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Treatment with antipsychotics is associated with an increased risk of type 2 diabetes mellitus (T2D), and increased levels of inflammatory biomarkers are present in patients with T2D. We previously demonstrated that the glucagon-like peptide-1 receptor agonist liraglutide significantly reduced glucometabolic disturbances and body weight in prediabetic, overweight/obese schizophrenia-spectrum disorder patients treated with clozapine or olanzapine. This study aims to assess the involvement of cytokines in the therapeutic effects of liraglutide.
Serum concentrations of 10 cytokines (interferon-γ [IFN-γ], tumor necrosis factor-α, interleukin 1β [IL-1β], IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, and IL-13) from fasting prediabetic and normal glucose-tolerant (NGT) patients with schizophrenia-spectrum disorders were measured using multiplexed immunoassays. Prediabetic patients were randomized to 16 weeks of treatment with liraglutide or placebo, and cytokines were measured again at the end of the treatment.
IFN-γ (1.98 vs 1.17 pg/ml, P = .001), IL-4 (0.02 vs 0.01 pg/ml, P < .001), and IL-6 (0.73 vs 0.46 pg/ml, P < .001) were significantly higher in prediabetic (n = 77) vs NGT patients (n = 31). No significant changes in cytokine levels following treatment with liraglutide (n = 37) vs placebo (n = 40) were found.
Prediabetic vs NGT patients with schizophrenia treated with clozapine or olanzapine had increased serum levels of several proinflammatory cytokines, further substantiating the link between inflammation and T2D. Treatment with liraglutide did not affect the investigated cytokines. Further testing of these findings in larger numbers of individuals is needed.
Quality of life (QoL) measures are increasingly recognized as necessary parts of outcome assessments in psychosis. The present paper is a comprehensive study of patients with first-episode psychosis where QoL is measured by the commonly used Lehman Quality of Life Interview (L-QoLI). The aim is to examine if the L-QoLI maintain its original structure when used in a group of patients with first-episode psychosis, and to investigate what determines global subjective QoL with a specific emphasis on premorbid adjustment, duration of untreated psychosis (DUP) and clinical symptoms. The study indicates that the psychometric properties of the L-QoLI do not change significantly when used in first-episode samples. The patients report subjective and objective QoL in the fair to good range, with only a moderate association between the objective and subjective measures. Poor global satisfaction is predicted by being single, abusing drugs, being depressed, having a diagnosis of psychotic affective disorder, having poor premorbid social adjustment and DUP over 10 weeks. The study supports the notion that patients with first-episode psychosis construct QoL in the same way as other groups, and that longer durations of compromised function at this stage produces poor satisfaction with life rather than a downward readjustment of expectations.
During the last decades we have seen a new focus on early treatment of psychosis. Several reviews have shown that duration of untreated psychosis (DUP) is correlated to better outcome. However, it is still unknown whether early treatment will lead to a better long term outcome. This study reports the effects of reducing DUP on 5-year course and outcome.
During 1997-2000 a total of 281 consecutive patients aged > 17 years with first episode non-affective psychosis were recruited of which 192 participated in the 5-year follow-up. A comprehensive early detection (ED) program with public information campaigns and low-threshold psychosis detection teams was established in one health-care area (ED-area), but not in a comparable area (No-ED area). Both areas ran equivalent treatment programs during the first 2 years and need-adapted treatment thereafter.
At the start of treatment ED-patients had shorter DUP and less symptoms than No-ED-patients. There were no significant differences in treatment (psychotherapy and medication) for the 5 years. Mixed-effects modeling showed better scores for the ED-group on PANSS negative, depressive and cognitive factors and for GAF social functioning at 5 year follow-up. The ED-group also had more contacts with friends. Regression analysis did not find that these differences could be explained by confounders.
Early treatment had positive effects on clinical and functional status at 5 year follow-up in first episode psychosis.
Two common approaches to identify subgroups of patients with bipolar disorder are clustering methodology (mixture analysis) based on the age of onset, and a birth cohort analysis. This study investigates if a birth cohort effect will influence the results of clustering on the age of onset, using a large, international database.
