Search Results (1,019)

Background: Insomnia and stress-related sleep disorders are increasingly recognized as systemic conditions linked to the microbiota–gut–brain axis (MGBA). With growing clinical interest in natural products that modulate the gut environment, this systematic review evaluates the efficacy and mechanisms of non-pharmacological interventions, specifically probiotics, prebiotics, dietary indices, and botanicals, in alleviating insomnia, restoring circadian rhythms, and modulating neurochemical markers. Methods: In strict accordance with PRISMA 2020 guidelines, we searched PubMed, ScienceDirect, Scopus, and The Cochrane Library for English language studies published from inception to March 31, 2026. Eligibility was restricted to studies with rigorously controlled designs, specifically randomized controlled trials (RCTs) and controlled in vivo animal studies. Interventions had to target the gut microbiota, with primary outcomes measuring sleep quality (subjective or objective) or sleep-related neurochemical markers. We excluded uncontrolled, single-arm, or observational designs; in vitro studies; non-original research; and studies involving subjects with severe medical or psychiatric comorbidities (e.g., cancer, ADHD, severe psychiatric disorders) to prevent confounding variables, though mild-to-moderate anxiety and depression were permitted. Risk of bias was assessed using the Cochrane RoB 2.0 and SYRCLE tools. Due to significant methodological heterogeneity, a narrative synthesis stratified by intervention and population was conducted. This review was not registered in PROSPERO. Results: A total of 56 studies (33 humans, 23 animals) met the inclusion criteria. Taxonomic nomenclature was updated to reflect 2020 reclassifications (e.g., Lactiplantibacillus plantarum). In human trials, interventions significantly improved subjective sleep metrics (PSQI, ISI). Recent additions demonstrated the efficacy of the Dietary Index for Gut Microbiota (DI-GM) and the improvement in N3 sleep latency by yeast mannan. Furthermore, whole-food patterns (e.g., the MIND diet) and Traditional Chinese Medicine (TCM) decoctions successfully enriched beneficial taxa, such as Bacteroides coprophilus, and increased short-chain fatty acid (SCFA) production. Animal models demonstrated that “psychobiotic” strains (Bifidobacterium breve, Lacticaseibacillus paracasei), prebiotics (GOS/PDX), and TCM formulas effectively restored GABA/5-HT profiles, lowered morning cortisol, and facilitated REM rebound in PCPA-induced models, while also consolidating non-rapid eye movement (NREM) sleep and downregulating clock genes (Per1/Per2). Conclusions: Psychobiotics, prebiotics, and botanicals represent a highly viable non-pharmacological strategy for treating insomnia. However, current evidence is constrained by a heavy reliance on subjective human questionnaires, short follow-up durations limiting insight into long-term stability, and a substantial translational gap between mechanistic rodent models and human clinical outcomes. Full article

Background: Medication adherence is a major determinant of treatment effectiveness in psychiatric care and is influenced by patients’ attitudes toward medication and beliefs about treatment. Objective: This study aimed to evaluate medication adherence, drug attitudes, and beliefs about medicines, and to examine their relationships in the study population. Methods: A total of 300 participants were assessed using the Medication Adherence Rating Scale (MARS), Drug Attitude Inventory-10 (DAI-10), and Beliefs about Medicines Questionnaire (BMQ-General and BMQ-Specific). Descriptive statistics, independent-samples t-tests, Pearson correlation analyses, and multiple linear regression were performed. Results: The mean DAI-10 score was 3.57 ± 3.44, indicating an overall positive attitude toward medication, although 27.33% of participants had neutral or negative attitudes. The mean MARS score was 6.27 ± 2.24, suggesting moderate adherence. Mean BMQ-General and BMQ-Specific scores were 21.70 ± 5.81 and 31.64 ± 6.13, respectively. Significant gender differences were found across all scales. DAI-10 was positively correlated with MARS, while BMQ-General was negatively correlated with MARS. Multiple regression showed that DAI-10, BMQ-General, and BMQ-Specific significantly predicted MARS scores, explained 30.8% of variance after adjustment. Conclusions: Medication adherence was moderate and was significantly associated with treatment attitudes and beliefs about medicines. The findings support multidimensional assessment and targeted interventions addressing both positive attitudes and negative medication beliefs. Full article

