Can a Novel Algorithmic Approach Operationalise the Management of Depression & Anxiety for Primary Care?

Research Paper Title

Effects of Brief Depression and Anxiety Management Training on a US Army Division’s Primary Care Providers.

Background

There is a nation-wide gap between the prevalence of mental illness and the availability of psychiatrists. This places reliance on primary care providers (PCPs) to help meet some of these mental health needs.

Similarly, the US Army expects its PCPs to be able to manage common mental illnesses such as anxiety and depression. Therefore, PCPs must be able to close their psychiatric skills gaps via lifelong learning.

Methods

Following needs assessment of PCPs in a US Army division, the curriculum was developed. Objectives targeted pharmacological management of depression and anxiety. Behavioural intervention skills were also taught to treat insomnia.

Didactics and case-based small groups were used. A novel psychotropic decisional tool was developed and provided to learners to assist and influence their future psychiatric practice. Pre-training, immediate post-training, and 6-month assessments were done via survey to evaluate confidence and perceived changes in practice.

The curriculum was executed as a quality improvement project using the Plan, Do, Study, Act framework.

Results

Among 35 learners, immediate confidence in selecting optimal psychotropic and perceived knowledge, skill to change the dose or type of medication, and confidence in prescribing behavioural sleep improved significantly with large effect sizes.

At 6-month follow-up, learners reported that they were more likely to adjust medications for anxiety or depression and were more likely to start a new medication for anxiety or depression because of the training with moderate effect sizes. Use and satisfaction with the psychotropic decisional tool are also reported.

Conclusions

The psychotropic decisional tool illustrates a novel algorithmic approach for operationalising the management of depression and anxiety.

Similar approaches can improve the skills of a variety of PCPs in the management of psychiatric disorders.

Further studies in the military operational setting are needed to assess the effects of similar educational interventions on access to behavioural health care, suicidal behaviours, and unit medical readiness.

Reference

Amin, R. & Thomas, M.A. (2020) Effects of Brief Depression and Anxiety Management Training on a US Army Division’s Primary Care Providers. Military Medicine. doi: 10.1093/milmed/usz443. Online ahead of print.

Gaming Disorders & their Association with Mental Disorders for African Countries

Research Paper Title

Insomnia, Sleepiness, Anxiety and Depression Among Different Types of Gamers in African Countries.

Background

Gaming has increasingly become a part of life in Africa. Currently, no data on gaming disorders or their association with mental disorders exist for African countries.

This study for the first time investigated:

  1. The prevalence of insomnia, excessive daytime sleepiness, anxiety and depression among African gamers;
  2. The association between these conditions and gamer types (i.e. non-problematic, engaged, problematic and addicted); and
  3. The predictive power of socioeconomic markers (education, age, income, marital status, employment status) on these conditions.

Methods

10,566 people from 2 low- (Rwanda, Gabon), 6 lower-middle (Cameroon, Nigeria, Morocco, Tunisia, Senegal, Ivory Coast) and 1 upper-middle income countries (South Africa) completed online questionnaires containing validated measures on insomnia, sleepiness, anxiety, depression and gaming addiction.

Results

Results showed the sample of gamers (24 ± 2.8 yrs; 88.64% Male), 30% were addicted, 30% were problematic, 8% were engaged and 32% were non-problematic.

Gaming significantly contributed to 86.9% of the variance in insomnia, 82.7% of the variance in daytime sleepiness and 82.3% of the variance in anxiety [p < 0.001].

Conclusions

This study establishes the prevalence of gaming, mood and sleep disorders, in a large African sample.

The results corroborate previous studies, reporting problematic and addicted gamers show poorer health outcomes compared with non-problematic gamers.

Reference

Sosso, F.A.E, Kuss, D.J., Vandelanotte, C., Jasso-Medrano, J.L., Husain, M.E., Curcio, G., Papadopoulos, D., Aseem, A., Bhati, P., Lopez-Rosales, F., Becerra, J.R., D’Aurizio, G., Mansouri, H., Khoury, T., Campbell, M. & Toth, A.J. (2020) Insomnia, Sleepiness, Anxiety and Depression Among Different Types of Gamers in African Countries. Scientific Reports. 10(1):1937. doi: 10.1038/s41598-020-58462-0.

Is Type 2 Diabetes an Independent Risk Factor for Alzheimer Patients with Depression?

Research Paper Title

Analysis of Risk Factors for Depression in Alzheimer’s Disease Patients.