The database includes 4037 patients with a diagnosis of bipolar I disorder, previously collected at 36 collection sites in 23 countries. Generalized estimating equations (GEE) were used to adjust the data for country median age, and in some models, birth cohort. Model-based clustering (mixture analysis) was then performed on the age of onset data using the residuals. Clinical variables in subgroups were compared.
There was a strong birth cohort effect. Without adjusting for the birth cohort, three subgroups were found by clustering. After adjusting for the birth cohort or when considering only those born after 1959, two subgroups were found. With results of either two or three subgroups, the youngest subgroup was more likely to have a family history of mood disorders and a first episode with depressed polarity. However, without adjusting for birth cohort (three subgroups), family history and polarity of the first episode could not be distinguished between the middle and oldest subgroups.
These results using international data confirm prior findings using single country data, that there are subgroups of bipolar I disorder based on the age of onset, and that there is a birth cohort effect. Including the birth cohort adjustment altered the number and characteristics of subgroups detected when clustering by age of onset. Further investigation is needed to determine if combining both approaches will identify subgroups that are more useful for research.
Few studies have examined rate and predictors of self-harm in discharged psychiatric patients.
To investigate the rate, coding, timing, predictors and characteristics of self-harm induced somatic admission after discharge from psychiatric acute admission.
Cohort study of 2827 unselected patients consecutively admitted to a psychiatric acute ward during three years. Mean observation period was 2.3 years. Combined register linkage and manual data examination. Cox regression was used to investigate covariates for time to somatic admission due to self-harm, with covariates changing during follow-up entered time dependently.
During the observation period, 10.5% of the patients had 792 somatic self-harm admissions. Strongest risk factors were psychiatric admission due to non-suicidal self-harm, suicide attempt and suicide ideation. The risk was increased throughout the first year of follow-up, during readmission, with increasing outpatient consultations and in patients diagnosed with recurrent depression, personality disorders, substance use disorders and anxiety/stress-related disorders. Only 49% of the somatic self-harm admissions were given hospital self-harm diagnosis.
Self-harm induced somatic admissions were highly prevalent during the first year after discharge from acute psychiatric admission. Underdiagnosing of self-harm in relation to somatic self-harm admissions may cause incorrect follow-up treatments and unreliable register data.
Evidence based treatment of schizophrenia as well as antipsychotic drug utility patterns have changed considerably in recent years and the present study aims to investigate the current level of unplanned hospital readmissions in a cohort of patients with schizophrenia, and to determine the risk-reducing effects of current antipsychotic drug treatment.
An open cohort study included all consecutively discharged patients with schizophrenia in a 3-year period (n = 277). The treatment-dependent variables were entered in a multivariate Cox survival analyses with time to unplanned readmission as the dependent variable.
11.2% of patients were readmitted within 30days of discharge, and 44.8% were readmitted within 12months. Antipsychotic monotherapy reduced the risk of readmission by 74.9%. Treatment in CMHC also had a risk-reducing effect. The prescription rate of clozapine in this sample was 10.1%.
The over-all level of unplanned readmissions was in correspondence with the findings of others. Current antipsychotic drug treatment independently offers strong protection against unplanned readmissions. There may be a potential for further optimalizing antipsychotic drug treatment according to treatment guidelines.
Unplanned readmissions are very common for patients with schizophrenia but antipsychotic drug treatment is associated with a strong risk-reducing effect in this regard.
Antipsychotic maintenance treatment for patients with schizophrenia has been demonstrated to be the single most important modifiable factor to prevent unplanned readmissions. Effectiveness studies have indicated different risk for drug discontinuation between current antipsychotics.
Objectives & aims
To evaluate time until discontinuation of antipsychotic treatment, and specifically to investigate if differences between the prescribed antipsychotics could be detected.
396 patients with schizophrenia were included in an open cohort study and followed through treatment until all antipsychotics prescribed at inclusion were discontinued, predictors for time to discontinuation were analysed with univariate and multivariate Cox survival analyses with time until discontinuation as the dependent variable and antipsychotic monotherapy as the predictor variable. The analysis was controlled for common confounders.
