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.

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 examine the cross-sectional and longitudinal (2-year follow-up) associations between dietary diversity (DD) and depressive symptoms.

An energy-adjusted dietary diversity score (DDS) was assessed using a validated FFQ and was categorised into quartiles (Q). The variety in each food group was classified into four categories of diversity (C). Depressive symptoms were assessed with Beck Depression Inventory-II (Beck II) questionnaire and depression cases defined as physician-diagnosed or Beck II >= 18. Linear and logistic regression models were used.

Spanish older adults with metabolic syndrome (MetS).

A total of 6625 adults aged 55–75 years from the PREDIMED-Plus study with overweight or obesity and MetS.

Total DDS was inversely and statistically significantly associated with depression in the cross-sectional analysis conducted; OR Q4 v. Q1 = 0·76 (95 % CI (0·64, 0·90)). This was driven by high diversity compared to low diversity (C3 v. C1) of vegetables (OR = 0·75, 95 % CI (0·57, 0·93)), cereals (OR = 0·72 (95 % CI (0·56, 0·94)) and proteins (OR = 0·27, 95 % CI (0·11, 0·62)). In the longitudinal analysis, there was no significant association between the baseline DDS and changes in depressive symptoms after 2 years of follow-up, except for DD in vegetables C4 v. C1 = (β = 0·70, 95 % CI (0·05, 1·35)).

According to our results, DD is inversely associated with depressive symptoms, but eating more diverse does not seem to reduce the risk of future depression. Additional longitudinal studies (with longer follow-up) are needed to confirm these findings.

The coronavirus disease 2019 (COVID-19) pandemic has been a global challenge. High mortality rates have been reported in some risk groups, including patients with pre-existing mental disorders.

We used electronic health records to retrospectively identify people infected due to COVID-19 (between March 2020 and March 2021) in the three territories of the Basque Country. COVID-19 cases were defined as individuals who had tested positive on a reverse transcription-polymerase chain reaction (PCR) test. Univariate and multivariate logistic regression models and multilevel analyses with generalized estimated equations were used to determine factors associated with COVID-19-related mortality and hospital admission.

The COVID-19 mortality rate was increased for patients with psychotic disorders [odds ratio (OR) adjusted: 1.45, 95% confidence interval (CI) (1.09–1.94), p = 0.0114] and patients with substance abuse [OR adjusted: 1.88, 95% CI (1.13–3.14, p < 0.0152)]. The mortality rate was lower for patients with affective disorders [OR adjusted: 0.80, 95% CI (0.61–0.99), p = 0.0407]. Hospital admission rates due to COVID-19 were higher in psychosis [OR adjusted: 2.90, 95% CI (2.36–3.56), p < 0.0001] and anxiety disorder groups [OR adjusted: 1.54, 95% CI (1.37–1.72), p < 0.0001]. Among admitted patients, COVID-19 mortality rate was decreased for those with affective disorders rate [OR adjusted: 0.72, 95% CI (0.55–0.95), p = 0.0194].

COVID-19-related mortality and hospitalizations rates were higher for patients with a pre-existing psychotic disorder.

Healthcare workers (HCWs) exposed to coronavirus 19 (COVID-19) are at high risk of developing mental health concerns across several domains. The aim of this study is to determine the updated, global frequency of these outcomes.

A multistep literature search was performed from database inception until March 1, 2021. PRISMA/MOOSE-compliant systematic review and PROSPERO protocol were used to identify studies reporting on depression, anxiety, acute stress, post-traumatic symptoms, insomnia, and burnout in HCWs exposed to COVID-19. A quantitative meta-analysis with random effects was conducted to analyze the proportion rate of the mental health disorders. Sensitivity analyses were performed to investigate the effect of the different continents and scales. Meta-regression analyses were conducted to examine the effect of gender, age, and work position.

239 articles were included (n = 271,319 HCWs, mean age = 36.08 ± 8.33 (66.99% female). 33% HCWs exposed to COVID-19 reported depressive symptoms (95% confidence intervals [CI] = 28–38%), 42% anxiety features (95% CI = 35–48), 40% acute stress (95% CI = 32–47), 32% post-traumatic symptoms (95% CI = 26–37%), 42% insomnia (95% CI = 36–48), 37% burnout (95% CI = 31–42). Sensitivity analyses did not show statistically significant differences. Meta-regressions found a statistically significant lower prevalence of post-traumatic symptoms in Asia.