Background

Depression, which affects about 52% of Alzheimer’s disease (AD) patients, can worsen cognitive impairment and increase mortality and suicide rates.

The researchers hope to provide clinical evidence for the prevention and treatment of depression in AD patients by investigating related risk factors of depression in AD patients.

Methods

158 AD inpatients of the Department of Neurology, Daping Hospital from September 2017 to March 2019 were enrolled. General information, laboratory tests, cognitive and emotional function assessments of the inpatients were collected.

Logistic regression was used to analyse the risk factors of depression in AD patients, and the relationship between 17 Hamilton depression scale scores and HbA1c levels in AD patients was further analysed.

Results

The prevalence of age, gender, hypertension, hyperlipidemia, Type 2 diabetes mellitus (T2DM), and white matter lesions (WML) in the AD with depression group was significantly different from without depression group.

Hypertension, T2DM, and WML are independent risk factors for depression in AD patients.

The depression scores of AD patients with HbA1c>6.5% were significantly higher than AD patients with HbA1c ≤ 6.5%, and there were significant difference in depression scale scores between using anti-diabetes drugs group and not using anti-diabetes drugs group whose HbA1c level is >6.5%, while no difference in depression scores between using anti-diabetes drugs group and not using anti-diabetes drugs group whose HbA1c level is ≤6.5%.

Conclusions

T2DM is an independent risk factor for AD patients with depression.

Increased HbA1c levels aggravate depression in AD patients, and controlling HbA1c levels and anti-diabetes drugs can reduce the severity of depression in AD patients.

Reference

Yang, H., Hong, W., Chen, L., Tao, Y., Peng, Z. & Zhou, H. (2020) Analysis of Risk Factors for Depression in Alzheimer’s Disease Patients. The International Journal of Neuroscience. 1-6. doi: 10.1080/00207454.2020.1730369. Online ahead of print.

Is Early Improvement within the First 2 Weeks of Receiving Antidepressant Treatment a Predictor of Outcome in Patients with MDD and a High Level of Anxiety?

Research Paper Title

Antidepressant treatment strategy with an early onset of action improves the clinical outcome in patients with major depressive disorder and high anxiety: a multicenter and 6-week follow-up study.

Background

Major depressive disorder (MDD) is a prevalent, often chronic, and highly disabling multidimensional psychiatric illness. Moreover, co-occurring anxiety symptoms are extremely common among patients with MDD; up to 90% of patients present with anxiety symptoms. Notably, high levels of anxiety symptoms may predict worse clinical outcomes because of poor response to pharmacotherapy for MDD. So use of augmentation or combination strategies during early course of treatment could be necessary, but ensuring the accurate and timely change is difficult because of the lack of consensus to assess the early improvement of initial treatment. To date, replicated evidence indicates that the lack of early improvement (eg, <20% reduction in a depression scale score) in 2 weeks can be an accurate predictor to identify eventual non-responders. This study aimed to evaluate the early onset of antidepressant action and clinical outcomes in patients with MDD and high anxiety, and to explore the potential influencing factors of early onset improvement.

Methods

This study was a post-hoc analysis of a multi-centre, randomised, parallel-controlled, open-label study. The study protocol was approved by the independent ethics committee in each research centre or the ethics committee of the Peking University Sixth Hospital. All the participants provided written informed consent before the study. A total of 245 patients (aged 18–65 years) were diagnosed with MDD based on the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision criteria. They were required to have a current major depressive episode with a total score ≥17 on the Hamilton Depression Rating Scale 17-item (HAMD-17), and also have a high level of anxiety symptoms with a total score ≥14 on the Hamilton Anxiety Rating Scale (HAMA) at the baseline visit.

All eligible patients were assigned to receive at least 6 weeks of follow-up and antidepressant treatment, including selective serotonin reuptake inhibitors (SSRIs) alone or coupled with a flexible dose of tandospirone. The involved SSRIs were fluoxetine, paroxetine, fluvoxamine, sertraline, citalopram, and escitalopram. Notably, not all the patients were naive to any antidepressants at the first visit, but they were not treated with adequate dose of antidepressants for more than 2 weeks in the current episode. Treatment with several sedative-hypnotic drugs for short-term use was permitted as needed for sleep disorders, including zopiclone, lorazepam, alprazolam, clonazepam, midazolam, zaleplon, and zolpidem.

