Weight change following diagnosis with psychosis: a retrospective cohort study in Greater Manchester, UK.

INTRODUCTION: Weight gain in the months/years after diagnosis/treatment of severe enduring mental illness (SMI) is a major predictor of future diabetes, dysmetabolic profile and increased risk of cardiometabolic diseases. There is limited data on the longer-term profile of weight change in people with a history of SMI and how this may differ between individuals. We here report a retrospective study on weight change over the 5 years following an SMI diagnosis in Greater Manchester UK, an ethnically and culturally diverse community, with particular focus on comparing non-affective psychosis (NAP) vs affective psychosis (AP) diagnoses. METHODS: We undertook an anonymised search in the Greater Manchester Care Record (GMCR). We reviewed the health records of anyone who had been diagnosed for the first time with first episode psychosis, schizophrenia, schizoaffective disorder, delusional disorder (non-affective psychosis = NAP) or affective psychosis (AP). We analysed body mass index (BMI) change in the 5-year period following the first prescription of antipsychotic medication. All individuals had taken an antipsychotic agent for at least 3 months. The 5-year follow-up point was anywhere between 2003 and 2023. RESULTS: We identified 9125 people with the diagnoses above. NAP (n = 5618; 37.3% female) mean age 49.9 years; AP (n = 4131; 60.5% female) mean age 48.7 years. 27.0% of NAP were of non-White ethnicity vs 17.8% of AP individuals. A higher proportion of people diagnosed with NAP were in the highest quintile of social disadvantage 52.4% vs 39.5% for AP. There were no significant differences in baseline BMI profile. In a subsample with HbA1c data (n = 2103), mean HbA1c was higher in NAP at baseline (40.4 mmol/mol in NAP vs 36.7 mmol/mol for AP). At 5-year follow-up, there was similarity in both the overall % of individuals in the obese ≥ 30 kg/m2 category (39.8% NAP vs 39.7% AP), and % progressing from a normal healthy BMI transitioned to obese/overweight BMI (53.6% of NAP vs 55.6% with AP). 43.7% of those NAP with normal BMI remained at a healthy BMI vs 42.7% with AP. At 5-year follow-up for NAP, 83.1% of those with BMI ≥ 30 kg/m2 stayed in this category vs 81.5% of AP. CONCLUSION: The results of this real-world longitudinal cohort study suggest that the changes in BMI with treatment of non-affective psychosis vs bipolar disorder are not significantly different, while 43% maintain a healthy weight in the first 5 years following antipsychotic prescription.

Variability of glucose, insulin, and lipid disturbances in first-episode psychosis: a meta-analysis.

BACKGROUND: First-episode psychosis (FEP) is associated with metabolic alterations. However, it is not known if there is heterogeneity in these alterations beyond what might be expected due to normal individual differences, indicative of subgroups of patients at greater vulnerability to metabolic dysregulation. METHODS: We employed meta-analysis of variance, indexed using the coefficient of variation ratio (CVR), to compare variability of the following metabolic parameters in antipsychotic naïve FEP and controls: fasting glucose, glucose post-oral glucose tolerance test (OGTT), fasting insulin, insulin resistance, haemoglobin A1c (HbA1c), total-cholesterol, low-density lipoprotein (LDL)-cholesterol, high-density lipoprotein (HDL)-cholesterol, and triglycerides. Standardised mean difference in metabolic parameters between groups was also calculated; meta-regression analyses examined physiological/demographic/psychopathological moderators of metabolic change. RESULTS: Twenty-eight studies were analysed (1716 patients, 1893 controls). Variability of fasting glucose [CVR = 1.32; 95% confidence interval (CI) 1.12-1.55; p = 0.001], glucose post-OGTT (CVR = 1.43; 95% CI 1.10-1.87; p = 0.008), fasting insulin (CVR = 1.31; 95% CI 1.09-1.58; p = 0.01), insulin resistance (CVR = 1.34; 95% CI 1.12-1.60; p = 0.001), HbA1c (CVR = 1.18; 95% CI 1.06-1.27; p < 0.0001), total-cholesterol (CVR = 1.15; 95% CI 1.01-1.31; p = 0.03), LDL-cholesterol (CVR = 1.28; 95% CI 1.09-1.50; p = 0.002), and HDL-cholesterol (CVR = 1.15; 95% CI 1.00-1.31; p < 0.05), but not triglycerides, was greater in patients than controls. Mean glucose, glucose post-OGTT, fasting insulin, insulin resistance, and triglycerides were greater in patients; mean total-cholesterol and HDL-cholesterol were reduced in patients. Increased symptom severity and female sex were associated with worse metabolic outcomes. CONCLUSIONS: Patients with FEP present with greater variability in metabolic parameters relative to controls, consistent with a subgroup of patients with more severe metabolic changes compared to others. Understanding determinants of metabolic variability could help identify patients at-risk of developing metabolic syndrome. Female sex and severe psychopathology are associated with poorer metabolic outcomes, with implications for metabolic monitoring in clinical practice.