Background: Unhealthy alcohol use may lead to arrhythmia and cardiomyopathy, but its impact on sudden death is not well understood. Objective: To investigate the association of unhealthy alcohol use with sudden death. Methods: We conducted a case-control study in Wake County, a large (~1 million inhabitants), diverse county in North Carolina. We screened and adjudicated victims of sudden, unexpected, out-of-hospital deaths in adults aged 18–64 years reported by emergency medical services between 2013 and 2015. We randomly selected sex- and age-matched control patients from a university health system from the same county and time period. Characteristics of sudden death victims and controls were ascertained via standardized chart reviews. Unhealthy alcohol use was identified via chart review and was defined as any evidence of excessive alcohol use, such as it being stated in the social history or medical history, alcohol abuse being listed as a possible contributor to death, or alcohol-related diagnoses. We used logistic regression to estimate odds ratios (ORs) for the association of unhealthy alcohol use and sudden death, adjusting for age, sex, race, and other psychiatric diagnoses, including depression, anxiety, schizophrenia, bipolar disorder, and substance use disorders other than tobacco and alcohol. We also calculated the E-value to estimate the impact of any unmeasured confounders. Results: We identified 399 sudden death victims, of whom 374 (94%) had alcohol use data available. Among these 374 included victims, 256 (68%) were male, and 239 (62%) were White, with a median age at death of 55 years (IQR 48, 60). The demographic characteristics of the 1114 matched controls were similar to those of sudden death victims. Unhealthy alcohol use was present in 115 (31%) sudden death victims and 27 (2%) controls. In analyses adjusted for demographics only, unhealthy alcohol use was associated with a higher incidence of sudden death, with an OR of 17.5 (95% CI 11.4, 27.8). When further adjusted for other psychiatric diagnoses, the OR was 11.2 (95% CI 7.1, 18.0). The calculated E-value was 21.8, meaning an unmeasured confounder would need to be associated with both unhealthy alcohol use and sudden death by 21.8-fold to explain away the observed OR. Conclusions: Unhealthy alcohol use was strongly associated with higher sudden death risk in working-age adults. Our calculated E-value indicates it is unlikely that any unmeasured confounders alone would account for the observed association. Our findings suggest that interventions to reduce unhealthy alcohol use may be an effective strategy to prevent sudden death in working-age adults. Full article

Background: As glucagon-like peptide-1 (GLP-1) receptor agonist use expands globally, reports of psychiatric adverse events (AEs) have increased in spontaneous reporting databases. However, which case-level characteristics are associated with these reporting patterns remains insufficiently characterized. This study aimed to characterize case-level features associated with psychiatric AE reporting in GLP-1 receptor agonist users through pharmacovigilance and explainable machine learning methods. Methods: The FDA Adverse Event Reporting System (FAERS) data (2021 Q2–2025 Q3) were analyzed using a comparator-based approach comprising other antidiabetic and anti-obesity agents. Disproportionality analyses (PRR, ROR, and IC) were performed to detect consolidated safety signals at the Preferred Term (PT) level, with additional drug-specific analyses for individual GLP-1 receptor agonists. Three classification models (logistic regression, XGBoost, and LightGBM) were developed, and SHAP values were used to identify case-level features associated with psychiatric AE reporting patterns. Results: A total of 211,195 unique cases were included (111,105 for GLP-1 receptor agonists; 100,090 for comparators). Sixteen PTs met consolidated signal criteria, with suicidal ideation being the most frequently reported (ROR 2.95). Drug-specific analyses indicated that signal magnitudes were consistently higher for semaglutide than tirzepatide. The XGBoost model achieved an AUROC of 0.816. SHAP analysis showed that age ≥65 years had the highest mean |SHAP| value (0.57) with a negative direction, corresponding to a lower predicted probability of psychiatric AE reporting in older adults. Semaglutide use ranked second (0.35) and showed a positive direction. Absence of concomitant medications (0.20) and diabetes indication (0.10) showed negative directions, while younger age (19–44 years, 0.08) showed a positive direction. These patterns remained consistent in sensitivity analysis excluding concomitant psychotropic medication users (AUROC 0.797). Conclusions: Older age status was associated with decreased predicted probability of psychiatric AE reporting, while semaglutide use and younger age showed positive contributions. These case-level patterns, identified through pharmacovigilance analysis using a comparator-based approach and explainable machine learning, suggest that reporting patterns may differ across subgroups and that the observed reporting heterogeneity among younger adults and semaglutide users merits further investigation in prospective studies. Full article