The efficacy measurements were evaluated at different visit points, including week 2, week 4, and week 6. The evaluation tools included HAMD-17 total scores, HAMA total scores, and Clinical Global Impressions Severity Subscale (CGI-S) score. Moreover, short form-12 (SF-12) physical component score (PCS) and mental component score (MCS) were used to assess the quality of life of these patients. Remission assessment was defined as showing an HAMD-17 total score ≤7 points.

At the end of week 2,240 patients remained and were divided into two groups based on the reduction rate of HAMD-17 total score compared with the baseline: early-improvement group (≥20% decrease in HAMD-17 total score, n = 134) and early-unimproved group (<20% decrease in HAMD-17 total score, n = 106). Finally, 230 patients completed the 6-week follow-up, including 128 patients with early-improvement and 102 early-unimproved patients. The comparison of the remission rate between the two groups was conducted in week 6. In addition, the potential influencing factors of early improvement in week 2 were also analysed.

The data analysis was based on the full analysis set. The data collected at each visit point were analysed using the mixed-effects repeated-measures model. The influencing factors of early improvement were analysed by logistic regression. All the statistical analyses were performed using the Statistical Package for the Social Sciences for Windows, version 24.0 (SPSS, Inc., Chicago, IL, USA). P < 0.05 was considered statistically significant.

Results

The baseline demographic data were similar between the two groups (P > 0.05), except for the number of patients taking sedative-hypnotic drugs. The patients in the early-improvement group showed more combination of sedative-hypnotic drugs compared with the patients in the early-unimproved group (12.7% [17/134] vs. 1.9% [2/106], χ2 = 11.979, P = 0.002).

At baseline, the total scores of HAMD-17 (24.76 vs. 23.11, P = 0.007) and CGI-S (4.89 vs. 4.54, P = 0.002) in the early-improvement group were significantly higher, and SF-12 (PCS) (38.77 vs. 41.65, P = 0.022) and SF-12 (MCS) (26.01 vs. 28.05, P = 0.035) scores were significantly lower than those in the early-unimproved group. The statistical superiority was observed for the early-improvement group in the HAMD-17 total score, HAMA total score, and CGI-S total score during weeks 2 to 6, SF-12 (PCS) score in week 6 and SF-12 (MCS) score between weeks 2 and 6.

Notably, the patients in the early-improvement group showed greater improvements in several important rating scales compared with the patients in the early-unimproved group at the endpoint visit. The least-squares (LS) mean in the HAMD-17 total score was statistically lower for the early-improvement group than the early-unimproved group (6.48 vs. 12.17, P < 0.001). The LS means in both HAMA total score (7.19 vs. 11.8, P < 0.001) and CGI-S total score (1.91 vs. 2.65, P < 0.001) were also significantly lower in the early-improvement group than in the early-unimproved patients. The greater improvements were observed in both SF-12 (PCS) score (48.26 vs. 45.36, P = 0.014) and SF-12 (MCS) score (44.21 vs. 36.36, P < 0.001) for the early-improvement group than for the early-unimproved group. In addition, the early-improvement group showed a significant difference in the remission rate in week 6 compared with the early-unimproved group (62.8% [80/128] vs. 29.4% [30/102], χ2 = 25.424, P < 0.001).

The logistic regression model was used to analyse the influencing factors for early improvement. The dependent variable was a dichotomous variable, which was an early improvement vs. early un-improvement. The independent variables included in the model were treatment (SSRIs + tandospirone vs. SSRIs), combination with sedative-hypnotic drugs, age, body weight, sex, age of onset of psychiatric symptoms, course of recent episode, and baseline total scores of HAMD-17, HAMA, CGI-S, SF-12 (MCS), and SF-12 (PCS) scales. Of these variables, the combination with sedative-hypnotic drugs was statistically significant (odds ratio: 7.556, 95% confidence interval: 1.607–35.530, P = 0.010), indicating that the combination with sedative-hypnotic therapy was more helpful for early improvement.

Conclusions

The present study successfully replicated the findings of previous major studies, which demonstrated a significant relationship between early improvement within the first weeks of antidepressant treatment and later remission rate in patients with MDD. Specifically, a similar association was found in patients with MDD and high level of anxiety symptoms. The results showed that patients who achieved the early improvement of the depressive symptoms in week 2 after antidepressant treatment also obtained the sustained relief of symptoms and improved quality of life during weeks 2 to 6. Further, these patients with early improvement displayed more significant clinical remission of depressive symptoms in week 6.

