Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for major depressive disorder (MDD), but initial outcomes can be modest.

To compare SSRI dose optimisation with four alternative second-line strategies in MDD patients unresponsive to an SSRI.

Of 257 participants, 51 were randomised to SSRI dose optimisation (SSRI-Opt), 46 to lithium augmentation (SSRI+Li), 48 to nortriptyline combination (SSRI+NTP), 55 to switch to venlafaxine (VEN) and 57 to problem-solving therapy (SSRI+PST). Primary outcomes were week-6 response/remission rates, assessed by blinded evaluators using the 17-item Hamilton Depression Rating Scale (HDRS-17). Changes in HDRS-17 scores, global improvement and safety outcomes were also explored. EudraCT No. 2007-002130-11.

Alternative second-line strategies led to higher response (28.2% v. 14.3%, odds ratio = 2.36 [95% CI 1.0–5.6], p = 0.05) and remission (16.9% v. 12.2%, odds ratio = 1.46, [95% CI 0.57–3.71], p = 0.27) rates, with greater HDRS-17 score reductions (−2.6 [95% CI −4.9 to −0.4], p = 0.021]) than SSRI-Opt. Significant/marginally significant effects were only observed in both response rates and HDRS-17 decreases for VEN (odds ratio = 2.53 [95% CI 0.94–6.80], p = 0.067; HDRS-17 difference: −2.7 [95% CI −5.5 to 0.0], p = 0.054) and for SSRI+PST (odds ratio = 2.46 [95% CI 0.92 to 6.62], p = 0.074; HDRS-17 difference: −3.1 [95% CI −5.8 to −0.3], p = 0.032). The SSRI+PST group reported the fewest adverse effects, while SSRI+NTP experienced the most (28.1% v. 75%; p < 0.01), largely mild.

Patients with MDD and insufficient response to SSRIs would benefit from any other second-line strategy aside from dose optimisation. With limited statistical power, switching to venlafaxine and adding psychotherapy yielded the most consistent results in the DEPRE'5 study.

Studies conducted during the COVID-19 pandemic found high occurrence of suicidal thoughts and behaviours (STBs) among healthcare workers (HCWs). The current study aimed to (1) develop a machine learning-based prediction model for future STBs using data from a large prospective cohort of Spanish HCWs and (2) identify the most important variables in terms of contribution to the model’s predictive accuracy.

This is a prospective, multicentre cohort study of Spanish HCWs active during the COVID-19 pandemic. A total of 8,996 HCWs participated in the web-based baseline survey (May–July 2020) and 4,809 in the 4-month follow-up survey. A total of 219 predictor variables were derived from the baseline survey. The outcome variable was any STB at the 4-month follow-up. Variable selection was done using an L1 regularized linear Support Vector Classifier (SVC). A random forest model with 5-fold cross-validation was developed, in which the Synthetic Minority Oversampling Technique (SMOTE) and undersampling of the majority class balancing techniques were tested. The model was evaluated by the area under the Receiver Operating Characteristic (AUROC) curve and the area under the precision–recall curve. Shapley’s additive explanatory values (SHAP values) were used to evaluate the overall contribution of each variable to the prediction of future STBs. Results were obtained separately by gender.

The prevalence of STBs in HCWs at the 4-month follow-up was 7.9% (women = 7.8%, men = 8.2%). Thirty-four variables were selected by the L1 regularized linear SVC. The best results were obtained without data balancing techniques: AUROC = 0.87 (0.86 for women and 0.87 for men) and area under the precision–recall curve = 0.50 (0.55 for women and 0.45 for men). Based on SHAP values, the most important baseline predictors for any STB at the 4-month follow-up were the presence of passive suicidal ideation, the number of days in the past 30 days with passive or active suicidal ideation, the number of days in the past 30 days with binge eating episodes, the number of panic attacks (women only) and the frequency of intrusive thoughts (men only).

Machine learning-based prediction models for STBs in HCWs during the COVID-19 pandemic trained on web-based survey data present high discrimination and classification capacity. Future clinical implementations of this model could enable the early detection of HCWs at the highest risk for developing adverse mental health outcomes.

NCT04556565

One of the most relevant risk factors for suicide is the presence of previous attempts. The symptomatic profile of people who reattempt suicide deserves attention. Network analysis is a promising tool to study this field.

To analyze the symptomatic network of patients who have attempted suicide recently and compare networks of people with several attempts and people with just one at baseline.

