Feasibility and Acceptability of Methods to Collect Follow-Up Information From Parents 12 Months After Their Child's Emergency Admission to Pediatric Intensive Care.

OBJECTIVES: To evaluate the feasibility and acceptability of different methods of collecting follow-up data from parents 12 months after their child's emergency admission to a PICU. DESIGN: Mixed-methods explanatory sequential design. SETTING: One regional PICU transport service and three PICUs in England. PATIENTS: Children undergoing emergency transport to PICU recruited to an ongoing biomarker study whose parents consented to be contacted for follow-up 12 months after PICU admission. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Parents or guardians who consented were asked to complete three questionnaires about their child's functional status, quality of life, and behavior 12 months after PICU admission. Parents were given a choice about method of questionnaire completion: postal, online, or telephone interview and also asked for telephone feedback about the process and the reasons for their choice. Of 486 parents who consented to be contacted at 12 months, 232 were successfully contacted. Consent to receive questionnaires was obtained in 218 of 232 (94%). Of the 218 parents, 102 (47%) chose to complete questionnaires online (with 77% completion rate), 91 (42%) chose to complete postal questionnaires (48% completion rate), and 25 (11%) chose to complete questionnaires by telephone interview (44% completion rate). CONCLUSIONS: Parents expressed different preferences for follow-up questionnaire completion. Response rates varied by completion method. Understanding and catering for parental preferences is an important factor in maximizing response rates for follow-up studies in intensive care

The horizon of pediatric cardiac critical care.

Pediatric Cardiac Critical Care (PCCC) is a challenging discipline where decisions require a high degree of preparation and clinical expertise. In the modern era, outcomes of neonates and children with congenital heart defects have dramatically improved, largely by transformative technologies and an expanding collection of pharmacotherapies. Exponential advances in science and technology are occurring at a breathtaking rate, and applying these advances to the PCCC patient is essential to further advancing the science and practice of the field. In this article, we identified and elaborate on seven key elements within the PCCC that will pave the way for the future

The role of anion gap normalization time in the management of pediatric diabetic ketoacidosis

IntroductionOur aims were to determine whether anion gap normalization time (AGNT) correlates with risk factors related to the severity of diabetic ketoacidosis (DKA) in children, and to characterize AGNT as a criterion for DKA resolution in children admitted with moderate or severe disease.MethodsA ten-year retrospective cohort study of children admitted to the intensive care unit with DKA. We used a survival analysis approach to determine changes in serum glucose, bicarbonate, pH, and anion gap following admission. Using multivariate analysis, we examined associations between patients' demographic and laboratory characteristics with delayed normalization of the anion gap.ResultsA total of 95 patients were analyzed. The median AGNT was 8 h. Delayed AGNT (>8 h) correlated with pH < 7.1 and serum glucose >500 mg/dL. In multivariate analysis, glucose >500 mg/dL was associated with an increased risk for delayed AGNT, by 3.41 fold. Each 25 mg/dL elevation in glucose was associated with a 10% increment in risk for delayed AGNT. Median AGNT preceded median PICU discharge by 15 h (8 vs. 23 h).DiscussionAGNT represents a return to normal glucose-based physiology and an improvement in dehydration. The correlation observed between delayed AGNT and markers of DKA severity supports the usefulness of AGNT for assessing DKA recovery

Therapeutic potential of injectable Nano-mupirocin liposomes for infections involving multidrug-resistant bacteria

Antibiotic resistance is a global health threat. There are a few antibiotics under development, and even fewer with new modes of action and no cross-resistance to established antibiotics. Accordingly, reformulation of old antibiotics to overcome resistance is attractive. Nano-mupirocin is a PEGylated nano-liposomal formulation of mupirocin, potentially enabling parenteral use in deep infections, as previously demonstrated in several animal models. Here, we describe extensive in vitro profiling of mupirocin and Nano-mupirocin and correlate the resulting MIC data with the pharmacokinetic profiles seen for Nano-mupirocin in a rat model. Nano-mupirocin showed no cross-resistance with other antibiotics and retained full activity against vancomycin-, daptomycin-, linezolid- and methicillin- resistant Staphylococcus aureus, against vancomycin-resistant Enterococcus faecium, and cephalosporin-resistant Neisseria gonorrhoeae. Following Nano-mupirocin injection to rats, plasma levels greatly exceeded relevant MICs for > 24 h, and a biodistribution study in mice showed that mupirocin concentrations in vaginal secretions greatly exceeded the MIC 90 for N. gonorrhoeae (0.03 µg/mL) for > 24 h. In summary, Nano-mupirocin has excellent potential for treatment of several infection types involving multiresistant bacteria. It has the concomitant benefits from utilizing an established antibiotic and liposomes of the same size and lipid composition as Doxil®, an anticancer drug product now used for the treatment of over 700,000 patients globally