65.7% of the patients were men, mean age was 42.4 years, and 12.9% were first-episode patients. 287 were prescribed antipsychotic monotherapy. In the multivariate Cox analysis with time to all-cause discontinuation only clozapine was significant different from olanzapine, Adjusted Hazard Rate (AHR) 0.17 (0.07,0.45) (p = 0.0003), this was also the case for the prediction of time to clinician-decided discontinuation, AHR (0.20 (0.06,0.70) (p = 0.012). In the analysis with time to patient-decided discontinuation as the dependent variable also Second Generation Antipsychotic Long-Acting Injectables (LAI) (AHR 0.26 (0.09,0.77) (p = 0.015) and First Generation Antipsychotic (LAI) (AHR 0.35 (0.16,0.80) (p = 0.013) had significant lower risk for discontinuation.
Clinicians and patients discontinued clozapine at a lower rate than olanzapine, patients also discontinued LAI formulations at a lower rate than olanzapine.
The use of coercion raises ethical dilemmas, as it deprives patients of their autonomy. In Denmark, the subject has gained political attention, and decreases in the use of coercion are demanded. In the attempt of reducing the use of coercion, it is of interest to obtain more knowledge about the circumstances bound to it.
The aim of this study was to investigate a possible correlation between the incidence of mechanical restraint (MR), and staffing level, staff demographics, patient characteristics, type of shift (day/evening/night) and change of shifts.
A naturalistic descriptive method was used to study cases of mechanical restraint in patients admitted to a psychiatric ward. In the study period of one year, 114 cases of MR were carried out. In 66% of cases, the patient was diagnosed with borderline personality disorder. Each case of MR was obtained from Statens Serum Institut's Electronic Reporting System. The care workers from each shift were identified using duty rosters. The statistical package SPSS version 20 was used for data processing, including a logistic regression analysis.
A significant association was found between the use of MR and the presence of male care workers on the ward, OR = 1.639, 95% CI: 1.163–2.311, P = 0.005. The risk of MR is increased during evening shifts, compared to day and night shifts, OR = 1.868, 95% CI: 1.165–2.995, P = 0.009. No significant associations were found between MR and staffing level, age, education, or experience of care workers.
Disclosure of interest
The authors have not supplied their declaration of competing interest.
Both blood- and milk-based biomarkers have been analysed for decades in research settings, although often only in one herd, and without focus on the variation in the biomarkers that are specifically related to herd or diet. Biomarkers can be used to detect physiological imbalance and disease risk and may have a role in precision livestock farming (PLF). For use in PLF, it is important to quantify normal variation in specific biomarkers and the source of this variation. The objective of this study was to estimate the between- and within-herd variation in a number of blood metabolites (β-hydroxybutyrate (BHB), non-esterified fatty acids, glucose and serum IGF-1), milk metabolites (free glucose, glucose-6-phosphate, urea, isocitrate, BHB and uric acid), milk enzymes (lactate dehydrogenase and N-acetyl-β-D-glucosaminidase (NAGase)) and composite indicators for metabolic imbalances (Physiological Imbalance-index and energy balance), to help facilitate their adoption within PLF. Blood and milk were sampled from 234 Holstein dairy cows from 6 experimental herds, each in a different European country, and offered a total of 10 different diets. Blood was sampled on 2 occasions at approximately 14 days-in-milk (DIM) and 35 DIM. Milk samples were collected twice weekly (in total 2750 samples) from DIM 1 to 50. Multilevel random regression models were used to estimate the variance components and to calculate the intraclass correlations (ICCs). The ICCs for the milk metabolites, when adjusted for parity and DIM at sampling, demonstrated that between 12% (glucose-6-phosphate) and 46% (urea) of the variation in the metabolites’ levels could be associated with the herd-diet combination. Intraclass Correlations related to the herd-diet combination were generally higher for blood metabolites, from 17% (cholesterol) to approximately 46% (BHB and urea). The high ICCs for urea suggest that this biomarker can be used for monitoring on herd level. The low variance within cow for NAGase indicates that few samples would be needed to describe the status and potentially a general reference value could be used. The low ICC for most of the biomarkers and larger within cow variation emphasises that multiple samples would be needed - most likely on the individual cows - for making the biomarkers useful for monitoring. The majority of biomarkers were influenced by parity and DIM which indicate that these should be accounted for if the biomarker should be used for monitoring.
