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ABSTRACT Objective: to analyze how the process of implementing an onco-hematology nursing service at a pediatric hospital in Rio de Janeiro took place. Methods: a historical, qualitative study. Sources included written and oral documents, produced through semi-structured interviews, carried out between August 2022 and February 2023 with nurses who worked on implementing the service, represented by 40 minutes, nine care protocols and eight reports from the hospital’s internal website. Results: nursing staff reorganization and investment in professional improvement, through courses and graduate courses, culminated in the establishment of protocols, committees and nursing indicators, which enabled the implementation of a service with quality and safety. Final considerations: the implementation of a nursing service in pediatric onco-hematology was successful and, while highlighting the importance of nursing, also delivered quality service to society, strengthening the Brazilian Health System. RESUMEN Objetivo: analizar cómo se desarrolló el proceso de implementación del servicio de enfermería de oncohematología en un hospital pediátrico de Río de Janeiro. Métodos: estudio histórico, cualitativo. Las fuentes incluyeron documentos escritos y orales, elaborados a partir de entrevistas semiestructuradas, realizadas entre agosto de 2022 y febrero de 2023 con enfermeros que trabajaron en la implementación del servicio, representados por 40 minutos, nueve protocolos de atención y ocho informes del sitio web interno del hospital. Resultados: la reorganización del equipo de enfermería y la inversión en superación profesional, a través de cursos y posgrados, culminaron en el establecimiento de protocolos, comités e indicadores de enfermería, que permitieron implementar un servicio con calidad y seguridad. Consideraciones finales: la implementación del servicio de enfermería en oncohematología pediátrica fue exitosa y, al tiempo que destacó la importancia de la enfermería, también entregó un servicio de calidad a la sociedad, fortaleciendo el Sistema Único de Salud. RESUMO Objetivo: analisar como se deu o processo de implantação do serviço de enfermagem em onco-hematologia de um hospital pediátrico no Rio de Janeiro. Métodos: estudo histórico, qualitativo. Fontes incluíram documentos escritos e orais, produzidos por entrevistas semiestruturadas, realizadas entre agosto de 2022 e fevereiro de 2023 com enfermeiras que atuaram na implantação do serviço, representados por 40 atas, nove protocolos assistenciais e oito reportagens do site interno do hospital. Resultados: a reorganização da equipe de enfermagem e o investimento no aprimoramento profissional, por meio de cursos e pós-graduações, culminaram na instituição de protocolos, comissões e indicadores de enfermagem, os quais possibilitaram a implantação de um serviço com qualidade e segurança. Considerações finais: a implantação do serviço de enfermagem em onco-hematologia pediátrica foi exitosa e, ao tempo que evidenciou a importância da enfermagem, também entregou à sociedade um serviço de qualidade, fortalecendo o Sistema Único de Saúde.

Background Acute kidney injury (AKI) in pediatric critical care patients is diagnosed using elevated serum creatinine, which occurs only after kidney impairment. There are no treatments other than supportive care for AKI once it has developed, so it is important to identify patients at risk to prevent injury. This study develops a machine learning model to learn pre-disease patterns of physiological measurements and predict pediatric AKI up to 48 h earlier than the currently established diagnostic guidelines. Methods EHR data from 16,863 pediatric critical care patients between 1 month to 21 years of age from three independent institutions were used to develop a single machine learning model for early prediction of creatinine-based AKI using intelligently engineered predictors, such as creatinine rate of change, to automatically assess real-time AKI risk. The primary outcome is prediction of moderate to severe AKI (Stage 2/3), and secondary outcomes are prediction of any AKI (Stage 1/2/3) and requirement of renal replacement therapy (RRT). Predictions generate alerts allowing fast assessment and reduction of AKI risk, such as: “patient has 90% risk of developing AKI in the next 48 h” along with contextual information and suggested response such as “patient on aminoglycosides, suggest check level and review dose and indication”. Results The model was successful in predicting Stage 2/3 AKI prior to detection by conventional criteria with a median lead-time of 30 h at AUROC of 0.89. The model predicted 70% of subsequent RRT episodes, 58% of Stage 2/3 episodes, and 41% of any AKI episodes. The ratio of false to true alerts of any AKI episodes was approximately one-to-one (PPV 47%). Among patients predicted, 79% received potentially nephrotoxic medication after being identified by the model but before development of AKI. Conclusions As the first multi-center validated AKI prediction model for all pediatric critical care patients, the machine learning model described in this study accurately predicts moderate to severe AKI up to 48 h in advance of AKI onset. The model may improve outcome of pediatric AKI by providing early alerting and actionable feedback, potentially preventing or reducing AKI by implementing early measures such as medication adjustment.

