Low heart rate variability (HRV) levels may be a susceptibility factor for major depressive disorder (MDD). Sleep-state HRV may be more likely to reveal the pathological features of MDD compared with resting state HRV (RS-HRV). This study aimed to elucidate HRV alterations in the sleep states of patients with MDD.

Physiological signal data from the resting state before sleep, first non-rapid eye movement (NREM) and rapid eye movement (REM) stages, and last NREM and REM stages were acquired using polysomnography.

The RS-HRV indices (the standard deviation [SD] of all normal-to-normal [NN] intervals [SDNN], the square root of the mean of the sum of the squares of the differences between adjacent NN intervals [RMSSD], the percentage difference between adjacent NN intervals >50 ms [pNN50], high-frequency [HF], low-frequency [LF], very low frequency [VLF], SD1, and sample entropy [SampEn]) were lower in patients with MDD than in healthy controls (HCs). Patients with MDD had lower SDNN, RMSSD, pNN50, HF, LF, VLF, SD1, SD2, and SampEn and higher SD2/SD1, α1, and α2 than HCs in the NREM stage. They also had lower SDNN, RMSSD, pNN50, HF, LF, VLF, SD1, SD2, and SampEn and higher LF/HF than HCs in the REM stage. Fewer indices changed significantly during different sleep stages in patients with MDD than in HCs.

Patients with MDD had a generalised reduction in HRV in both RS and sleep state and decreased dynamic changes during sleep. Altered autonomic nervous system activity has been implicated in MDD pathology.

A previous study by our research group identified psychomotor and neurofunctional impairments following SARS-CoV-2 infection. This study continues that investigation, aiming to evaluate whether these impairments persisted over time, as part of the broader characterisation of long COVID. Moreover, it was explored potential correlations with variables such as age, blood type, symptoms, and medical care.

From an initial pool of 214 subjects, 30 post-COVID-19 participants and 30 healthy controls were selected after strict exclusion criteria. The assessments protocol included eight psychomotor tests – Fine Motor Development (Diadochokinesia, Puppets, Fan, and Paper) and Balance (Immobility, Static Balance on One Foot, Feet in Line, and Persistence) – as well as three cognitive screening tasks from the Mini-Mental State Examination: Episodic Memory After Distracters, Verbal Fluency, and Clock tests. Evaluations were performed at three time points: baseline (post-COVID-19), 12 weeks, and 24 weeks. Participants were stratified by age (18–30, 31–45, and 46–64 years), symptoms profile, medical care, and blood type.

COVID-19 induced psychomotor and neurofunctional sequelae lasting at least 24 weeks post-infection. These impairments were more pronounced and persistent in the 31–45-years age group, while memory-related impairments were more evident in the 18–30 age group. Body pain, coryza, and sore throat were key symptoms linked to long-term sequelae. Rh-negative blood type was suggested as a potential risk factor.

The findings support that long COVID included sustained psychomotor and neurofunctional sequelae, premature senescence, and associations with specific clinical and biological variables.

The comorbidity of psychiatric and metabolic conditions is prevalent and poses a heavy burden on public health. Several biopsychosocial factors are known to influence both metabolic and psychiatric health, including inflammation, eating behavior, physical activity, and early life stress. Few studies, however, have examined the constellation of interrelationships among multiple risk domains simultaneously.

Using a sample of 200 medically healthy adults enrolled in a parent study, we used Gaussian Graphical Modeling, a type of network analysis, to characterize interdependent cross-sectional associations between early life stress (childhood trauma), health behaviors (diet quality and physical activity), blood-based biomarkers of metabolic functioning (insulin resistance, HDL cholesterol, triglycerides) and inflammation (C-reactive protein [CRP]), and three domains of mental health symptoms (depressive, anxious, and post-traumatic stress symptoms). We hypothesized that the network structure would highlight a pattern whereby higher CRP, poorer diet quality, lower physical activity, and higher childhood trauma would associate with increased risk for both metabolic and psychiatric impairments.

Findings revealed a positive conditional association between CRP and childhood trauma, which may function as an intermediary process to increase risk for both metabolic impairments and psychiatric symptoms in adulthood. Further, higher physical activity was associated with lower insulin resistance and fewer depressive symptoms, and better diet quality was associated with lower CRP levels.

Results highlight potential avenues for interventions aimed at reducing inflammation, improving health behavior, and addressing the effects of childhood trauma to improve physical and mental health comorbidities.

This systematic review and meta-analysis aimed to quantify the magnitude of placebo and nocebo effects in pharmacological trials for OCRDs and identify clinical and methodological moderators influencing these effects.

A comprehensive literature search was conducted across multiple databases and clinical trial registries up to May 2025. Randomised, placebo-controlled trials involving pharmacological interventions for OCRDs were included. The primary outcomes were placebo effect size and placebo response rate; secondary outcomes included nocebo response rate and side effect profile. Data were extracted independently and meta-analysed using random effects models. Meta-regression was performed to assess moderators of placebo response.

Fifteen eligible trials (N = 640; placebo N = 341) were included. The pooled placebo effect size was moderate (SMC = −0.63; 95% CI −0.77 to −0.48), with low heterogeneity (I2 = 4.73%). The placebo response rate was 21%, and the nocebo response rate was 18%. Despite testing a broad range of potential moderators, including clinical characteristics, methodological design, and medication class, no significant predictors of placebo effect size were identified. Side effects were reported in nearly one-third of placebo recipients, underscoring the relevance of nocebo effects.

Placebo and nocebo responses are noteworthy in trials for OCRDs and may influence perceived treatment efficacy. Variability in placebo responses is not well explained by currently measurable moderators. Further research is needed to explore neurobiological, psychological, and methodological contributors to expectancy effects in OCRD pharmacotherapy trials.

Early economic evaluations (EEE) can evaluate the economic potential of new innovative healthcare solutions. We present a methodological framework for EEE in bipolar disorder and use eLi12 as an illustrative case, a new method to estimate 12-h lithium blood levels when blood sampling deviates from the 12-h timing, enabling more flexibility for patients and better data on 12-h lithium levels.

A decision-analytic model evaluated the costs and consequences of eLi12 for the treatment of bipolar disorder from a Danish national healthcare payer perspective, assessing the minimum efficacy threshold where eLi12 would be considered cost-effective compared with standard of care. The primary outcome was net monetary benefit (NMB), and we estimated quality-adjusted life-years (QALYs) assuming a willingness-to-pay threshold of €67,000/QALY gained. Costs associated with bipolar disorder and lithium treatment (e.g. hospitalisations, suicides, lost productivity, implementation costs) were estimated from literature, Danish registries, and expert opinion.

Assuming 28,000 patients with bipolar disorder whereof 10,000 are treated with lithium, a 2.5% reduction in number of hospitalisations and suicides are sufficient for eLi12 to be considered cost-effective within one year of implementation. When using a longer time horizon, allowing more savings to be included and thus considering a smaller improvement to be sufficient, less than 1% improvement by using eLi12 would be sufficient within a three-year time horizon.

EEE can evaluate the health economic potential of new innovative methods, supporting early investment decisions and guiding research. eLi12 can have significant healthcare savings, emphasising the relevance of studying clinical implementation.