Altered expression of the L-arginine/nitric oxide pathway in ovarian cancer: metabolic biomarkers and biological implications.

MOTIVATION: Ovarian cancer (OC) is a highly lethal gynecological malignancy. Extensive research has shown that OC cells undergo significant metabolic alterations during tumorigenesis. In this study, we aim to leverage these metabolic changes as potential biomarkers for assessing ovarian cancer. METHODS: A functional module-based approach was utilized to identify key gene expression pathways that distinguish different stages of ovarian cancer (OC) within a tissue biopsy cohort. This cohort consisted of control samples (n = 79), stage I/II samples (n = 280), and stage III/IV samples (n = 1016). To further explore these altered molecular pathways, minimal spanning tree (MST) analysis was applied, leading to the formulation of metabolic biomarker hypotheses for OC liquid biopsy. To validate, a multiple reaction monitoring (MRM) based quantitative LCMS/MS method was developed. This method allowed for the precise quantification of targeted metabolite biomarkers using an OC blood cohort comprising control samples (n = 464), benign samples (n = 3), and OC samples (n = 13). RESULTS: Eleven functional modules were identified as significant differentiators (false discovery rate, FDR < 0.05) between normal and early-stage, or early-stage and late-stage ovarian cancer (OC) tumor tissues. MST analysis revealed that the metabolic L-arginine/nitric oxide (L-ARG/NO) pathway was reprogrammed, and the modules related to "DNA replication" and "DNA repair and recombination" served as anchor modules connecting the other nine modules. Based on this analysis, symmetric dimethylarginine (SDMA) and arginine were proposed as potential liquid biopsy biomarkers for OC assessment. Our quantitative LCMS/MS analysis on our OC blood cohort provided direct evidence supporting the use of the SDMA-to-arginine ratio as a liquid biopsy panel to distinguish between normal and OC samples, with an area under the ROC curve (AUC) of 98.3%. CONCLUSION: Our comprehensive analysis of tissue genomics and blood quantitative LC/MSMS metabolic data shed light on the metabolic reprogramming underlying OC pathophysiology. These findings offer new insights into the potential diagnostic utility of the SDMA-to-arginine ratio for OC assessment. Further validation studies using adequately powered OC cohorts are warranted to fully establish the clinical effectiveness of this diagnostic test.

Butyrate induces development-dependent necrotizing enterocolitis-like intestinal epithelial injury via necroptosis.

BACKGROUND: The accumulation of short-chain fatty acids (SCFAs) from bacterial fermentation may adversely affect the under-developed gut as observed in premature newborns at risk for necrotizing enterocolitis (NEC). This study explores the mechanism by which specific SCFA fermentation products may injure the premature newborn intestine mucosa leading to NEC-like intestinal cell injury. METHODS: Intraluminal injections of sodium butyrate were administered to 14- and 28-day-old mice, whose small intestine and stool were harvested for analysis. Human intestinal epithelial stem cells (hIESCs) and differentiated enterocytes from preterm and term infants were treated with sodium butyrate at varying concentrations. Necrosulfonamide (NSA) and necrostatin-1 (Nec-1) were used to determine the protective effects of necroptosis inhibitors on butyrate-induced cell injury. RESULTS: The more severe intestinal epithelial injury was observed in younger mice upon exposure to butyrate (p = 0.02). Enterocytes from preterm newborns demonstrated a significant increase in sensitivity to butyrate-induced cell injury compared to term newborn enterocytes (p = 0.068, hIESCs; p = 0.038, differentiated cells). NSA and Nec-1 significantly inhibited the cell death induced by butyrate. CONCLUSIONS: Butyrate induces developmental stage-dependent intestinal injury that resembles NEC. A primary mechanism of cell injury in NEC is necroptosis. Necroptosis inhibition may represent a potential preventive or therapeutic strategy for NEC. IMPACT: Butyrate induces developmental stage-dependent intestinal injury that resembles NEC. A primary mechanism of cell injury caused by butyrate in NEC is necroptosis. Necroptosis inhibitors proved effective at significantly ameliorating the enteral toxicity of butyrate and thereby suggest a novel mechanism and approach to the prevention and treatment of NEC in premature newborns.