Background/Objectives: Insomnia is one of the most prevalent and persistent symptoms among patients with breast cancer, yet it remains under-recognized and undertreated in routine clinical practice. Beyond its impact on sleep quality, insomnia is increasingly understood as a multidimensional condition involving neurobiological, psychological, and behavioral mechanisms, closely intertwined with cancer-related stress and psychiatric comorbidities. This narrative review aims to provide a comprehensive and integrative overview of insomnia in breast cancer, focusing on its epidemiology, pathophysiological underpinnings, neuropsychiatric correlates, and clinical implications, while highlighting gaps in current research and management. Methods: A narrative review of the literature was conducted, including studies published in major medical databases (PubMed, Scopus, and Web of Science) up to 2025. Relevant articles addressing insomnia, sleep disturbances, psychiatric symptoms, and neurobiological mechanisms in breast cancer populations were selected and synthesized. Results: Insomnia affects a substantial proportion of breast cancer patients across the disease trajectory, from diagnosis to survivorship. Its etiology is multifactorial, involving dysregulation of the hypothalamic–pituitary–adrenal axis, inflammatory processes, and circadian rhythm, as well as treatment-related factors such as chemotherapy, endocrine therapy, and menopausal symptoms. Insomnia frequently co-occurs with depression, anxiety, fatigue, and pain, forming symptom clusters that significantly impair quality of life and may influence clinical outcomes. Emerging evidence supports a bidirectional relationship between insomnia and psychiatric vulnerability, suggesting a shared neurobiological substrate within the brain–body stress axis. Conclusions: Insomnia in breast cancer should be conceptualized as a neuropsychiatric condition embedded within a broader stress-related symptom network rather than as an isolated sleep disturbance. Improved screening, interdisciplinary management, and the integration of evidence-based interventions such as cognitive behavioral therapy for insomnia are essential. Research should focus on personalized and mechanistically informed approaches to better address this highly prevalent yet insufficiently managed condition. Full article

Background: Insomnia is common among people with mental health conditions and can exacerbate symptoms, impair functioning and negatively impact treatment outcomes. Community mental health services require practical data to quantify the burden of insomnia in routine care and to identify groups at a higher risk of experiencing clinically significant insomnia. Methods: We conducted a retrospective analysis of anonymized routinely collected clinical data from adult psychiatric outpatients attending the Community Mental Health Center in Bra (Department of Mental Health, Asl Cuneo 2, Italy). Consecutive patients were included over a three-month period (1 September to 30 November 2025). Insomnia severity was assessed using the Insomnia Severity Index (ISI). Diagnoses were established by psychiatrists using the Structured Clinical Interview for DSM-5 (SCID-5). Results: The sample included 506 patients (mean age: 45.1 ± 16.7 years; 265 women, 52.4%). The mean ISI total score was 12.18 ± 6.99. Clinically significant insomnia (ISI ≥ 15) was present in 205 out of 506 patients (40.5%), while severe insomnia (ISI ≥ 22) was present in 55 out of 506 patients (10.9%). The ISI score differed across diagnostic groups (ANOVA, F(8, 497) = 2.82, p = 0.0046, η² = 0.043). Post hoc comparisons revealed higher ISI scores in patients with depressive disorders than in those with anxiety disorders (Tukey, p = 0.0056). In a multivariable logistic regression model (outcome: ISI score of at least 15), adjusted for age, sex, education and the complexity of concurrent psychotropic medication (number of medication classes), depressive disorders were associated with clinically significant insomnia (OR: 1.99; 95% CI: 1.07–3.73). Attention deficit hyperactivity disorder (ADHD) also showed higher odds (OR: 3.64; 95% CI: 1.26–10.55). Medication complexity was also associated with an ISI score of at least 15 (OR: 1.43 per additional class; 95% CI: 1.16–1.77). In a sensitivity model additionally adjusting for benzodiazepine prescription (yes/no), benzodiazepine prescription was associated with ISI ≥ 15 (OR 1.82; 95% CI 1.13–2.95), while the estimate for medication complexity was attenuated using this association (OR 1.17; 95% CI 0.90–1.53). The eating disorders group was excluded from multivariable models due to the very small sample size (n = 4). Conclusions: Clinically significant insomnia was prevalent among this sample of psychiatric outpatients, with modest differences in insomnia severity across diagnostic groups. Sensitivity analyses suggested that the signal of medication complexity may be partly accounted for by benzodiazepine prescribing, supporting the cautious interpretation of medication-related correlates in routine cross-sectional data. These findings support routine insomnia screening in psychiatric outpatient care, while prospective studies are needed to clarify directionality and clinical implications. Full article