CellSighter: a neural network to classify cells in highly multiplexed images

Abstract Multiplexed imaging enables measurement of multiple proteins in situ, offering an unprecedented opportunity to chart various cell types and states in tissues. However, cell classification, the task of identifying the type of individual cells, remains challenging, labor-intensive, and limiting to throughput. Here, we present CellSighter, a deep-learning based pipeline to accelerate cell classification in multiplexed images. Given a small training set of expert-labeled images, CellSighter outputs the label probabilities for all cells in new images. CellSighter achieves over 80% accuracy for major cell types across imaging platforms, which approaches inter-observer concordance. Ablation studies and simulations show that CellSighter is able to generalize its training data and learn features of protein expression levels, as well as spatial features such as subcellular expression patterns. CellSighter’s design reduces overfitting, and it can be trained with only thousands or even hundreds of labeled examples. CellSighter also outputs a prediction confidence, allowing downstream experts control over the results. Altogether, CellSighter drastically reduces hands-on time for cell classification in multiplexed images, while improving accuracy and consistency across datasets

Cohort profile of the Biomarkers of Acute Serious Illness in Children (BASIC) study: a prospective multicentre cohort study in critically ill children.

PURPOSE: Despite significant progress, challenges remain in the management of critically ill children, including early identification of infection and organ failure and robust early risk stratification to predict poor outcome. The Biomarkers of Acute Serious Illness in Children study aims to identify genetic and biological pathways underlying the development of critical illness in infections and organ failure and those leading to poor outcome (death or severe disability) in children requiring emergency intensive care. PARTICIPANTS: We recruited a prospective cohort of critically ill children undergoing emergency transport to four paediatric intensive care units (PICUs) in Southeast England between April 2014 and December 2016. FINDINGS TO DATE: During the study period, 1017 patients were recruited by the regional PICU transport team, and blood and urine samples were obtained at/around first contact with the patient by the transport team. Consent for participation in the study was deferred until after PICU admission and 674 parents/carers were consented. Further samples (blood, urine, stool and throat swabs) were collected after consent. Samples were processed and stored for genomic, transcriptomic, proteomic and metabolomic analyses. Demographic, clinical and laboratory data at first contact, during PICU stay and at discharge, were collected, as were detailed data regarding infectious or non-infectious aetiology. In addition, 115 families have completed 12-month validated follow-up questionnaires to assess quality of life and child behaviour.The first phase of sample analyses (transcriptomic profiling) is currently in progress. FUTURE PLANS: Stored samples will be analysed using genomic, proteomic and metabolic profiling. Advanced bioinformatics techniques will be used to identify biomarkers for early diagnosis of infection, identification of organ failure and risk stratification to predict poor outcome (death/severe disability). TRIAL REGISTRATION NUMBER: NCT03238040.Great Ormond St Hospital Childrens Charit

Cohort profile of the Biomarkers of Acute Serious Illness in Children (BASIC) study: a prospective multicentre cohort study in critically ill children.

PURPOSE: Despite significant progress, challenges remain in the management of critically ill children, including early identification of infection and organ failure and robust early risk stratification to predict poor outcome. The Biomarkers of Acute Serious Illness in Children study aims to identify genetic and biological pathways underlying the development of critical illness in infections and organ failure and those leading to poor outcome (death or severe disability) in children requiring emergency intensive care. PARTICIPANTS: We recruited a prospective cohort of critically ill children undergoing emergency transport to four paediatric intensive care units (PICUs) in Southeast England between April 2014 and December 2016. FINDINGS TO DATE: During the study period, 1017 patients were recruited by the regional PICU transport team, and blood and urine samples were obtained at/around first contact with the patient by the transport team. Consent for participation in the study was deferred until after PICU admission and 674 parents/carers were consented. Further samples (blood, urine, stool and throat swabs) were collected after consent. Samples were processed and stored for genomic, transcriptomic, proteomic and metabolomic analyses. Demographic, clinical and laboratory data at first contact, during PICU stay and at discharge, were collected, as were detailed data regarding infectious or non-infectious aetiology. In addition, 115 families have completed 12-month validated follow-up questionnaires to assess quality of life and child behaviour.The first phase of sample analyses (transcriptomic profiling) is currently in progress. FUTURE PLANS: Stored samples will be analysed using genomic, proteomic and metabolic profiling. Advanced bioinformatics techniques will be used to identify biomarkers for early diagnosis of infection, identification of organ failure and risk stratification to predict poor outcome (death/severe disability). TRIAL REGISTRATION NUMBER: NCT03238040.Great Ormond St Hospital Childrens Charit