1043 adult participants from the Spanish cohort “SURVIVE” were part of this study. Participants were classified into two groups: single attempt group (n = 390) and reattempt group (n = 653). Different network analyses were carried out to study the relationships between suicidal ideation, behavior, psychiatric symptoms, diagnoses, childhood trauma, and impulsivity. A general network and one for each subgroup were estimated.

People with several suicide attempts at baseline scored significantly higher across all clinical scales. The symptomatic networks were equivalent in both groups of patients (p > .05). Although there were no overall differences between the networks, some nodes were more relevant according to group belonging.

People with a history of previous attempts have greater psychiatric symptom severity but the relationships between risk factors show the same structure when compared with the single attempt group. All risk factors deserve attention regardless of the number of attempts, but assessments can be adjusted to better monitor the occurrence of reattempts.

Suicidal behavior constitutes a multi-cause phenomenon that may also be present in people without a mental disorder. This study aims to analyze suicidal behavior outcomes in a sample of attempters, from a symptom-based approach.

The sample comprised 673 patients (72% female; M = 40.9 years) who attended a hospital emergency department due to a suicide attempt. A wide range of clinical factors (e.g., psychopathology symptoms, psychiatric diagnoses, impulsivity, acquired capability), was administered within 15 days after the index attempt. Nine psychopathology domains were explored to identify the profile of symptoms, using latent profile analysis. The relationship between the profile membership and suicide outcome (i.e., intensity of suicidal ideation, number of suicide behaviors, and medical injury derived from index attempt) was also studied, using linear and logistic regression.

Three psychopathology profiles were identified: high-symptom profile (45.02% of participants), moderate-symptom profile (42.50%), and low-symptom profile (12.48%). High-symptom profile members were more likely to show higher risk of non-suicidal self-injury, acquired capability for suicide, and more severe suicide behavior and ideation. On the other hand, a more severe physical injury was associated with low-symptom profile membership in comparison to membership from the other profiles (OR < 0.45, p < .05).

A symptom-based approach may be useful to monitor patients and determine the risk of attempt repetition in the future and potential medical injury, and to optimize prevention and intervention strategies.

Suicide is one of the main external causes of death worldwide. People who have already attempted suicide are at high risk of new suicidal behavior. However, there is a lack of information on the risk factors that facilitate the appearance of reattempts. The aim of this study was to calculate the risk of suicide reattempt in the presence of suicidal history and psychosocial risk factors and to estimate the effect of each individual risk factor.

This systematic review and meta-analysis were conducted following the PRISMA-2020 guidelines. Studies on suicide reattempt that measured risk factors were searched from inception to 2022. The risk factors studied were those directly related to suicide history: history of suicide prior to the index attempt, and those that mediate the transition from suicidal ideation to attempt (alcohol or drug misuse, impulsivity, trauma, and non-suicidal self-injury).

The initial search resulted in 11 905 articles. Of these, 34 articles were selected for this meta-analysis, jointly presenting 52 different effect sizes. The pooled effect size across the risk factors was significant (OR 2.16). Reattempt risk may be increased in presence of any of the following risk factors: previous history, active suicidal ideation, trauma, alcohol misuse, and drug misuse. However, impulsivity, and non-suicidal self-injury did not show a significant effect on reattempt.

Most of the risk factors traditionally associated with suicide are also relevant when talking about suicide reattempts. Knowing the traits that define reattempters can help develop better preventive and intervention plans.

Observations from different fields of research coincide in indicating that a defective gamma-aminobutyric acid (GABA) interneuron system may be among the primary factors accounting for the varied clinical expression of schizophrenia. GABA interneuron deficiency is locally expressed in the form of neural activity desynchronization. We mapped the functional anatomy of local synchrony in the cerebral cortex in schizophrenia using functional connectivity MRI.

Data from 86 patients with schizophrenia and 137 control subjects were obtained from publicly available repositories. Resting-state functional connectivity maps based on Iso-Distant Average Correlation measures across three distances were estimated detailing the local functional structure of the cerebral cortex.

Patients with schizophrenia showed weaker local functional connectivity (i.e., lower MRI signal synchrony) in (i) prefrontal lobe areas, (ii) somatosensory, auditory, visual, and motor cortices, (iii) paralimbic system at the anterior insula and anterior cingulate cortex, and (iv) hippocampus. The distribution of the defect in cortical area synchrony largely coincided with the synchronization effect of the GABA agonist alprazolam previously observed using identical functional connectivity measures. There was also a notable resemblance between the anatomy of our findings and cortical areas showing higher density of parvalbumin (prefrontal lobe and sensory cortices) and somatostatin (anterior insula and anterior cingulate cortex) GABA interneurons in humans.