Brain glucose metabolism in schizophrenia: a systematic review and meta-analysis of 18FDG-PET studies in schizophrenia.

BACKGROUND: Impaired brain metabolism may be central to schizophrenia pathophysiology, but the magnitude and consistency of metabolic dysfunction is unknown. METHODS: We searched MEDLINE, PsychINFO and EMBASE between 01/01/1980 and 13/05/2021 for studies comparing regional brain glucose metabolism using 18FDG-PET, in schizophrenia/first-episode psychosis v. controls. Effect sizes (Hedges g) were pooled using a random-effects model. Primary measures were regional absolute and relative CMRGlu in frontal, temporal, parietal and occipital lobes, basal ganglia and thalamus. RESULTS: Thirty-six studies (1335 subjects) were included. Frontal absolute glucose metabolism (Hedge's g = -0.74 ± 0.54, p = 0.01; I2 = 67%) and metabolism relative to whole brain (g = -0.44 ± 0.34, p = 0.01; I2 = 55%) were lower in schizophrenia v. controls with moderate heterogeneity. Absolute frontal metabolism was lower in chronic (g = -1.18 ± 0.73) v. first-episode patients (g = -0.09 ± 0.88) and controls. Medicated patients showed frontal hypometabolism relative to controls (-1.04 ± 0.26) while metabolism in drug-free patients did not differ significantly from controls. There were no differences in parietal, temporal or occipital lobe or thalamic metabolism in schizophrenia v. controls. Excluding outliers, absolute basal ganglia metabolism was lower in schizophrenia v. controls (-0.25 ± 0.24, p = 0.049; I2 = 5%). Studies identified reporting voxel-based morphometry measures of absolute 18FDG uptake (eight studies) were also analysed using signed differential mapping analysis, finding lower 18FDG uptake in the left anterior cingulate gyrus (Z = -4.143; p = 0.007) and the left inferior orbital frontal gyrus (Z = -4.239; p = 0.02) in schizophrenia. CONCLUSIONS: We report evidence for hypometabolism with large effect sizes in the frontal cortex in schizophrenia without consistent evidence for alterations in other brain regions. Our findings support the hypothesis of hypofrontality in schizophrenia.

Treatment resistance in psychiatry: state of the art and new directions.

Treatment resistance affects 20-60% of patients with psychiatric disorders; and is associated with increased healthcare burden and costs up to ten-fold higher relative to patients in general. Whilst there has been a recent increase in the proportion of psychiatric research focussing on treatment resistance (R2 = 0.71, p < 0.0001), in absolute terms this is less than 1% of the total output and grossly out of proportion to its prevalence and impact. Here, we provide an overview of treatment resistance, considering its conceptualisation, assessment, epidemiology, impact, and common neurobiological models. We also review new treatments in development and future directions. We identify 23 consensus guidelines on its definition, covering schizophrenia, major depressive disorder, bipolar affective disorder, and obsessive compulsive disorder (OCD). This shows three core components to its definition, but also identifies heterogeneity and lack of criteria for a number of disorders, including panic disorder, post-traumatic stress disorder, and substance dependence. We provide a reporting check-list to aid comparisons across studies. We consider the concept of pseudo-resistance, linked to poor adherence or other factors, and provide an algorithm for the clinical assessment of treatment resistance. We identify nine drugs and a number of non-pharmacological approaches being developed for treatment resistance across schizophrenia, major depressive disorder, bipolar affective disorder, and OCD. Key outstanding issues for treatment resistance include heterogeneity and absence of consensus criteria, poor understanding of neurobiology, under-investment, and lack of treatments. We make recommendations to address these issues, including harmonisation of definitions, and research into the mechanisms and novel interventions to enable targeted and personalised therapeutic approaches.

Real-world clinical and cost-effectiveness of community clozapine initiation: mirror cohort study.