Analysis of human remains and a copper band found in the center of a Late Archaic (ca. 5000–3000 cal BP) shell ring demonstrate an exchange network between the Great Lakes and the coastal southeast United States. Similarities in mortuary practices suggest that the movement of objects between these two regions was more direct and unmediated than archaeologists previously assumed based on “down-the-line” models of exchange. These findings challenge prevalent notions that view preagricultural Native American communities as relatively isolated from one another and suggest instead that wide social networks spanned much of North America thousands of years before the advent of domestication.
Paediatric hearing loss rates in Ghana are currently unknown.
A cross-sectional study was conducted in peri-urban Kumasi, Ghana; children (aged 3–15 years) were recruited from randomly selected households. Selected children underwent otoscopic examination prior to in-community pure tone screening using the portable ShoeBox audiometer. The LittlEars auditory questionnaire was also administered to caregivers and parents.
Data were collected from 387 children. After conditioning, 362 children were screened using monaural pure tones presented at 25 dB. Twenty-five children could not be conditioned to behavioural audiometric screening. Eight children were referred based on audiometric screening results. Of those, four were identified as having hearing loss. Four children scored less than the maximum mark of 35 on the LittleEars questionnaire. Of those, three had hearing loss as identified through pure tone screening. The predominant physical finding on otoscopy was ear canal cerumen impaction.
Paediatric hearing loss is prevalent in Ghana, and should be treated as a public health problem warranting further evaluation and epidemiology characterisation.
To assess variability in antimicrobial use and associations with infection testing in pediatric ventilator-associated events (VAEs).
Descriptive retrospective cohort with nested case-control study.
Pediatric intensive care units (PICUs), cardiac intensive care units (CICUs), and neonatal intensive care units (NICUs) in 6 US hospitals.
Children≤18 years ventilated for≥1 calendar day.
We identified patients with pediatric ventilator-associated conditions (VACs), pediatric VACs with antimicrobial use for≥4 days (AVACs), and possible ventilator-associated pneumonia (PVAP, defined as pediatric AVAC with a positive respiratory diagnostic test) according to previously proposed criteria.
Among 9,025 ventilated children, we identified 192 VAC cases, 43 in CICUs, 70 in PICUs, and 79 in NICUs. AVAC criteria were met in 79 VAC cases (41%) (58% CICU; 51% PICU; and 23% NICU), and varied by hospital (CICU, 20–67%; PICU, 0–70%; and NICU, 0–43%). Type and duration of AVAC antimicrobials varied by ICU type. AVAC cases in CICUs and PICUs received broad-spectrum antimicrobials more often than those in NICUs. Among AVAC cases, 39% had respiratory infection diagnostic testing performed; PVAP was identified in 15 VAC cases. Also, among AVAC cases, 73% had no associated positive respiratory or nonrespiratory diagnostic test.
Antimicrobial use is common in pediatric VAC, with variability in spectrum and duration of antimicrobials within hospitals and across ICU types, while PVAP is uncommon. Prolonged antimicrobial use despite low rates of PVAP or positive laboratory testing for infection suggests that AVAC may provide a lever for antimicrobial stewardship programs to improve utilization.
Improving milk nitrogen efficiency through a reduction of CP supply without detrimental effect on productivity requires usage of feeding systems estimating both the flows of digestible protein, the exported true proteins and from these predict milk protein yield (MPY). Five feeding systems were compared in their ability to predict MPY v. observed MPY in two studies where either protein supply or protein and energy supply were changed. The five feedings systems were: Cornell Net Carbohydrate and Protein System (v6.5.5), Dutch protein evaluation system (1991 and 2007), Institut National de la Recherche Agronomique in France (INRA), National Research Council and NorFor. The key characteristic of the systems with the best predicted MPY was the inclusion of a variable efficiency of utilisation of protein supply taking into account the supply of both protein and energy. The systems still using a fixed efficiency had the highest slope bias in their prediction of MPY. Therefore, the development of new feeding systems or improvement of existing systems should include a variable efficiency of utilisation of the protein related to both the protein and energy supply. The limitation of the current comparison did not allow determining if additional factors, as used in INRA, were beneficial. This concept should also probably be transferred to essential amino acids.
