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.

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.

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).

Non-arteritic ischemic optic neuropathy (NAION) can rarely occur in the setting of sudden vascular compromise, especially in patients with a \"disk-at-risk\" appearance. Anemia and hypotension are believed to be the main precipitators of shock-induced NAION. Early recognition of this phenomenon can prevent further visual loss and result in partial visual recovery. We here present a 56-year-old patient who developed NAION characterized by optic disc edema in both eyes and visual loss in the left eye secondary to hypotension in the setting of septic shock. He received aggressive blood pressure management (stopping all his anti-hypertensives, hydration, and midrodrine) which resulted in stabilization of vision in the right eye and likely prevented further visual loss in the left eye.

Adenovirus pneumonia is common in pediatric upper respiratory tract infection, which is comparatively easy to develop into severe cases and has a high mortality rate with many influential sequelae. As for pathogenesis, adenoviruses can directly damage target cells and activate the immune response to varying degrees. Early clinical recognition depends on patients\' symptoms and laboratory tests, including those under 2 years old, dyspnea with systemic toxic symptoms, atelectasis or emphysema in CT image, decreased leukocytes, and significantly increased C-reaction protein (CRP) and procalcitonin (PCT), indicating the possibility of severe cases. Until now, there is no specific drug for adenovirus pneumonia, so in clinical practice, current treatment comprises antiviral drugs, respiratory support and bronchoscopy, immunomodulatory therapy, and blood purification. Additionally, post-infectious bronchiolitis obliterans (PIBO), hemophagocytic syndrome, and death should be carefully noted. Independent risk factors associated with the development of PIBO are invasive mechanical ventilation, intravenous steroid use, duration of fever, and male gender. Meanwhile, hypoxemia, hypercapnia, invasive mechanical ventilation, and low serum albumin levels are related to death. Among these, viral load and serological identification are not only \"gold standard\" for adenovirus pneumonia, but are also related to the severity and prognosis. Here, we discuss the progress of pathogenesis, early recognition, therapy, and risk factors for poor outcomes regarding severe pediatric adenovirus pneumonia.

A survivor of child sexual abuse felt that doctors missed opportunities to notice her distress when, at fourteen, she had an unexplained illness that lasted for a year. The cause, she wrote, was \"explained by Doctors as psychological, but nobody questioned further. WHY??? … If adults don\'t listen[,] then we have no one to turn to.\" For decades, community health practitioners have been identified as an important group in protecting children from maltreatment, but survivor testimony and agency statistics demonstrate that they rarely receive verbal disclosures or recognize the physical or behavioural warning signs of sexual abuse. The accounts we have of the 1980s tell of swiftly heightening professional awareness, followed by a visceral backlash in the latter part of the decade that discouraged practitioners from acting on their concerns. This article uses trade and professional journals, training materials, textbooks, and new oral histories to consider why community-based doctors and nurses have struggled to notice and respond to the sexually abused child. It will argue that the conceptual model of child sexual abuse that community health practitioners encountered in the workplace encouraged a mechanical and procedural response to suspicions of abuse. In a highly gendered and contested workplace, practitioners\' feelings about how survivors, non-abusing family members, and perpetrators should be understood were rarely debated in training or in practice. The emotional cost to the practitioners of engagement with sexual abuse, and their need for spaces of reflexivity and structures of support, were ignored.

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.

Digital technologies have the potential to support psychiatric diagnostics and, in particular, differential diagnostics of autism spectrum disorder in the near future, making clinical decisions more objective, reliable and evidence-based while reducing clinical resources. Multimodal automatized measurement of symptoms at cognitive, behavioral, and neuronal levels combined with artificial intelligence applications offer promising strides toward personalized prognostics and treatment strategies. In addition, these new technologies could enable systematic and continuous assessment of longitudinal symptom development, beyond the usual scope of clinical practice. Early recognition of exacerbation and simplified, as well as detailed, progression control would become possible. Ultimately, digitally assisted diagnostics will advance early recognition. Nonetheless, digital technologies cannot and should not substitute clinical decision making that takes the comprehensive complexity of individual longitudinal and cross-section presentation of autism spectrum disorder into account. Yet, they might aid the clinician by objectifying decision processes and provide a welcome relief to resources in the clinical setting.

Perioperative critical events will affect the quality of medical services and threaten the safety of patients. Using scientific methods to evaluate the perioperative risk of critical illness is of great significance for improving the quality of medical services and ensuring the safety of patients.
At present, the traditional scoring system is mainly used to predict the score of critical illness, which is mainly dependent on the judgment of doctors. The result is affected by doctors\' knowledge and experience, and the accuracy is difficult to guarantee and has a serious lag. Besides, the statistical prediction method based on pure data type do not make use of the patient\'s diagnostic text information and cannot identify comprehensive risk factor. Therefore, this paper combines the text features extracted by deep neural network with the pure numerical type features extracted by XGBOOST to propose a deep neural decision gradient boosting model. Supervised learning was used to train the risk prediction model to analyze the occurrence of critical illness during the perioperative period for early warning.
We evaluated the proposed methods based on the real data of critical illness patients in one hospital from 2014 to 2018. The results showed that the critical disease risk prediction model based on multiple modes had faster convergence rate and better performance than the risk prediction model based on text data and pure data type.
Based on the machine learning method and multi-modal data of patients, this paper built a prediction model for critical adverse events in patients, so that the risk of critical events can be predicted for any patient directly based on the preoperative and intraoperative characteristic data. At present, this work only classifies and predicts the occurrence of critical illness during or after operation based on the preoperative examination data of patients, but does not discuss the specific time when the patient was critical illness, which is also the direction of our future work.