Fever, methods of fever management, and caretakers' perceptions of pediatric after-hour telephone triage and advice services for children between the ages of twelve months and three years with fever

Despite the frequency with which fevers occur in children ages 1–3 years, lack of knowledge and understanding about the implications of fever and methods of fever management often results in anxiety among caretakers, sometimes prompting them to seek help at nearby emergency departments. Caretakers often look to health care professionals for advice and guidance over the telephone. The purpose of this study was to investigate caretakers' knowledge of the implications of fever, methods of fever management, perceptions of pediatric telephone triage and advice services regarding fever, and the effectiveness of after hour telephone triage directed toward improving the caretakers' ability to manage their child's fever at home. Pre-triage questionnaires were completed by 72 caretakers over the telephone before the triage encounter. Twenty-two of those same caretakers whose children were triaged using the fever guideline completed and returned the mailed post-triage questionnaire. Descriptive statistics were used to analyze responses for the larger pre-intervention group and describe comparisons for the pre and post-triage responses in the smaller sample subset (n = 22). ^

Design and implementation of a multisite data repository for pediatric epilepsy

This dissertation established a software-hardware integrated design for a multisite data repository in pediatric epilepsy. A total of 16 institutions formed a consortium for this web-based application. This innovative fully operational web application allows users to upload and retrieve information through a unique human-computer graphical interface that is remotely accessible to all users of the consortium. A solution based on a Linux platform with My-SQL and Personal Home Page scripts (PHP) has been selected. Research was conducted to evaluate mechanisms to electronically transfer diverse datasets from different hospitals and collect the clinical data in concert with their related functional magnetic resonance imaging (fMRI). What was unique in the approach considered is that all pertinent clinical information about patients is synthesized with input from clinical experts into 4 different forms, which were: Clinical, fMRI scoring, Image information, and Neuropsychological data entry forms. A first contribution of this dissertation was in proposing an integrated processing platform that was site and scanner independent in order to uniformly process the varied fMRI datasets and to generate comparative brain activation patterns. The data collection from the consortium complied with the IRB requirements and provides all the safeguards for security and confidentiality requirements. An 1-MR1-based software library was used to perform data processing and statistical analysis to obtain the brain activation maps. Lateralization Index (LI) of healthy control (HC) subjects in contrast to localization-related epilepsy (LRE) subjects were evaluated. Over 110 activation maps were generated, and their respective LIs were computed yielding the following groups: (a) strong right lateralization: (HC=0%, LRE=18%), (b) right lateralization: (HC=2%, LRE=10%), (c) bilateral: (HC=20%, LRE=15%), (d) left lateralization: (HC=42%, LRE=26%), e) strong left lateralization: (HC=36%, LRE=31%). Moreover, nonlinear-multidimensional decision functions were used to seek an optimal separation between typical and atypical brain activations on the basis of the demographics as well as the extent and intensity of these brain activations. The intent was not to seek the highest output measures given the inherent overlap of the data, but rather to assess which of the many dimensions were critical in the overall assessment of typical and atypical language activations with the freedom to select any number of dimensions and impose any degree of complexity in the nonlinearity of the decision space.

A research platform for artificial neural networks with applications in pediatric epilepsy

This dissertation established a state-of-the-art programming tool for designing and training artificial neural networks (ANNs) and showed its applicability to brain research. The developed tool, called NeuralStudio, allows users without programming skills to conduct studies based on ANNs in a powerful and very user friendly interface. A series of unique features has been implemented in NeuralStudio, such as ROC analysis, cross-validation, network averaging, topology optimization, and optimization of the activation function’s slopes. It also included a Support Vector Machines module for comparison purposes. Once the tool was fully developed, it was applied to two studies in brain research. In the first study, the goal was to create and train an ANN to detect epileptic seizures from subdural EEG. This analysis involved extracting features from the spectral power in the gamma frequencies. In the second application, a unique method was devised to link EEG recordings to epileptic and nonepileptic subjects. The contribution of this method consisted of developing a descriptor matrix that can be used to represent any EEG file regarding its duration and the number of electrodes. The first study showed that the inter-electrode mean of the spectral power in the gamma frequencies and its duration above a specific threshold performs better than the other frequencies in seizure detection, exhibiting an accuracy of 95.90%, a sensitivity of 92.59%, and a specificity of 96.84%. The second study yielded that Hjorth’s parameter activity is sufficient to accurately relate EEG to epileptic and non-epileptic subjects. After testing, accuracy, sensitivity and specificity of the classifier were all above 0.9667. Statistical tests measured the superiority of activity at over 99.99 % certainty. It was demonstrated that (1) the spectral power in the gamma frequencies is highly effective in locating seizures from EEG and (2) activity can be used to link EEG recordings to epileptic and non-epileptic subjects. These two studies required high computational load and could be addressed thanks to NeuralStudio. From a medical perspective, both methods proved the merits of NeuralStudio in brain research applications. For its outstanding features, NeuralStudio has been recently awarded a patent (US patent No. 7502763).