Background and Objectives: This study aimed to estimate the prevalence of documented borderline personality disorder (BPD) diagnosis and study-defined BPD indicators among adults with depressive disorders in outpatient psychiatric care, and to quantify a subgroup who were indicator-positive but had no documented diagnosis (potential under-recognition). Materials and Methods: This retrospective, cross-sectional study included adult outpatients with depressive disorders receiving pharmacological treatment at Maharaj Nakorn Chiang Mai Hospital. BPD status was classified using (1) a documented BPD diagnosis in the electronic medical record (EMR) and (2) study-defined indicators, comprising a symptom-based indicator (documentation of ≥5 DSM-5 BPD criteria) and a prescribing-based indicator (antidepressant treatment with concurrent use of antipsychotics and/or mood stabilizers). Prevalence and overlap across diagnoses and indicators were summarized using a Venn distribution. Results: Among 1175 patients, 63 (5.4%) had a documented BPD diagnosis. Using EMR indicators, 84 (7.1%) met the symptom-based indicator and 325 (27.7%) met the prescribing-based indicator. In total, 374 (31.8%) had either a documented BPD diagnosis or at least one indicator, while 801 (68.2%) had neither. Overall, 370 (31.5%) met at least one indicator (symptom-based and/or prescribing-based). Among indicator-positive patients, 311 (84.1%) had no documented BPD diagnosis, representing 26.5% (311/1175) of the total cohort. Conclusions: Study-defined EMR indicators flagged a substantial subgroup with potential under-recognition of BPD features in depressive-disorder clinics. These indicators may help prioritize targeted assessment and structured diagnostic evaluation to support access to BPD-informed care and support referral to BPD-informed psychotherapy. Full article

Introduction: Medical care for transgender minors is understudied, largely because these forms of care are relatively recent. The primary objective of this work was to describe the cohort of transgender adolescents who initiated follow-up at the Strasbourg University Hospital before the age of 18, whether or not they began hormone therapy prior to reaching adulthood. Method: This was an observational, retrospective, single-center, descriptive study conducted among adolescents who had attended at least one consultation in our center before the age of 18 between January 2017 and March 2024. Results: Our population consisted of 115 patients predominantly made up of transmasculine (AFAB) adolescents (68%). Compared with the general population, we observed significantly higher rates of psychiatric co-occurrences, autism spectrum disorder (ASD), and attention-deficit/hyperactivity disorder (ADHD). Only 46.1% initiated gender-affirming hormone therapy (GAHT) in our cohort, and just 34.8% before age 18. A total of 6% of adolescents received puberty blockers as monotherapy. The mean age at GAHT initiation was 16.99 years. Transition pathways appear to differ according to the adolescent’s type of schooling. The rate of retransition/treatment interruption in our sample ranged from 0% to 6.1%, depending on the criteria applied. We did not identify any adolescent who retransitioned to their sex assigned at birth after starting GAHT by the end of the data collection. Discussion: The high prevalence of psychiatric co-occurrences raises important questions regarding how to improve care for these adolescents. The predominance of AFAB adolescents similarly prompts reflection on the barriers that transfeminine adolescents may face when seeking to transition before adulthood. In addition, the substantial number of adolescents presenting with ASD or ADHD underscores the need for particular vigilance regarding their specific needs and overall well-being. Finally, the variability in retransition rates depending on the criteria applied highlights the absence of a consensual definition, which limits the comparability and validity of existing studies. Conclusions: Long-term prospective studies are needed to objectively demonstrate the effectiveness of current transition pathways. Academic research in this field should be strengthened, along with the development of larger prospective datasets, to improve the overall health of this population. Full article

