bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association of FKBP5 gene methylation and adolescents’ sex with depressive symptoms outcomes: a nested case-control study among Chinese adolescents
Authors: Li W. , Lu C. 
Published: September 2022

IntroductionAltered DNA methylation in the FK506 binding protein 5 (FKBP5) gene has been shown to regulate stress response, which may serve as a biomarker of depression and a promising candidate for explaining sexual differences. However, there is no consistent conclusion so far.ObjectivesThe present study aimed to test the associations of FKBP5 DNA methylation with depressive symptoms and whether these associations were influenced by sex.MethodsA nested case-control study comprising 87 cases and 151 controls was conducted in South China from January 2019 and December 2019. Peripheral blood for DNA extraction and DNA methylation analysis of FKBP5 gene promoter was collected, and severity of depressive symptoms was assessed at baseline and after one year follow-up.ResultsCompared to healthy controls, lower methylation percentage of FKBP5-12 CpG 1 was observed in adolescents with depressive symptoms after adjusting covariates (case: 0.94 ± 2.00, control: 0.47 ± 0.92; F = 5.41, P = 0.021). In addition, hypomethylation of FKBP5 CpG sites was not an independent risk factor for depressive symptoms after adjustment for environmental stress factors (P > 0.05). No significant sex differences were found in the association of FKBP5 gene methylation with depressive symptoms.ConclusionsLower levels of FKBP5 methylation were found in adolescents with depressive symptoms. Our study supported that the epigenetic factors did not act alone in the development of depressive symptoms. Taken together, these findings contribute to a better understanding of complex mechanisms of gene-environment interactions involved in depression.DisclosureNo significant relationships.
Specifics of depression in epilepsy
Authors: Mitikhin V. , Kuzminova M. 
Published: September 2022

IntroductionThe strong comorbidity between depression and epilepsy is widely acknowledged. However, depression in epilepsy can manifest atypically, leading to its low detection rate and lack of access to treatment in patients with epilepsyObjectivesTo study the specifics and pattern of depression in epilepsy for its timely diagnosis and therapy and to prevent suicide risk and improve the quality of life in patients with epilepsyMethodsClinical, statistical, psychometric. A total of 149 patients, mean age 45.0 ± 11.7 years, 74 males, 75 females, were examinedResultsIt was found that depression was manifested in 46.3% of patients before the onset of epileptic seizures, and in 20.8% of patients it developed after treatment with some AEDs. The incidence of symptoms characteristic of depression in epilepsy, such as unstable mood, irritability, euphoria, episodes of pain and sleep disturbances, and its’ impact on the quality of life in patients with epilepsy were analysed. Gender differences were identified for a range of symptomsConclusionsThe authors expanded their understanding of the clinical specifics of depressive manifestations in patients with epilepsy to allow timely detection and medical and rehabilitative care for these patientsDisclosureNo significant relationships.
Sleep and Mental Disorders
Authors: Pollmächer T. 
Published: September 2022

Since ancient times, the close connection between disturbed sleep and mental disorders has been well known. And yet, it was not until the middle of the 20th century that these connections could be studied in detail, after the EEG and REM sleep were discovered. Especially the study of the sleep EEG of depressed patients has brought to light alterations of SWS and REM sleep that could be of considerable clinical value, but at least in part still await broad confirmation. In the treatment of disturbed sleep in psychiatric patients, cognitive behavioral therapy in particular has become increasingly established in recent years, whereas only limited innovations have been recorded with regard to pharmacological treatment. Only in recent years it has become clear that psychiatric disorders are often accompanied by clinically relevant somatic disorders of sleep, such as obstructive sleep apnea syndrome, and that such comorbidities urgently require attention and treatment. It is becoming increasingly clear that detailed knowledge of sleep disorders is essential for the effective treatment of mental disorders. Moreover, it is likely that the scientific study of sleep in mentally ill people still has untapped potential in terms of understanding the pathophysiology.DisclosureNo significant relationships.
Prevalence of treatment resistant schizophrenia according to minima TRRIP criteria in a mental health catchment area in southern Spain
Authors: Muñoz-Manchado L.I. , Pascual Paño J.M. , Rodríguez-Gómez C. , Mongil-Sanjuan J.M. , Pérez-Revuelta J.I. , Torrecilla-Olavarrieta R. , González-Saiz F. , Villagrán-Moreno J.M. 
Published: September 2022

