OBJECTIVE: Validated assessment tools are needed to identify clinically high risk for psychosis. This study aimed to validate the early recognition inventory ERIraos, which consists of the ERIraos Checklist for risk screening and the ERIraos Symptom List for a more thorough risk assessment in the Estonian language to detect psychotic prodromal symptoms.
METHODS: A prospective cohort study provided an opportunity to evaluate the characteristics of the ERIraos instrument in predicting the increased risk of a psychotic disorder in the future. The 177 study participants, aged 13-42 years old, were divided into groups without an increased risk and three risk groups with different risk severity levels based on the ERIraos Symptom List assessment.
RESULTS: The results indicated excellent inter-rater reliability for the ERIraos Symptom List total score. The ability of the ERIraos checklist to screen persons with an elevated psychosis risk was very good (ROC-AUC = 0.86). The capability of the ERIraos Symptom List scores to predict the probability of transitioning to psychosis within 2 years was very good (ROC-AUC = 0.83). Brief limited intermittent psychotic symptoms and observable behavioural and affective symptoms were statistically significant predictors of transition to psychosis. There were strong and statistically significant correlations between the ERIraos Symptom List scores and other clinical measures assessing functioning and psychopathology.
CONCLUSIONS: The results of this study demonstrate the reliability and validity of the Estonian version of the ERIraos instrument and support the usability of ERIraos as a two-step tool for the early recognition of psychosis risk.

Formal thought disorder (FThD) is a core feature of psychosis, and its severity and long-term persistence relates to poor clinical outcomes. However, advances in developing early recognition and management tools for FThD are hindered by a lack of insight into the brain-level predictors of FThD states and progression at the individual level.
Two hundred thirty-three individuals with recent-onset psychosis were drawn from the multisite European Prognostic Tools for Early Psychosis Management study. Support vector machine classifiers were trained within a cross-validation framework to separate two FThD symptom-based subgroups (high vs. low FThD severity), using cross-sectional whole-brain multiband fractional amplitude of low frequency fluctuations, gray matter volume and white matter volume data. Moreover, we trained machine learning models on these neuroimaging readouts to predict the persistence of high FThD subgroup membership from baseline to 1-year follow-up.
Cross-sectionally, multivariate patterns of gray matter volume within the salience, dorsal attention, visual, and ventral attention networks separated the FThD severity subgroups (balanced accuracy [BAC] = 60.8%). Longitudinally, distributed activations/deactivations within all fractional amplitude of low frequency fluctuation sub-bands (BACslow-5 = 73.2%, BACslow-4 = 72.9%, BACslow-3 = 68.0%), gray matter volume patterns overlapping with the cross-sectional ones (BAC = 62.7%), and smaller frontal white matter volume (BAC = 73.1%) predicted the persistence of high FThD severity from baseline to follow-up, with a combined multimodal balanced accuracy of BAC = 77%.
We report the first evidence of brain structural and functional patterns predictive of FThD severity and persistence in early psychosis. These findings open up avenues for the development of neuroimaging-based diagnostic, prognostic, and treatment options for the early recognition and management of FThD and associated poor outcomes.

UNASSIGNED: To assess accuracy of early diagnosis, appropriateness and timeliness of response, and clinical outcomes of older general medical inpatients with hospital-acquired sepsis.
UNASSIGNED: Hospital abstracts of inpatient encounters from seven digital Queensland public hospitals between July 2018 and September 2020 were screened retrospectively for diagnoses of hospital-acquired sepsis. Electronic medical records were retrieved and cases meeting selection criteria and classified as confirmed or probable sepsis using pre-specified criteria were included. Investigations and treatments following the first digitally generated alert of clinical deterioration were compared with a best practice sepsis care bundle. Outcome measures comprised 30-day all-cause mortality after deterioration, and unplanned readmissions at 14 days after discharge.
UNASSIGNED: Of the 169 screened care episodes, 59 comprised probable or confirmed cases of sepsis treated by general medicine teams at the time of initial deterioration. Of these, 43 (72.9%) had no mention of sepsis in the differential diagnosis on first medical review, and only 38 (64%) were managed as having sepsis. Each care bundle component of blood cultures, serum lactate, and intravenous fluid resuscitation and antibiotics was only delivered in approximately 30% of cases, and antibiotic administration was delayed more than an hour in 28 of 38 (73.7%) cases.
UNASSIGNED: Early recognition of sepsis and timely implementation of care bundles are challenging in older general medical patients. Education programs in sepsis care standards targeting nurses and junior medical staff, closer patient monitoring, and post-discharge follow-up may improve patient outcomes.