BACKGROUND: Clozapine is the only drug licensed for treatment-resistant schizophrenia (TRS) but the real-world clinical and cost-effectiveness of community initiation of clozapine is unclear. AIMS: The aim was to assess the feasibility and cost-effectiveness of community initiation of clozapine. METHOD: This was a naturalistic study of community patients recommended for clozapine treatment. RESULTS: Of 158 patients recommended for clozapine treatment, 88 (56%) patients agreed to clozapine initiation and, of these, 58 (66%) were successfully established on clozapine. The success rate for community initiation was 65.4%; which was not significantly different from that for in-patient initiation (58.82%, χ2(1,88) = 0.47, P = 0.49). Following clozapine initiation, there was a significant reduction in median out-patient visits over 1 year (from 24.00 (interquartile range (IQR) = 14.00-41.00) to 13.00 visits (IQR = 5.00-24.00), P < 0.001), and 2 years (from 47.50 visits (IQR = 24.75-71.00) to 22.00 (IQR = 11.00-42.00), P < 0.001), and a 74.71% decrease in psychiatric hospital bed days (z = -2.50, P = 0.01). Service-use costs decreased (1 year: -£963/patient (P < 0.001); 2 years: -£1598.10/patient (P < 0.001). Subanalyses for community-only initiation also showed significant cost reductions (1 year: -£827.40/patient (P < 0.001); 2 year: -£1668.50/patient (P < 0.001) relative to costs prior to starting clozapine. Relative to before initiation, symptom severity was improved in patients taking clozapine at discharge (median Positive and Negative Syndrome Scale total score: initial visit: 80 (IQR = 71.00-104.00); discharge visit 50.5 (IQR = 44.75-75.00), P < 0.001) and at 2 year follow-up (Health of Nation Outcome Scales total score median initial visit: 13.00 (IQR = 9.00-15.00); 2 year follow-up: 8.00 (IQR = 3.00-13.00), P = 0.023). CONCLUSIONS: These findings indicate that community initiation of clozapine is feasible and is associated with significant reductions in costs, service use and symptom severity.

The efficacy and heterogeneity of antipsychotic response in schizophrenia: A meta-analysis.

The response to antipsychotic treatment in schizophrenia appears to vary, and as such it has been proposed that different subtypes of schizophrenia exist, defined by treatment-response. This has not been formally examined using meta-analysis. Randomised controlled trials comparing placebo and antipsychotics in acute treatment of schizophrenia listed in PubMed, EMBASE and PsycINFO from inception until 30 November 2018 were examined. Relative variability of symptomatic improvement in antipsychotic-treated individuals compared to placebo-treated individuals was quantified using coefficient of variation ratio (CVR). Mean difference in symptom change was quantified using Hedges' g. In addition, individual patient data from two clinical trials was examined in terms of both the distribution of total symptom change, and the variability of individual symptoms and symptom factors. In total, 11,006 articles were identified. Sixty six met inclusion criteria, reporting on 17,202 patients. Compared with placebo, antipsychotic-treated patients demonstrated greater total symptom improvement (g = 0.47, p < 0.001) and reduced variability in symptomatic improvement for total (CVR = 0.86, p < 0.001), positive (CVR = 0.89, p < 0.001), and negative symptoms (CVR = 0.86, p = 0.001). Lower variability in antipsychotic-response relative to placebo was associated with studies published earlier (z = 3.98, p < 0.001), younger patients (z = 3.07, p = 0.002), higher dose treatments (z = -2.62, p = 0.009), and greater mean-difference in symptom-change (z = -5.70, p < 0.001). In the individual patient dataset (N = 522 patients), antipsychotic treated patients did not show significantly increased variability for any individual symptom, and there was no evidence of a bimodal distribution of response. Compared to placebo, antipsychotic treatment shows greater improvement and lower variability of change in total, positive and negative symptoms. This is contrary to the hypothesis that there is a subtype of antipsychotic non-responsive schizophrenia. Instead our findings, provide evidence for a relatively homogeneous effect of antipsychotic treatment in improving symptoms of schizophrenia.

Cardiac structure and function in schizophrenia: cardiac magnetic resonance imaging study.

BACKGROUND: Heart disease is the leading cause of death in schizophrenia. However, there has been little research directly examining cardiac function in schizophrenia. AIMS: To investigate cardiac structure and function in individuals with schizophrenia using cardiac magnetic resonance imaging (CMR) after excluding medical and metabolic comorbidity. METHOD: In total, 80 participants underwent CMR to determine biventricular volumes and function and measures of blood pressure, physical activity and glycated haemoglobin levels. Individuals with schizophrenia ('patients') and controls were matched for age, gender, ethnicity and body surface area. RESULTS: Patients had significantly smaller indexed left ventricular (LV) end-diastolic volume (effect size d = -0.82, P = 0.001), LV end-systolic volume (d = -0.58, P = 0.02), LV stroke volume (d = -0.85, P = 0.001), right ventricular (RV) end-diastolic volume (d = -0.79, P = 0.002), RV end-systolic volume (d = -0.58, P = 0.02), and RV stroke volume (d = -0.87, P = 0.001) but unaltered ejection fractions relative to controls. LV concentricity (d = 0.73, P = 0.003) and septal thickness (d = 1.13, P < 0.001) were significantly larger in the patients. Mean concentricity in patients was above the reference range. The findings were largely unchanged after adjusting for smoking and/or exercise levels and were independent of medication dose and duration. CONCLUSIONS: Individuals with schizophrenia show evidence of concentric cardiac remodelling compared with healthy controls of a similar age, gender, ethnicity, body surface area and blood pressure, and independent of smoking and activity levels. This could be contributing to the excess cardiovascular mortality observed in schizophrenia. Future studies should investigate the contribution of antipsychotic medication to these changes.