The possibility of other types of diabetes should be considered in the child who has negative diabetes-associated autoantibodies and (B): an autosomal dominant family history of diabetes (maturity-onset diabetes of the young [MODY]) age less than 12 months and especially in first 6 months of life (NDM [neonatal diabetes mellitus]) mild-fasting hyperglycemia (5.5-8.5 mmol [100-150 mg/dL]), especially if young, non-obese, and asymptomatic a prolonged honeymoon period over 1 year or an unusually low requirement for insulin of ≤0.5 U/kg/day after 1 year of diabetes associated conditions such as deafness, optic atrophy, or syndromic features (mitochondrial disease) a history of exposure to drugs known to be toxic to β-cells or cause insulin resistance (eg, immunosuppressive drugs such as tacrolimus or cyclosporin; gluocorticoids or some antidepressants). While type 1 diabetes remains the most common form of diabetes in young people in many populations, especially those of European background, type 2 diabetes has become an increasingly important public health concern globally among children in high risk ethnic populations as well as in those with severe obesity, see ISPAD guideline on type 2 diabetes . Diabetes in young people usually presents with characteristic symptoms such as polyuria, polydipsia, nocturia, enuresis, weight loss—which may be accompanied by polyphagia, behavioral disturbance including reduced school performance, and blurred vision. Glycated hemoglobin (HbA1c) can be used as a diagnostic test for diabetes providing that stringent quality assurance tests are in place and assays are standardized to criteria aligned to the international reference values, and there are no conditions present which preclude its accurate measurement. [...]the validity of HbA1c as a measure of average glucose is complicated in the context of hemoglobinopathies, certain forms of anemia, or any other condition that affects normal red blood cell turnover.

ObjectivesTo develop evidence-based recommendations for clinicians caring for children (including infants, school-aged children, and adolescents) with septic shock and other sepsis-associated organ dysfunction.DesignA panel of 49 international experts, representing 12 international organizations, as well as three methodologists and three public members was convened. Panel members assembled at key international meetings (for those panel members attending the conference), and a stand-alone meeting was held for all panel members in November 2018. A formal conflict-of-interest policy was developed at the onset of the process and enforced throughout. Teleconferences and electronic-based discussion among the chairs, co-chairs, methodologists, and group heads, as well as within subgroups, served as an integral part of the guideline development process.MethodsThe panel consisted of six subgroups: recognition and management of infection, hemodynamics and resuscitation, ventilation, endocrine and metabolic therapies, adjunctive therapies, and research priorities. We conducted a systematic review for each Population, Intervention, Control, and Outcomes question to identify the best available evidence, statistically summarized the evidence, and then assessed the quality of evidence using the Grading of Recommendations Assessment, Development, and Evaluation approach. We used the evidence-to-decision framework to formulate recommendations as strong or weak, or as a best practice statement. In addition, “in our practice” statements were included when evidence was inconclusive to issue a recommendation, but the panel felt that some guidance based on practice patterns may be appropriate.ResultsThe panel provided 77 statements on the management and resuscitation of children with septic shock and other sepsis-associated organ dysfunction. Overall, six were strong recommendations, 49 were weak recommendations, and nine were best-practice statements. For 13 questions, no recommendations could be made; but, for 10 of these, “in our practice” statements were provided. In addition, 52 research priorities were identified.ConclusionsA large cohort of international experts was able to achieve consensus regarding many recommendations for the best care of children with sepsis, acknowledging that most aspects of care had relatively low quality of evidence resulting in the frequent issuance of weak recommendations. Despite this challenge, these recommendations regarding the management of children with septic shock and other sepsis-associated organ dysfunction provide a foundation for consistent care to improve outcomes and inform future research.