BACKGROUND: Bipolar disorder is one of the most severe mental disorders. Its chronic course is associated with high rates of morbidity and mortality, a high risk of suicide and poor social and occupational outcomes. Despite the great advances over the last decades in understanding mental disorders, the mechanisms underlying bipolar disorder at the neural network level still remain elusive. This has severe consequences for clinical practice, for instance by inadequate diagnoses or delayed treatments. The German research consortium BipoLife aims to shed light on the mechanisms underlying bipolar disorders. It was established in 2015 and incorporates ten university hospitals across Germany. Its research projects focus in particular on individuals at high risk of bipolar disorder, young patients in the early stages of the disease and patients with an unstable highly relapsing course and/or with acute suicidal ideation.
METHODS: Functional and structural magnetic resonance imaging (MRI) data was acquired across nine sites within three different studies. Obtaining neuroimaging data in a multicenter setting requires among others the harmonization of the acquisition protocol, the standardization of paradigms and the implementation of regular quality control procedures. The present article outlines the MRI imaging protocols, the acquisition parameters, the imaging paradigms, the neuroimaging quality assessment procedures and the number of recruited subjects.
CONCLUSIONS: The careful implementation of a MRI study protocol as well as the adherence to well-defined quality assessment procedures is one key benchmark in the evaluation of the overall quality of large-scale multicenter imaging studies. This article contributes to the BipoLife project by outlining the rationale and the design of the MRI study protocol. It helps to set the necessary standards for follow-up analyses and provides the technical details for an in-depth understanding of follow-up publications.

This study aimed to identify the clinical characteristic of prodromal symptoms in Chinese patients with bipolar disorder (BD), prior to the first affective episode. It further aimed to characterize the prodromal traits between bipolar disorder type I (BD-I) and type II (BD-II).
120 individuals with BD-I (n = 92) and BD- II (n = 28) were recruited to the study. Semi-structured interviews were then administered to evaluate prodromal symptoms in patients, within 3 years of BD onset, by using the Bipolar Prodrome Symptom Scale-Retrospective (BPSS-R).
In the prodromal phase of the first depressive episode, patients with BD-II experienced more prodromal symptoms (p = 0.0028) compared to BD-I. Additionally, more frequent predictors were reported in patients with BD-II than BD-I including educational and occupational dysfunction (p = 0.0023), social isolation (p < 0.001), difficulty making decisions (p = 0.0012), oppositionality (p = 0.012), and suspiciousness/persecutory ideas (p = 0.017). There were also differences in the duration of the precursors. The duration of \"weight loss or decrease in appetite\" (p = 0.016) lasted longer in patients with BD-I, while \"obsessions and compulsions\" (p = 0.023) started earlier in patients with BD-II and occurred during the pre-depressive period. The prevalence and duration of each reported prodrome, preceding a first (hypo) manic episode, showed no difference between patients with BD-I and BD-II.
Specific affective, general, or psychotic symptoms occurred prior to both affective episodes. The characteristic of prodromal symptoms were key predictors for later episodes of BD including attenuated mania-like symptoms, subthreshold depressed mood, mood swings/lability, and anxiety. In the pre-depressive state, when compared to BD-II, BD-I presented with more prodromal symptoms in nonspecific dimensions, which indicated the substantial burden of BD-II. In conclusion, this study extends the understanding of the characteristics of prodromes of BD-I and BD-II.