Inflammatory markers in depression: A meta-analysis of mean differences and variability in 5,166 patients and 5,083 controls.

IMPORTANCE: The magnitude and variability of cytokine alterations in depression are not clear. OBJECTIVE: To perform an up to date meta-analysis of mean differences of immune markers in depression, and to quantify and test for evidence of heterogeneity in immune markers in depression by conducting a meta-analysis of variability to ascertain whether only a sub-group of patients with depression show evidence of inflammation. DATA SOURCES: Studies that reported immune marker levels in peripheral blood in patients with depression and matched healthy controls in the MEDLINE database from inception to August 29th 2018 were examined. STUDY SELECTION: Case-control studies that reported immune marker levels in peripheral blood in patients with depression and healthy controls were selected. DATA EXTRACTION AND SYNTHESIS: Means and variances (SDs) were extracted for each measure to calculate effect sizes, which were combined using multivariate meta-analysis. MAIN OUTCOMES AND MEASURES: Hedges g was used to quantify mean differences. Relative variability of immune marker measurements in patients compared with control groups as indexed by the coefficient of variation ratio (CVR). RESULTS: A total of 107 studies that reported measurements from 5,166 patients with depression and 5,083 controls were included in the analyses. Levels of CRP (g = 0.71; 95%CI: 0.50-0.92; p < 0.0001); IL-3 (g = 0.60; 95%CI: 0.31-0.89; p < 0.0001); IL-6 (g = 0.61; 95%CI: 0.39-0.82; p < 0.0001); IL-12 (g = 1.18; 95%CI: 0.74-1.62; p < 0.0001); IL-18 (g = 1.97; 95%CI: 1.00-2.95; p < 0.0001); sIL-2R (g = 0.71; 95%CI: 0.44-0.98; p < 0.0001); and TNFα (g = 0.54; 95%CI: 0.32-0.76; p < 0.0001) were significantly higher in patients with depression. These findings were robust to a range of potential confounds and moderators. Mean-scaled variability, measured as CVR, was significantly lower in patients with depression for CRP (CVR = 0.85; 95%CI: 0.75-0.98; p = 0.02); IL-12 (CVR = 0.61; 95%CI: 0.46-0.80; p < 0.01); and sIL-2R (CVR = 0.85; 95%CI: 0.73-0.99; p = 0.04), while it was unchanged for IL-3, IL-6, IL-18, and TNF α. CONCLUSIONS AND RELEVANCE: Depression is confirmed as a pro-inflammatory state. Some of the inflammatory markers elevated in depression, including CRP and IL-12, show reduced variability in patients with depression, therefore supporting greater homogeneity in terms of an inflammatory phenotype in depression. Some inflammatory marker elevations in depression do not appear due to an inflamed sub-group, but rather to a right shift of the immune marker distribution.

Is psychosis a multisystem disorder? A meta-review of central nervous system, immune, cardiometabolic, and endocrine alterations in first-episode psychosis and perspective on potential models.

