No abstract

An accurate detection of individuals at clinical high risk (CHR) for psychosis is a prerequisite for effective preventive interventions. Several psychometric interviews are available, but their prognostic accuracy is unknown. We conducted a prognostic accuracy meta-analysis of psychometric interviews used to examine referrals to high risk services. The index test was an established CHR psychometric instrument used to identify subjects with and without CHR (CHR1 and CHR2). The reference index was psychosis onset over time in both CHR1 and CHR2 subjects. Data were analyzed with MIDAS (STATA13). Area under the curve (AUC), summary receiver operating characteristic curves, quality assessment, likelihood ratios, Fagan's nomogram and probability modified plots were computed. Eleven independent studies were included, with a total of 2,519 help-seeking, predominately adult subjects (CHR1: N51,359; CHR2: N51,160) referred to high risk services. The mean follow-up duration was 38 months. The AUC was excellent (0.90; 95% CI: 0.87-0.93), and comparable to other tests in preventive medicine, suggesting clinical utility in subjects referred to high risk services. Meta-regression analyses revealed an effect for exposure to antipsychotics and no effects for type of instrument, age, gender, follow-up time, sample size, quality assessment, proportion of CHR1 subjects in the total sample. Fagan's nomogram indicated a low positive predictive value (5.74%) in the general non-help-seeking population. Albeit the clear need to further improve prediction of psychosis, these findings support the use of psychometric prognostic interviews for CHR as clinical tools for an indicated prevention in subjects seeking help at high risk services worldwide.

This online individualized risk calculator can be of clinical usefulness for the transdiagnostic prediction of psychosis in secondary mental health care. The risk calculator can help to identify those patients at risk of developing psychosis who require an ARMS assessment and specialized care. The use of this calculator may eventually facilitate the implementation of an individualized provision of preventive focused interventions and improve outcomes of first episode psychosis.

Background:The individual risk of developing psychosis after being tested for clinical high-risk (CHR) criteria (posttest risk of psychosis) depends on the underlying risk of the disease of the population from which the person is selected (pretest risk of psychosis), and thus on recruitment strategies. Yet, the impact of recruitment strategies on pretest risk of psychosis is unknown.Methods:Meta-analysis of the pretest risk of psychosis in help-seeking patients selected to undergo CHR assessment: total transitions to psychosis over the pool of patients assessed for potential risk and deemed at risk (CHR+) or not at risk (CHR−). Recruitment strategies (number of outreach activities per study, main target of outreach campaign, and proportion of self-referrals) were the moderators examined in meta-regressions.Results:11 independent studies met the inclusion criteria, for a total of 2519 (CHR+: n = 1359; CHR−: n = 1160) help-seeking patients undergoing CHR assessment (mean follow-up: 38 months). The overall meta-analytical pretest risk for psychosis in help-seeking patients was 15%, with high heterogeneity (95% CI: 9%–24%, I 2 = 96, P < .001). Recruitment strategies were heterogeneous and opportunistic. Heterogeneity was largely explained by intensive (n = 11, β = −.166, Q = 9.441, P = .002) outreach campaigns primarily targeting the general public (n = 11, β = −1.15, Q = 21.35, P < .001) along with higher proportions of self-referrals (n = 10, β = −.029, Q = 4.262, P = .039), which diluted pretest risk for psychosis in patients undergoing CHR assessment.Conclusions:There is meta-analytical evidence for overall risk enrichment (pretest risk for psychosis at 38monhts = 15%) in help-seeking samples selected for CHR assessment as compared to the general population (pretest risk of psychosis at 38monhts=0.1%). Intensive outreach campaigns predominantly targeting the general population and a higher proportion of self-referrals diluted the pretest risk for psychosis.

No abstract

Significant risk enrichment occurs before individuals are assessed for a suspected CHR state. Race/ethnicity and source of referral are associated with pretest risk enrichment in individuals undergoing CHR assessment. A stratification model can identify individuals at differential pretest risk of psychosis. Identification of these subgroups may inform outreach campaigns and subsequent testing and eventually optimize psychosis prediction.

Among UHR patients, persistence or recurrence of non-psychotic comorbid mental disorders, mostly affective disorders, is associated with 6-year poor functional outcomes.

Major depression is associated with a 4-fold increased risk for premature death, largely accounted by cardiovascular disease (CVD). The relationship between depression and CVD is thought to be mediated by the so-called metabolic syndrome (MeS). Epidemiological studies have consistently demonstrated a co-occurrence of depression with MeS components, ie, visceral obesity, dyslipidemia, insulin resistance, and hypertension. Although the exact mechanisms linking MeS to depression are unclear, different hypotheses have been put forward. On the one hand, MeS could be the hallmark of the unhealthy lifestyle habits of depressed patients. On the other, MeS and depression might share common alterations of the stress system, including the hypothalamus-pituitary-adrenal (HPA) axis, the autonomic nervous system, the immune system, and platelet and endothelial function. Both the conditions induce a low grade chronic inflammatory state that, in turn, leads to increased oxidative and nitrosative (O&NS) damage of neurons, pancreatic cells, and endothelium. Recently, neurobiological research revealed that peripheral hormones, such as leptin and ghrelin, which are classically involved in homeostatic energy balance, may play a role in mood regulation. Metabolic risk should be routinely assessed in depressed patients and taken into account in therapeutic decisions. Alternative targets should be considered for innovative antidepressant agents, including cytokines and their receptors, intracellular inflammatory mediators, glucocorticoids receptors, O&NS pathways, and peripheral mediators.