Kawasaki syndrome: Cluster analysis of incident cases presenting to a pediatric tertiary care hospital in Texas from January 1, 2005 to December 31, 2009

Background: Despite almost 40 years of research into the etiology of Kawasaki Syndrome (KS), there is little research published on spatial and temporal clustering of KS cases. Previous analysis has found significant spatial and temporal clustering of cases, therefore cluster analyses were performed to substantiate these findings and provide insight into incident KS cases discharged from a pediatric tertiary care hospital. Identifying clusters from a single institution would allow for prospective analysis of risk factors and potential exposures for further insight into KS etiology. ^ Methods: A retrospective study was carried out to examine the epidemiology and distribution of patients presenting to Texas Children’s Hospital in Houston, Texas, with a diagnosis of Acute Febrile Mucocutaneous Lymph Node Syndrome (MCLS) upon discharge from January 1, 2005 to December 31, 2009. Spatial, temporal, and space-time cluster analyses were performed using the Bernoulli model with case and control event data. ^ Results: 397 of 102,761 total patients admitted to Texas Children’s Hospital had a principal or secondary diagnosis of Acute Febrile MCLS upon over the 5 year period. Demographic data for KS cases remained consistent with known disease epidemiology. Spatial, temporal, and space-time analyses of clustering using the Bernoulli model demonstrated no statistically significant clusters. ^ Discussion: Despite previous findings of spatial-temporal clustering of KS cases, there were no significant clusters of KS cases discharged from a single institution. This implicates the need for an expanded approach to conducting spatial-temporal cluster analysis and KS surveillance given the limitations of evaluating data from a single institution.^

Pediatric motivational interviewing to address obesity and overweight

Not only are obesity and overweight associated with a myriad of medical and psychological concerns in childhood, but these health problems can persist even into adulthood. With the obvious need for better approaches in tackling childhood obesity and overweight and the strong evidence of motivational interviewing's effectiveness in the adult population, it is likely that an updated review will provide a more complete picture of the application of motivational interviewing in the pediatric population. The objective of this review is whether or not motivational interviewing will be instrumental in promoting factors that help in reducing the number of children who are or become overweight or obese. A literature search was completed that identified ten studies that incorporated MI as an intervention. Studies focused on either behavior health changes like increased physical activity, improved nutrition, or reducing parameters of weight like BMI or body composition. Three out of the 10 articles were still in progress and no results were provided. Five studies were able to achieve statistical significance in health benefits to control childhood overweight and obesity. Results revealed the overall feasibility of applying MI in the pediatric overweight and obese population, but the scarce number of studies limits conclusions about its efficacy. Therefore, additional scientific evidence is necessary to fully understand MI's role in affecting behavior changes in this population.^

Nurse likelihood to report a pediatric medication error: Examination of the "pre-reporting" period