BACKGROUND: Bipolar disorders (BD) belong to the most severe mental disorders, characterized by an early onset and recurrent, severe episodes or a chronic course with poor psychosocial functioning in a proportion of patients. Many patients with BD experience substantial symptomatology months or even years before full BD manifestation. Adequate diagnosis and treatment is often delayed, which is associated with a worse outcome. This study aims to prospectively evaluate and improve early recognition and intervention strategies for persons at-risk for BD.
METHODS: Early-BipoLife is a prospective-longitudinal cohort study of 1419 participants (aged 15-35 years) with at least five waves of assessment over a period of at least 2 years (baseline, 6, 12, 18 and 24 months). A research consortium of ten university and teaching hospitals across Germany conducts this study. The following risk groups (RGs) were recruited: RG I: help-seeking youth and young adults consulting early recognition centres/facilities presenting ≥ 1 of the proposed risk factors for BD, RG II: in-/outpatients with unipolar depressive syndrome, and RG III: in-/outpatients with attention-deficit/hyperactivity disorder (ADHD). The reference cohort was selected from the German representative IMAGEN cohort. Over the study period, the natural course of risk and resilience factors, early symptoms of BD and changes of symptom severity (including conversion to manifest BD) are observed. Psychometric properties of recently developed, structured instruments on potential risk factors for conversion to BD and subsyndromal symptomatology (Bipolar Prodrome Symptom Scale, Bipolar at-risk criteria, EPIbipolar) and biomarkers that potentially improve prediction are investigated. Moreover, actual treatment recommendations are monitored in the participating specialized services and compared to recently postulated clinical categorization and treatment guidance in the field of early BD.
CONCLUSIONS: Findings from this study will contribute to an improved knowledge about the natural course of BD, from the onset of first noticeable symptoms (precursors) to fully developed BD, and about mechanisms of conversion from subthreshold to manifest BD. Moreover, these generated data will provide information for the development of evidence-based guidelines for early-targeted detection and preventive intervention for people at risk for BD.

The emotional Stroop effect is defined as increased reaction times to emotional stimuli compared to neutral ones. It has been often reported in the literature, on both behavioral and neurophysiological level. The goal of this study was to investigate the frontal brain activation in individuals at risk for schizophrenic psychosis and bipolar disorder during an emotional Stroop task. We expected to observe decreased activation in the at-risk individuals compared to the healthy controls.
Individuals at high risk for psychosis (HR), at ultra-high risk for psychosis (UHR), at risk for bipolar disorder (BIP) and healthy controls (HC) performed an emotional Stroop task, which included positively, negatively and neutrally valenced words. Functional near-infrared spectroscopy (fNIRS) was used to measure levels of oxygenated hemoglobin (O2Hb) representing brain activity in the dorsolateral prefrontal and frontotemporal cortex.
Results showed significantly decreased levels of O2Hb in the right dorsolateral prefrontal cortex (DLPFC) in the HR and UHR groups compared to the HC, indicating lower activity. Even though the decrease was independent from the valence of the words, it was the most visible for the negative ones. Moreover, significantly lower O2Hb levels in the frontotemporal cortex (FTC) were observed in all at risk groups compared to the HC.
Lower activity in the FTC in groups at risk for psychosis and bipolar disorder reflects unspecific dysfunctions. Decreased activity in the DLPFC in the HR and UHR groups indicates that hypofrontality can be found already in individuals at risk for schizophrenic psychosis.

OBJECTIVE: To report on the modification and exploration of a 21-item Early Detection of Pediatric Sepsis Assessment Checklist aimed at improving nursing students\' recognition of key factors that contribute to early detection of sepsis in pediatric patients through clinical simulation.
METHODS: One hundred and thirty-one undergraduate, pre-licensure nursing students were evaluated using the adapted 21-item Early Detection of Pediatric Sepsis Assessment Checklist in simulation using high-fidelity manikins. Categorical Principle Component Analysis was used to evaluate for factor structure, with items accounting for <0.20 of the variance were dropped from the loadings.
RESULTS: Two factors emerged from the analysis: assessment and deterioration, accounting for 68% of the variance. Factor one, assessment, contained nine items (α = 0.77; λ = 3.36). Factor two, deterioration, contained seven items (α = 0.72; λ = 2.85). Five items did not load and were dropped from the factor structure, resulting in a 16-item checklist.
CONCLUSIONS: Two factors emerged from the analysis which is key to improving the early detection of pediatric sepsis. Assessment, factor one, accounted for the nursing students\' central skills of recognizing baseline vital signs and timely medication administration. Deterioration, factor two, contained items reflecting the recognition of changes from baseline that require action. Conceptually, these factors reflect the most central points in the early detection of signs in pediatric patients at risk for sepsis.
CONCLUSIONS: This checklist forms a valuable tool to assess the knowledge of pre-licensure students and may possibly be extended as a tool to assess the clinical readiness and performance of new graduates through the safety and supervision allotted by simulation.