Principal component analysis and assessment of language network activation patterns in pediatric epilepsy

This dissertation establishes a novel data-driven method to identify language network activation patterns in pediatric epilepsy through the use of the Principal Component Analysis (PCA) on functional magnetic resonance imaging (fMRI). A total of 122 subjects’ data sets from five different hospitals were included in the study through a web-based repository site designed here at FIU. Research was conducted to evaluate different classification and clustering techniques in identifying hidden activation patterns and their associations with meaningful clinical variables. The results were assessed through agreement analysis with the conventional methods of lateralization index (LI) and visual rating. What is unique in this approach is the new mechanism designed for projecting language network patterns in the PCA-based decisional space. Synthetic activation maps were randomly generated from real data sets to uniquely establish nonlinear decision functions (NDF) which are then used to classify any new fMRI activation map into typical or atypical. The best nonlinear classifier was obtained on a 4D space with a complexity (nonlinearity) degree of 7. Based on the significant association of language dominance and intensities with the top eigenvectors of the PCA decisional space, a new algorithm was deployed to delineate primary cluster members without intensity normalization. In this case, three distinct activations patterns (groups) were identified (averaged kappa with rating 0.65, with LI 0.76) and were characterized by the regions of: (1) the left inferior frontal Gyrus (IFG) and left superior temporal gyrus (STG), considered typical for the language task; (2) the IFG, left mesial frontal lobe, right cerebellum regions, representing a variant left dominant pattern by higher activation; and (3) the right homologues of the first pattern in Broca's and Wernicke's language areas. Interestingly, group 2 was found to reflect a different language compensation mechanism than reorganization. Its high intensity activation suggests a possible remote effect on the right hemisphere focus on traditionally left-lateralized functions. In retrospect, this data-driven method provides new insights into mechanisms for brain compensation/reorganization and neural plasticity in pediatric epilepsy.

Prenatal environmental exposure and neurodevelopmentally important gene expression in malformed brain tissue from pediatric intractable epilepsy patients

The primary objective of this proposal was to determine whether mitochondrial oxidative stress and variation in a particular mtDNA lineage contribute to the risk of developing cortical dysplasia and are potential contributing factors in epileptogenesis in children. The occurrence of epilepsy in children is highly associated with malformations of cortical development (MCD). It appears that MCD might arise from developmental errors due to environmental exposures in combination with inherited variation in response to environmental exposures and mitochondrial function. Therefore, it is postulated that variation in a particular mtDNA lineage of children contributes to the effects of mitochondrial DNA damage on MCD phenotype. Quantitative PCR and dot blot were used to examine mitochondrial oxidative damage and single nucleotide polymorphism (SNP) in the mitochondrial genome in brain tissue from 48 pediatric intractable epilepsy patients from Miami Children’s Hospital and 11 control samples from NICHD Brain and Tissue Bank for Developmental Disorders. Epilepsy patients showed higher mtDNA copy number compared to normal health subjects (controls). Oxidative mtDNA damage was lower in non-neoplastic but higher in neoplastic epilepsy patients compared to controls. There was a trend of lower mtDNA oxidative damage in the non-neoplastic (MCD) patients compared to controls, yet, the reverse was observed in neoplastic (MCD and Non-MCD) epilepsy patients. The presence of mtDNA SNP and haplogroups did not show any statistically significant relationships with epilepsy phenotypes. However, SNPs G9804A and G9952A were found in higher frequencies in epilepsy samples. Logistic regression analysis showed no relationship between mtDNA oxidative stress, mtDNA copy number, mitochondrial haplogroups and SNP variations with epilepsy in pediatric patients. The levels of mtDNA copy number and oxidative mtDNA damage and the SNPs G9952A and T10010C predicted neoplastic epilepsy, however, this was not significant due to a small sample size of pediatric subjects. Findings of this study indicate that an increase in mtDNA content may be compensatory mechanisms for defective mitochondria in intractable epilepsy and brain tumor. Further validation of these findings related to mitochondrial genotypes and mitochondrial dysfunction in pediatric epilepsy and MCD may lay the ground for the development of new therapies and prevention strategies during embryogenesis.