Each year, hospitalized patients experience 1.5 million preventable injuries from medication errors and hospitals incur an additional $3.5 billion in cost (Aspden, Wolcott, Bootman, & Cronenwatt; (2007). It is believed that error reporting is one way to learn about factors contributing to medication errors. And yet, an estimated 50% of medication errors go unreported. This period of medication error pre-reporting, with few exceptions, is underexplored. The literature focuses on error prevention and management, but lacks a description of the period of introspection and inner struggle over whether to report an error and resulting likelihood to report. Reporting makes a nurse vulnerable to reprimand, legal liability, and even threat to licensure. For some nurses this state may invoke a disparity between a person‘s belief about him or herself as a healer and the undeniable fact of the error.^ This study explored the medication error reporting experience. Its purpose was to inform nurses, educators, organizational leaders, and policy-makers about the medication error pre-reporting period, and to contribute to a framework for further investigation. From a better understanding of factors that contribute to or detract from the likelihood of an individual to report an error, interventions can be identified to help the nurse come to a psychologically healthy resolution and help increase reporting of error in order to learn from error and reduce the possibility of future similar error.^ The research question was: "What factors contribute to a nurse's likelihood to report an error?" The specific aims of the study were to: (1) describe participant nurses' perceptions of medication error reporting; (2) describe participant explanations of the emotional, cognitive, and physical reactions to making a medication error; (3) identify pre-reporting conditions that make it less likely for a nurse to report a medication error; and (4) identify pre-reporting conditions that make it more likely for a nurse to report a medication error.^ A qualitative research study was conducted to explore the medication error experience and in particular the pre-reporting period from the perspective of the nurse. A total of 54 registered nurses from a large private free-standing not-for-profit children's hospital in the southwestern United States participated in group interviews. The results describe the experience of the nurse as well as the physical, emotional, and cognitive responses to the realization of the commission of a medication error. The results also reveal factors that make it more and less likely to report a medication error.^ It is clear from this study that upon realization that he or she has made a medication error, a nurse's foremost concern is for the safety of the patient. Fear was also described by each group of nurses. The nurses described a fear of several things including physician reaction, manager reaction, peer reaction, as well as family reaction and possible lack of trust as a result. Another universal response was the description of a struggle with guilt, shame, imperfection, blaming oneself, and questioning one's competence.^

Descriptive analysis of Ben Taub Pediatric Weight Management Program

The purpose of this study is to descriptively analyze the current program at Ben Taub Pediatric Weight Management Program in Houston, Texas, a program designed to help overweight children ages three to eighteen to lose weight. In Texas, approximately one in every three children is overweight or obese. Obesity is seen at an even greater level within Ben Taub due to the hospital's high rate of service for underserved minority populations (Dehghan et al, 2005; Tyler and Horner, 2008; Hunt, 2009). The weight management program consists of nutritional, behavioral, physical activity, and medical counseling. Analysis will focus on changes in weight, BMI, cholesterol levels, and blood pressure from 2007–2010 for all participants who attended at least two weight management sessions. Recommendations will be given in response to the results of the data analysis.^

MLST analysis of Staphylococcus aureus isolates identified in a pediatric cohort in northwest Houston

The purpose of this research was to identify S. aureus isolates among a pediatric outpatient population served by the Northwest Assistance Ministries clinic as a means of identifying unique clones using multi-locus sequence typing (MLST). DNA was extracted from previously collected isolates and seven housekeeping genes were amplified and sequenced. It was hypothesized that due to the unique demographics of the population studied, there would be a high diversity of clones identified and unique strains would exist in the population. Current literature and results from this study found this to be true. 9 strains were identified in a sample of 20 patients and 5 were unique strains. Three of 4 pairs of siblings enrolled in the study were colonized with the same strain, and all cultures known to be MRSA were novel sequence strain F. These types of genetic analyses can help identify mechanisms associated with strain colonization and spread throughout respective communities. ^

Pathogenesis of antibiotic-associated diarrhea (AAD)---a systematic review

A common complication of antibiotic use is the development of diarrheal illness. The pathogenesis of antibiotic associated diarrhea (AAD) may be mediated through alteration of intestinal microbiota, overgrowth of opportunistic pathogens, and direct drug toxicity on the gut. Alterations in the intestinal microbiota result in metabolic imbalances, loss of colonization resistance and in turn allow proliferation of opportunistic pathogens. Currently less than 33% of AAD cases can be attributable to Clostridium difficile leaving a large number of cases undiagnosed and poorly treated. Although the pathogenesis of Clostridium difficile infection (CDI) has been well documented, the role of other putative microbial etiologies (Clostridium perfringens, Staphylococcus aureus, Klebsiella oxytoca, Candida species) and their pathogenic mechanisms in AAD has been unclear. This review provides a comprehensive and systematic approach to the existing data on AAD and includes concise descriptions of the pathogenesis of CDI and non-CDI AAD in the form of figures.^

Development of a standard sign-out procedure for clinicians in a pediatric intensive care unit