IntroductionThe response to antipsychotic treatment in patients with schizophrenia varies from 14 to 34% in first episodes, and from 45 to 61% in more chronic patients. Nevertheless, the concept of treatment resistant schizophrenia (TRS) is still a matter of great controversy. Recently, an international group of experts has developed the TRRIP criteria to define treatment resistant schizophrenia (TRS), including an ultra-resistance category for clozapine resistant patients. Up till now, there is a scarcity of epidemiological data of TRS with TRRIP criteria.ObjectivesThis study attempts to identify the population diagnosed of schizophrenia that fulfils the minima TRRIP criteria for TRS in our mental health catchment area.MethodsA descriptive and retrospective study has been developed on the patients diagnosed of schizophrenia (ICD.10, F.20) in the catchment area of the Mental Health Service at Jerez Hospital between 2018 and 2019. TRRIP criteria were applied for two independent researchers and, in case of disagreement, consensus was reached by using the LEAD procedure.ResultsThe total number of ICD-10 schizophrenic patients identified was 590, from a population of 456.752 in 2019. A group of these, 206 patients (35%) qualified as TRS according to the minima TRRIP criteria, 50% were positive subtype and the rest the negative one. 46.8% were treated with clozapine.ConclusionsConsensus criteria of TRS minimise the heterogeneity of epidemiological data in literature. Our data suggest a prevalence rate of TRS lower than that of similar studies. Accordingly, a comprehensive understanding of this population would undoubtedly contribute to improve preventive and therapeutic strategies.DisclosureNo significant relationships.
Exploring the association between brain-derived neurotrophic factor (BDNF) levels and longitudinal psychopathological and cognitive changes in Sardinian psychotic patients
Authors: Isayeva U. , Manchia M. , Primavera D. , Deriu L. , Caboni E. , Iaselli N. , Sundas D. , Tusconi M. , Collu R. , Scherma M. , Squassina A. , Congiu D. , Fratta W. , Fadda P. , Carpiniello B. 
Published: September 2022

IntroductionSchizophrenia spectrum disorders are among the most debilitating mental disorders and evidence on its pathophysiological underpinnings is scant. The brain-derived neurotrophic factor (BDNF) appears to be involved in the pathophysiology of these complex psychiatric disorders.ObjectivesThe present study investigates the longitudinal variation of serum BDNF levels in a 24-month observational cohort study of Sardinian psychotic patients (LABSP). This study assessed the variation in BDNF serum levels and its relationship with psychopathological and cognitive changes. Further, we also examined if genetic variations within the BDNF gene could moderate these relationships.MethodsEvery six months 105 LABSP patients were assessed for their BDNF serum levels, as well as for a series of psychopathological, cognitive, and drug-related measures. Four tag single nucleotide polymorphisms (SNPs) within the BDNF gene were selected and analyzed using Polymerase Chain Reaction (PCR). Longitudinal data were analyzed using mixed-effects linear regression models (MLRM).ResultsAnalysis showed significantly lower peripheral BDNF levels in psychotic patients with depressive and negative symptoms. BDNF levels were also decreased in patients scoring lower in cognitive measures such as symbol coding and semantic fluency. In addition, Val66Met polymorphism within the BDNF gene significantly moderated the relationship between the severity of negative symptoms and BDNF levels.ConclusionsOur findings are consistent with previous literature suggesting that peripheral BDNF levels are associated with some cognitive domains and mood disruption in major psychosis. The results also suggest the lack of association between most BDNF genetic variants, except Val66Met polymorphism, with the severity of negative symptoms.DisclosureNo significant relationships.
Point-of-care test for rapid assessment of blood lithium levels in women with bipolar disorder during perinatal period
Authors: Imaz M.L. , Torra M. , Martin M. , Aliart I. , Martin-Santos R. , Vieta E. , Garcia-Esteve L. 
Published: September 2022