The influence of spirituality, race/ethnicity and religion on parent grief and mental health at one and three months after their infant's/child's death in the neonatal or pediatric intensive care unit

The death of an infant/child is one of the most devastating experiences for parents and immediately throws them into crisis. Spiritual and religious coping strategies may help parents with their loss. The purposes of this longitudinal study were to: (1) describe differences in bereaved parents' use of spiritual coping strategies across racial/ethnic and religious groups, mother/father dyads, and time—one (T1) and three (T2) months after the infant's/child's death in the neonatal (NICU) or pediatric intensive care unit (PICU), and (2) test the relationship between spiritual coping strategies and grief, mental health, and personal growth for mothers and fathers at T1 and T2. A sample of 126 Hispanic, Black/African American, and White parents of 119 deceased children completed the Spiritual Coping Strategies scale, Beck Depression Inventory-II, Impact of Events-Revised, Hogan Grief Reaction Checklist, and a demographic form at T1 and T2. Controlling for race and religion, spiritual coping was a strong predictor of lower grief, better mental health, and greater personal growth for mothers at T1 and T2 and lower grief for fathers at T1. The findings of this study will guide bereaved parents to effective strategies to help them cope with their early grief.

Physeal Growth Plate Fractures: Implications for the Pediatric Athlete

Pediatric musculoskeletal trauma accounts for most childhood injuries. The anatomy and physiology of the pediatric skeleton is unique as is its response to trauma. The pediatric skeleton has periods of rapid growth; therefore the effect of trauma to the musculoskeletal system may have significant long-term complications.

Caring for the Caregiver: Emotional Challenges of Pediatric Palliative Care Nurses

Pediatric Palliative Care (PPC) nurses provide quality-of-life for critically ill children. This paper looks at how PPC nurses cope with caregiver emotions within the conceptual framework of emotional labor and emotional intelligence.

Children with special health care needs: Comparison of the effects of home care setting, prescribed pediatric extended care setting, and long-term care setting on child and family health outcomes and health care service use

Technological advances during the past 30 years have dramatically improved survival rates for children with life-threatening conditions (preterm births, congenital anomalies, disease, or injury) resulting in children with special health care needs (CSHCN), children who have or are at increased risk for a chronic physical, developmental, behavioral, or emotional condition and who require health and related services beyond that required by children generally. There are approximately 10.2 million of these children in the United States or one in five households with a child with special health care needs. Care for these children is limited to home care, medical day care (Prescribed Pediatric Extended Care; P-PEC) or a long term care (LTC) facility. There is very limited research examining health outcomes of CSHCN and their families. The purpose of this research was to compare the effects of home care settings, P-PEC settings, and LTC settings on child health and functioning, family health and function, and health care service use of families with CSHCN. Eighty four CSHCN ages 2 to 21 years having a medically fragile or complex medical condition that required continual monitoring were enrolled with their parents/guardians. Interviews were conducted monthly for five months using the PedsQL™ Generic Core Module for child health and functioning, PedsQL™ Family Impact Module for family health and functioning, and Access to Care from the NS-CSHCN survey for health care services. Descriptive statistics, chi square, and ANCOVA were conducted to determine differences across care settings. Children in the P-PEC settings had a highest health care quality of life (HRQL) overall including physical and psychosocial functioning. Parents/guardians with CSHCN in LTC had the highest HRQL including having time and energy for a social life and employment. Parents/guardians with CSHCN in home care settings had the poorest HRQL including physical and psychosocial functioning with cognitive difficulties, difficulties with worry, communication, and daily activities. They had the fewest hours of employment and the most hours providing direct care for their children. Overall health care service use was the same across the care settings.