Newborn screen metabolic panels reflect the impact of common disorders of pregnancy.

BACKGROUND: Hypertensive disorders of pregnancy and maternal diabetes profoundly affect fetal and newborn growth, yet disturbances in intermediate metabolism and relevant mediators of fetal growth alterations remain poorly defined. We sought to determine whether there are distinct newborn screen metabolic patterns among newborns affected by maternal hypertensive disorders or diabetes in utero. METHODS: A retrospective observational study investigating distinct newborn screen metabolites in conjunction with data linked to birth and hospitalization records in the state of California between 2005 and 2010. RESULTS: A total of 41,333 maternal-infant dyads were included. Infants of diabetic mothers demonstrated associations with short-chain acylcarnitines and free carnitine. Infants born to mothers with preeclampsia with severe features and chronic hypertension with superimposed preeclampsia had alterations in acetylcarnitine, free carnitine, and ornithine levels. These results were further accentuated by size for gestational age designations. CONCLUSIONS: Infants of diabetic mothers demonstrate metabolic signs of incomplete beta oxidation and altered lipid metabolism. Infants of mothers with hypertensive disorders of pregnancy carry analyte signals that may reflect oxidative stress via altered nitric oxide signaling. The newborn screen analyte composition is influenced by the presence of these maternal conditions and is further associated with the newborn size designation at birth. IMPACT: Substantial differences in newborn screen analyte profiles were present based on the presence or absence of maternal diabetes or hypertensive disorder of pregnancy and this finding was further influenced by the newborn size designation at birth. The metabolic health of the newborn can be examined using the newborn screen and is heavily impacted by the condition of the mother during pregnancy. Utilizing the newborn screen to identify newborns affected by common conditions of pregnancy may help relate an infant's underlying biological disposition with their clinical phenotype allowing for greater risk stratification and intervention.

Treating Center Volume and Congenital Diaphragmatic Hernia Outcomes in California.

OBJECTIVE: To examined outcomes for infants born with congenital diaphragmatic hernias (CDH), according to specific treatment center volume indicators. STUDY DESIGN: A population-based retrospective cohort study was conducted involving neonatal intensive care units in California. Multivariable analysis was used to examine the outcomes of infants with CDH including mortality, total days on ventilation, and respiratory support at discharge. Significant covariables of interest included treatment center surgical and overall neonatal intensive care unit volumes. RESULTS: There were 728 infants in the overall CDH cohort, and 541 infants (74%) in the lower risk subcohort according to a severity-weighted congenital malformation score and never requiring extracorporeal membrane oxygenation. The overall cohort mortality was 28.3% (n = 206), and 19.8% (n = 107) for the subcohort. For the lower risk subcohort, the adjusted odds of mortality were significantly lower at treatment centers with higher CDH repair volume (OR, 0.41; 95% CI, 0.23-0.75; P = .003), ventilator days were significantly lower at centers with higher thoracic surgery volume (OR, 0.56; 9 5% CI, 0.33-0.95; P = .03), and respiratory support at discharge trended lower at centers with higher neonatal intensive care unit admission volumes (OR, 0.51; 9 5% CI, 0.26-1.02; P = .06). CONCLUSIONS: Overall and surgery-specific institutional experience significantly contribute to optimized outcomes for infants with CDH. These data and follow-on studies may help inform the ongoing debate over the optimal care setting and relevant quality indicators for newborn infants with major surgical anomalies.

Racial/ethnic disparities and human milk use in necrotizing enterocolitis.

BACKGROUND: The impact of human milk use on racial/ethnic disparities in necrotizing enterocolitis (NEC) incidence is unknown. METHODS: Trends in NEC incidence and human milk use at discharge were evaluated by race/ethnicity among 47,112 very low birth weight infants born in California from 2008 to 2017. We interrogated the association between race/ethnicity and NEC using multilevel regression analysis, and evaluated the effect of human milk use at discharge on the relationship between race/ethnicity and NEC using mediation analysis. RESULTS: Annual NEC incidence declined across all racial/ethnic groups from an aggregate average of 4.8% in 2008 to 2.6% in 2017. Human milk use at discharge increased over the time period across all racial groups, and non-Hispanic (NH) black infants received the least human milk each year. In multivariable analyses, Hispanic ethnicity (odds ratio (OR) 1.27, 95% confidence interval (CI) 1.02-1.57) and Asian or Pacific Islander race (OR 1.35, 95% CI 1.01-1.80) were each associated with higher odds of NEC, while the association of NH black race with NEC was attenuated after adding human milk use at discharge to the model. Mediation analysis revealed that human milk use at discharge accounted for 22% of the total risk of NEC in non-white vs. white infants, and 44% in black vs. white infants. CONCLUSIONS: Although NEC incidence has declined substantially over the past decade, a sizable racial/ethnic disparity persists. Quality improvement initiatives augmenting human milk use may further reduce the incidence of NEC in vulnerable populations.