People with psychotic disorders show abnormalities in several organ systems in addition to the central nervous system (CNS); and this contributes to excess mortality. However, it is unclear how strong the evidence is for alterations in non-CNS systems at the onset of psychosis, how the alterations in non-CNS systems compare to those in the CNS, or how they relate to symptoms. Here, we consider these questions, and suggest potential models to account for findings. We conducted a systematic meta-review to summarize effect sizes for both CNS (focusing on brain structural, neurophysiological, and neurochemical parameters) and non-CNS dysfunction (focusing on immune, cardiometabolic, and hypothalamic-pituitary-adrenal (HPA) systems) in first-episode psychosis (FEP). Relevant meta-analyses were identified in a systematic search of Pubmed and the methodological quality of these was assessed using the AMSTAR checklist (A Measurement Tool to Assess Systematic Reviews). Case-control data were extracted from studies included in these meta-analyses. Random effects meta-analyses were re-run and effect size magnitudes for individual parameters were calculated, as were summary effect sizes for each CNS and non-CNS system. We also grouped studies to obtain overall effect sizes for non-CNS and CNS alterations. Robustness of data for non-CNS and CNS parameters was assessed using Rosenthal's fail-safe N. We next statistically compared summary effect size for overall CNSand overall non-CNS alterations, as well as for each organ system separately. We also examined how non-CNS alterations correlate CNS alterations, and with psychopathological symptoms. Case-control data were extracted for 165 studies comprising a total sample size of 13,440. For people with first episode psychosis compared with healthy controls, we observed alterations in immune parameters (summary effect size: g = 1.19), cardiometabolic parameters (g = 0.23); HPA parameters (g = 0.68); brain structure (g = 0.40); neurophysiology (g = 0.80); and neurochemistry (g = 0.43). Grouping non-CNS organ systems together provided an effect size for overall non-CNS alterations in patients compared with controls (g = 0.58), which was not significantly different from the overall CNS alterations effect size (g = 0.50). However, the summary effect size for immune alterations was significantly greater than that for brain structural (P < 0.001) and neurochemical alterations (P < 0.001), while the summary effect size for cardiometabolic alterations was significantly lower than neurochemical (P = 0.04), neurophysiological (P < 0.001), and brain structural alterations (P = 0.001). The summary effect size for HPA alterations was not significantly different from brain structural (P = 0.14), neurophysiological (P = 0.54), or neurochemical alterations (P = 0.22). These outcomes remained similar in antipsychotic naive sensitivity analyses. We found some, but limited and inconsistent, evidence that non-CNS alterations were associated with CNS changes and symptoms in first episode psychosis. Our findings indicate that there are robust alterations in non-CNS systems in psychosis, and that these are broadly similar in magnitude to a range of CNS alterations. We consider models that could account for these findings and discuss implications for future research and treatment.

Correction to: Is psychosis a multisystem disorder? A meta-review of central nervous system, immune, cardiometabolic, and endocrine alterations in first-episode psychosis and perspective on potential models.

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Neuroinflammation in schizophrenia: meta-analysis of in vivo microglial imaging studies.

BACKGROUND: Converging lines of evidence implicate an important role for the immune system in schizophrenia. Microglia are the resident immune cells of the central nervous system and have many functions including neuroinflammation, axonal guidance and neurotrophic support. We aimed to provide a quantitative review of in vivo PET imaging studies of microglia activation in patients with schizophrenia compared with healthy controls. METHODS: Demographic, clinical and imaging measures were extracted from each study and meta-analysis was conducted using a random-effects model (Hedge's g). The difference in 18-kDa translocator protein (TSPO) binding between patients with schizophrenia and healthy controls, as quantified by either binding potential (BP) or volume of distribution (VT), was used as the main outcome. Sub-analysis and sensitivity analysis were carried out to investigate the effects of genotype, ligand and illness stage. RESULTS: In total, 12 studies comprising 190 patients with schizophrenia and 200 healthy controls met inclusion criteria. There was a significant elevation in tracer binding in schizophrenia patients relative to controls when BP was used as an outcome measure, (Hedge's g = 0.31; p = 0.03) but no significant differences when VT was used (Hedge's g = -0.22; p = 0.29). CONCLUSIONS: In conclusion, there is evidence for moderate elevations in TSPO tracer binding in grey matter relative to other brain tissue in schizophrenia when using BP as an outcome measure, but no difference when VT is the outcome measure. We discuss the relevance of these findings as well as the methodological issues that may underlie the contrasting difference between these outcomes.

Cholesterol and triglyceride levels in first-episode psychosis: systematic review and meta-analysis.

BackgroundThe extent of metabolic and lipid changes in first-episode psychosis (FEP) is unclear.AimsTo investigate whether individuals with FEP and no or minimal antipsychotic exposure show lipid and adipocytokine abnormalities compared with healthy controls.MethodWe conducted a meta-analysis of studies examining lipid and adipocytokine parameters in individuals with FEP and no or minimal antipsychotic exposure v. a healthy control group. Studies reported fasting total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and leptin levels.ResultsOf 2070 citations retrieved, 20 case-control studies met inclusion criteria including 1167 patients and 1184 controls. Total cholesterol and LDL cholesterol levels were significantly decreased in patients v. controls, corresponding to an absolute reduction of 0.26 mmol/L and 0.15 mmol/L respectively. Triglyceride levels were significantly increased in the patient group, corresponding to an absolute increase of 0.08 mmol/L. However, HDL cholesterol and leptin levels were not altered in patients v. controls.ConclusionsTotal and LDL cholesterol levels are reduced in FEP, indicating that hypercholesterolaemia in patients with chronic disorder is secondary and potentially modifiable. In contrast, triglycerides are elevated in FEP. Hypertriglyceridaemia is a feature of type 2 diabetes mellitus, therefore this finding adds to the evidence for glucose dysregulation in this cohort. These findings support early intervention targeting nutrition, physical activity and appropriate antipsychotic prescription.