Unbalanced metabolic status in the weeks after calving predisposes dairy cows to metabolic and infectious diseases. Blood glucose, IGF-I, non-esterified fatty acids (NEFA) and β-hydroxybutyrate (BHB) are used as indicators of the metabolic status of cows. This work aims to (1) evaluate the potential of milk mid-IR spectra to predict these blood components individually and (2) to evaluate the possibility of predicting the metabolic status of cows based on the clustering of these blood components. Blood samples were collected from 241 Holstein cows on six experimental farms, at days 14 and 35 after calving. Blood samples were analyzed by reference analysis and metabolic status was defined by k-means clustering (k=3) based on the four blood components. Milk mid-IR analyses were undertaken on different instruments and the spectra were harmonized into a common standardized format. Quantitative models predicting blood components were developed using partial least squares regression and discriminant models aiming to differentiate the metabolic status were developed with partial least squares discriminant analysis. Cross-validations were performed for both quantitative and discriminant models using four subsets randomly constituted. Blood glucose, IGF-I, NEFA and BHB were predicted with respective R2 of calibration of 0.55, 0.69, 0.49 and 0.77, and R2 of cross-validation of 0.44, 0.61, 0.39 and 0.70. Although these models were not able to provide precise quantitative values, they allow for screening of individual milk samples for high or low values. The clustering methodology led to the sharing out of the data set into three groups of cows representing healthy, moderately impacted and imbalanced metabolic status. The discriminant models allow to fairly classify the three groups, with a global percentage of correct classification up to 74%. When discriminating the cows with imbalanced metabolic status from cows with healthy and moderately impacted metabolic status, the models were able to distinguish imbalanced group with a global percentage of correct classification up to 92%. The performances were satisfactory considering the variables are not present in milk, and consequently predicted indirectly. This work showed the potential of milk mid-IR analysis to provide new metabolic status indicators based on individual blood components or a combination of these variables into a global status. Models have been developed within a standardized spectral format, and although robustness should preferably be improved with additional data integrating different geographic regions, diets and breeds, they constitute rapid, cost-effective and large-scale tools for management and breeding of dairy cows.
Avian influenza virus (AIV) subtypes H5 and H7 can infect poultry causing low pathogenicity (LP) AI, but these LPAIVs may mutate to highly pathogenic AIV in chickens or turkeys causing high mortality, hence H5/H7 subtypes demand statutory intervention. Serological surveillance in the European Union provides evidence of H5/H7 AIV exposure in apparently healthy poultry. To identify the most sensitive screening method as the first step in an algorithm to provide evidence of H5/H7 AIV infection, the standard approach of H5/H7 antibody testing by haemagglutination inhibition (HI) was compared with an ELISA, which detects antibodies to all subtypes. Sera (n = 1055) from 74 commercial chicken flocks were tested by both methods. A Bayesian approach served to estimate diagnostic test sensitivities and specificities, without assuming any ‘gold standard’. Sensitivity and specificity of the ELISA was 97% and 99.8%, and for H5/H7 HI 43% and 99.8%, respectively, although H5/H7 HI sensitivity varied considerably between infected flocks. ELISA therefore provides superior sensitivity for the screening of chicken flocks as part of an algorithm, which subsequently utilises H5/H7 HI to identify infection by these two subtypes. With the calculated sensitivity and specificity, testing nine sera per flock is sufficient to detect a flock seroprevalence of 30% with 95% probability.