BACKGROUND: Bipolar disorder is a severe and heterogeneous mental disorder. Despite great advances in neuroscience over the past decades, the precise causative mechanisms at the transmitter, cellular or network level have so far not been unraveled. As a result, individual treatment decisions cannot be tailor-made and the uncertain prognosis is based on clinical characteristics alone. Although a subpopulation of patients have an excellent response to pharmacological monotherapy, other subpopulations have been less well served by the medical system and therefore require more focused attention. In particular individuals at high risk of bipolar disorder, young patients in the early stages of bipolar disorder, patients with an unstable highly relapsing course and patients with acute suicidal ideation have been identified as those in need.
UNASSIGNED: A research consortium of ten universities across Germany has therefore implemented a 4 year research agenda including three randomized controlled trials, one epidemiological trial and one cross-sectional trial to address these areas of unmet needs. The topics under investigation will be the improvement of early recognition, specific psychotherapy, and smartphones as an aid for early episode detection and biomarkers of lithium response. A subset of patients will be investigated utilizing neuroimaging (fMRI), neurophysiology (EEG), and biomaterials (genomics, transcriptomics).
CONCLUSIONS: This article aims to outline the rationale, design, and methods of these individual studies.

BACKGROUND: Nurses\' \'worry\' is used as a calling criterion in many Rapid Response Systems, however it is valued inconsistently. Furthermore, barriers to call the Rapid Response Team can cause delay in escalating care. The literature identifies nine indicators which trigger nurses to worry about a patient\'s condition.
OBJECTIVE: The objective of this study is to determine the significance of nurses\' \'worry\' and/or indicators underlying \'worry\' to predict unplanned Intensive-Care/High-Dependency-Unit admission or unexpected mortality among surgical ward patients.
METHODS: A prospective cohort study.
METHODS: A 500-bed tertiary University affiliated teaching hospital.
METHODS: Adult, native speaking surgical patients, admitted to three surgical wards (traumatology, vascular- and abdominal/oncological surgery). We excluded patients with a non-ICU policy or with no curative treatment. Mentally incapacitated patients were also excluded.
METHODS: We developed a new clinical assessment tool, the Dutch-Early-Nurse-Worry-Indicator-Score (DENWIS) based on signs underlying \'worry\'. Nurses systematically scored their \'worry\' and the DENWIS once per shift or at any moment of \'worry\'. DENWIS measurements were linked to routinely measured vital signs. The composite endpoint was unplanned Intensive-Care/High-Dependency-Unit admission or unexpected mortality. The DENWIS-indicators were included in a univariate and multivariate logistic regression analysis, subsequently inserting \'worry\' and the Early Warning Score into the model. We calculated the area under the receiver-operating characteristics curve.
RESULTS: In 3522 patients there were 102 (2.9%) patients with unplanned Intensive Care Unit/High Dependency Unit-admissions or unexpected mortality. \'Worry\' (0.81) and the DENWIS-model (0.85) had a lower area under the receiver-operating characteristics curve than the Early Warning Score (0.86). Adding \'worry\' and the Early Warning Score to the DENWIS-model resulted in higher areas under the receiver operating characteristics curves (0.87 and 0.91, respectively) compared with the Early Warning Score only based on vital signs.
CONCLUSIONS: In this single-center study we showed that adding the Early Warning Score based on vital signs to the DENWIS-indicators improves prediction of unplanned Intensive-Care/High-Dependency-Unit admission or unexpected mortality.