Studying the Effect of Sertraline in Reducing Aggressive Behavior in Patients with Major Depression

The Mental Health Outcomes and Cost Estimates of Korean Medicine for Anxiety Disorder Patients

Korean medicine (KM) is used to treat anxiety disorders, but there is limited research on its effects. This study aimed to examine the associations between improved QoL and reduced clinical symptoms and KM in patients with anxiety disorders. The medical records of patients with anxiety who were treated with KM (acupuncture, psychotherapy, Chuna therapy, aromatherapy, or herbal medicine) for at least 4 weeks were retrospectively analyzed. Clinical, QoL, and cost outcomes were measured at baseline and at weeks 4 and 12 (Anxiety: State-Trait Anxiety Inventory [STAI X-1 (state), X-2 (trait)], Beck Anxiety Inventory [BAI]; anger: State-Trait Anger Expression Inventory State [STAXI-S (state), T (trait)], Anger Expression Inventory [AXI-K-I (anger-in), AXI-K-O (anger-out), AXI-K-C (anger-control); depression: Beck Depression Inventory-II [BDI II], QoL: QoL-related instruments Euro Quality of Life 5 Dimensions utility score [EQ-5D], Euro QoL Visual Analog Scale [EQ-VAS]). The total costs for each item were calculated in terms of NHIS-covered costs and patients' out-of-pocket costs from the perspective of the healthcare system. The medical records of 67 patients were evaluated. The KM treatments were found to be associated with decreased anxiety (STAI X-1; STAI X-2; BAI, p < 0.0001), depression (BDI-II, p < 0.0001), and anger (AKI-K-I; AKI-K-O, p < 0.05) and increased QoL (EQ-5D; EQ-VAS, p < 0.0001). An average of USD 1360 was paid for the KM treatments for 4 weeks. The study findings suggested that KM may improve clinical symptoms and QoL outcomes in patients with anxiety disorders.

Machine learning-based prediction of sertraline concentration in patients with depression through therapeutic drug monitoring

Background: Sertraline is a commonly employed antidepressant in clinical practice. In order to control the plasma concentration of sertraline within the therapeutic window to achieve the best effect and avoid adverse reactions, a personalized model to predict sertraline concentration is necessary. Aims: This study aimed to establish a personalized medication model for patients with depression receiving sertraline based on machine learning to provide a reference for clinicians to formulate drug regimens. Methods: A total of 415 patients with 496 samples of sertraline concentration from December 2019 to July 2022 at the First Hospital of Hebei Medical University were collected as the dataset. Nine different algorithms, namely, XGBoost, LightGBM, CatBoost, random forest, GBDT, SVM, lasso regression, ANN, and TabNet, were used for modeling to compare the model abilities to predict sertraline concentration. Results: XGBoost was chosen to establish the personalized medication model with the best performance (R 2 = 0.63). Five important variables, namely, sertraline dose, alanine transaminase, aspartate transaminase, uric acid, and sex, were shown to be correlated with sertraline concentration. The model prediction accuracy of sertraline concentration in the therapeutic window was 62.5%. Conclusion: In conclusion, the personalized medication model of sertraline for patients with depression based on XGBoost had good predictive ability, which provides guidance for clinicians in proposing an optimal medication regimen.

Predicting plasma concentration of quetiapine in patients with depression using machine learning techniques based on real-world evidence

OBJECTIVES

We develop a model for predicting quetiapine levels in patients with depression, using machine learning to support decisions on clinical regimens.

METHODS

Inpatients diagnosed with depression at the First Hospital of Hebei Medical University from 1 November 2019, to 31 August were enrolled. The ratio of training cohort to testing cohort was fixed at 80%:20% for the whole dataset. Univariate analysis was executed on all information to screen the important variables influencing quetiapine TDM. The prediction abilities of nine machine learning and deep learning algorithms were compared. The prediction model was created using an algorithm with better model performance, and the model's interpretation was done using the SHapley Additive exPlanation.

RESULTS

There were 333 individuals and 412 cases of quetiapine TDM included in the study. Six significant variables were selected to establish the individualized medication model. A quetiapine concentration prediction model was created through CatBoost. In the testing cohort, the projected TDM's accuracy was 61.45%. The prediction accuracy of quetiapine concentration within the effective range (200-750 ng/mL) was 75.47%.

CONCLUSIONS

This study predicts the plasma concentration of quetiapine in depression patients by machine learning, which is meaningful for the clinical medication guidance.

Anti-anger Effects of Herbal Medicine: A Mini-Review of Rat Studies

OBJECTIVE

To analyze the available data on the anti-anger effects of herbal medicines (HMs) as well as their underlying mechanisms in rat models.

METHODS

From 6 electronic databases [PubMed, EMBASE, China National Knowledge Infrastructure (CNKI), Wanfang, Oriental Medicine Advanced Searching Integrated System (OASIS), and Research Information Sharing Service (RISS)], relevant animal experiments were searched by using "anger," "rats," and "animal" as search keywords. The last search was conducted on November 22, 2019, and all experiments involving rat models of anger and treatment using HMs published until the date of the search were considered.

