Evidence suggests that somatic rather than cognitive depressive symptoms are risk factors for recurrent cardiac events in at-risk patients. However, this has never been explored using a time-dependent approach in a narrow time-frame, allowing a cardiac event-free time-window.

The analysis was performed on 595 participants [70.6% male, median age 72 (27–98)] drawn from the UPBEAT-UK heart disease patient cohort with 6-monthly follow-ups over 3 years. Depressive symptomatology was measured using the Patient Health Questionnaire-9 (PHQ-9) (four somatic, five cognitive items). New cardiac events (NCEs) including cardiac-related mortality were identified by expert examination of patient records. Analyses were performed using Cox proportional hazard models with delayed entry, with time-dependent depressive dimensions and covariates measured 12–18 months (median: 14.1, IQR: 3.5) prior to the event, with a 12-month cardiac event-free gap.

There were 95 NCEs during the follow-up [median time-to-event from baseline: 22.3 months (IQR: 13.4)]. Both the somatic (HR 1.12, 95% CI 1.05–1.20, p = 0.001) and cognitive dimensions (HR 1.11, 95% CI 1.03–1.18, p = 0.004) were time-dependent risk factors for an NCE in the multi-adjusted models. Specific symptoms (poor appetite/overeating for the somatic dimension, hopelessness and feeling like a failure for the cognitive dimension) were also significantly associated.

This is the first study of the association between depressive symptom dimensions and NCEs in at-risk patients using a time-to-event standardised approach. Both dimensions considered apart were independent predictors of an NCE, along with specific items, suggesting regular assessments and tailored interventions targeting specific depressive symptoms may help to prevent NCEs in at-risk populations.

Depression affects approximately 27% of adults with chronic kidney disease (CKD) and end-stage kidney failure (ESKF). Depression in this population is associated with impaired quality of life and increased mortality. The extent of inflammation and the impact on depression in CKD/ESKF is yet to be established. Through a systematic literature review and meta-analysis, we aim to understand the relationship between depression and inflammation in CKD/ESKF patients.

We searched nine electronic databases for published studies until January 2022. Titles and abstracts were screened against inclusion and exclusion criteria. Data extraction and study quality assessment was carried out independently by two reviewers. A meta-analysis was carried out where appropriate; otherwise a narrative review of studies was completed.

Sixty studies met our inclusion criteria and entered the review (9481 patients included in meta-analysis). Meta-analysis of cross-sectional associations revealed significantly higher levels of pro-inflammatory biomarkers; C-reactive protein; Interleukin 6 (IL-6) and tumour necrosis factor-alpha in patients with depressive symptoms (DS) compared to patients without DS. Significantly lower levels of anti-inflammatory cytokine IL-10 were found in patients with DS compared to patients without DS. Considerable heterogeneity was detected in the analysis for most inflammatory markers.

We found evidence for an association of higher levels of pro-inflammatory and lower anti-inflammatory cytokines and DS in patients with CKD/ESKF. Clinical trials are needed to investigate whether anti-inflammatory therapies will be effective in the prevention and treatment of DS in these patients with multiple comorbidities.

Executive deficits are a core characteristic of schizophrenia. Yet, the origin of these impairments remains unclear as they may be caused by processing slowing. This issue is of particular interest for aging insofar as cognitive aging is also associated with a decline in executive functioning and a slowing of processing speed. As schizophrenia patients’ life expectancy increases, a better understanding of the origin of older patients’ cognitive deficits becomes essential so that healthcare can be adapted to suit them. This study aims to determine whether processing speed mediates how schizophrenia affects executive functions and whether these relationships are moderated by age.

Sixty-two schizophrenia patients (27 women) and 62 healthy comparison subjects matched for age (range: 18–76 years), gender and education performed neurocognitive tests to evaluate their executive functions (shifting, updating, inhibition and access) and processing speed.

Processing speed mediated the effect of schizophrenia on the four specific executive functions, and age moderated this mediation for shifting, updating and access, but in different ways. Age moderated the effect of processing speed on shifting, the direct effect of schizophrenia on access, and both the effect of processing speed and the direct effect of schizophrenia on updating.

This research highlights the need to evaluate processing speed routinely during therapeutic follow-up, as it is easy and simple to assess and appears to be at the heart of the cognitive deficits in schizophrenia. Finally, processing speed abilities yield information about the evolution of cognition with aging in schizophrenia.

Prediction of treatment outcomes is a key step in improving the treatment of major depressive disorder (MDD). The Canadian Biomarker Integration Network in Depression (CAN-BIND) aims to predict antidepressant treatment outcomes through analyses of clinical assessment, neuroimaging, and blood biomarkers.