Nicotinic Acid Adenine Dinucleotide Phosphate (NAADP) and Endolysosomal Two-pore Channels Modulate Membrane Excitability and Stimulus-Secretion Coupling in Mouse Pancreatic ß Cells.

Pancreatic ß cells are electrically excitable and respond to elevated glucose concentrations with bursts of Ca(2+) action potentials due to the activation of voltage-dependent Ca(2+) channels (VDCCs), which leads to the exocytosis of insulin granules. We have examined the possible role of nicotinic acid adenine dinucleotide phosphate (NAADP)-mediated Ca(2+) release from intracellular stores during stimulus-secretion coupling in primary mouse pancreatic ß cells. NAADP-regulated Ca(2+) release channels, likely two-pore channels (TPCs), have recently been shown to be a major mechanism for mobilizing Ca(2+) from the endolysosomal system, resulting in localized Ca(2+) signals. We show here that NAADP-mediated Ca(2+) release from endolysosomal Ca(2+) stores activates inward membrane currents and depolarizes the ß cell to the threshold for VDCC activation and thereby contributes to glucose-evoked depolarization of the membrane potential during stimulus-response coupling. Selective pharmacological inhibition of NAADP-evoked Ca(2+) release or genetic ablation of endolysosomal TPC1 or TPC2 channels attenuates glucose- and sulfonylurea-induced membrane currents, depolarization, cytoplasmic Ca(2+) signals, and insulin secretion. Our findings implicate NAADP-evoked Ca(2+) release from acidic Ca(2+) storage organelles in stimulus-secretion coupling in ß cells.

Evaluating sustainability: a retrospective cohort analysis of the Oxfordshire therapeutic community.

BACKGROUND: Therapeutic communities (TCs) could reduce the health care use of people with personality disorder (Davies S, Campling P and Ryan K, Psychiatrist 23:79-83, 1999; Barr W, Kirkcaldy A, Horne A, Hodge S, Hellin K and Göpfert M, J Ment Health 19:412-421, 2010) and in turn reduce the financial and environmental costs of services. Our hypothesis is that 3 years following entry to a TC service, patients have reduced subsequent health care use and associated reductions in financial costs and carbon footprint. METHODS: A retrospective 4-year cohort study examined changes in health care use following entry to the Oxfordshire TC service. Comparative analysis was undertaken on a treated (n = 40) and a control group (referred but who declined treatment; n = 45). Financial costs and carbon footprint of health care use were calculated using national tariffs and standard carbon conversion factors. Mean changes in these outcomes were compared over 1, 2 and 3 years and adjusted for costs and carbon footprints in the year prior to joining the TC service. RESULTS: Compared to baseline, the group receiving TC care had greater reductions in financial costs and carbon footprint associated with A&E attendances (p = 0.04) and crisis mental health appointments (p = 0.04) than the control group. There were significantly greater reductions in carbon footprint for all secondary health care use, both physical and mental health care, after 3 years (p = 0.04) in the TC group. CONCLUSIONS: TC services may have the potential to reduce the financial cost and carbon footprint of health care.

Prevalence of multimorbidity in people with and without severe mental illness: a systematic review and meta-analysis.

BACKGROUND: People with severe mental illness, such as schizophrenia-spectrum disorder and bipolar disorder, face poorer health outcomes from multiple chronic illnesses. Physical multimorbidity, the coexistence of two or more chronic physical conditions, and psychiatric multimorbidity, the coexistence of three or more psychiatric disorders, are both emerging concepts useful in conceptualising disease burden. However, the prevalence of physical and psychiatric multimorbidity in this cohort is unknown. This study aimed to estimate the absolute prevalence of both physical and psychiatric multimorbidity in people with severe mental illness, and also compare the odds of physical multimorbidity prevalence against people without severe mental illness. METHODS: We searched CINAHL, EMBASE, PubMed, and PsycINFO from inception until Feb 15, 2024, for observational studies that measured multimorbidity prevalence. To be included, studies had to have an observational study design, be conducted in an adult population (mean age ≥18 years) diagnosed with either schizophrenia-spectrum disorder or bipolar disorder, and include a measurement of occurrence of either physical multimorbidity (≥2 physical health conditions) or psychiatric multimorbidity (≥3 psychiatric conditions total, including the severe mental illness). From control studies, a random-effects meta-analysis compared odds of physical multimorbidity between people with and without severe mental illness. Absolute prevalence of physical and psychiatric multimorbidity in people with severe mental illness was also calculated. Sensitivity and meta-regression analyses tested an array of demographic, diagnostic, and methodological variables. FINDINGS: From 11 144 citations we included 82 observational studies featuring 1 623 773 individuals with severe mental illness (specifically schizophrenia-spectrum disorder or bipolar disorder), of which 21 studies featured 13 235 882 control individuals without severe mental illness (descriptive data for the entire pooled cohorts were not available for numbers of males and females, age, and ethnicity). This study did not feature involvement of people with lived experience. The odds ratio (OR) of physical multimorbidity between people with and without severe mental illness was 2·40 (95% CI 1·57-3·65, k=11, p=0·0009). This ratio was higher in younger severe mental illness populations (mean age ≤40 years, OR 3·99, 95% CI 1·43-11·10) compared with older populations (mean age >40 years, OR 1·55, 95% CI 0·96-2·51; subgroup differences p=0·0013). For absolute prevalence, 25% of those with severe mental illness have physical multimorbidity (95% CI 0·19-0·32, k=29) and 14% have psychiatric multimorbidity (95% CI 0·08-0·23, k=21). INTERPRETATION: This is the first meta-analysis to estimate physical alongside psychiatric multimorbidity prevalence, showing that these are common in people with schizophrenia-spectrum disorder and bipolar disorder. The greater burden of physical multimorbidity in people with severe mental illness compared with those without is higher for younger cohorts, reflecting a need for earlier intervention. Our findings speak to the utility of multimorbidity for characterising the disease burden associated with severe mental illness, and the importance of facilitating integrated physical and mental health care. FUNDING: None.