Current diagnostic criteria for bronchopulmonary dysplasia rely heavily on the level and duration of oxygen therapy, do not reflect contemporary neonatal care, and do not adequately predict childhood morbidity. To determine which of 18 prespecified, revised definitions of bronchopulmonary dysplasia that variably define disease severity according to the level of respiratory support and supplemental oxygen administered at 36 weeks' postmenstrual age best predicts death or serious respiratory morbidity through 18-26 months' corrected age. We assessed infants born at less than 32 weeks of gestation between 2011 and 2015 at 18 centers of the Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network. Of 2,677 infants, 683 (26%) died or developed serious respiratory morbidity. The diagnostic criteria that best predicted this outcome defined bronchopulmonary dysplasia according to treatment with the following support at 36 weeks' postmenstrual age, regardless of prior or current oxygen therapy: no bronchopulmonary dysplasia, no support (  = 773); grade 1, nasal cannula ≤2 L/min (  = 1,038); grade 2, nasal cannula >2 L/min or noninvasive positive airway pressure (  = 617); and grade 3, invasive mechanical ventilation (  = 249). These criteria correctly predicted death or serious respiratory morbidity in 81% of study infants. Rates of this outcome increased stepwise from 10% among infants without bronchopulmonary dysplasia to 77% among those with grade 3 disease. A similar gradient (33-79%) was observed for death or neurodevelopmental impairment. The definition of bronchopulmonary dysplasia that best predicted early childhood morbidity categorized disease severity according to the mode of respiratory support administered at 36 weeks' postmenstrual age, regardless of supplemental oxygen use.

Background The rapid development in big data analytics and the data-rich environment of intensive care units together provide unprecedented opportunities for medical breakthroughs in the field of critical care. We developed and validated a machine learning-based model, the Pediatric Risk of Mortality Prediction Tool (PROMPT), for real-time prediction of all-cause mortality in pediatric intensive care units. Methods Utilizing two separate retrospective observational cohorts, we conducted model development and validation using a machine learning algorithm with a convolutional neural network. The development cohort comprised 1445 pediatric patients with 1977 medical encounters admitted to intensive care units from January 2011 to December 2017 at Severance Hospital (Seoul, Korea). The validation cohort included 278 patients with 364 medical encounters admitted to the pediatric intensive care unit from January 2016 to November 2017 at Samsung Medical Center. Results Using seven vital signs, along with patient age and body weight on intensive care unit admission, PROMPT achieved an area under the receiver operating characteristic curve in the range of 0.89–0.97 for mortality prediction 6 to 60 h prior to death. Our results demonstrated that PROMPT provided high sensitivity with specificity and outperformed the conventional severity scoring system, the Pediatric Index of Mortality, in predictive ability. Model performance was indistinguishable between the development and validation cohorts. Conclusions PROMPT is a deep model-based, data-driven early warning score tool that can predict mortality in critically ill children and may be useful for the timely identification of deteriorating patients.

Purpose: Implementation of novel genetic diagnostic tests is generally driven by technological advances because they promise shorter turnaround times and/or higher diagnostic yields. Other aspects, including impact on clinical management or cost-effectiveness, are often not assessed in detail prior to implementation. Methods: We studied the clinical utility of whole-exome sequencing (WES) in complex pediatric neurology in terms of diagnostic yield and costs. We analyzed 150 patients (and their parents) presenting with complex neurological disorders of suspected genetic origin. In a parallel study, all patients received both the standard diagnostic workup (e.g., cerebral imaging, muscle biopsies or lumbar punctures, and sequential gene-by-gene–based testing) and WES simultaneously. Results: Our unique study design allowed direct comparison of diagnostic yield of both trajectories and provided insight into the economic implications of implementing WES in this diagnostic trajectory. We showed that WES identified significantly more conclusive diagnoses (29.3%) than the standard care pathway (7.3%) without incurring higher costs. Exploratory analysis of WES as a first-tier diagnostic test indicates that WES may even be cost-saving, depending on the extent of other tests being omitted. Conclusion: Our data support such a use of WES in pediatric neurology for disorders of presumed genetic origin. Genet Med advance online publication 23 March 2017

Many paediatric clinical research studies, whether observational or interventional, have as an eventual aim the identification or quantification of causal relationships. One might ask: does screen time influence childhood obesity? Could overuse of paracetamol in infancy cause wheeze? How does breastfeeding affect later cognitive outcomes? In this review, we present causal directed acyclic graphs (DAGs) to a paediatric audience. DAGs are a graphical tool which provide a way to visually represent and better understand the key concepts of exposure, outcome, causation, confounding, and bias. We use clinical examples, including those outlined above, framed in the language of DAGs, to demonstrate their potential applications. We show how DAGs can be most useful in identifying confounding and sources of bias, demonstrating inappropriate statistical adjustments for presumed biases, and understanding threats to validity in randomised controlled trials. We believe that a familiarity with DAGs, and the concepts underlying them, will be of benefit both to the researchers planning studies, and practising clinicians interpreting them.