-Y and VASA correlated well, and the short VASA may replace the lengthy STAI-Y in clinical practice. Identification of women with risk factors may help in implementing strategies to reduce anxiety.

Predictive biosignature of major depressive disorder derived from physiological measurements of outpatients using machine learning

Major Depressive Disorder (MDD) has heterogeneous manifestations, leading to difficulties in predicting the evolution of the disease and in patient's follow-up. We aimed to develop a machine learning algorithm that identifies a biosignature to provide a clinical score of depressive symptoms using individual physiological data. We performed a prospective, multicenter clinical trial where outpatients diagnosed with MDD were enrolled and wore a passive monitoring device constantly for 6 months. A total of 101 physiological measures related to physical activity, heart rate, heart rate variability, breathing rate, and sleep were acquired. For each patient, the algorithm was trained on daily physiological features over the first 3 months as well as corresponding standardized clinical evaluations performed at baseline and months 1, 2 and 3. The ability of the algorithm to predict the patient's clinical state was tested using the data from the remaining 3 months. The algorithm was composed of 3 interconnected steps: label detrending, feature selection, and a regression predicting the detrended labels from the selected features. Across our cohort, the algorithm predicted the daily mood status with 86% accuracy, outperforming the baseline prediction using MADRS alone. These findings suggest the existence of a predictive biosignature of depressive symptoms with at least 62 physiological features involved for each patient. Predicting clinical states through an objective biosignature could lead to a new categorization of MDD phenotypes.

Bifidobacterium breve CCFM1025 attenuates major depression disorder via regulating gut microbiome and tryptophan metabolism: A randomized clinical trial

OBJECTIVE

Psychobiotics, as a novel class of probiotics mainly acting on the gut-brain axis, have shown promising prospects in treating psychiatric disorders. Bifidobacterium breve CCFM1025 was validated to have an antidepressant-like effect in mice. This study aims to assess its psychotropic potential in managing major depression disorder (MDD) and unravel the underlying mechanisms.

METHODS

Clinical Trial Registration: https://www.chictr.org.cn/index.aspx (identifier: NO. ChiCTR2100046321). Patients (n = 45) diagnosed with MDD were randomly assigned to the Placebo (n = 25) and CCFM1025 (n = 20) groups. The freeze-dried CCFM1025 in a dose of viable bacteria of 10¹⁰ CFU was given to MDD patients daily for four weeks, while the placebo group was given maltodextrin. Changes from baseline in psychometric and gastrointestinal symptoms were evaluated using Hamilton Depression Rating scale-24 Items (HDRS-24), Montgomery-Asberg Depression Rating Scale (MADRS), Brief Psychiatric Rating Scale (BPRS), and Gastrointestinal Symptom Rating Scale (GSRS). Serum measures were also determined, i.e., cortisol, TNF-α, and IL-β. Serotonin turnover in the circulation, gut microbiome composition, and tryptophan metabolites were further investigated for clarifying the probiotics' mechanisms of action.

RESULTS

CCFM1025 showed a better antidepressant-like effect than placebo, based on the HDRS-24 (placebo: M = 6.44, SD = 5.44; CCFM1025: M = 10.40, SD = 6.85; t(43) = 2.163, P = 0.036, d = 0.640) and MADRS (placebo: M = 4.92, SD = 7.15; CCFM1025: M = 9.60, SD = 7.37; t(43) = 2.152, P = 0.037, d = 0.645) evaluation. The factor analysis of BPRS and GSRS suggested that patients' emotional and gastrointestinal problems may be affected by the serotonergic system. Specifically, CCFM1025 could significantly and to a larger extend reduce the serum serotonin turnover compared with the placebo (placebo: M = -0.01, SD = 0.41; CCFM1025: M = 0.27, SD = 0.40; t(43) = 2.267, P = 0.029, d = 0.681). It may be due to changes in gut microbiome and gut tryptophan metabolism under the probiotic treatment, such as changes in alpha diversity, tryptophan, and indoles derivatives.

CONCLUSION

B. breve CCFM1025 is a promising candidate psychobiotic strain that attenuates depression and associated gastrointestinal disorders. The mechanisms may be relevant to the changes in the gut microbiome and tryptophan metabolism. These findings support the future clinical applications of psychobiotics in the treatment of psychiatric disorders.

The prevalence of and factors associated with antenatal depression among all pregnant women first attending antenatal care: a cross-sectional study in a comprehensive teaching hospital

BACKGROUND

Antenatal depression has become a common and serious problem, significantly affecting maternal and fetal health. However, evaluation and intervention methods for pregnant women in obstetric clinics are inadequate. This study aimed to determine the prevalence of and risk factors for depression among all pregnant women at their first attending antenatal care in the obstetrics clinic, a comprehensive teaching hospital, southwest of China.

METHODS

From June to December 2019, 5780 pregnant women completed online psychological assessments, and data from 5728 of the women were analyzed. The women were categorized into two groups according to the presence or absence of depression. Depression was assessed by the Patient Health Questionnaire-9 (PHQ-9), with a cutoff point of 10 for depression. Anxiety and somatic symptoms were measured by the Generalized Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire-15 (PHQ-15), respectively. Univariate analysis and binary logistic regression analysis were used to determine the association among antenatal depression, anxiety, somatic symptoms and participants' characteristics.

RESULTS

The prevalence of antenatal depression among all the pregnant women at their first attending antenatal care was 16.3%, higher in the first trimester (18.1%). Anxiety symptoms (Mild anxiety AOR = 2.937; 95% CI: 2.448-3.524) and somatic symptoms (Mild somatic symptoms AOR = 3.938; 95% CI: 2.888-3.368) were major risk factors for antenatal depression among women and the risk increased more with the anxiety level or somatic symptoms level. Gestational weeks (second trimester AOR = 0.611; 95% CI: 0.483-0.773; third trimester AOR = 0.337; 95% CI: 0.228-0.498) and urban residence (AOR = 0.786; 95% CI: 0.652-0.947) were protective factors for antenatal depression among women.

CONCLUSIONS

About one in six pregnant women would experience depression, and special attention should be paid to some risk factors (i.e., early pregnancy, anxiety symptoms, somatic symptoms, rural residence). Online psychological assessments might be a time-saving and convenient screening method for pregnant women in obstetric clinics.