Comparative physiological effects of antipsychotic drugs in children and young people: a network meta-analysis.

BACKGROUND: The degree of physiological responses to individual antipsychotic drugs is unclear in children and adolescents. With network meta-analysis, we aimed to investigate the effects of various antipsychotic medications on physiological variables in children and adolescents with neuropsychiatric and neurodevelopmental conditions. METHODS: For this network meta-analysis, we searched Medline, EMBASE, PsycINFO, Web of Science, and Scopus from database inception until Dec 22, 2023, and included randomised controlled trials comparing antipsychotics with placebo in children or adolescents younger than 18 years with any neuropsychiatric and neurodevelopmental condition. Primary outcomes were mean change from baseline to end of acute treatment in bodyweight, BMI, fasting glucose, total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, prolactin, heart rate, systolic blood pressure (SBP), and QT interval corrected for heart rate (QTc) for patients receiving either active treatment or placebo. For multigroup trials reporting several doses, we calculated a summary value for each physiological variable for all doses. After transitivity assessment, we fitted frequentist random-effects network meta-analyses for all comparisons in the network. A Kilim plot was used to summarise the results for all treatments and outcomes, providing information regarding the strength of the statistical evidence of treatment effects, using p values. Network heterogeneity was assessed with τ, risk of bias of individual trials was assessed with the Cochrane Collaboration's Tool for Assessing Risk of Bias, and the credibility of findings from each network meta-analysis was assessed with the Confidence in Network Meta-Analysis (CINEMA) app. This study is registered on PROSPERO (CRD42021274393). FINDINGS: Of 6676 studies screened, 47 randomised controlled trials were included, which included 6500 children (mean age 13·29 years, SD 2·14) who received treatment for a median of 7 weeks (IQR 6-8) with either placebo (n=2134) or one of aripiprazole, asenapine, blonanserin, clozapine, haloperidol, lurasidone, molindone, olanzapine, paliperidone, pimozide, quetiapine, risperidone, or ziprasidone (n=4366). Mean differences for bodyweight change gain compared with placebo ranged from -2·00 kg (95% CI -3·61 to -0·39) with molindone to 5·60 kg (0·27 to 10·94) with haloperidol; BMI -0·70 kg/m2 (-1·21 to -0·19) with molindone to 2·03 kg/m2 (0·51 to 3·55) with quetiapine; total cholesterol -0·04 mmol/L (-0·39 to 0·31) with blonanserin to 0·35 mmol/L (0·17 to 0·53) with quetiapine; LDL cholesterol -0·12 mmol/L (-0·31 to 0·07) with risperidone or paliperidone to 0·17 mmol/L (-0·06 to 0·40) with olanzapine; HDL cholesterol 0·05 mmol/L (-0·19 to 0·30) with quetiapine to 0·48 mmol/L (0·18 to 0·78) with risperidone or paliperidone; triglycerides -0·03 mmol/L (-0·12 to 0·06) with lurasidone to 0·29 mmol/L (0·14 to 0·44) with olanzapine; fasting glucose from -0·09 mmol/L (-1·45 to 1·28) with blonanserin to 0·74 mmol/L (0·04 to 1·43) with quetiapine; prolactin from -2·83 ng/mL (-8·42 to 2·75) with aripiprazole to 26·40 ng/mL (21·13 to 31·67) with risperidone or paliperidone; heart rate from -0·20 bpm (-8·11 to 7·71) with ziprasidone to 12·42 bpm (3·83 to 21·01) with quetiapine; SBP from -3·40 mm Hg (-6·25 to -0·55) with ziprasidone to 10·04 mm Hg (5·56 to 14·51) with quetiapine; QTc from -0·61 ms (-1·47 to 0·26) with pimozide to 0·30 ms (-0·05 to 0·65) with ziprasidone. INTERPRETATION: Children and adolescents show varied but clinically significant physiological responses to individual antipsychotic drugs. Treatment guidelines for children and adolescents with a range of neuropsychiatric and neurodevelopmental conditions should be updated to reflect each antipsychotic drug's distinct profile for associated metabolic changes, alterations in prolactin, and haemodynamic alterations. FUNDING: UK Academy of Medical Sciences, Brain and Behaviour Research Foundation, UK National Institute of Health Research, Maudsley Charity, the Wellcome Trust, Medical Research Council, National Institute of Health and Care Research Biomedical Centre at King's College London and South London and Maudsley NHS Foundation Trust, the Italian Ministry of University and Research, the Italian National Recovery and Resilience Plan, and Swiss National Science Foundation.