In fetuses with congenital lung masses, decreased ventricular and atrioventricular valve dimensions are associated with lesion size and clinical outcome.

INTRODUCTION: The clinical importance of mass effect from congenital lung masses on the fetal heart is unknown. We aimed to report cardiac measurements in fetuses with congenital lung masses and to correlate lung mass severity/size with cardiac dimensions and clinical outcomes. METHODS: Cases were identified from our institutional database between 2009 and 2016. We recorded atrioventricular valve (AVVz) annulus dimensions and ventricular widths (VWz) converted into z scores, ratio of aortic to total cardiac output (AoCO), lesion side, and congenital pulmonary airway malformation volume ratio (CVR). Respiratory intervention (RI) was defined as intubation, extracorporeal membrane oxygenation (ECMO), or use of surgical intervention prior to discharge. RESULTS: Fifty-two fetuses comprised the study cohort. Mean AVVz and VWz were below expected for gestational age. CVR correlated with ipsilateral AVVz (RS = -.59, P < .001) and ipsilateral VWz (-0.59, P < .001). Lower AVVz and AoCO and higher CVR were associated with RI. No patient had significant structural heart disease identified postnatally. CONCLUSION: In fetuses with left-sided lung masses, ipsilateral cardiac structures tend to be smaller, but in our cohort, there were no patients with structural heart disease. However, smaller left-sided structures may contribute to the need for RI that affects a portion of these fetuses.

Predicting Pathology From Imaging in Children Undergoing Resection of Congenital Lung Lesions.

BACKGROUND: Prenatal magnetic resonance imaging (MRI) is increasingly obtained to define congenital lung lesions (CLL) for surgical management. Postnatal, preoperative computed tomography (CT) provides further clarity at the cost of radiation. Depending on the lesion identified, the indication for resection remains controversial. We investigated the differences in detail found on prenatal MRI and postnatal CT compared with final pathology to determine their utility in preoperative decision-making. MATERIALS AND METHODS: All children undergoing resection of CLLs at a single institution between July 2009 and February 2018 were retrospectively identified. Their imaging, operative, and pathology reports were compared. All imaging studies were examined by pediatric radiologists with experience in prenatal CLL diagnosis. RESULTS: Fifty-five patients underwent CLL resection during the study period with 31 undergoing prenatal MRI, 45 postnatal CT, and 22 both. Resection was performed before 6 mo of age in 62% of patients. In the cohort undergoing both imaging studies, pathologic CLL diagnosis correlated with prenatal MRI and CT in 82% and 100% of patients, respectively (P = 0.13). Eight patients had systemic feeding vessels, of which 38% were identified on MRI, and 88% on CT (P = 0.13). Both studies had a specificity of 100% for detecting systemic feeding vessels. CONCLUSIONS: For children where prenatal MRI detected a systemic feeding vessel, CT was redundant for preoperative planning but had greater sensitivity. Ultimately, the CLL type predicted from postnatal CT was not significantly different from that predicted by prenatal MRI; however, both imaging modalities had some level of discrepancy with pathology.

Recent Advances in Prevention and Therapies for Clinical or Experimental Necrotizing Enterocolitis.