According to the logistic regression analysis, the results revealed that the combination with sedative-hypnotic drugs was a significant predictor of early improvement in week 2. Benzodiazepines are primarily used as a sedative-hypnotics in patients with MDD to alleviate anxiety symptom and insomnia, and they might contribute to the response to antidepressants in the first two weeks because they produce a faster onset of effect on anxiety symptoms than antidepressants alone. Thus, it may be justifiable to combine benzodiazepines as a short-term treatment in patients with MDD and high-level anxiety.

In summary, the early improvement within the first 2 weeks of receiving antidepressant treatment is a powerful predictor of outcome in patients with MDD and a high level of anxiety. Notably, the short-term combination with sedative-hypnotic drugs within the first few weeks may augment the early-onset improvement of antidepressant therapy.

Reference

Liao, Xue-Mei., Su, Yun-Ai1., Wang, Ying.; Yu, Xin. & Si, Tian-Mei. (2020) Antidepressant treatment strategy with an early onset of action improves the clinical outcome in patients with major depressive disorder and high anxiety: a multicenter and 6-week follow-up study. Chinese Medical Journal. 6, pp.726-728. doi: 10.1097/CM9.0000000000000673.

What is the Role of Combat Exposure & Malevolent Environments in Mental Health?

Research Paper Title

Do different types of war stressors have independent relations with mental health? Findings from the Korean Vietnam Veterans Study.

Background

South Korea had the second largest contingent of soldiers in the Vietnam War, but little is known about their adaptation, especially in later life.

Previous work in a different sample found very high rates of post-traumatic stress disorder (PTSD; 41%) among Korean Vietnam veterans (KVVs; Kang, Kim, & Lee, 2014), compared to 19-31% for American Vietnam veterans.

The researchers explored possible reasons for this high rate of PTSD, as well as anxiety and depressive symptoms, utilising both vulnerability factors (e.g., war stressors) and protective factors (optimism, unit cohesion, and homecoming experiences).

Method

The sample included 367 male KVVs surveyed by mail (M age = 72, SD = 2.66).

Using hierarchical regressions controlling for demographics, the researchers examined the relative contributions of different types of war stressors and then the protective factors.

Results

Combat exposure was significantly associated with the three types of negative psychological symptoms, but their associations became non-significant when “subjective” war stressors (malevolent environments, perceived threat, and moral injury) were added.

In the final models, malevolent environments were the strongest predictor for all three outcomes.

In addition, moral injury was independently associated with PTSD symptoms, while perceived threat was marginally associated with depressive and anxiety symptoms.

Among psychosocial factors, only optimism was negatively associated with the mental health outcomes.

Conclusions

KVVs had very high rates of combat exposure, but malevolent environments played a more important role in their mental health in later life.

These findings suggest the importance of considering adverse environmental factors in understanding PTSD in future studies.

Reference

Lee, H., Aldwin, C.M. & Kang, S. (2020) Do different types of war stressors have independent relations with mental health? Findings from the Korean Vietnam Veterans Study. Psychological Trauma: Theory, Research, Practice, and Policy. doi: 10.1037/tra0000557. [Epub ahead of print].

Do Physical Comorbidities affect the Diagnosis of Depression & Anxiety?

Research Paper Title

A systematic review and meta-analysis of the prevalence of common mental disorders in people with non-communicable diseases in Bangladesh, India, and Pakistan.

Background

The prevalence of mental and physical comorbidities is unknown in South Asia, as estimates of mental ill health in patients with non-communicable diseases (NCDs) have predominantly come from studies based in the United States, Europe and Australasia.

This systematic review and meta-analysis summarises evidence and provides pooled estimates of the prevalence of common mental disorders in adults with non-communicable diseases in South Asia.

Methods

The researchers included prevalence studies of depression and anxiety in adults with diabetes, cancer, cardiovascular disease, and chronic respiratory conditions in Bangladesh, India, and Pakistan, published from 1990 onwards in international and country-specific databases.

Results

Out of 96 included studies, 83 provided data for random effects meta-analyses.

The pooled prevalence of depression was 44% (95% confidence interval (CI) = 26 to 62) for patients with COPD, 40% (95% CI = 34 to 45) for diabetes, 39% (95% CI = 23 to 56) for stroke, 38% (95% CI = 32 to 45) for hypertension, and 37% (95% CI = 30 to 45) for cancer.

The pooled prevalence of anxiety based on 28 studies was 29% (95% CI = 22 to 36).

Many quality issues were identified in a critical appraisal of included studies, mostly relating to the sampling frame and selection process, the description of the methods and basic data, and the description of non-responders.