Background: Poor communication among health care providers is cited as the most common cause of sentinel events involving patients. Sign-out of patient data at the change of clinician shifts is a component of communication that is especially vulnerable to errors. Sign-outs are particularly extensive and complex in intensive care units (ICUs). There is a paucity of validated tools to assess ICU sign-outs. ^ Objective: To design a valid and reliable survey tool to assess the perceptions of Pediatric ICU (PICU) clinicians about sign-out. ^ Design: Cross-sectional, web-based survey ^ Setting: Academic hospital, 31-bed PICU ^ Subjects: Attending faculty, fellows, nurse practitioners and physician assistants. ^ Interventions: A survey was designed with input from a focus group and administered to PICU clinicians. Test-retest reliability, internal consistency and validity of the survey tool were assessed. ^ Measurements and Main Results: Forty-eight PICU clinicians agreed to participate. We had 42(88%) and 40(83%) responses in the test and retest phases. The mean scores for the ten survey items ranged from 2.79 to 3.67 on a five point Likert scale with no significant test-retest difference and a Pearson correlation between pre and post answers of 0.65. The survey item scores showed internal consistency with a Cronbach's Alpha of 0.85. Exploratory factor analysis revealed three constructs: efficacy of sign-out process, recipient satisfaction and content applicability. Seventy eight % clinicians affirmed the need for improvement of the sign-out process and 83% confirmed the need for face- to-face verbal sign-out. A system-based sign-out format was favored by fellows and advanced level practitioners while attendings preferred a problem-based format (p=0.003). ^ Conclusions: We developed a valid and reliable survey to assess clinician perceptions about the ICU sign-out process. These results can be used to design a verbal template to improve and standardize the sign-out process.^

Comparative virulence of enterotoxigenic non-Escherichia coli Enterobacteriaceae species from patients with travelers' diarrhea

Background: Family members of Enterobacteriaceae are found in small numbers associated with acute diarrhea. These species are sometimes mistaken for ETEC. ^ Methods: Forty-four non-E. coli species from travelers' diarrhea are compared to 30 strains of Escherichia coli (ETEC) and 30 strains of normal flora E. coli. Tissue culture supernatants were assayed by enzyme-linked immunosorbent assay for amounts of IL-8, IL-1, and IL-1ra. Amounts of heat-stable (ST) and heat-labile (LT) enterotoxins were assayed from cell culture supernatants by enzyme-linked immunoassay. PCR was use to determine which species was positive colonization factor antigens, CFA/I, CS3, and CS6. ^ Results: Normal flora E. coli significantly induced the production of more IL-8 than non- E. coli and ETEC. Normal E. coli also induced the production of more IL-1and IL-1ra than ETEC. Non-E. coli produced more ST than ETEC. A small percentage of enterotoxigenic non- E. coli gram negatives and ETEC were positive for CFA/I and CS6. None of the strains were positive for CS3. ^ Conclusions: Non-E. coli enterotoxigenic gram negatives were similar to ETEC in their virulence factors. Identification and further study of these non-E.coli strains is important for understanding their pathogenic role in acute diarrhea.^

Pediatric asthma incidence in Texas and associations with ambient ozone levels in an urban area an analysis using Medicaid claims data