Necrotizing enterocolitis (NEC) is one of the most severe diseases of preterm neonates and has a high mortality rate. With the development of inspection techniques and new biomarkers, the diagnostic accuracy of NEC is constantly improving. The most recognized potential risk factors include prematurity, formula-feeding, infection, and microbial dysbiosis. With further understanding of the pathogenesis, more effective prevention and therapies will be applied to clinical or experimental NEC. At present, such new potential prevention and therapies for NEC are mainly focused on the Toll-like receptor 4 inflammatory signaling pathway, the repair of intestinal barrier function, probiotics, antioxidative stress, breast-feeding, and immunomodulatory agents. Many new studies have changed our understanding of the pathogenesis of NEC and improve our approaches for preventing and treating of NEC each year. This review provides an overview of the recent researches focused on clinical or experimental NEC and highlights the advances made within the past 5 years toward the development of new potential preventive approaches and therapies for this disease.

A Real-Time Early Warning System for Monitoring Inpatient Mortality Risk: Prospective Study Using Electronic Medical Record Data.

BACKGROUND: The rapid deterioration observed in the condition of some hospitalized patients can be attributed to either disease progression or imperfect triage and level of care assignment after their admission. An early warning system (EWS) to identify patients at high risk of subsequent intrahospital death can be an effective tool for ensuring patient safety and quality of care and reducing avoidable harm and costs. OBJECTIVE: The aim of this study was to prospectively validate a real-time EWS designed to predict patients at high risk of inpatient mortality during their hospital episodes. METHODS: Data were collected from the system-wide electronic medical record (EMR) of two acute Berkshire Health System hospitals, comprising 54,246 inpatient admissions from January 1, 2015, to September 30, 2017, of which 2.30% (1248/54,246) resulted in intrahospital deaths. Multiple machine learning methods (linear and nonlinear) were explored and compared. The tree-based random forest method was selected to develop the predictive application for the intrahospital mortality assessment. After constructing the model, we prospectively validated the algorithms as a real-time inpatient EWS for mortality. RESULTS: The EWS algorithm scored patients' daily and long-term risk of inpatient mortality probability after admission and stratified them into distinct risk groups. In the prospective validation, the EWS prospectively attained a c-statistic of 0.884, where 99 encounters were captured in the highest risk group, 69% (68/99) of whom died during the episodes. It accurately predicted the possibility of death for the top 13.3% (34/255) of the patients at least 40.8 hours before death. Important clinical utilization features, together with coded diagnoses, vital signs, and laboratory test results were recognized as impactful predictors in the final EWS. CONCLUSIONS: In this study, we prospectively demonstrated the capability of the newly-designed EWS to monitor and alert clinicians about patients at high risk of in-hospital death in real time, thereby providing opportunities for timely interventions. This real-time EWS is able to assist clinical decision making and enable more actionable and effective individualized care for patients' better health outcomes in target medical facilities.

Prediction of the 1-Year Risk of Incident Lung Cancer: Prospective Study Using Electronic Health Records from the State of Maine.

BACKGROUND: Lung cancer is the leading cause of cancer death worldwide. Early detection of individuals at risk of lung cancer is critical to reduce the mortality rate. OBJECTIVE: The aim of this study was to develop and validate a prospective risk prediction model to identify patients at risk of new incident lung cancer within the next 1 year in the general population. METHODS: Data from individual patient electronic health records (EHRs) were extracted from the Maine Health Information Exchange network. The study population consisted of patients with at least one EHR between April 1, 2016, and March 31, 2018, who had no history of lung cancer. A retrospective cohort (N=873,598) and a prospective cohort (N=836,659) were formed for model construction and validation. An Extreme Gradient Boosting (XGBoost) algorithm was adopted to build the model. It assigned a score to each individual to quantify the probability of a new incident lung cancer diagnosis from October 1, 2016, to September 31, 2017. The model was trained with the clinical profile in the retrospective cohort from the preceding 6 months and validated with the prospective cohort to predict the risk of incident lung cancer from April 1, 2017, to March 31, 2018. RESULTS: The model had an area under the curve (AUC) of 0.881 (95% CI 0.873-0.889) in the prospective cohort. Two thresholds of 0.0045 and 0.01 were applied to the predictive scores to stratify the population into low-, medium-, and high-risk categories. The incidence of lung cancer in the high-risk category (579/53,922, 1.07%) was 7.7 times higher than that in the overall cohort (1167/836,659, 0.14%). Age, a history of pulmonary diseases and other chronic diseases, medications for mental disorders, and social disparities were found to be associated with new incident lung cancer. CONCLUSIONS: We retrospectively developed and prospectively validated an accurate risk prediction model of new incident lung cancer occurring in the next 1 year. Through statistical learning from the statewide EHR data in the preceding 6 months, our model was able to identify statewide high-risk patients, which will benefit the population health through establishment of preventive interventions or more intensive surveillance.