Conclusions

Depression and anxiety are prevalent and underdiagnosed in people with physical comorbidities in Bangladesh, India, and Pakistan.

Reference

Uphoff, E.P., Newbould, L., Walker, I., Ashraf, N., Chaturvedi, S., Kandasamy, A., Mazumdar, P., Meader, N., Naheed, A., Rana, R., Wright, J., Wright, J.M., Siddiqi, N., Churchill, R. & NIHR Global Health Research Group – IMPACT. (2019) A systematic review and meta-analysis of the prevalence of common mental disorders in people with non-communicable diseases in Bangladesh, India, and Pakistan. Journal of Global Health. 9(2):020417. doi: 10.7189/jogh.09.020417.

Are E-Mental Health Applications for Depression Beneficial?

Research Paper Title

E-mental health applications for depression: an evidence-based ethical analysis.

Background

E-mental health applications (apps) are an increasingly important factor for the treatment of depression.

To assess the risks and benefits for patients, an in-depth ethical analysis is necessary.

The objective of this paper is to determine the ethical implications of app-based treatment for depression.

Methods

An evidence-based ethical analysis was conducted.

The material was meta-reviews and randomised control studies (RCTs) on app-based treatment.

Based on the empirical data, an ethical analysis was conducted using the 3-ACES-approach by Thornicroft and Tansella.

Results

Apps may empower autonomy, offer an uninterrupted series of contacts over a period of time, show evidence-based benefits for patients with subclinical and mild-to-moderate-symptoms, are easily accessible, may be used for coordinating information and services within an episode of care, and are on the whole cost-effective.

Their risks are that they are not suitable for the whole range of severity of mental illnesses and patient characteristics, show severe deficits in the data privacy policy, and a big variability in quality standards.

Conclusions

The use of apps in depression treatment can be beneficial for patients as long as:

  • The usefulness of an app-based treatment is assessed for each individual patient;
  • Apps are chosen according to symptom severity as well as characteristics like the patient’s level of self-reliance, their e-literacy, and their openness vis-à-vis apps; and
  • Manufacturers improve their privacy policies and the quality of apps.

Reference

Rubeis, G. (2020) E-mental health applications for depression: an evidence-based ethical analysis. European Archives of Psychiatry and Clinical Neuroscience. doi: 10.1007/s00406-019-01093-y. [Epub ahead of print].

Postpartum: Linking Poor Body Image & Depressive Symptoms

Research Paper Title

A qualitative insight into the relationship between postpartum depression and body image.

Background

This study qualitatively explored the experience of depression and body image concerns in women diagnosed with depression in the postpartum period.

Women’s bodies undergo substantial changes during the perinatal period which can impact their body image and mood post-birth.

However, it remains unknown how women diagnosed with depression experience their body image in the postpartum period.

Methods

Seventeen women in their first postpartum year completed qualitative telephone interviews: seven women diagnosed with depression and ten without depression.

Thematic content analysis identified the main themes of the women’s narratives:

  • Expectations and adjustments to motherhood;
  • Mood in response to changing postpartum body;
  • The context of feeling bad about my body; and
  • Body letting me down and relationship to mood.

Results

Differences in the relationship between body image and mood for postpartum women with depression compared to women without depression were revealed.

Other themes seemed to be experienced in the same way by women with and without depression.

Conclusions

Poor body image and depressive symptoms appear linked during postpartum.

An improved understanding of this association may assist postpartum women to manage negative body image post-birthand prevent the exacerbation of negative emotional health in this period.

Reference

Hartley, E., Fuller-Tyszkiewicz, M., Skouteris, H. & Hill, B. (2020) A qualitative insight into the relationship between postpartum depression and body image. Journal of Reproductive and Infant Psychology. 1-13. doi: 10.1080/02646838.2019.1710119. [Epub ahead of print].

Does Early Maternal Separation Exert a Negative Influence on Student’s Depression & Dysfunctional Attitude?

Research Paper Title

The impacts of maternal separation experience and its pattern on depression and dysfunctional attitude in middle school students in rural China.

Background

In China, because of the growth of economically driven rural-to-urban migration, there are lots of children in rural area who are separating or have separation experience with their parents.

Until now, few studies focused on solely maternal separation and no research studied whether its pattern will affect children’s later psychological status.

The aim of this study was to determine whether early or late maternal separation affects depression and dysfunctional attitude in middle school students and what is the role of cumulative duration and meeting frequency.