Background: Congenital heart defects (CHD) are prevalent, affecting 1% of live births globally. Despite improved survival rates, adults with CHD face increased risks of psychological distress and neurocognitive deficits. The P-BAHn study (P-BAHn = “Psyche Bei Angeborenen Herzfehlern”, Psyche for congenital heart defects) evaluates the mental health status and psychosocial challenges of German children and adolescents with CHD, focusing on retrospectively assessed COVID-19-related burden and patient-/parent-rated experiences with psychological, psychotherapeutic, or psychiatric treatment (PST). Methods: A cross-sectional, online-based survey was conducted using the National Register for Congenital Heart Defects (NRCHD). The final dataset comprised 1567 respondent-level records from 1310 families, including 992 parent reports and 575 self-reports from children/adolescents aged 6 to <18 years. The survey assessed mental health, emotional well-being, psychosocial status, demographics, medical history, and psychological treatment. Data were analyzed descriptively using chi-square tests and t-tests for exploratory unadjusted group comparisons. In addition, exploratory multivariable logistic regression analyses were performed for selected key outcomes. Results: School-related stress was common in young CHD patients (45.3%) and was associated with older age and female sex (51.5% female vs. 35.6% male) in adjusted analyses. Overall, 17.0% of patients reported having a mental illness, most commonly anxiety (6.8%), eating disorders (5.6%), and depression (4.7%); neither sex nor CHD severity was significantly associated with self-reported mental illness in adjusted analyses. Less good/poor self-rated health was associated with older age and complex CHD in both patient and parent reports. Retrospectively assessed pandemic-related changes were perceived as quite or extremely stressful by 23.9% of patients. High COVID-19-related burden was associated with female sex, whereas CHD severity was not significant after adjustment. Among patients with previous or current PST, patient- and parent-rated treatment benefit varied by patient sex and CHD complexity. Previous/current PST was reported by 25.9% of patients and 23.8% of parents and was associated with older age in both respondent groups and with complex CHD in parent reports. Among patients with previous/current PST, 56.4% reported high perceived support. Conclusions: The P-BAHn study highlights the need for targeted psychosocial support for children and adolescents with CHD, including female patients, those with complex conditions, and patients reporting school- or crisis-related burden. Retrospectively reported pandemic-related burden underscores the importance of integrating crisis-sensitive strategies into psychosocial care frameworks. Longitudinal studies are essential to understand mental health trajectories and to evaluate the sustained patient- and parent-perceived benefit as well as clinical effectiveness of PST use. Enhancing support services and refining intervention models will improve the well-being and quality of life for young CHD patients. Full article

Background and Objectives: Mental illnesses place a substantial burden on healthcare systems and often require complex pharmacological management. However, it remains unclear whether early antipsychotic polypharmacy independently predicts length of stay after adjusting for important confounders. This study aimed to investigate drug utilization patterns, including polypharmacy and drug–drug interactions (DDIs), assess anticholinergic burden, and identify predictors of the length of hospital stay in a psychiatric inpatient setting. Materials and Methods: This retrospective, observational study was conducted at Bolu İzzet Baysal Mental Health and Diseases Hospital with 280 adult patients admitted during 2022. Medication data were extracted from electronic medical records based on medication orders within the first 72 h of admission. Potential DDIs were assessed using Lexi-Interact, and anticholinergic burden was calculated using the ACB, ADS, and ARS scales. Predictors of the length of stay (LOS) were modelled using negative binomial regression. Results: The mean age of the population was 38.65 ± 13.86 years, and 62.1% were male. Polypharmacy was present in 37.9% of patients, while antipsychotic polypharmacy was observed in 63.9%. Potential DDIs were identified in 88.9% of patients, with a significantly higher prevalence in those with polypharmacy. Mean ACB and ADS scores were high at 5.56 ± 3.32 and 4.15 ± 2.79, respectively. Multivariable regression analysis revealed that antipsychotic polypharmacy was the primary independent predictor of prolonged hospitalization, associated with a 20.9% increase in LOS (IRR = 1.209, 95% CI: 1.044–1.400, p = 0.011). While age was also statistically significant (IRR = 1.006, 95% CI: 1.001–1.012, p = 0.019), its clinical impact was minimal, representing only a 0.6% increase in LOS per year. Conclusions: Antipsychotic polypharmacy within the first 72 h of admission is a significant independent predictor of prolonged hospitalization. The high prevalence of drug interactions and substantial anticholinergic burden highlight the need for systematic early medication review. Instead of general monitoring, targeted medication therapy review focusing on antipsychotic polypharmacy in the early period of admission may be essential to identify and mitigate modifiable risk factors for prolonged hospitalization, thereby optimizing pharmacotherapy in psychiatric inpatient settings. Full article

