The growing concern of pediatric mortality demands heightened preparedness in clinical settings, especially within intensive care units (ICUs). As respiratory-related admissions account for a substantial portion of pediatric illnesses, there is a pressing need to predict ICU mortality in these cases. This study based on data from 1188 patients, addresses this imperative using machine learning techniques and investigating different class balancing methods for pediatric ICU mortality prediction. This study employs the publicly accessible \"Paediatric Intensive Care database\" to train, validate, and test a machine learning model for predicting pediatric patient mortality. Features were ranked using three machine learning feature selection techniques, namely Random Forest, Extra Trees, and XGBoost, resulting in the selection of 16 critical features from a total of 105 features. Ten machine learning models and ensemble techniques are used to make accurate mortality predictions. To tackle the inherent class imbalance in the dataset, we applied a unique data partitioning technique to enhance the model\'s alignment with the data distribution. The CatBoost machine learning model achieved an area under the curve (AUC) of 72.22%, while the stacking ensemble model yielded an AUC of 60.59% for mortality prediction. The proposed subdivision technique, on the other hand, provides a significant improvement in performance metrics, with an AUC of 85.2% and an accuracy of 89.32%. These findings emphasize the potential of machine learning in enhancing pediatric mortality prediction and inform strategies for improved ICU readiness.

Bipolar disorder is a highly heritable and functionally impairing disease. The recognition and intervention of BD especially that characterized by early onset remains challenging. Risk biomarkers for predicting BD transition among at-risk youth may improve disease prognosis. We reviewed the more recent clinical studies to find possible pre-diagnostic biomarkers in youth at familial or (and) clinical risk of BD. Here we found that putative biomarkers for predicting conversion to BD include findings from multiple sample sources based on different hypotheses. Putative risk biomarkers shown by perspective studies are higher bipolar polygenetic risk scores, epigenetic alterations, elevated immune parameters, front-limbic system deficits, and brain circuit dysfunction associated with emotion and reward processing. Future studies need to enhance machine learning integration, make clinical detection methods more objective, and improve the quality of cohort studies.

BACKGROUND: POCD is a common complication among patients who underwent coronary artery bypass graft (CABG), it is linked to loss of independence and reduced quality of life.
OBJECTIVE: To examine the association between postoperative cognitive dysfunction (POCD), postoperative delirium (POD) and interleukin-6 (IL-6).
METHODS: A prospective cohort study.
METHODS: Patients who underwent elective isolated CABG were enrolled. POCD was assessed by a set of cognitive function tools. Delirium was assessed using the CAM-ICU. The logistic regression analyses were used to identify the predictive value of POD or IL-6 on POCD. The path analysis was used to analyse the relationship among POD, IL-6 and POCD.
RESULTS: A total of 212 patients were enrolled, with 25.0% of patients developing POD and 32.5% developing POCD. The multiple logistic regression analysis revealed that patients with POD had a four-fold increased hazard of POCD (OR = 3.655), and patients with IL-6 ≥ 830.50 pg/mL at the 6th hours after surgery had a 5-fold increased risk of experiencing POCD (OR = 5.042). However, the mediation effect of POD between IL-6 and POCD was not statistically significant (β = 0.059, p = .392).
CONCLUSIONS: POD and IL-6 at the 6th hour after surgery (≥830.50 pg/mL) are two potent predictors for POCD, while POD did not play a mediation effect between IL-6 and POCD.
CONCLUSIONS: Early identification of risk factors (e.g., delirium assessment and testing for serum IL-6 levels) by clinical nurses for POCD may contribute to the clinical practice for the targeted prevention nursing strategies.

OBJECTIVE: Sepsis has a high incidence and a poor prognosis. Early recognition is important to facilitate timely initiation of adequate care. Sepsis screening tools, such as the (quick) Sequential Organ Failure Assessment ((q)SOFA) and National Early Warning Score (NEWS), could help recognize sepsis. These tools have been validated in a general immunocompetent population, while their performance in immunocompromised patients, who are particularly at risk of sepsis development, remains unknown.
METHODS: This study is a post hoc analysis of a prospective observational study performed at the emergency department. Inclusion criteria were age ≥ 18 years with a suspected infection, while ≥ two qSOFA and/or SOFA criteria were used to classify patients as having suspected sepsis. The primary outcome was in-hospital mortality.
RESULTS: 1516 patients, of which 40.5% used one or more immunosuppressives, were included. NEWS had a higher prognostic accuracy as compared to qSOFA for predicting poor outcome among immunocompromised sepsis patients. Of all tested immunosuppressives, high-dose glucocorticoid therapy was associated with a threefold increased risk of both in-hospital and 28-day mortality.
CONCLUSIONS: In contrast to NEWS, qSOFA underestimates the risk of adverse outcome in patients using high-dose glucocorticoids. As a clinical consequence, to adequately assess the severity of illness among immunocompromised patients, health care professionals should best use the NEWS.

