A recent suicide attempt and the heartbeat: Electrophysiological findings from a trans-diagnostic cohort of patients and healthy controls

Suicidal behavior is influenced by a multitude of factors, making prediction and prevention of suicide attempts (SA) a challenge. A useful tool to uncover underlying pathophysiology or propose new therapy approaches are biomarkers, especially within the context of point-of-care tests. Heart rate variability (HRV) is a well-established biomarker of mental health, and measures the activity of the sympathetic and parasympathetic nervous system (PNS). Previous studies reported a correlation between lower PNS activity and suicidality. However, most studies involved participants from a healthy population, patients without history of suicide attempts, or patients with a single diagnosis. 52 in-patients with a recent suicide attempt (<6 months), and 43 controls without history of SA or psychiatric diagnoses confirmed study participation. The included patients age ranged between 18 and 65 years, 65% had psychiatric comorbidities. Patients with dementia, cognitive impairments, acute psychosis, chronic non suicidal self-harming behavior, or current electroconvulsive therapy were excluded. A 15-min resting state electrocardiography was recorded with two bipolar electrodes attached to the right and left insides of the wrists. The multiple regression analyses showed lower parasympathetic, and higher sympathetic activity in patients compared to controls. Partial correlation found a positive trend result between self-reported suicidality and the very low frequency band. ROC curve analysis revealed an acceptable to excellent clinical accuracy of HRV parameters. Therefore, HRV parameters could be reliable discriminative biomarkers between in-patients with a recent SA and healthy controls. One limitation is the lack of a control group consisting of in-patients without life-time suicidal ideation or attempts

Suicidal ideations and suicide attempts prior to admission to a psychiatric hospital in the first six months of the COVID-19 pandemic: interrupted time-series analysis to estimate the impact of the lockdown and comparison of 2020 with 2019

Background There is a substantial burden on global mental health as a result of the Coronavirus disease 2019 (COVID-19) pandemic that has become putting pressure on healthcare systems. There is increasing concern about rising suicidality consequential to the COVID-19 pandemic and the measures taken. Existing research about the impact of earlier epidemics and economic crises as well as current studies about the effects of the pandemic on public mental health and populations at risk indicate rising suicidality, especially in the middle and longer term. Aims This study investigated the early impact of the COVID-19 pandemic on suicidality by comparing weekly in-patient admissions for individuals who were suicidal or who attempted suicide just before admission, for the first 6 months after the pandemic's onset in Switzerland with corresponding 2019 control data. Method Data was collected at the Psychiatric University Hospital of Zurich. An interrupted time-series design was used to analyse the number of patients who were suicidal. Results Instead of a suggested higher rate of suicidality, fewer admissions of patients with suicidal thoughts were found during the first 6-months after the COVID-19 outbreak. However, the proportion of involuntary admissions was found to be higher and more patients have been admitted after a first suicide attempt than in the corresponding control period from 2019. Conclusions Although admissions relating to suicidality decreased during the pandemic, the rising number of patients admitted with a first suicide attempt may be an early indicator for an upcoming extra burden on public mental health (and care). Being a multifactorial process, suicidality is influenced in several ways; low in-patient admissions of patients who are suicidal could also reflect fear of contagion and related uncertainty about seeking mental healthcare

Inflexible social inference in individuals with subclinical persecutory delusional tendencie

It has been suspected that abnormalities in social inference (e.g., learning others’ intentions) play a key role in the formation of persecutory delusions (PD). In this study, we examined the association between subclinical PD and social inference, testing the prediction that proneness to PD is related to altered social inference and beliefs about others’ intentions. We included 151 participants scoring on opposite ends of Freeman’s Paranoia Checklist (PCL). The participants performed a probabilistic advice-taking task with a dynamically changing social context (volatility) under one of two experimental frames. These frames differentially emphasized possible reasons behind unhelpful advice: (i) the adviser’s possible intentions (dispositional frame) or (ii) the rules of the game (situational frame). Our design was thus 2x2 factorial (high vs. low delusional tendencies, dispositional vs. situational frame). We found significant group-by- frame interactions, indicating that in the situational frame high PCL scorers took advice less into account than low scorers. Additionally, high PCL scorers believed more frequently that incorrect advice was delivered intentionally and that such misleading behaviour was directed towards them personally. Overall, our results suggest that social inference in individuals with subclinical PD tendencies is shaped by negative prior beliefs about the intentions of others and is thus less sensitive to the attributional framing of adviser-related information. These findings may help future attempts of identifying individuals at risk for developing psychosis and understanding persecutory delusions in psychosis

Inflexible social inference in individuals with subclinical persecutory delusional tendencies

It has been suspected that abnormalities in social inference (e.g., learning others' intentions) play a key role in the formation of persecutory delusions (PD). In this study, we examined the association between subclinical PD and social inference, testing the prediction that proneness to PD is related to altered social inference and beliefs about others' intentions. We included 151 participants scoring on opposite ends of Freeman's Paranoia Checklist (PCL). The participants performed a probabilistic advice-taking task with a dynamically changing social context (volatility) under one of two experimental frames. These frames differentially emphasised possible reasons behind unhelpful advice: (i) the adviser's possible intentions (dispositional frame) or (ii) the rules of the game (situational frame). Our design was thus 2 × 2 factorial (high vs. low delusional tendencies, dispositional vs. situational frame). We found significant group-by-frame interactions, indicating that in the situational frame high PCL scorers took advice less into account than low scorers. Additionally, high PCL scorers believed more frequently that incorrect advice was delivered intentionally and that such misleading behaviour was directed towards them personally. Overall, our results suggest that social inference in individuals with subclinical PD tendencies is shaped by negative prior beliefs about the intentions of others and is thus less sensitive to the attributional framing of adviser-related information. These findings may help future attempts of identifying individuals at risk for developing psychosis and understanding persecutory delusions in psychosis

NeuroPharm study: EEG wakefulness regulation as a biomarker in MDD

While several electroencephalogram (EEG)-based biomarkers have been proposed as diagnostic or predictive tools in major depressive disorder (MDD), there is a clear lack of replication studies in this field. Markers that link clinical features such as disturbed wakefulness regulation in MDD with neurophysiological patterns are particularly promising candidates for e.g., EEG-informed choices of antidepressive treatment. We investigate if we in an independent MDD sample can replicate abnormal findings of EEG-vigilance regulation during rest and as a predictor for antidepressive treatment response. EEG-resting state was recorded in 91 patients and 35 healthy controls from the NeuroPharm trial. EEG-vigilance was assessed using the Vigilance Algorithm Leipzig (VIGALL). We compared the vigilance regulation during rest between patients and healthy controls and between remitters/responders and non-remitters/non-responders after eight weeks of SSRI/SNRI treatment using two different sets of response criteria (NeuroPharm and iSPOT-D). We replicated previous findings showing hyperstable EEG-wakefulness regulation in patients in comparison to healthy subjects. Responders defined by the iSPOT-D criteria showed a higher propensity toward low vigilance stages in comparison to patients with no response at pretreatment, however, this did not apply when using the NeuroPharm criteria. EEG-wakefulness regulation patterns normalized toward patterns of healthy controls after 8 weeks of treatment. This replication study supports the diagnostic value of EEG-vigilance regulation and its usefulness as a biomarker for the choice of treatment in MDD