Objective: To identify FDA-authorized prescription or clinician-directed digital mental health products, including applications and software-enabled devices, for psychiatric treatment or diagnostic support. Methods: FDA Medical Device Databases were searched for records associated with nine product codes relevant to digital mental health. Eligible records were consolidated into distinct product families. Peer-reviewed literature and FDA documentation were reviewed to characterize indications, authorization pathways, and the quality of supporting evidence. Results: Sixteen digital mental health products and software-enabled devices authorized by the FDA met the inclusion criteria. Twelve products supported treatment for substance use disorders, insomnia, attention-deficit/hyperactivity disorder (ADHD), posttraumatic stress disorder (PTSD)-related conditions, major depressive disorder, generalized anxiety disorder, and postpartum depression. Four products provided diagnostic support for ADHD or autism spectrum disorder. Authorization was granted through either 510(k) clearance or De Novo classification, with considerable variation in the quantity, independence, and clinical relevance of supporting evidence. Conclusions: FDA marketing authorization does not uniformly indicate clinical effectiveness. Because 510(k) clearance, De Novo classification, and premarket approval (PMA) reflect distinct regulatory standards, clinicians should interpret digital mental health products in the context of the specific authorization pathway, product indication, and supporting evidence base. Full article

Background/Objectives: Survival rates after pediatric liver transplantation have improved substantially over recent decades, yet the psychiatric consequences for recipients remain a concern that warrants closer attention. We sought to map the psychiatric symptom burden across multiple domains in this population and to determine which symptom clusters carry the greatest impact on health-related quality of life (HRQOL). Materials and Methods: Fifty liver transplant recipients between the ages of 8 and 18 were enrolled at a single center. Children and their parents completed four psychiatric measures—the CBCL, CDI, SCARED, and CRIES-13—alongside the parent-proxy PedsQL to capture HRQOL across physical, emotional, social, and school functioning domains. Correlations between instruments were calculated, and linear regression was used to determine which psychiatric variables independently predicted PedsQL Total scores. Results: Across all psychiatric measures, higher symptom scores were associated with lower HRQOL, with school functioning recording the lowest absolute PedsQL domain score, while emotional functioning demonstrated the strongest and most consistent inverse correlations with all psychiatric symptom measures across instruments. CBCL Total (r = −0.607), SCARED Total (r = −0.557), and CRIES-13 Total (r = −0.548) scores all correlated meaningfully with overall HRQOL. When entered into multivariable analysis, anxiety symptoms measured by the SCARED (β = −0.295, p = 0.032) and post-traumatic stress symptoms measured by the CRIES-13 (β = −0.400, p = 0.004) stood out as the two independent predictors of worse PedsQL Total scores. Conclusions: Even in medically stable recipients, anxiety and post-traumatic stress symptoms were independently associated with lower daily functioning scores and overall quality of life. These findings suggest that routine psychosocial screening and trauma-informed approaches may warrant integration into post-transplant care protocols, and that prospective, adequately powered studies are needed to confirm and extend these associations. Full article