Mapping the Fetomaternal Peripheral Immune System at Term Pregnancy.

Preterm labor and infections are the leading causes of neonatal deaths worldwide. During pregnancy, immunological cross talk between the mother and her fetus is critical for the maintenance of pregnancy and the delivery of an immunocompetent neonate. A precise understanding of healthy fetomaternal immunity is the important first step to identifying dysregulated immune mechanisms driving adverse maternal or neonatal outcomes. This study combined single-cell mass cytometry of paired peripheral and umbilical cord blood samples from mothers and their neonates with a graphical approach developed for the visualization of high-dimensional data to provide a high-resolution reference map of the cellular composition and functional organization of the healthy fetal and maternal immune systems at birth. The approach enabled mapping of known phenotypical and functional characteristics of fetal immunity (including the functional hyperresponsiveness of CD4+ and CD8+ T cells and the global blunting of innate immune responses). It also allowed discovery of new properties that distinguish the fetal and maternal immune systems. For example, examination of paired samples revealed differences in endogenous signaling tone that are unique to a mother and her offspring, including increased ERK1/2, MAPK-activated protein kinase 2, rpS6, and CREB phosphorylation in fetal Tbet+CD4+ T cells, CD8+ T cells, B cells, and CD56loCD16+ NK cells and decreased ERK1/2, MAPK-activated protein kinase 2, and STAT1 phosphorylation in fetal intermediate and nonclassical monocytes. This highly interactive functional map of healthy fetomaternal immunity builds the core reference for a growing data repository that will allow inferring deviations from normal associated with adverse maternal and neonatal outcomes.

Prediction of Incident Hypertension Within the Next Year: Prospective Study Using Statewide Electronic Health Records and Machine Learning.

BACKGROUND: As a high-prevalence health condition, hypertension is clinically costly, difficult to manage, and often leads to severe and life-threatening diseases such as cardiovascular disease (CVD) and stroke. OBJECTIVE: The aim of this study was to develop and validate prospectively a risk prediction model of incident essential hypertension within the following year. METHODS: Data from individual patient electronic health records (EHRs) were extracted from the Maine Health Information Exchange network. Retrospective (N=823,627, calendar year 2013) and prospective (N=680,810, calendar year 2014) cohorts were formed. A machine learning algorithm, XGBoost, was adopted in the process of feature selection and model building. It generated an ensemble of classification trees and assigned a final predictive risk score to each individual. RESULTS: The 1-year incident hypertension risk model attained areas under the curve (AUCs) of 0.917 and 0.870 in the retrospective and prospective cohorts, respectively. Risk scores were calculated and stratified into five risk categories, with 4526 out of 381,544 patients (1.19%) in the lowest risk category (score 0-0.05) and 21,050 out of 41,329 patients (50.93%) in the highest risk category (score 0.4-1) receiving a diagnosis of incident hypertension in the following 1 year. Type 2 diabetes, lipid disorders, CVDs, mental illness, clinical utilization indicators, and socioeconomic determinants were recognized as driving or associated features of incident essential hypertension. The very high risk population mainly comprised elderly (age>50 years) individuals with multiple chronic conditions, especially those receiving medications for mental disorders. Disparities were also found in social determinants, including some community-level factors associated with higher risk and others that were protective against hypertension. CONCLUSIONS: With statewide EHR datasets, our study prospectively validated an accurate 1-year risk prediction model for incident essential hypertension. Our real-time predictive analytic model has been deployed in the state of Maine, providing implications in interventions for hypertension and related diseases and hopefully enhancing hypertension care.

Assessing Statewide All-Cause Future One-Year Mortality: Prospective Study With Implications for Quality of Life, Resource Utilization, and Medical Futility.