Network construction and graph theoretical analysis of functional language networks in pediatric epilepsy

This dissertation introduces a new approach for assessing the effects of pediatric epilepsy on the language connectome. Two novel data-driven network construction approaches are presented. These methods rely on connecting different brain regions using either extent or intensity of language related activations as identified by independent component analysis of fMRI data. An auditory description decision task (ADDT) paradigm was used to activate the language network for 29 patients and 30 controls recruited from three major pediatric hospitals. Empirical evaluations illustrated that pediatric epilepsy can cause, or is associated with, a network efficiency reduction. Patients showed a propensity to inefficiently employ the whole brain network to perform the ADDT language task; on the contrary, controls seemed to efficiently use smaller segregated network components to achieve the same task. To explain the causes of the decreased efficiency, graph theoretical analysis was carried out. The analysis revealed no substantial global network feature differences between the patient and control groups. It also showed that for both subject groups the language network exhibited small-world characteristics; however, the patient's extent of activation network showed a tendency towards more random networks. It was also shown that the intensity of activation network displayed ipsilateral hub reorganization on the local level. The left hemispheric hubs displayed greater centrality values for patients, whereas the right hemispheric hubs displayed greater centrality values for controls. This hub hemispheric disparity was not correlated with a right atypical language laterality found in six patients. Finally it was shown that a multi-level unsupervised clustering scheme based on self-organizing maps, a type of artificial neural network, and k-means was able to fairly and blindly separate the subjects into their respective patient or control groups. The clustering was initiated using the local nodal centrality measurements only. Compared to the extent of activation network, the intensity of activation network clustering demonstrated better precision. This outcome supports the assertion that the local centrality differences presented by the intensity of activation network can be associated with focal epilepsy.^

A Research Platform for Artificial Neural Networks with Applications in Pediatric Epilepsy

This dissertation established a state-of-the-art programming tool for designing and training artificial neural networks (ANNs) and showed its applicability to brain research. The developed tool, called NeuralStudio, allows users without programming skills to conduct studies based on ANNs in a powerful and very user friendly interface. A series of unique features has been implemented in NeuralStudio, such as ROC analysis, cross-validation, network averaging, topology optimization, and optimization of the activation function’s slopes. It also included a Support Vector Machines module for comparison purposes. Once the tool was fully developed, it was applied to two studies in brain research. In the first study, the goal was to create and train an ANN to detect epileptic seizures from subdural EEG. This analysis involved extracting features from the spectral power in the gamma frequencies. In the second application, a unique method was devised to link EEG recordings to epileptic and non-epileptic subjects. The contribution of this method consisted of developing a descriptor matrix that can be used to represent any EEG file regarding its duration and the number of electrodes. The first study showed that the inter-electrode mean of the spectral power in the gamma frequencies and its duration above a specific threshold performs better than the other frequencies in seizure detection, exhibiting an accuracy of 95.90%, a sensitivity of 92.59%, and a specificity of 96.84%. The second study yielded that Hjorth’s parameter activity is sufficient to accurately relate EEG to epileptic and non-epileptic subjects. After testing, accuracy, sensitivity and specificity of the classifier were all above 0.9667. Statistical tests measured the superiority of activity at over 99.99 % certainty. It was demonstrated that 1) the spectral power in the gamma frequencies is highly effective in locating seizures from EEG and 2) activity can be used to link EEG recordings to epileptic and non-epileptic subjects. These two studies required high computational load and could be addressed thanks to NeuralStudio. From a medical perspective, both methods proved the merits of NeuralStudio in brain research applications. For its outstanding features, NeuralStudio has been recently awarded a patent (US patent No. 7502763).

Principal Component Analysis and Assessment of Language Network Activation Patterns in Pediatric Epilepsy

This dissertation establishes a novel data-driven method to identify language network activation patterns in pediatric epilepsy through the use of the Principal Component Analysis (PCA) on functional magnetic resonance imaging (fMRI). A total of 122 subjects’ data sets from five different hospitals were included in the study through a web-based repository site designed here at FIU. Research was conducted to evaluate different classification and clustering techniques in identifying hidden activation patterns and their associations with meaningful clinical variables. The results were assessed through agreement analysis with the conventional methods of lateralization index (LI) and visual rating. What is unique in this approach is the new mechanism designed for projecting language network patterns in the PCA-based decisional space. Synthetic activation maps were randomly generated from real data sets to uniquely establish nonlinear decision functions (NDF) which are then used to classify any new fMRI activation map into typical or atypical. The best nonlinear classifier was obtained on a 4D space with a complexity (nonlinearity) degree of 7. Based on the significant association of language dominance and intensities with the top eigenvectors of the PCA decisional space, a new algorithm was deployed to delineate primary cluster members without intensity normalization. In this case, three distinct activations patterns (groups) were identified (averaged kappa with rating 0.65, with LI 0.76) and were characterized by the regions of: 1) the left inferior frontal Gyrus (IFG) and left superior temporal gyrus (STG), considered typical for the language task; 2) the IFG, left mesial frontal lobe, right cerebellum regions, representing a variant left dominant pattern by higher activation; and 3) the right homologues of the first pattern in Broca's and Wernicke's language areas. Interestingly, group 2 was found to reflect a different language compensation mechanism than reorganization. Its high intensity activation suggests a possible remote effect on the right hemisphere focus on traditionally left-lateralized functions. In retrospect, this data-driven method provides new insights into mechanisms for brain compensation/reorganization and neural plasticity in pediatric epilepsy.