Problem-based review: The patient with acute adrenal failure.

Acute adrenal crisis is an important condition to consider in any shocked patient presenting to the acute medical unit. This article aims to highlight the key aspects of initial management, focussing on the importance of rapid recognition and prompt initiation of steroid treatment.

Does Slow and Steady Win the Race? Rates of Antipsychotic Discontinuation, Antipsychotic Dose, and Risk of Psychotic Relapse.

BACKGROUND: Antipsychotics are recommended for prevention of relapse in schizophrenia. It is unclear whether increased risk of relapse following antipsychotic discontinuation is predominantly associated with an absolute magnitude of dose reduction or rate of antipsychotic reduction. Establishing the responsible mechanism is important because prolonged withdrawal schedules have been suggested to reduce risk of relapse. STUDY DESIGN: Individual patient data from antipsychotic discontinuation studies were obtained. We estimated the occupancy of receptors over time using half-lives and median effective dose ED50 values obtained from pharmacokinetic and receptor occupancy studies. Hazard ratios for relapse events were calculated using Cox proportional hazards models to assess the influence of formulation (oral, 1-monthly, and 3-monthly injections). The change in hazard ratio over time was estimated, and the effect of time-varying covariates was calculated, including rate of occupancy reduction and absolute receptor occupancy. STUDY RESULTS: Five studies including 1388 participants with schizophrenia were identified (k = 2: oral, k = 2: 1-monthly injection, k = 1: 3-monthly injection). Withdrawal of long-acting injectable medication did not lead to a lower hazard ratio compared with withdrawal of oral medication, and this included the period immediately following randomization. Hazard ratios were not associated with the rate of decline of receptor occupancy; however, they were associated with reduced absolute occupancy in trials of long-acting injections (P = .038). CONCLUSIONS: Antipsychotic discontinuation is associated with an increased risk of psychotic relapse, related to receptor occupancy. Although relapse does not appear to be related to the rate of discontinuation, gradual discontinuation strategies may allow for easier antipsychotic reinstatement in case of symptomatic worsening.

Data-Driven Taxonomy for Antipsychotic Medication: A New Classification System.

BACKGROUND: Globally, there are more than 25 licensed antipsychotic medications. Antipsychotics are commonly described as either typical or atypical, but this dichotomous classification does not reflect the diversity of their pharmacological and clinical profiles. There is a need for a data-driven antipsychotic classification scheme suitable for clinicians and researchers that maps onto both pharmacological and clinical effects. Receptor affinity provides one starting point for such a scheme. METHODS: We analyzed affinities of 27 antipsychotics for 42 receptors from 3325 in vitro receptor binding studies. We used a clustering algorithm to group antipsychotics based on receptor affinity. Using a machine learning model, we examined the ability of this grouping to predict antipsychotic-induced clinical effects quantified according to an umbrella review of clinical trial and treatment guideline data. RESULTS: Clustering resulted in 4 groups of antipsychotics. The predominant receptor affinity and clinical effect "fingerprints" of these 4 groups were defined as follows: group 1, muscarinic (M2-M5) receptor antagonism (cholinergic and metabolic side effects); group 2, dopamine (D2) partial agonism and adrenergic antagonism (overall low side-effect burden); group 3, serotonergic and dopaminergic antagonism (overall moderate side-effect burden); and group 4, dopaminergic antagonism (extrapyramidal side effects and hyperprolactinemia). Groups 1 and 4 were more efficacious than groups 2 and 3. The classification was shown to predict out-of-sample clinical effects of individual drugs. CONCLUSIONS: A receptor affinity-based grouping not only reflects compound pharmacology but also detects meaningful clinical differences. This approach has the potential to benefit both patients and researchers by guiding treatment and informing drug development.