BACKGROUND: Due to the high disease burden, the early onset and often long-term trajectories mental disorders are among the most widespread diseases with growing significance. The German Center for Mental Health (DZPG) was established to enhance research conditions and expedite the translation of clinically relevant findings into practice.
OBJECTIVE: The aim of the DZPG is to optimize mental healthcare in Germany, influence modifiable social causes and to develop best practice models of care for vulnerable groups. It seeks to promote mental health and resilience, combat the stigmatization associated with mental disorders, and contribute to the enhancement of treatment across all age groups.
METHODS: The DZPG employs a translational research program that accelerates the translation of basic research findings into clinical studies and general practice. University hospitals and outpatient departments, other university disciplines, and extramural research institutions are working together to establish a collaboratively coordinated infrastructure for accelerated translation and innovation.
UNASSIGNED: The research areas encompass 1) the interaction of somatic and mental risk and resilience factors and disorders across the lifespan, 2) influencing relevant modifiable environmental factors and 3) based on this personalized prevention and intervention.
CONCLUSIONS: The DZPG aims to develop innovative preventive and therapeutic tools that enable an improvement in care for individuals with mental disorders. It involves a comprehensive integration of experts with experience at all levels of decision-making and employs trilogue and participatory approaches in all research projects.
UNASSIGNED: HINTERGRUND: Aufgrund der hohen Krankheitslast, des frühen Beginns und der oft langfristigen Verläufe zählen psychische Erkrankungen zu den Volkskrankheiten mit wachsender Bedeutung. Das Deutsche Zentrum für Psychische Gesundheit (DZPG) wurde gegründet, um Forschungsbedingungen zu verbessern und versorgungsrelevante Ergebnisse schneller in die Praxis zu bringen.
UNASSIGNED: Das DZPG hat das Ziel, die psychische Gesundheitsversorgung in Deutschland zu optimieren, modifizierbare, gesellschaftliche Ursachen zu beeinflussen und Best-Practice-Modelle zur Versorgung vulnerabler Gruppen zu entwickeln. Es soll die psychische Gesundheit und Resilienz fördern, die Stigmatisierung psychischer Erkrankungen bekämpfen und dazu beitragen, die Behandlung dieser in allen Altersgruppen zu verbessern.
METHODS: Das DZPG nutzt ein translationales Forschungsprogramm, das die Übersetzung von Ergebnissen der Grundlagenforschung in die Klinik und deren breite Anwendung beschleunigt. Es werden Universitätsklinika und -ambulanzen, andere universitäre Fachbereiche und außeruniversitäre Forschungseinrichtungen eingebunden, um eine gemeinsam abgestimmte Infrastruktur für beschleunigte Translation und Innovation zu entwickeln.
UNASSIGNED: Die Forschungsbereiche adressieren 1) die Interaktion psychischer und somatischer Risiko- und Resilienzfaktoren und Erkrankungen über die Lebensspanne, 2) die Beeinflussung relevanter modifizierbarer Umweltfaktoren und 3) darauf aufbauend die personalisierte Prävention und Intervention.
UNASSIGNED: Das DZPG verfolgt das Ziel, innovative präventive und therapeutische Werkzeuge zu entwickeln, die eine verbesserte Versorgung psychisch erkrankter Menschen ermöglichen. Es beinhaltet eine umfassende Integration von Erfahrungsexpert:innen auf allen Entscheidungsebenen und trialogisch-partizipativ in allen Forschungsprojekten.

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.

Mucopolysaccharidoses are rare lysosomal storage disorders in which glycosaminoglycans accumulate in tissues, causing multiorgan dysfunction. Mucopolysaccharidosis type I is an autosomal recessive disease caused by a deficiency of the enzyme alpha-L-iduronidase, resulting in the accumulation of dermatan and heparan sulfate. Early diagnosis is crucial for early treatment and improved outcomes. We report the case of a female child with classic clinical features who was diagnosed early which allowed hematopoietic stem cell transplantation and slowed disease progression. She presented at birth with linea alba and umbilical and inguinal hernias. Since the first months of life, she had recurrent respiratory infections. At nine months, a motor delay was noticed, and at 20 months, craniosynostosis was corrected with surgery. Coarse facial features, thoracolumbar kyphosis, and hepatomegaly prompted a urinary glycosaminoglycan study at 22 months, which showed elevated levels. Alfa-L-iduronidase activity in dried blood spot testing was low, compatible with mucopolysaccharidosis type I. Molecular testing of gene IDUA, performed for genetic counseling, revealed the pathogenic variants c.1205G>A (p.Trp402Ter) and c.1598C>G (p.Pro533Arg) in compound heterozygosity. At 26 months, her development quotient was average for her age. She started enzyme replacement therapy at 29 months and underwent hematopoietic stem cell transplantation at 33 months, which softened the coarse features, reduced respiratory infections, and improved hepatomegaly. However, at age five, her development quotient was 76 (mean = 100, standard deviation = 15). This intellectual impairment might have been prevented with an earlier diagnosis and treatment.