Background: Antenatal depression has been associated with systemic inflammation, autonomic imbalance, and vascular dysfunction, yet its relationship with clinically relevant cardiovascular complications during pregnancy remains insufficiently defined. Objective: To evaluate whether antenatal depression diagnosed before cardiologic assessment is associated with gestational hypertension, preeclampsia, and clinically significant Holter-confirmed arrhythmias in a tertiary-care population of pregnant women referred for cardiology assessment. Methods: We conducted a retrospective secondary matched cohort analysis nested within a prospectively approved doctoral research protocol (approval no. 76/02.10.2023; approved study interval: 2 October 2023–10 February 2025), including deliveries from October 2023 to February 2025. During this 16-month interval, 12,436 deliveries were recorded. The index point was the first cardiology specialist evaluation performed between 22 + 0 and 36 + 6 weeks’ gestation. Pregnancies with a depressive disorder diagnosed by structured psychiatric interview (SCID-5) before cardiology evaluation were classified as exposed. Depression severity was categorized as mild (n = 44), moderate (n = 62), or severe (n = 24), and psychotropic medication class at index was recorded. Each depressed case was matched 1:3 with non-depressed controls by gestational age at index, calendar year, maternal age, BMI category, smoking status, and parity; adjusted models included BMI and psychotropic medication class. Results: The final referral-enriched cohort included 130 depressed pregnancies and 390 matched controls (n = 520), all of whom underwent cardiology evaluation. Between 22 + 0 and 36 + 6 weeks’ gestation, gestational hypertension occurred in 18.5% vs. 10.0% (p = 0.010), preeclampsia in 8.5% vs. 4.9% (p = 0.12), and clinically significant Holter-confirmed arrhythmias in 15.4% vs. 6.9% (p = 0.003) in depressed versus control groups, respectively. After adjustment, depression remained independently associated with gestational hypertension (aOR 1.85, 95% CI 1.12–3.05; p = 0.016) and arrhythmia (aOR 2.05, 95% CI 1.18–3.57; p = 0.011). A numerical, exploratory severity-response gradient was observed across mild, moderate, and severe depression strata, most clearly for Holter-confirmed arrhythmias; however, the severe-depression stratum was small (n = 24). Conclusions: Antenatal depression was associated with a modest but significant increase in gestational hypertension and clinically significant Holter-confirmed arrhythmias during late pregnancy among women referred for cardiology assessment. The higher preeclampsia rate in depressed pregnancies was not statistically significant. These findings support antenatal depression as a cardiovascular risk marker in gestation rather than proof of causality. Full article

Heart rate variability (HRV) refers to variations in the time intervals between consecutive heart beats. Changes in HRV reflect changes in either sympathetic or decreased parasympathetic tone that can originate in the brain. This brain–heart connection has led to the proposal that HRV may have utility in the diagnosis of psychiatric conditions and/or be a predictor of the response to psychiatric medications. There have been attempts to improve the correlation between HRV and psychological and psychiatric conditions by using artificial intelligence or specific machine learning algorithms. The objective of this review is to synthesize data on the use of machine learning to improve accuracy in differentiating psychological conditions such as mental stress, as well as distinguishing persons with anxiety disorders, panic disorders, major depression disorders and schizophrenia from health subjects. Reported accuracies for the identification of mental stress vary from 42 to 94%, while accuracies for anxiety vary from 67 to 98%, panic disorders from 71 to 93% and depression from 71 to 95%. The ability of HRV to differentiate different psychological or psychiatric conditions from each other requires more investigation. The ‘best’ machine learning algorithm varied between studies, with some reporting the k-nearest neighbor algorithm, support vector machine, random forest, or neural networks to be the best. A number of studies combined HRV with other variables such as respiration, EEG, or electromyography to obtain a composite index, but in doing so obscured the independent contribution of HRV. In summary, HRV has shown promise in detecting abnormalities in a range of psychological and psychiatric conditions. The use of machine learning algorithms improves diagnostic accuracy. Full article

Background/Objectives: Alexithymia is a potential transdiagnostic risk factor for psychiatric and medical disorders involving affect dysregulation. But there is debate over whether a constricted imaginal capacity constitutes a core component of the construct or is a separable correlate. Our aim was to further explore this controversy as any revision to the construct has implications for clinical formulation, neurobiological models of associated default mode network dysfunction, and the coherence of the original psychiatric conceptualization. Methods: To replicate and extend previous factor analytic work, we conducted a two-stage exploratory factor analysis in a community sample that included individuals with a psychiatric history (N = 681). Using most of the subscale indicators employed in two prior factor analytic studies, we used a two-stage procedure: Stage 1 re-employed the general design of those studies. Stage 2 re-specified the analytic space by removing emotional reactivity and fantasizing-for-regulation variables that form their own separable latent dimensions. Results: Stage 1 yielded a conceptual replication of structural separation between alexithymia and imaginal processes. Stage 2 revealed meaningful cross-loadings obscured in the full set, most notably positive constructive daydreaming loading negatively on an externally oriented thinking factor, providing empirical support for the pensée opératoire construct. Additional cross-loadings linked dysphoric daydreaming and poor attentional control with negative emotion appraisal. Conclusions: The structural independence of alexithymia and imaginal processes is partly contingent on indicator set composition. Construct revision should be grounded not on two factor analytic studies using abbreviated self-report measures, but in convergent evidence across methods, including neuroimaging, electroencephalography, structured interview, performance-based assessment, and clinical observation. Full article