BACKGROUND: For many elderly patients, a disproportionate amount of health care resources and expenditures is spent during the last year of life, despite the discomfort and reduced quality of life associated with many aggressive medical approaches. However, few prognostic tools have focused on predicting all-cause 1-year mortality among elderly patients at a statewide level, an issue that has implications for improving quality of life while distributing scarce resources fairly. OBJECTIVE: Using data from a statewide elderly population (aged ≥65 years), we sought to prospectively validate an algorithm to identify patients at risk for dying in the next year for the purpose of minimizing decision uncertainty, improving quality of life, and reducing futile treatment. METHODS: Analysis was performed using electronic medical records from the Health Information Exchange in the state of Maine, which covered records of nearly 95% of the statewide population. The model was developed from 125,896 patients aged at least 65 years who were discharged from any care facility in the Health Information Exchange network from September 5, 2013, to September 4, 2015. Validation was conducted using 153,199 patients with same inclusion and exclusion criteria from September 5, 2014, to September 4, 2016. Patients were stratified into risk groups. The association between all-cause 1-year mortality and risk factors was screened by chi-squared test and manually reviewed by 2 clinicians. We calculated risk scores for individual patients using a gradient tree-based boost algorithm, which measured the probability of mortality within the next year based on the preceding 1-year clinical profile. RESULTS: The development sample included 125,896 patients (72,572 women, 57.64%; mean 74.2 [SD 7.7] years). The final validation cohort included 153,199 patients (88,177 women, 57.56%; mean 74.3 [SD 7.8] years). The c-statistic for discrimination was 0.96 (95% CI 0.93-0.98) in the development group and 0.91 (95% CI 0.90-0.94) in the validation cohort. The mortality was 0.99% in the low-risk group, 16.75% in the intermediate-risk group, and 72.12% in the high-risk group. A total of 99 independent risk factors (n=99) for mortality were identified (reported as odds ratios; 95% CI). Age was on the top of list (1.41; 1.06-1.48); congestive heart failure (20.90; 15.41-28.08) and different tumor sites were also recognized as driving risk factors, such as cancer of the ovaries (14.42; 2.24-53.04), colon (14.07; 10.08-19.08), and stomach (13.64; 3.26-86.57). Disparities were also found in patients' social determinants like respiratory hazard index (1.24; 0.92-1.40) and unemployment rate (1.18; 0.98-1.24). Among high-risk patients who expired in our dataset, cerebrovascular accident, amputation, and type 1 diabetes were the top 3 diseases in terms of average cost in the last year of life. CONCLUSIONS: Our study prospectively validated an accurate 1-year risk prediction model and stratification for the elderly population (≥65 years) at risk of mortality with statewide electronic medical record datasets. It should be a valuable adjunct for helping patients to make better quality-of-life choices and alerting care givers to target high-risk elderly for appropriate care and discussions, thus cutting back on futile treatment.

CK2α/CSNK2A1 Phosphorylates SIRT6 and Is Involved in the Progression of Breast Carcinoma and Predicts Shorter Survival of Diagnosed Patients.

Recently, the roles of sirtuins (SIRTs) in tumorigenesis have been of interest to oncologists, and protein kinase CK2 α1 (CSNK2A1) has been shown to be involved in tumorigenesis by phosphorylating various proteins, including SIRT1. Therefore, we evaluated the roles of CSNK2A1, SIRT6, and phosphorylated SIRT6 and their relationships in breast carcinoma. Nuclear expression of CSNK2A1 and SIRT6 predicted shorter overall survival and relapse-free survival by multivariate analysis. Inhibition of CSNK2A1 decreased the proliferative and invasive activity of cancer cells. In addition, CSNK2A1 was bound to SIRT6 and phosphorylated SIRT6; evidence for this is provided from immunofluorescence staining, co-immunoprecipitation of CSNK2A1 and SIRT6, a glutathione S-transferase pull-down assay, an in vitro kinase assay, and transfection of mutant CSNK2A1. Knockdown of SIRT6 decreased the proliferation and invasiveness of cancer cells. Overexpression of SIRT6 increased proliferation, but mutation at the Ser338 phosphorylation site of SIRT6 inhibited the proliferation of MCF7 cells. Moreover, both knockdown of SIRT6 and a mutation at the phosphorylation site of SIRT6 decreased expression of matrix metallopeptidase 9, ß-catenin, cyclin D1, and NF-κB. Especially, SIRT6 expression was associated with the nuclear localization of ß-catenin. This study demonstrates that CSNK2A1 and SIRT6 are indicators of poor prognosis for breast carcinomas and that CSNK2A1-mediated phosphorylation of SIRT6 might be involved in the progression of breast carcinoma.