IntroductionDetermination of lithium levels in serum has become a standard of care due to its narrow therapeutic rang, thus an immediate test for determination of blood lithium may contribute to minimize toxicit, to avoid relapse and to ensure treatment adherence. This is particularly relevant during pregnancy and early postpartum because pharmaokinetic changes in renal physiology.ObjectivesThe aim of this study is verify Medimate point-of-care method performance and systematically compare it with the routine laboratory measurement of lithium.MethodsThis cross-sectional method comparison study was conductec in the Unit of Perinatal Mental Health in the Hospital Clinic of Barcelona. Pearson and Bland-Altman analyses were performed to assess the accuracy, precision and correlation between the capillary electrophoresis technology (Medimate MiniLab) and the ion selective electrode (ISE) potentiometry method (AVL 9180).ResultsTwenty-five women with bipolar disorder in treatment with lithium during perinatal period were enrolled, corresponding to 75 blood specimens for analyses. Correlation (r), mean difference (bias), and 95% limit of agreement (LOA) of the point-of-care method [r=0.917; bias 0.0021 (95% LOA; 0.440, 0.619) mEq/L], showed that difference between ISE method and capillary electrophoresis technology was not statistically significant.ConclusionsConsidering the practicality, the microchip capillary electrophoresis technology provides a simple and highly affordable way of measuring lithium levels in a single drop of blood outside the clinical laboratory. The Medimate point-of-care system (POC) appears well adapted for the rapid and specific detection of lithium as an alternative to the current ISE procedure.DisclosureNo significant relationships.
Applying existing clinical staging models in a sample of Italian bipolar patients over a 10-years follow-up
Authors: Macellaro M. , Girone N. , Cremaschi L. , Bosi M. , Cesana B. , Ambrogi F. , Dell’Osso B. 
Published: September 2022

IntroductionBipolar Disorder (BD) is a life-course illness with evidence of a progressive nature. Although different staging models have been proposed from a theoretical perspective,longitudinal studies are scarce.ObjectivesThe aim of the present study was to apply four staging models in a sample of BD patients and to observe their progression in 10 years of retrospective evaluation.MethodsIn a naturalistic sample of 100 BD patients, a retrospective assessment of clinical stages across 10 years of observation at six time points (T0: 2010; T1: 2013; T2: 2015; T3: 2018; T4: 2019; T5:2020) was performed according to the BD staging models (Berk et al., 2007; Kapczinski et al., 2009; Kupka et al., 2012 and Duffy et al., 2014). Socio-demographic and clinical variables were collected and the staging progression across time was analyzed.ResultsA significant progressive staging worsening emerged over 10 years of BD observation for each examined model (p<0.001). Moreover, for all considered staging approaches, stage values were lower over the time points for BD II, lower number of lifetime episodes and hospitalizations (p<0.05). Finally, the stage increase was associated with a lower age at first elevated episode (p<0.05).ConclusionsPresent preliminary results confirm the relevance of illness onset and early intervention in BD, given their role in patients classified into worse clinical staging. There is an emerging need of a standardized universal staging model in order to better characterize BD patients, their treatment and their clinical course.DisclosureNo significant relationships.
Social Hypersensitivity in Bipolar Disorder: An ERP Study
Authors: Kwan Y. , Lee J. , Hwang S. , Choi S. 
Published: September 2022

IntroductionBipolar Disorder (BD) is a disorder in which cognitive function is relatively preserved but social functioning is markedly impaired. Interestingly, studies on BD show that the patients have a strong desire for social rewards. Hypersensitivity to social rewards in BD has not yet been sufficiently examined through experimental methods, although recent studies have pointed out that their reward hypersensitivity is the cause of symptoms and dysfunction.ObjectivesThe purpose of this study was to investigate whether patients with BD are hypersensitive to social rewards using the social value capture task.MethodsGroups of 25 BD and healthy control (HC) each completed the social value attention capture task. This task consists of a practice phase in which associative learning of social rewards with specific stimuli occurs, and a test phase in which the stimuli associated with rewards appear as distractors during the participants performing a selective attention task. We also recorded event-related potential (ERP) in the practice phase in order to investigate BDs’ cortical activity for social reward.Resultsshowed significantly decreased accuracy rate and increased reaction time in the high social reward-associated distractor trials of the test phase in the BD compared to the HC. As a result of analysis in ERP components, P3 amplitude for social reward was significantly greater in the BD than the HC.ConclusionsBD patients exhibit behavioral and physiological hypersensitivity to social rewards that might contribute to social dysfunction.DisclosureNo significant relationships.
Do Clinicians Need to Rethink Antipsychotic Maintenance Treatment?
Authors: Kane J. 
Published: September 2022