HCWs exposed to COVID-19 were found to have a significant prevalence of mental health concerns in all domains analyzed. The effects of COVID-19 on HCWs’ mental health could be underestimated and the future consequences dismissed.

To assess the association between pregestational BMI and offspring’s risk of overweight/obesity after accounting for the most important confounders, especially maternal smoking habit.

Prospective cohort study.

The Seguimiento Universidad de Navarra (SUN) study is a prospective cohort of Spanish graduates with more than 22 000 participants nationwide. Recruitment started in 1999, and it is permanently open. Data on diet, lifestyle and clinical diagnoses are collected at baseline and every 2 years.

Women from the SUN cohort who reported at least one pregnancy during follow-up (n 3496) were invited to this study. Among them, 1527 agreed to participate and completed an additional more detailed online questionnaire on their pregnancy history and their offspring’s nutritional status.

After excluding 165 children, we analysed data of 2791 participants born to 1485 mothers and observed that each 5 kg/m2 increase in pregestational BMI was associated with a 0·22 (95 % CI 0·15, 0·29) higher z-score in offspring’s BMI and higher risk of overweight/obesity (multivariable-adjusted relative risk (RR) 1·57 (95 % CI 1·39, 1·77)) in childhood or adolescence. Furthermore, we observed stronger association in children born to smoker mothers (RR 1·91; 95 % CI 1·48, 2·46) than from non-smoker mothers (RR 1·51; 95 % CI 1·31, 1·73) (Pfor interaction = 0·02).

We found a synergistic interaction between pregestational BMI and maternal smoking habit on offspring’s z-score of the BMI and in their risk of overweight/obesity. Although further research is needed to analyse dose–response relationships, these findings reinforce the importance of promoting healthy lifestyles in pregnant women in order to prevent childhood obesity.

Subclinical psychotic symptoms are present in the general population. Furthermore, they are quite common in diagnostic categories beyond psychosis, such as BPD patients.

We want to assess the differences between 3 groups: BPD (n = 68), FEP (n = 83) and controls (n = 203) in an experimental paradigm measuring the presence of speech illusions in white noise. The Positive and Negative Syndrome Scale was administered in the patient group, the Structured Interview for Schizotypy-Revised, and the Community Assessment of Psychic Experiences in the control and BPD group. The white noise task was also analysed within a signal detection theory (SDT) framework. Logistic regression analyses and the general linear models were used to analyse the adjusted differences between groups.

Differences were more prevalent in signals that were perceived as affectively salient in patients groups (9.6% in FEP vs 5.9% in BPD and 1% in controls; OR: 10.7; 95%CI: 2.2–51.6, p = 0.003 in FEP; OR: 6.3; 95%CI: 1.1–35.0, p = 0.036 in BPD). Besides, we found a worse general performance and more false alarms in the task for FEP group using SDT framework.

Experimental paradigms indexing the tendency to detect affectively salient signals in noise may be used to identify liability to psychosis in people with vulnerability. Its predictable value in other diagnostic categories and general population requires further research.

The aim of this study was to develop and to assess a specific Multi-Criteria Decision Analysis (MCDA) framework to evaluate new drugs in an hospital pharmacy and therapeutics committee (P&TC) setting.

A pilot criteria framework was developed based on the EVIDEM (Evidence and Value: Impact on DEcisionMaking) framework, together with other relevant criteria, and assessed by a group of P&TC's members. The weighting of included criteria was done using a 5-point weighting technique. Two drugs were chosen by evaluation: an orphan-drug for Gaucher disease, and a nonorphan drug for the treatment of inflammatory bowel disease. Evidence matrices were developed, and value contribution of each drug was evaluated by P&TC's members. An agreed final framework was obtained through a discussion between the P&TC's members.

After criteria assessment, the pilot framework included eight quantitative criteria: “disease severity,” “unmet needs,” “comparative efficacy/effectiveness,” “comparative safety/tolerability,” “comparative patient-reported outcomes,” “comparative cost consequences-cost of treatment,” “comparative cost consequences-other medical costs,” and “quality of evidence”; and one contextual criterion: “opportunity costs and affordability.” The most valued criteria were: “comparative safety/tolerability,” “disease severity,” and “comparative efficacy/effectiveness.” When assessing the drugs most valued characteristics of the MCDA were the possibility that all team may contribute to drug assessment by means of scoring the matrices and the discussion to reach a consensus in drug positioning and value decision making.

The reflective MCDA would integrate quantitative and qualitative criteria relevant for a P&TC setting, allowing reflective discussions based on the criteria weighting score.