The Effect of Level of Care on Gastroschisis Outcomes.

OBJECTIVE: To examine the relationship between level of care in neonatal intensive care units (NICUs) and outcomes for newborns with gastroschisis. STUDY DESIGN: A retrospective cohort study was conducted at 130 California Perinatal Quality Care Collaborative NICUs from 2008 to 2014. All gastroschisis births were examined according to American Academy of Pediatrics NICU level of care at the birth hospital. Multivariate analyses examined odds of mortality, duration of mechanical ventilation, and duration of stay. RESULTS: For 1588 newborns with gastroschisis, the adjusted odds of death were higher for those born into a center with a level IIA/B NICU (OR, 6.66; P = .004), a level IIIA NICU (OR, 5.95; P = .008), or a level IIIB NICU (OR, 5.85; P = .002), when compared with level IIIC centers. The odds of having more days on ventilation were significantly higher for births at IIA/B and IIIB centers (OR, 2.05 [P < .001] and OR, 1.91 [P < .001], respectively). The odds of having longer duration of stay were significantly higher at IIA/B and IIIB centers (OR, 1.71 [P < .004]; OR, 1.77 [P < .001]). CONCLUSIONS: NICU level of care was associated with significant disparities in odds of mortality for newborns with gastroschisis.

Acylcarnitine Profiles Reflect Metabolic Vulnerability for Necrotizing Enterocolitis in Newborns Born Premature.

OBJECTIVE: To evaluate the association between newborn acylcarnitine profiles and the subsequent development of necrotizing enterocolitis (NEC) with the use of routinely collected newborn screening data in infants born preterm. STUDY DESIGN: A retrospective cohort study was conducted with the use of discharge records for infants born preterm admitted to neonatal intensive care units in California from 2005 to 2009 who had linked state newborn screening results. A model-development cohort of 94 110 preterm births from 2005 to 2008 was used to develop a risk-stratification model that was then applied to a validation cohort of 22 992 births from 2009. RESULTS: Fourteen acylcarnitine levels and acylcarnitine ratios were associated with increased risk of developing NEC. Each log unit increase in C5 and free carnitine /(C16 + 18:1) was associated with a 78% and a 76% increased risk for developing NEC, respectively (OR 1.78, 95% CI 1.53-2.02, and OR 1.76, 95% CI 1.51-2.06). Six acylcarnitine levels, along with birth weight and total parenteral nutrition, identified 89.8% of newborns with NEC in the model-development cohort (area under the curve 0.898, 95% CI 0.889-0.907) and 90.8% of the newborns with NEC in the validation cohort (area under the curve 0.908, 95% CI 0.901-0.930). CONCLUSIONS: Abnormal fatty acid metabolism was associated with prematurity and the development of NEC. Metabolic profiling through newborn screening may serve as an objective biologic surrogate of risk for the development of disease and thus facilitate disease-prevention strategies.

Prediction of neonatal respiratory distress in pregnancies complicated by fetal lung masses.

OBJECTIVE: The objective of this article is to evaluate the utility of fetal lung mass imaging for predicting neonatal respiratory distress. METHOD: Pregnancies with fetal lung masses between 2009 and 2014 at a single center were analyzed. Neonatal respiratory distress was defined as intubation and mechanical ventilation at birth, surgery before discharge, or extracorporeal membrane oxygenation (ECMO). The predictive utility of the initial as well as maximal lung mass volume and congenital pulmonary airway malformation volume ratio by ultrasound (US) and magnetic resonance imaging (MRI) was analyzed. RESULTS: Forty-seven fetal lung mass cases were included; of those, eight (17%) had respiratory distress. The initial US was performed at similar gestational ages in pregnancies with and without respiratory distress (26.4 ± 5.6 vs 22.3 ± 3 weeks, p = 0.09); however, those with respiratory distress had higher congenital volume ratio at that time (1.0 vs 0.3, p = 0.01). The strongest predictors of respiratory distress were maximal volume >24.0 cm3 by MRI (100% sensitivity, 91% specificity, 60% positive predictive value, and 100% negative predictive value) and maximal volume >34.0 cm3 by US (100% sensitivity, 85% specificity, 54% positive predictive value, and 100% negative predictive value). CONCLUSION: Ultrasound and MRI parameters can predict neonatal respiratory distress, even when obtained before 24 weeks. Third trimester parameters demonstrated the best positive predictive value. © 2017 John Wiley & Sons, Ltd.