Few recent estimates of childhood asthma incidence exist in the literature, although the importance of incidence surveillance for understanding asthma risk factors has been recognized. Asthma prevalence, morbidity and mortality reports have repeatedly shown that low-income children are disproportionately impacted by the disease. The aim of this study was to demonstrate the utility of Medicaid claims data for providing statewide estimates of asthma incidence. Medicaid Analytic Extract (MAX) data for Texas children ages 0-17 enrolled in Medicaid between 2004 and 2007 were used to estimate incidence overall and by age group, gender, race and county of residence. A 13+ month period of continuous enrollment was required in order to distinguish incident from prevalent cases identified in the claims data. Age-adjusted incidence of asthma was 4.26/100 person-years during 2005-2007, higher than reported in other populations. Incidence rates decreased with age, were higher for males than females, differed by race, and tended to be higher in rural than urban areas. With this study, we were able to demonstrate the utility of MAX data for estimating asthma incidence, and create a dataset of incident cases to use in further analysis. ^ In subsequent analyses, we investigated a possible association between ambient air pollutants and incident asthma among Medicaid-enrolled children in Harris County Texas between 2005 and 2007. This population is at high risk for asthma, and living in an area with historically poor air quality. We used a time-stratified case-crossover design and conditional logistic regression to calculate odds ratios, adjusted for weather variables and aeroallergens, to assess the effect of increases in ozone, NO2 and PM2.5 concentrations on risk of developing asthma. Our results show that a 10 ppb increase in ozone was significantly associated with asthma during the warm season (May-October), with the strongest effect seen when a 6-day cumulative lag period was used to compute the exposure metric (OR=1.05, 95% CI, 1.02–1.08). Similar results were seen for NO2 and PM 2.5 (OR=1.07, 95% CI, 1.03–1.11 and OR=1.12, 95% CI, 1.03–1.22, respectively). PM2.5 also had significant effects in the cold season (November-April), 5-day cumulative lag: OR=1.11, 95% CI, 1.00–1.22. When compared with children in the lowest quartile of O3 exposure, the risk for children in the highest quartile was 20% higher. This study indicates that these pollutants are associated with newly-diagnosed childhood asthma in this low-income urban population, particularly during the summer months. ^

Risk factors for metabolic syndrome among overweight and obese Hispanic children attending a pediatric clinic in New Braunfels, Texas

Childhood obesity is a persistent problem in the U.S., especially among Hispanics. Health complications like hypertension, type II diabetes, and metabolic syndrome (Met-S) are being seen at younger ages, and current screening procedures may be inadequate. This study sought to describe the risk factors for Met-S present in a sample of 106 overweight and obese Hispanic children, aged 5-14 years, participating in Nutrition and Exercise Start Today (NEST), a randomized weight management intervention trial at a rural health clinic in New Braunfels, Texas; and to determine associations between these factors and other clinical and socio-demographic characteristics linked to obesity. Baseline data was analyzed for the prevalence of large waist circumference (WC), elevated blood pressure (BP), high fasting serum glucose and serum triglycerides (TG), and low serum HDL cholesterol, in relationship with selected sample characteristics. Main findings included high baseline prevalence rates of large WC (77%), reduced HDL (57%), and elevated BP (30%). WC was significantly associated with BMI percentile and the serum liver function test alanine aminotransferase (ALT) by Fisher's exact test (p<0.001 and p=0.032, respectively), while there were significant relationships between HDL and both female gender and ALT. BMI percentile and ALT were associated with all sets of Met-S diagnostic criteria examined. BMI percentile also had a strong association (p=0.005) with total number of Met-S risk factors, while ALT had a weaker association (p=0.093). WC is a low-cost, simple measure whose use may improve clinic surveillance for childhood obesity and complications like Met-S. WC, BP, HDL and ALT may be used as part of targeted screening for obesity complications like Met-S, particularly in situations where resources are limited.^

Is H. pylori infection associated with diarrhea in a cohort of 3- to 8-year-old Colombian children?