In the CAN-BIND-1 dataset of 192 adults with MDD and outcomes of treatment with escitalopram, we applied machine learning models in a nested cross-validation framework. Across 210 analyses, we examined combinations of predictive variables from three modalities, measured at baseline and after 2 weeks of treatment, and five machine learning methods with and without feature selection. To optimize the predictors-to-observations ratio, we followed a tiered approach with 134 and 1152 variables in tier 1 and tier 2 respectively.

A combination of baseline tier 1 clinical, neuroimaging, and molecular variables predicted response with a mean balanced accuracy of 0.57 (best model mean 0.62) compared to 0.54 (best model mean 0.61) in single modality models. Adding week 2 predictors improved the prediction of response to a mean balanced accuracy of 0.59 (best model mean 0.66). Adding tier 2 features did not improve prediction.

A combination of clinical, neuroimaging, and molecular data improves the prediction of treatment outcomes over single modality measurement. The addition of measurements from the early stages of treatment adds precision. Present results are limited by lack of external validation. To achieve clinically meaningful prediction, the multimodal measurement should be scaled up to larger samples and the robustness of prediction tested in an external validation dataset.

Previous findings revealed that the acquisition of new semantic concepts' labels was impaired in uncomplicated alcoholic patients. The use of errorless learning may therefore allow them to improve learning performance. However, the flexibility of the new knowledge and the memory processes involved in errorless learning remain unclear.

New concepts' labels acquisition was examined in 15 alcoholic patients and 15 control participants in an errorless learning condition compared with 19 alcoholic patients and 19 control subjects in a trial-and-error learning condition. The flexibility of the new information was evaluated using different photographs from those used in the learning sessions but representing the same concepts. All of the participants carried out an additional explicit memory task and an implicit memory task was also performed by subjects in the errorless learning condition.

The alcoholic group in the errorless condition differed significantly from the alcoholic group in the trial-and-error condition but did not differ from the two control groups. There was no significant difference between results in the learning test and the flexibility task. Finally, in the alcoholic group, the naming score in the learning test was correlated with the explicit memory score but not with the implicit memory score.

Using errorless learning, alcoholics improved their abilities to learn new concepts' labels. Moreover, new knowledge acquired with errorless learning was flexible. The errorless learning advantage may rely on explicit rather than implicit memory processes in these alcohol-dependent patients presenting only mild to moderate deficits of explicit memory capacities.

The findings of the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study and the Cost Utility of the Latest Antipsychotic Drugs in Schizophrenia Study (CUtLASS) called previous trials of antipsychotics into question, including pre-licensing trials. Concerns regarding methodological robustness and quality of reporting increased. This systematic review aimed to examine the quality of reporting of phase II and III trials for new antipsychotics in the aftermath of the CATIE and CUtLASS studies.

Electronic searches were conducted in EMBASE, Medline and Cochrane databases and also ClinicalTrials.gov for antipsychotic trials (published between January 2006 and February 2012). Phase II and III randomized controlled trials (RCTs) for iloperidone, asenapine, paliperidone, olanzapine, lurasidone and pomaglumetad methionil were selected for schizophrenia and schizoaffective disorder. The reporting of the methodology was evaluated in accordance with Consolidated Standards of Reporting Trials (CONSORT) guidelines.

Thirty-one articles regarding 32 studies were included. There was insufficient reporting of design in 47% of studies and only 13% explicitly stated a primary hypothesis. Exclusion criteria were poorly reported for diagnosis in 22% of studies. Detail regarding comparators, particularly placebos, was suboptimal for 56% of studies, and permitted concomitant medication was often not reported (19%). Randomization methods were poorly described in 56% of studies and reporting on blinding was insufficient in 84% of studies. Sample size calculations were insufficiently reported in 59% of studies.

The quality of reporting of phase II and III trials for new antipsychotics does not reach the standards outlined in the CONSORT guidelines. Authors often fail to adequately report design and methodological processes, potentially impeding the progress of research on antipsychotic efficacy. Both policymakers and clinicians require high quality reporting before decisions are made regarding licensing and prescribing of new antipsychotics.

Maternal stress during pregnancy may increase the risk of preterm delivery (PD), but the associations between stress and subtypes of PD are not clear. We investigated maternal loss of a close relative and risks of very and moderately PD (<32 and 32–36 weeks, respectively) and spontaneous and medically indicated PD.

We studied 4 940 764 live singleton births in Denmark (1978–2008) and Sweden (1973–2006). We retrieved information on death of women's family members (children, partner, siblings, parents), birth outcomes and maternal characteristics from nationwide registries.