Prospective stratification of patients at risk for emergency department revisit: resource utilization and population management strategy implications.

BACKGROUND: Estimating patient risk of future emergency department (ED) revisits can guide the allocation of resources, e.g. local primary care and/or specialty, to better manage ED high utilization patient populations and thereby improve patient life qualities. METHODS: We set to develop and validate a method to estimate patient ED revisit risk in the subsequent 6 months from an ED discharge date. An ensemble decision-tree-based model with Electronic Medical Record (EMR) encounter data from HealthInfoNet (HIN), Maine's Health Information Exchange (HIE), was developed and validated, assessing patient risk for a subsequent 6 month return ED visit based on the ED encounter-associated demographic and EMR clinical history data. A retrospective cohort of 293,461 ED encounters that occurred between January 1, 2012 and December 31, 2012, was assembled with the associated patients' 1-year clinical histories before the ED discharge date, for model training and calibration purposes. To validate, a prospective cohort of 193,886 ED encounters that occurred between January 1, 2013 and June 30, 2013 was constructed. RESULTS: Statistical learning that was utilized to construct the prediction model identified 152 variables that included the following data domains: demographics groups (12), different encounter history (104), care facilities (12), primary and secondary diagnoses (10), primary and secondary procedures (2), chronic disease condition (1), laboratory test results (2), and outpatient prescription medications (9). The c-statistics for the retrospective and prospective cohorts were 0.742 and 0.730 respectively. Total medical expense and ED utilization by risk score 6 months after the discharge were analyzed. Cluster analysis identified discrete subpopulations of high-risk patients with distinctive resource utilization patterns, suggesting the need for diversified care management strategies. CONCLUSIONS: Integration of our method into the HIN secure statewide data system in real time prospectively validated its performance. It promises to provide increased opportunity for high ED utilization identification, and optimized resource and population management.

CK2α phosphorylates DBC1 and is involved in the progression of gastric carcinoma and predicts poor survival of gastric carcinoma patients.

CK2α has diverse effects on the tumorigenesis owing to its kinase activity, which phosphorylates various proteins involved in tumorigenesis. We, therefore, investigated the expression and role of CK2α in the phosphorylation of deleted in breast cancer 1 (DBC1) in gastric carcinomas. We used 187 gastric carcinomas and human gastric cancer cells to investigate the roles and relationship between CK2α and DBC1 in gastric carcinomas. Positive expression of CK2α and phospho-DBC1 predicted shorter overall survival and relapse-free survival by univariate analysis. Especially, CK2α expression was an independent prognostic indicator for gastric carcinoma patients. In gastric carcinoma cells, CK2α was bound to DBC1 and phosphorylated DBC1. The phosphorylation of DBC1 by CK2α was evidenced by co-immunoprecipitation of CK2α and DBC1 in a GST pull-down assay, an in vitro kinase assay, and immunofluorescence staining. Inhibition of both CK2α and DBC1 decreased proliferation and invasive activity of cancer cells. Decreased migration and invasive activity was associated with a downregulation of MMP2, MMP9 and the epithelial-mesenchymal transition. A mutation at the phosphorylation site of DBC1 also downregulated the signals related with the epithelial-mesenchymal transition. Our study demonstrated that CK2α is an independent prognostic indicator for gastric carcinoma patients and is involved in tumorigenesis by regulating the phosphorylation of DBC1. In addition, the blocking of CK2α and DBC1 inhibited the proliferation and invasive potential of gastric cancer cells. Therefore, our study suggests that CK2α-DBC1 pathway might be a new therapeutic target for the treatment of gastric carcinoma.