The Estudio Comunitario sobre la Salud del Niño cohort study followed 326 3- to 8-year-old Colombian children for 4 years to observe the natural history of Helicobacter pylori infection and identify risk factors for acquisition, recurrence and persistence. Acute H. pylori infection during childhood may predispose to other enteric infections and therefore increase the risk of diarrheal disease. This dissertation aimed to estimate the effect of H. pylori infection on the occurrence of diarrhea and parasitic co-infections. The analysis used Generalized Estimating Equations to obtain odds ratios to estimate relative risks for diarrhea and the Zhang-Yu algorithm to estimate relative risks for on parasitic infections. Andersen-Gill models were used to estimate rate ratios for the effect of H. pylori status on the recurrence of parasitic infections. H. pylori status was classified for the entire follow-up duration in 1 of 3 categories: persistently positive, intermittently positive, and persistently negative. Multivariable models included child’s sex, age, symptoms, medication use, and socio-environmental factors. H. pylori infection was weakly and imprecisely associated with diarrheal disease, which occurred at an unexpectedly low frequency in this study. Persistently H. pylori-positive children had a somewhat higher incidence of reported diarrhea than intermittently positive or persistently negative children. Stratified analysis revealed that the presence of specific helminthes modified the effect of persistent H. pylori infection on diarrhea. The incidence of any parasitic infections was higher in children with persistent H. pylori infection relative to those with intermittent or persistently negative status, but this association did not hold when adjusted for the full set of selected covariates. The effects of H. pylori persistent status were similar for the occurrence or recurrence of Giardia duodenalis, Entamoeba histolytica, and Ascaris lumbricoides. These results show that H. pylori frequently co-exists with other parasites in Andean children and suggest that intermittently H. pylori–positive children might be at a lower risk of parasitic infections than persistently positive children. The relationship of H. pylori infection, helminthic infection and diarrheal disease should be further explored in studies that devote more intensive resources to accurate ascertainment of diarrhea.^

Identification of genetic risk factors for cerebellar mutism in pediatric brain tumor patients

Following posterior fossa surgery for resection of childhood medulloblastoma and primitive neuroectodermal tumor (M/PNET), cerebellar mutism (CM) may develop. This is a condition of absent or diminished speech in a conscious patient with no evidence of oral apraxia, which can be accompanied by other symptoms of the posterior fossa syndrome complex, which includes ataxia and hypotonia. Little is known about the etiology. Therefore, we conducted a SNP, gene, and pathway-level analysis to assess the role of host genetic variation on the risk of CM in M/PNET subjects following treatment. Cases (n= 20) and controls (n= 53) were recruited from the Childhood Cancer Epidemiology and Prevention Center, in Houston, TX. DNA samples were genotyped using the Illumina Human 1M Quad SNP chip. Ten pathways were identified from logistic regression used to identify the marginal effect of each SNP on CM risk. The minP test was conducted to identify associations between SNPs categorized to genes and CM risk. Pathways were assessed to determine if there was a significant enrichment of genes in the pathway compared to all other pathways. There were 78 genes that reached the threshold of min P ≤0.05 in 948 genes. The Neurotoxicity pathway was the most significant pathway after adjusting for multiple comparisons (q=0.040 and q=0.005, using Fisher's exact test and a test of proportions, respectively). Most genes within the Neurotoxicity pathway that reached a threshold of minP ≤0.05 were known to have an apoptosis function, possibly inducing neuronal apoptosis in the dentatothalamocortical pathway, and may be important in CM etiology in this population. This is the first study to assess the potential role of genetic risk factors on CM. As an exploratory study, these results should be replicated in a larger sample. ^

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

Observations from the Balcony: Directions for Pediatric Health Disparities Research and Policy

In 2002, the Institute of Medicine released Unequal Treatment: Confronting Racial and Ethnic Disparities in Healthcare, a landmark monograph documenting health disparities in the U.S. health care system. Since the publication of Unequal Treatment, the field of pediatric health disparities research has advanced significantly with a proliferation of studies examining a wide array of topics concerning inequities in child health. Advances in health care policy and legislation have also added to a heightened discourse on pediatric health disparities. While there has been substantial activity in efforts to address pediatric health disparities, questions remain regarding whether these efforts have changed the trajectory of health equity among children. The aim of this paper is to examine the practical challenges of addressing pediatric health disparities in the dynamic context of global changes in health care research, policy, and legislation relevant to children. Using the Adaptive Leadership framework, this paper outlines a conceptual model for assessing the scope of progress made in addressing pediatric health disparities, diagnoses the continued adaptive challenges of pediatric health disparities, and provides an agenda for further work and future investment.