Methods

Maternal separation experience was obtained by using questionnaires. The researchers got early maternal separation group first. Then, late maternal separation and control group were obtained with the same number by matching grade, sex and family socioeconomic status.

All the students in the three groups completed the scales of Children’s Depression Inventory (CDI) and Dysfunctional Attitude Scale (DAS).

Results

Both CDI and DAS scores of early separation group are higher than the other two groups.

  • When the researches split the data by sex, only females presented the same results.
  • When cumulative duration is short, there is significant difference in both scores of CDI and DAS among the three groups, which showed the scores of early separation group are higher than the other two groups.
  • When the cumulative duration is long, there is no significant difference among the three groups.
  • When meeting frequency is high, there is no significant difference among the three groups.
  • When it is low, there is significant difference among the three groups, which showed the CDI and DAS scores of early separation group are higher than the other two groups.

Furthermore, the same results are also found in females.

Conclusions

Early maternal separation may exert negative influence on student’s depression and dysfunctional attitude.

The sex, cumulative duration and meeting frequency may also play important roles in the effect.

Reference

Cao, X.J., Huang, Y.X., Zhu, P. & Zhang, Z.G. (2020) The impacts of maternal separation experience and its pattern on depression and dysfunctional attitude in middle school students in rural China. The International Journal of Social Psychiatry. 66(2), pp.188-197. doi: 10.1177/0020764019895795. Epub 2020 Jan 2.

What is the Potential Utility of EEG as a Treatment Planning Tool for Escitalopram Therapy?

Research Paper Title

Use of Machine Learning for Predicting Escitalopram Treatment Outcome From Electroencephalography Recordings in Adult Patients With Depression.

Background

Social and economic costs of depression are exacerbated by prolonged periods spent identifying treatments that would be effective for a particular patient. Thus, a tool that reliably predicts an individual patient’s response to treatment could significantly reduce the burden of depression.

To estimate how accurately an outcome of escitalopram treatment can be predicted from electroencephalographic (EEG) data on patients with depression.

Methods

This prognostic study used a support vector machine classifier to predict treatment outcome using data from the first Canadian Biomarker Integration Network in Depression (CAN-BIND-1) study.

The CAN-BIND-1 study comprised 180 patients (aged 18-60 years) diagnosed with major depressive disorder who had completed 8 weeks of treatment. Of this group, 122 patients had EEG data recorded before the treatment; 115 also had EEG data recorded after the first 2 weeks of treatment.

All participants completed 8 weeks of open-label escitalopram (10-20 mg) treatment.

The ability of EEG data to predict treatment outcome, measured as accuracy, specificity, and sensitivity of the classifier at baseline and after the first 2 weeks of treatment.

The treatment outcome was defined in terms of change in symptom severity, measured by the Montgomery-Åsberg Depression Rating Scale, before and after 8 weeks of treatment.

A patient was designated as a responder if the Montgomery-Åsberg Depression Rating Scale score decreased by at least 50% during the 8 weeks and as a nonresponder if the score decrease was less than 50%.

Results

Of the 122 participants who completed a baseline EEG recording (mean [SD] age, 36.3 [12.7] years; 76 [62.3%] female), the classifier was able to identify responders with an estimated accuracy of 79.2% (sensitivity, 67.3%; specificity, 91.0%) when using only the baseline EEG data.

For a subset of 115 participants who had additional EEG data recorded after the first 2 weeks of treatment, use of these data increased the accuracy to 82.4% (sensitivity, 79.2%; specificity, 85.5%).

Conclusions

These findings demonstrate the potential utility of EEG as a treatment planning tool for escitalopram therapy.

Further development of the classification tools presented in this study holds the promise of expediting the search for optimal treatment for each patient.

Reference

Zhdanov, A., Atluri, S., Wong, W., Vaghei, Y., Daskalakis, Z.J., Blumberger, D.M., Frey, B.N., Giacobbe, P., Lam, R.W., Milev, R., Mueller, D.J., Turecki, G., Parikh, S.V., Rotzinger, S., Soares, C.N., Brenner, C.A., Vila-Rodriguez, F., McAndrews, M.P., Kleffner, K., Alonso-Prieto, E., Arnott, S.R., Foster, J.A., Strother, S.C., Uher, R., Kennedy, S.H. & Farzan, F. (2020) Use of Machine Learning for Predicting Escitalopram Treatment Outcome From Electroencephalography Recordings in Adult Patients With Depression. JAMA Network Open. 3(1):e1918377. doi: 10.1001/jamanetworkopen.2019.18377.