Overall, the death of a close family member the year before pregnancy or in the first 36 weeks of pregnancy was associated with a 7% increased risk of PD [95% confidence interval (CI) 1.04–1.10]. The highest hazard ratios (HR) for PD were found for death of an older child [HR (95% CI) 1.20 (1.10–1.31)] and for death of a partner [HR (95% CI) 1.31 (1.03–1.66)]. These losses were associated with higher risks of very preterm [HR (95% CI) 1.61 (1.29–2.01) and 2.07 (1.15–3.74), respectively] than of moderately preterm [HR (95% CI) 1.14 (1.03–1.26) and 1.22 (0.94–1.58), respectively] delivery. There were no substantial differences in the association between death of a child or partner and the risk of spontaneous v. medically indicated PD.

Death of a close family member the year before or during pregnancy was associated with an increased risk of PD, especially very PD. Possible mechanisms include both spontaneous and medically indicated preterm birth.

It has recently been proposed that major depression disorder (MDD) may, in a heterogeneous population-based cohort, be interpreted in terms of a random-mood model. Mood fluctuations are thought to result from stressors that occur randomly in time. We have investigated whether this concept also holds for more homogeneous groups, defined by known determinants for MDD, and whether the model's parameters, susceptibility (Z) and relaxation time (T), may be evaluated and used to differentiate between subcohorts.

From a large epidemiological survey, the Netherlands Mental Health Survey and Incidence Study (NEMESIS), data on the duration of MDD were obtained for subcohorts, based on gender, severity of depression, recurrence and co-morbidity with dysthymia, anxiety and somatic disorder, and were compared with random-mood simulation calculations.

Susceptibility, Z, is empirically found to be proportional to incidence and may be identified with a risk ratio. A second scaling rule states the proportionality of mean duration with the product of Z and T. This Z–T classification proves to be more sensitive than conventional significance tests. Notably for men/women and for co-morbid anxiety, differences are seen that have previously gone unnoticed.

Depression may be conceptualized as a disorder resulting from random-mood fluctuations, the response to which is influenced by a large variety of determinants or risk factors. The model's parameters can be evaluated and may be used in differentiating between risk factor-defined subgroups.

Individuals diagnosed with borderline personality disorder (BPD) often describe their lives as stressful and unpredictable. However, it is unclear whether the adversity faced by those with BPD is a product of stress reactivity or stress generation. Here, we examined the dynamic, prospective associations between BPD and stressful life events over 3 years. Given the heterogeneity present in BPD, we sought to understand which empirically derived dimensions of this heterogeneous disorder explain stress reactivity v. stress generation.

Participants included 355 individuals diagnosed with BPD and followed longitudinally at three annual assessments. Auto-regressive cross-lagged panel models were used to examine prospective associations between stressful life events and three latent dimensions implicated in BPD: negative affect, disinhibition, and antagonism.

Antagonism and disinhibition, but not negative affect, prospectively predicted dependent stressful life events (events the individual may have some role in). Evidence for decompensation under stress was more tenuous, with independent stressful life events (those presumably outside the individual's control) predicting increases in negative affect.

Our longitudinal study of a well-characterized clinical sample found more evidence for stress generation than for stress-induced decompensation in BPD. Stress generation in BPD is driven by externalizing dimensions: antagonism and disinhibition. These results highlight the utility of empirically derived dimensions for parsing heterogeneity present in BPD, leading to improvements in diagnostic evaluation, clinical prediction, and individualized approaches to treatment planning.

Cigarette smoking is associated with worse cognition and decreased cortical volume and thickness in healthy cohorts. Chronic cigarette smoking is prevalent in schizophrenia spectrum disorders (SSD), but the effects of smoking status on the brain and cognition in SSD are not clear. This study aimed to understand whether cognitive performance and brain morphology differed between smoking and non-smoking individuals with SSD compared to healthy controls.

Data were obtained from the Australian Schizophrenia Research Bank. Cognitive functioning was measured in 299 controls and 455 SSD patients. Cortical volume, thickness and surface area data were analysed from T1-weighted structural scans obtained in a subset of the sample (n = 82 controls, n = 201 SSD). Associations between smoking status (cigarette smoker/non-smoker), cognition and brain morphology were tested using analyses of covariance, including diagnosis as a moderator.

No smoking by diagnosis interactions were evident, and no significant differences were revealed between smokers and non-smokers across any of the variables measured, with the exception of a significantly thinner left posterior cingulate in smokers compared to non-smokers. Several main effects of smoking in the cognitive, volume and thickness analyses were initially significant but did not survive false discovery rate (FDR) correction.

Despite the general absence of significant FDR-corrected findings, trend-level effects suggest the possibility that subtle smoking-related effects exist but were not uncovered due to low statistical power. An investigation of this topic is encouraged to confirm and expand on our findings.