BACKGROUND: Sepsis is associated with about 20% of deaths worldwide. It often presents with non-specific initial symptoms, making its emergency treatment an interdisciplinary and cross-sectoral challenge. Three in four sepsis survivors suffers from new cognitive, psychological, or physical sequelae for which specific treatment concepts are scarce. The AVENIR project aims to improve the understanding of patient pathways, and subjective care experiences and needs along the entire healthcare pathway before, with and after sepsis. Based on this, concrete recommendations for the organization of care and patient information materials will be developed with close patient participation.
METHODS: Mixed-methods study including (1) analysis of anonymized nationwide health claims data from Germany, (2) linkage of health claims data with patient care reports (PCR) of emergency medical services from study regions in two federal states within Germany, and (3) qualitative exploration of the patient, relative, and care provider perspective on sepsis care. In (1), we analyze inpatient and outpatient health care utilization until 30 days pre-sepsis; clinical sepsis care including intra- and inter-hospital transfers; and rehabilitation, inpatient and outpatient aftercare of sepsis survivors as well as costs for health care utilization until 24 months post-sepsis. We attempt to identify survivor classes with similar health care utilization by Latent Class Analyses. In (2), PCR are linked with health claims data to establish a comprehensive database outlining care pathways for sepsis patients from pre-hospital to follow-up. We investigate e.g., whether correct initial assessment is associated with acute (e.g., same-day lethality) and long-term (e.g., new need for care, long-term mortality) outcomes of patients. We compare the performance of sepsis-specific screening tools such as qSOFA, NEWS-2 or PRESEP in the pre-clinical setting. In (3), semi-structured interviews as well as synchronous and asynchronous online focus groups are conducted and analyzed using qualitative content analyses techniques.
CONCLUSIONS: The results of the AVENIR study will contribute to a deeper understanding of sepsis care pathways in Germany. They may serve as a base for improvements and innovations in sepsis care, that in the long-term can contribute to reduce the personal, medical, and societal burden of sepsis and its sepsis sequelae.
BACKGROUND: Registered at German Clinical Trial Register (ID: DRKS00031302, date of registration: 5th May 2023).

BACKGROUND: To decrease the incidence of major depressive episodes, indicated prevention that targets clinical high-risk individuals with first detectable signs that forecast mental disorder is a highly relevant topic of preventive psychiatry. Still little is known about the prodrome of MDE. The aim of the current study was to identify the occurrence of a clinical high-risk state of depression, its duration and symptom constellation.
METHODS: Seventy-three patients with a diagnosed affective disorder in partial remission were assessed with our newly developed semi-structured extensive clinical instrument, the DEpression Early Prediction-INventory (DEEP-IN). Within DEEP-IN the course of prodromal symptoms was explored by using a life-chart method.
RESULTS: The significant majority of patients (93.2 %) reported a prodromal phase. The mean duration was 7.9 months (SD = 12.5). Within the group with an identified prodromal phase, psychopathological (95.6 %) as well as somatic symptoms (88.2 %) were reported. Somatic symptoms showed a moderate-to-strong effect of sex with higher prevalence in females than in males (97.6 % vs 73.1 %; V = 0.370).
CONCLUSIONS: This feasibility study had only a small sample size.
CONCLUSIONS: The majority of patients with affective disorders reported a clinical prodromal phase with both psychopathological and somatic symptoms that developed months before the onset of the depressive episode. The development of structured instruments for the assessment of depressive risk states is a promising approach for indicated prevention of depression in the future.

Due to antibiotic overuse, many bacteria have developed resistance, creating an urgent need for novel antimicrobial agents. It has been established that the filamentous temperature-sensitive mutant Z (FtsZ) of the bacterial cell division protein is an effective and promising antibacterial target. In this study, the optimal proteins were assessed by early recognition ability and the processed compound libraries were virtually screened using Vina. This effort resulted in the identification of 14 potentially active antimicrobial compounds. Among them, the compound T5S1607 demonstrated remarkable antibacterial efficacy against Bacillus subtilis ATCC9732 (MIC = 1 μg/mL) and Staphylococcus aureus ATC5C6538 (MIC = 4 μg/mL). Furthermore, in vitro experiments demonstrated that the selected compound T5S1607 rapidly killed bacteria and induced FtsZ protein aggregation, preventing bacterial division and leading to bacterial death. Additionally, cell toxicity and hemolysis experiments indicate that compound T5S1607 exhibits minimal toxicity to LO2 cells and shows no significant hemolytic effects on mammalian cells in vitro at the MIC concentration range. All the results indicate that compound T5S1607 is a promising antibacterial agent and a potential FtsZ inhibitor. In conclusion, this work successfully discovered FtsZ inhibitors with good activity through the virtual screening drug discovery process.