Our results thus provide detail of the functional anatomy of synchrony changes in the cerebral cortex in schizophrenia and suggest which elements of the interneuron system are affected. Such information could ultimately be relevant in the search for specific treatments.

The coronavirus disease 2019 (COVID-19) has serious physiological and psychological consequences. The long-term (>12 weeks post-infection) impact of COVID-19 on mental health, specifically in older adults, is unclear. We longitudinally assessed the association of COVID-19 with depression symptomatology in community-dwelling older adults with metabolic syndrome within the framework of the PREDIMED-Plus cohort.

Participants (n = 5486) aged 55–75 years were included in this longitudinal cohort. COVID-19 status (positive/negative) determined by tests (e.g. polymerase chain reaction severe acute respiratory syndrome coronavirus 2, IgG) was confirmed via event adjudication (410 cases). Pre- and post-COVID-19 depressive symptomatology was ascertained from annual assessments conducted using a validated 21-item Spanish Beck Depression Inventory-II (BDI-II). Multivariable linear and logistic regression models assessed the association between COVID-19 and depression symptomatology.

COVID-19 in older adults was associated with higher post-COVID-19 BDI-II scores measured at a median (interquartile range) of 29 (15–40) weeks post-infection [fully adjusted β = 0.65 points, 95% confidence interval (CI) 0.15–1.15; p = 0.011]. This association was particularly prominent in women (β = 1.38 points, 95% CI 0.44–2.33, p = 0.004). COVID-19 was associated with 62% increased odds of elevated depression risk (BDI-II ≥ 14) post-COVID-19 when adjusted for confounders (odds ratio; 95% CI 1.13–2.30, p = 0.008).

COVID-19 was associated with long-term depression risk in older adults with overweight/obesity and metabolic syndrome, particularly in women. Thus, long-term evaluations of the impact of COVID-19 on mental health and preventive public health initiatives are warranted in older adults.

To investigate the occurrence of traumatic stress symptoms (TSS) among healthcare workers active during the COVID-19 pandemic and to obtain insight as to which pandemic-related stressful experiences are associated with onset and persistence of traumatic stress.

This is a multicenter prospective cohort study. Spanish healthcare workers (N = 4,809) participated at an initial assessment (i.e., just after the first wave of the Spain COVID-19 pandemic) and at a 4-month follow-up assessment using web-based surveys. Logistic regression investigated associations of 19 pandemic-related stressful experiences across four domains (infection-related, work-related, health-related and financial) with TSS prevalence, incidence and persistence, including simulations of population attributable risk proportions (PARP).

Thirty-day TSS prevalence at T1 was 22.1%. Four-month incidence and persistence were 11.6% and 54.2%, respectively. Auxiliary nurses had highest rates of TSS prevalence (35.1%) and incidence (16.1%). All 19 pandemic-related stressful experiences under study were associated with TSS prevalence or incidence, especially experiences from the domains of health-related (PARP range 88.4–95.6%) and work-related stressful experiences (PARP range 76.8–86.5%). Nine stressful experiences were also associated with TSS persistence, of which having patient(s) in care who died from COVID-19 had the strongest association. This association remained significant after adjusting for co-occurring depression and anxiety.

TSSs among Spanish healthcare workers active during the COVID-19 pandemic are common and associated with various pandemic-related stressful experiences. Future research should investigate if these stressful experiences represent truly traumatic experiences and carry risk for the development of post-traumatic stress disorder.

Patients with obsessive-compulsive disorder (OCD) present difficulties in the cognitive regulation of emotions, possibly because of inefficient recruitment of distributed patterns of frontal cortex regions. The aim of the present study is to characterize the brain networks, and their dysfunctions, related to emotion regulation alterations observed during cognitive reappraisal in OCD.

Adult patients with OCD (n = 31) and healthy controls (HC; n = 30) were compared during performance of a functional magnetic resonance imaging cognitive reappraisal protocol. We used a free independent component analysis approach to analyze network-level alterations during emotional experience and regulation. Correlations with behavioral scores were also explored.

Analyses were focused on six networks encompassing the frontal cortex. OCD patients showed decreased activation of the frontotemporal network in comparison with HC (F(1,58) = 7.81, p = 0.007) during cognitive reappraisal. A similar trend was observed in the left frontoparietal network.

The present study demonstrates that patients with OCD show decreased activation of specific networks implicating the frontal cortex during cognitive reappraisal. These outcomes should help to better characterize the psychological processes modulating fear, anxiety, and other core symptoms of patients with OCD, as well as the associated neurobiological alterations, from a system-level perspective.