Schizophrenia remains a challenging illness to treat despite considerable progress. The heterogeneity of symptoms and variability in course, outcome, and treatment response lead to considerable uncertainties in treatment guidelines. One of the most challenging issues is how to determine the need for and duration of the maintenance treatment that is intended to reduce the risk of exacerbation, relapse, and hospitalization. It is clear that in large populations, antipsychotic medication is very effective in reducing those risks, however, there is likely a subpopulation of patients with diminished risk for such outcomes even when medication is discontinued. Although attempts have been made to utilize “intermittent” or “targeted” treatment, those randomized controlled trials that have been conducted show a statistically significant advantage for continuous treatment. At the same time, many patients continue to receive higher than necessary doses of antipsychotic medication and practice needs to be reevaluated in terms of dosage requirements. The challenge remains that there are no good biomarkers or predictors of who is at risk and, therefore, dosage reduction is only titrated against exacerbation or relapse. We need to proactively reconsider who requires maintenance treatment by establishing predictive biomarkers (clinical or biological) that can help us to have a more personalized approach.DisclosureConsultant to or receives honoraria: Alkermes, Allergan, Dainippon Sumitomo, H. Lundbeck, Indivior, Intracellular Therapies, Janssen Pharmaceutical, Johnson & Johnson, LB Pharmaceuticals, Merck, Minerva, Neurocrine, Novartis Pharmaceuticals,
Forced Normalization and other neuro-psychiatric manifestations of epilepsy - Case series and A literature review
Authors: Deol Y. , Morales M. , San Gabriel M. , Du Boulay M. 
Published: September 2022

IntroductionPsychosis of epilepsy has intrigued many neurologists and psychiatrists. We attempt to summarize the phenomenon, suggested diagnostic criteria and distinguishing features between different clinical entities linked with epilepsy.This case series is unique and rare as we include the case that meets full criteria of forced normalization.Objectives1) To understand the concept and diagnostic criteria of Forced Normalization 2) To differentiate different psychiatric manifestations of epilepsyMethodsA total of 13 studies were reviewed using the key words from 1999 –2021 using different search engines- Google scholar, Pub-med, Elsevier, Dynamed.ResultsPatients with epilepsy have an eightfold increased risk of psychosis (6). Forced Normalization has been described as the onset of psychotic or mood symptoms after the resolution or remission of >50% of seizures, evidenced by normal EEG. It was first described in 1950’s and has been extensively studied since 19thcentury. The age of onset can be 8 years to 71 years of age (mean - 28.3). The exact mechanism is still unknown. Different factors have been linked to this phenomenon like kindling, neurotransmitters etc.ConclusionsIt is interesting to understand the antagonistic relationship between epilepsy and psychosis. Forced normalization is a rare entity because it is hard to diagnose due to possible overlap with other clinical entities like post-ictal or side effects of AED. The prognosis seems to be favorable depending on the trigger for the symptoms with better prognosis if the resolution of seizures was achieved AED. Mood disorders had worse prognosis than dissociation and psychosis.DisclosureNo significant relationships.
The Management and Supervision Tool (MaST): an electronic crisis risk prediction tool to support safe and effective mental healthcare
Authors: Patel R. , Oram J. , Hebden N. , Payne Z. , Morse M. , Gadd C. 
Published: September 2022