To achieve functional but also productive females, we hypothesised that it is possible to modulate acquisition and allocation of animals from different genetic types by varying the main energy source of the diet. To test this hypothesis, we used 203 rabbit females belonging to three genetic types: H (n=66), a maternal line characterised by hyper-prolificacy; LP (n=67), a maternal line characterised by functional hyper-longevity; R (n=79), a paternal line characterised by growth rate. Females were fed with two isoenergetic and isoprotein diets differing in energy source: animal fat (AF) enhancing milk yield; cereal starch (CS) promoting body reserves recovery. Feed intake, weight, perirenal fat thickness (PFT), milk yield and blood traits were controlled during five consecutive reproductive cycles (RCs). Females fed with CS presented higher PFT (+0.2 mm, P<0.05) and those fed AF had higher milk yield (+11.7%, P<0.05). However, the effect of energy source varied with the genetic type and time. For example, R females presented a decrease in PFT at late lactation (−4.3%; P<0.05) significantly higher than that observed for H and LP lines (on av. −0.1%; P>0.05), particularly for those fed with AF. Moreover, LP females fed with AF progressively increased PFT across the RC, whereas those fed with CS increased PFT during early lactation (+7.3%; P<0.05), but partially mobilised it during late lactation (−2.8%; P<0.05). Independently of the diet offered, LP females reached weaning with similar PFT. H females fed with either of the two diets followed a similar trajectory throughout the RC. For milk yield, the effect of energy source was almost constant during the whole experiment, except for the first RC of females from the maternal lines (H and LP). These females yielded +34.1% (P<0.05) when fed with CS during this period. Results from this work indicate that the resource acquisition capacity and allocation pattern of rabbit females is different for each genetic type. Moreover, it seems that by varying the main energy source of the diet it is possible to modulate acquisition and allocation of resources of the different genetic types. However, the response of each one depends on its priorities over time.
Literature suggests an association between loneliness and mortality for both males and females. Yet, the linkage of loneliness to mortality is not thoroughly examined, and need to be replicated with a long follow-up time. This study assessed the association between loneliness and mortality, including associations to gender, in 1363 adult swedes.
This community-based prospective cohort study from the Swedish Lundby Study included 1363 individuals of whom 296 individuals (21.7%) were identified as lonely with use of semi-structured interviews in 1997. The cohort was followed until 2011 and survival analyses were used to estimate the relative risk of death.
Death occurred with an incidence rate of 2.63 per 100 person-years and 2.09 per 100 person-years for lonely and non-lonely individuals, respectively. In crude analysis, loneliness was associated with a significant increased mortality risk of 27% compared with non-lonely individuals [hazard ratio (HR) 1.27; 95% CI 1.01–1.60]. Unadjusted, lonely females had a significant increased risk (HR 1.76; 95% CI 1.31–2.34) and adjusted insignificant increased mortality risk of 27% (HR 1.27; 95% CI 0.92–1.74), compared with non-lonely females. Lonely males were found to have an adjusted significant decreased risk of mortality (HR 0.50; 95% CI 0.32–0.80), compared with non-lonely males.
Findings suggest an association between loneliness and increased risk of mortality and that gender differences may exist, which have not been previously reported. If replicated, our results indicate that loneliness may have differential physical implications in some subgroups. Future studies are needed to further investigate the influence of gender on the relationship.
The spread of African swine fever virus (ASFV) threatens to reach further parts of Europe. In countries with a large swine production, an outbreak of ASF may result in devastating economic consequences for the swine industry. Simulation models can assist decision makers setting up contingency plans. This creates a need for estimation of parameters. This study presents a new analysis of a previously published study. A full likelihood framework is presented including the impact of model assumptions on the estimated transmission parameters. As animals were only tested every other day, an interpretation was introduced to cover the weighted infectiousness on unobserved days for the individual animals (WIU). Based on our model and the set of assumptions, the within- and between-pen transmission parameters were estimated to βw = 1·05 (95% CI 0·62–1·72), βb = 0·46 (95% CI 0·17–1·00), respectively, and the WIU = 1·00 (95% CI 0–1). Furthermore, we simulated the spread of ASFV within a pig house using a modified SEIR-model to establish the time from infection of one animal until ASFV is detected in the herd. Based on a chosen detection limit of 2·55% equivalent to 10 dead pigs out of 360, the disease would be detected 13–19 days after introduction.