Ariel - Volume 12 Number 2

Executive Editors David G. Polin Larry H. Pastor Business Manager Alex Macones Jean Lien Editorial Page Editor Deepak Kapoor Sports Editor Todd Hoover Photography Editors Lois Leach Ken Yonemur

Transcriptomic And Metabolomic Analyses Of Acetaminophen Exposure In Human Ipscs: Potential Mechanisms Explaining Epidemiological Associations Between Prenatal Acetaminophen Exposure And Increased Risk Of Autism Spectrum Disorder

Acetaminophen (APAP) is the most common analgesic taken during pregnancy. Indeed, approximately 65% of pregnant women use the drug. Recent epidemiological studies suggest that prenatal exposure to APAP is associated with increased risk of autism spectrum disorder (ASD). Although this neurodevelopmental disorder affects 1 in 54 children in the U.S., no studies have investigated the molecular mechanism by which APAP may increase the risk of ASD. In vitro experiments in cell cultures have shown that high concentrations of APAP induces cell death. Through the use of a systems-level approach in human induced Pluripotent Stem Cells (iPSCs), the present study investigates the mechanisms by which prenatal exposure to physiologically relevant doses of APAP could increase the risk of ASD. Initial experiments examined the concentration-dependence of APAP toxicity in human iPSCs exposed for 6 days, as estimated by changes in cell counts. Thereafter, RNA-sequencing and metabolomic analyses were conducted on cells exposed to therapeutic (0.16 mM) and toxic (0.32 and 0.48 mM) APAP concentrations for 6 days. APAP concentration-dependent decreases in expression for COBL, CYP2B6, FZD5, GPC4, NCALD and FGFBP3, and increases in expression for ATP1A2, PROS1, HES1 and NRIP1 were observed. These changes in gene expression are identical to those described in the ASD literature. Metabolomic analyses revealed differential regulation of metabolites involved in aminoacyl-tRNA, and valine, leucine and isoleucine biosynthesis, both of which have been linked to ASD. Our integration of transcriptomics and metabolomics data has revealed an impact of APAP on biological processes that appear to parallel those seen in ASD. In so doing, the results of the present study provide an important first step in elucidating the potential mechanisms by which prenatal exposure to APAP may increase the risk of ASD and promote adverse neurodevelopmental outcomes

Control of hyperglycaemia in paediatric intensive care (CHiP): study protocol.

BACKGROUND: There is increasing evidence that tight blood glucose (BG) control improves outcomes in critically ill adults. Children show similar hyperglycaemic responses to surgery or critical illness. However it is not known whether tight control will benefit children given maturational differences and different disease spectrum. METHODS/DESIGN: The study is an randomised open trial with two parallel groups to assess whether, for children undergoing intensive care in the UK aged <or= 16 years who are ventilated, have an arterial line in-situ and are receiving vasoactive support following injury, major surgery or in association with critical illness in whom it is anticipated such treatment will be required to continue for at least 12 hours, tight control will increase the numbers of days alive and free of mechanical ventilation at 30 days, and lead to improvement in a range of complications associated with intensive care treatment and be cost effective. Children in the tight control group will receive insulin by intravenous infusion titrated to maintain BG between 4 and 7.0 mmol/l. Children in the control group will be treated according to a standard current approach to BG management. Children will be followed up to determine vital status and healthcare resources usage between discharge and 12 months post-randomisation. Information regarding overall health status, global neurological outcome, attention and behavioural status will be sought from a subgroup with traumatic brain injury (TBI). A difference of 2 days in the number of ventilator-free days within the first 30 days post-randomisation is considered clinically important. Conservatively assuming a standard deviation of a week across both trial arms, a type I error of 1% (2-sided test), and allowing for non-compliance, a total sample size of 1000 patients would have 90% power to detect this difference. To detect effect differences between cardiac and non-cardiac patients, a target sample size of 1500 is required. An economic evaluation will assess whether the costs of achieving tight BG control are justified by subsequent reductions in hospitalisation costs. DISCUSSION: The relevance of tight glycaemic control in this population needs to be assessed formally before being accepted into standard practice

Impact of the insulin and glucose content of the postoperative fluid on the outcome after pediatric cardiac surgery