IntroductionThe increasing global burden of mental disorders has led to rising demand for mental healthcare services. Effective resource management is essential to ensure safe and timely access to care. Electronic health records (EHRs) provide a real-time source of data on clinical presentation and prognostic factors that could be harnessed to provide clinicians with actionable insights to prioritise mental healthcare delivery. We describe the development and evaluation of MaST, an EHR data visualisation tool that provides information to clinicians on risk of mental health crisis defined as an admission to a psychiatric hospital or acceptance into a community crisis service.Objectives(i) To develop an EHR-data driven risk prediction tool for risk of crisis. (ii) To evaluate predictive performance in a real-world clinical setting.MethodsThe risk of crisis algorithm was developed and evaluated with EHR data from six UK NHS mental health providers using Ordered Predictor List propensity scores grouped into 5 quintiles. The predictor variables were clinical and sociodemographic factors including previous mental health service contacts.ResultsData from 2,620 patients contributed to algorithm development which was subsequently tested on data from 107,879 patients. The risk of crisis algorithm performed well with an overall accuracy for predicting the greatest risk of crisis (top quintile) ranging from 64% to 80%.ConclusionsThe MaST algorithm accurately predicted risk of mental health crisis in UK community mental health services. EHR data visualisation tools can provide actionable insights to clinicians to prioritise mental healthcare delivery in real-world clinical practice.DisclosureThis study was funded in full by Holmusk.
Relational factors predict telepsychotherapy acceptance in patients: The role of therapeutic relationship and attachment
Authors: Békés V. , Aafjes-Van Doorn K. 
Published: September 2022

IntroductionDuring the early months of the COVID-19 pandemic, patients receiving individual psychotherapy needed to transition to telepsychotherapy (TP). Since telemental health appears to be here to stay after the pandemic ends, it is crucial to understand factors that determine whether telemental health is a good fit for patients.ObjectivesThe aim of the present study was to (1) explore patients’ perception of the therapeutic relationship and attitudes towards TP, and (2) identify predictors of patients’ TP acceptance.MethodsWe used a longitudinal design, where patients (N = 719) receiving individual TP during the pandemic participated in an online survey, in which they responded to demographic questions and completed measures of symptom severity, Covid-related distress, attachment style (avoidant/anxious), perceived quality of the therapeutic relationship (working alliance and real relationship), and TP acceptance.ResultsWe found that (1) patients perceived the quality of the therapeutic relationship as reasonably good, and patients’ TP acceptance was moderately high. (2) patients’ TP acceptance was predicted by their attachment avoidance and their perception of the real relationship, whereas attachment anxiety, working alliance, as well as demographic variables, symptom severity, and Covid-related distress were unrelated to TP acceptance. The final model showed that perceived strength of the real relationship mediated the relationship between attachment avoidance and TP acceptance.ConclusionsBoth general (attachment) and situational (therapeutic relationship) relational variables are important predictors of patient’s acceptance of TP, and should be considered during decision making about suitability of TP to patients.DisclosureNo significant relationships.
A case study for assessing the utility of a decision tree based learning algorithm in mental health inpatient care quality management
Authors: Wernigg R. , Wernigg M. 
Published: September 2022

IntroductionThere is limited knowledge about the potential role of machine learning (ML) in quality improvement of psychiatric care.ObjectivesOur case study was to determine whether ML decision trees used on patient databases are suitable for focussing on specific patient population samples of mental healthcare quality audits. Populations were identified by patient and care provider variables, and the time of treatment. Outcomes were defined as hospital mortality, over-long hospitalization (over average +1SD or +2SD); and short hospitalization (under average -1SD; under 3 days).MethodsWe conducted a Split Train Test in Python for our outcomes on national mental health inpatient turnover data (2010 through 2018 for training and 2019 for testing). A well-fitting decision tree had the area under the curve (AUC) of the receiver operating characteristic (ROC) >= 0.7, and specificity >= 0.9. Performing qualitative analyses of decision trees, we rejected the ones with little clinical relevance.ResultsDecision trees fit well (AUC = 0.7 to 0.9; specificity = 0.7 to 1.0; sensitivity = 0 to 0.69). For hospital death cases, the decision tree had AUC = 0.86, no difference after controlling for the types of hospital units, and was clinically relevant. Models predicting over-long hospitalization fit well (AUC=0,9); however, controlling for care pathways, good fit and sensitivity both vanished. No valid models emerged for undertime discharges. The decision trees revealed unique combinations of variables.ConclusionsOur ML decision trees used on healthcare databases proved promising for focussing quality audit efforts. Narrative analysis for the clinical contexts of the decision trees is indispensable.DisclosureNo significant relationships.