Painful Symptomatology Reported by Dentistry Students at a Brazilian University

Objectives: Identification of the level of knowledge on ergonomics principles, and application of these by dentistry students to investigate whether painful symptomatology was experienced. An-other objective is the expansion of discussions on occupational health in academic settings. Study Design and Settings: Dentistry students of the Federal University of Rio Grande do Norte, Brazil (n = 148) were surveyed using the Nordic Musculoskeletal Questionnaire to determine the severity of musculoskeletal symptoms experienced. Data were analyzed through EpiInfo 7.0 to measure central trends and variability 5for quantitative variables, absolute and relative frequencies for categorical variables, and significance between groups (confidence intervals and chisquare). Association analysis (Pearson) was also carried out. Results: Ergonomic measures were not reported by students. Within the musculoskeletal symptoms described, females were the most affected, independent of academic level. Conclusions: Positive correlations were verified between all categories and all anatomic regions (e.g., neck, lower back, wrists, hands, and shoulders). Data suggest progressive worsening of symptoms, which will eventually result in leaves of absence.

The development of a self-directed learning module for rural emergency nurses on pediatric diabetic ketoacidosis

Background: Newfoundland and Labrador has a high incidence of type 1 diabetes and diabetic ketoacidosis (DKA) is a complication of type 1 diabetes. A clinical practice guideline was developed for the treatment of pediatric diabetic ketoacidosis (DKA) to standardize care in all Emergency Departments and improve patient outcomes. Rural emergency nurses are requires to maintain their competency and acquire new knowledge as stated by the Association of Registered Nurses of Newfoundland and Labrador (ARNNL). Purpose: The purpose of this practicum was to develop a self-learning module for rural emergency nurses to increase their knowledge and understanding of the clinical practise guideline to assess, treat, and prevent pediatric ketoacidosis. Methods: Two methodologies were used in this practicum. A review of the literature and consultations with key stakeholders were completed. Results: The self-learning module created was composed of three units and focused on the learning needs of rural emergency nurses in the areas of assessment, treatment, and prevention of pediatric DKA. Conclusion: The goal of the practicum was to increase rural emergency nurses’ knowledge and implementation of the clinical practice guideline when assessing and treating children and families experiencing DKA to improve patient outcomes. A planned evaluation of the self-learning module will be conducted following dissemination of the module throughout the rural Emergency Departments.

Pediatric CNS pathophysiology

Research in pediatric central nervous system pathophysiology is focused around three primary goals: identification of neurodevelopmental disorders, understanding the differences in brain development which underlie these disorders, and improving treatment for these young children. Autism spectrum disorders (ASDs) are a complex set of disorders which are characterized by difficulties in language and social interactions. These behavioral measures are highly variable and a number of underlying causes can generate similar behavioral effects. Therefore, it is important to identify neurophysiological markers to better identify and characterize these disorders. Recent ASD findings using MEG show atypical latency and amplitude responses and poor cortical connectivity in children with ASDs across the cognitive spectrum from basic auditory processing, multisensory integration, to face and semantic processing. These results further support the view that ASDs are a complex neurologically-based disorder. On the other hand, the cause of Down syndrome is well understood as originating from a partial or full replication of chromosome 21. However, the cognitive and neurological consequences of this chromosomal abnormality are not yet well understood. Using a simple observation and motor execution task, poor functional connectivity in sensory-motor areas, particularly in the gamma band range, has been identified in children with Down syndrome and is consistent with behavioral deficits in the sensory-motor realm. Additional studies are needed to better understand whether targeted identification of these abnormalities can facilitate treatment in this disorder. Finally, while epilepsy can be reliably diagnosed, seizure control is still limited in many cases where the seizure onset zone is not readily apparent. Advances in pre-surgical evaluation and intra-operative co-registration will be described. These studies describing pediatric CNS pathophysiology will be discussed. © Springer-Verlag 2010.