INTRODUCTION: The aim of this study was to investigate the role of the insulin and glucose content of the maintenance fluid in influencing the outcomes of pediatric patients undergoing heart surgery. METHODS: A total of 2063 consecutive pediatric patients undergoing cardiac surgery were screened between 2003 and 2008. A dextrose and an insulin propensity-matched group were constructed. In the dextrose model, 5% and 10% dextrose maintenance infusions were compared below 20 kg of weight. RESULTS: A total of 171 and 298 pairs of patients were matched in the insulin and glucose model, respectively. Mortality was lower in the insulin group (12.9% vs. 7%, p = 0.049). The insulin group had longer intensive care unit (ICU) stay [days, 10.9 (5.8–18.4) vs. 13.7 (8.2–21), p = 0.003], hospital stay [days, 19.8 (13.6–26.6) vs. 22.7 (17.6–29.7), p < 0.01], duration of mechanical ventilation [hours, 67 (19–140) vs. 107 (45–176), p = 0.006], and the incidence of severe infections (18.1% vs. 28.7%, p = 0.01) and dialysis (11.7% vs. 24%, p = 0.001) was higher. In the dextrose model, the incidence of pulmonary complications (13.09% vs. 22.5%, p < 0.01), low cardiac output (17.11% vs. 30.9%, p < 0.01), and severe infections (10.07% vs. 20.5%, p < 0.01) was higher, and the duration of the hospital stay [days, 16.4 (13.1–21.6) vs. 18.1 (13.8–24.6), p < 0.01] was longer in the 10% dextrose group. CONCLUSIONS: Insulin treatment appeared to decrease mortality, and lower glucose content was associated with lower occurrence of adverse events

Effects of an educational program and a standardized insulin order form on glycemic outcomes in non-critically ill hospitalized patients

BACKGROUND: The optimal approach to managing hyperglycemia in noncritically ill hospital patients is unclear. OBJECTIVE: To investigate the effects of targeted quality improvement interventions on insulin prescribing and glycemic control. DESIGN: A cohort study comparing an intervention group (IG) to a concurrent control group (CCG) and an historic control group (HCG). SETTING: University of Michigan Hospital. PATIENTS: Hyperglycemic, noncritically ill hospital patients treated with insulin. INTERVENTION: Physician and nurse education and a standardized insulin order form based on the principles of physiologic insulin use. MEASUREMENTS: Glycemic control and insulin prescribing patterns. RESULTS: Patients in the IG were more likely to be treated with a combination of scheduled basal and nutritional insulin than in the other groups. In the final adjusted regression model, patients in the IG were more likely to be in the target glucose range (odds ratio [OR], 1.72; P = 0.01) and less likely to be severely hyperglycemic (OR, 0.65; P < 0.01) when compared to those in the CCG. Patients in the IG were also less likely to experience hypoglycemia than those in the CCG ( P = 0.06) or the HCG ( P = 0.01). Over 80% of all patient-days for all groups contained glucose readings outside of the target range. CONCLUSIONS: Standardized interventions encouraging the physiologic use of subcutaneous insulin can lead to significant improvements in glycemic control and patient safety in hospitalized patients. However, the observed improvements are modest, and poor metabolic control remains common, despite these interventions. Additional research is needed to determine the best strategy for safely achieving metabolic control in these patients. Journal of Hospital Medicine 2010. © 2010 Society of Hospital Medicine.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/78247/1/780_ftp.pd

Economic Benefits of Intensive Insulin Therapy in Critically Ill Patients: The Targeted Insulin Therapy to Improve Hospital Outcomes (TRIUMPH) Project

OBJECTIVE—The purpose of this study was to analyze the economic outcomes of a clinical program implemented to achieve strict glycemic control with intensive insulin therapy in patients admitted to the intensive care unit (ICU)

An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model

Over the last century, outbreaks and pandemics have occurred with disturbing regularity, necessitating advance preparation and large-scale, coordinated response. Here, we developed a machine learning predictive model of disease severity and length of hospitalization for COVID-19, which can be utilized as a platform for future unknown viral outbreaks. We combined untargeted metabolomics on plasma data obtained from COVID-19 patients (n = 111) during hospitalization and healthy controls (n = 342), clinical and comorbidity data (n = 508) to build this patient triage platform, which consists of three parts: (i) the clinical decision tree, which amongst other biomarkers showed that patients with increased eosinophils have worse disease prognosis and can serve as a new potential biomarker with high accuracy (AUC = 0.974), (ii) the estimation of patient hospitalization length with ± 5 days error (R2 = 0.9765) and (iii) the prediction of the disease severity and the need of patient transfer to the intensive care unit. We report a significant decrease in serotonin levels in patients who needed positive airway pressure oxygen and/or were intubated. Furthermore, 5-hydroxy tryptophan, allantoin, and glucuronic acid metabolites were increased in COVID-19 patients and collectively they can serve as biomarkers to predict disease progression. The ability to quickly identify which patients will develop life-threatening illness would allow the efficient allocation of medical resources and implementation of the most effective medical interventions. We would advocate that the same approach could be utilized in future viral outbreaks to help hospitals triage patients more effectively and improve patient outcomes while optimizing healthcare resources