RESULTS

A total of 24 studies with 16 kinds of HMs were included. Most studies have used the "tail irritating method" and "social isolation and resident intruder" method to establish anger models. According to the included studies, the therapeutic mechanisms of HMs for anger regulation and important herbs by their frequency and/or preclinical evidence mainly incladed regulation of hemorheology (Bupleuri Radix, Paeoniae Radix Alba, and Glycyrrhizae Radix), regulation of sex hormones (Bupleuri Radix, Cyperi Rhizoma, and Paeoniae Radix Alba), regulation of neurotransmitters (Cyperi Rhizoma), regulation of anger-related genes (Bupleuri Radix, Glycyrrhizae Radix, and Paeoniae Radix Alba), and other effects. Overall, Liver (Gan) qi-smoothing herbs including Bupleuri Radix and Cyperi Rhizoma were the most frequently used.

CONCLUSIONS

This review found the frequent methods to establish an anger model, and major mechanisms of anti-anger effects of HMs. Interestingly, some Liver qi-smoothing herbs have been frequently used to investigate the anti-anger effects of HM. These findings provide insight into the role and relevance of HMs in the field of anger management.

The efficacy and safety of agomelatine, sertraline, and escitalopram for senile post-stroke depression: A randomized double-blind placebo-controlled trial

OBJECTIVES

This study aims to investigate the efficacy and safety of agomelatine, sertraline, and escitalopram for patients with senile post-stroke depression (SPSD, aged over 65 years).

PATIENTS AND METHODS

A total of 165 patients (aged over 65 years) with post-stroke depression (PSD) were recruited. These patients were randomly assigned to one of four groups and given an anti-depressant or a placebo as follows: group A (agomelatine in combination with conventional cerebrovascular disease medication) 48 patients; group B (sertraline in combination with conventional cerebrovascular disease medication) 47 patients; group C (escitalopram in combination with conventional cerebrovascular disease medication) 50 patients; and, a control group (conventional treatment alone) 20 patients. The efficacy of the different treatments was evaluated using the Hamilton Depression Scale (HAMD), the National Institute of Health Stroke Scale (NIHSS), and the Activities of Daily Living (ADL) Barthel index (BI) at one, two, four, and six weeks after treatment began.

RESULTS

According to the HAMD, NIHSS score, and BI index, the patients who received one of the three antidepressant treatments showed significant improvement compared with the control group (p < 0.05), but there was no significant difference between the three groups receiving anti-depressant medication (p > 0.05). Laboratory tests showed that the general adverse effects of the treatments were mild in all three groups, and patients generally tolerated the treatments.

CONCLUSION

A decrease of HAMD and NIHSS scores and an increase in the BI index could be observed in the patients receiving agomelatine, sertraline, or escitalopram treatment. Thus, it would appear that the condition of SPSD in older patients can be improved with the use of either agomelatine, sertraline, or escitalopram.

Is Sertraline a Good Pharmacological Strategy to Control Anger? Results of a Systematic Review

Introduction: Extensive research has made it possible to conclude that dysfunctions in serotoninergic transmission are associated with a tendency toward violence and behavioral dysregulations in humans. In this regard, it has been suggested that selective serotonin reuptake inhibitors (SSRIs), such as sertraline, which regulate the serotonin system, might reduce proneness to violence. Aims: This review aims to explore changes in feelings of anger-state (e.g., irritability and hostility) and anger expression as primary outcomes after sertraline treatment. Methods: Based on PRISMA quality criteria for reviews, a literature search was carried out through PubMed, PsycINFO, Dialnet, Psicodoc, Web of Knowledge, and the Cochrane Library. Results: Initially, 605 publications were identified, removing 219 duplicate manuscripts and screening the titles and abstracts of the remaining 386 records. This process left 248 articles for full-text reading, finally including 15 entries. Thus, several empirical studies were included that employed different research designs. In this regard, we considered 3 case reports, 5 open clinical trials, and 7 randomized placebo-controlled trials. The majority of the studies were unanimous in concluding that a large percentage of patients with high irritability levels responded satisfactorily to sertraline treatment. In fact, their mood improved, and they experienced a reduction in irritability and anger expression after a few weeks of treatment (approximately two weeks). However, it was necessary to increase the sertraline dose after months of treatment to avoid exhaustion effects. Moreover, not all the patients responded to the treatment and it is particularly interesting that a small percentage of patients were refractory to treatment or even showed an increase in irritability after a few weeks of treatment. In those cases, it was necessary to discontinue the treatment or reduce the dose to the initial levels. Discussion: Although it is necessary to be cautious about the benefits of sertraline as a way to control anger and irritability, it is relevant to consider pharmacological strategies to reduce anger-state as coadjutant treatments to psychotherapy in order to promote lasting changes in violent populations.