Use of an Online Photo Management and Sharing Application to Create a Searchable Digital Dental Radiograph Repository

Problem: Dental radiographs generally display one or more findings/diagnoses, and are linked to a unique set of patient demographics, medical history and other findings not represented by the image. However, this information is not associated with radiographs in any type of meta format, and images are not searchable based on any clinical criteria (1,2). The purpose of this pilot study is to create an online, searchable data repository of dental radiographs to be used for patient care, teaching and research. [See PDF for complete abstract]

The identification of child abuse in Harris County in 1998

Characteristics of child abuse cases are not well known. In this study I collected data on 70 child abuse cases that were reported to Children's Protective Services in Harris County in 1998. The purpose of this study was to determine the factors in Harris County that lead to the identification of physical and sexual abuse. In order to answer the questions of who, what, where and when relative to the discovery of abuse I applied the same questionnaire (see Appendix) to each of 35 Sexual Abuse case reports and to each of 35 Physical Abuse/Neglect case reports. Answers to the first four questions were arranged by frequency distribution to show the predominant reporter, the 10 most common indicators, the most common locale, and the most frequent timing. Tables of the age, sex, and ethnicity of the children indicate the identity of those whose victimization was most reported. In addition the relationship between the form questions and the characteristics of the children was explored. A comparison of Sexual Abuse cases with Physical Abuse/Neglect cases was conducted and the results were analyzed and recorded in the Tables. ^ Child maltreatment often has negative short and long term effects on children's mental health and development. Suicide, violence, delinquency, drug and alcohol abuse and other forms of criminality are frequently child abuse related. Early detection and treatment helps to alleviate the myriad mental and physical ailments that untreated victims present as adults. This translates into medical dollar savings. ^ The long term objectives of my research were to reduce the number of undetected and unreported child abuse cases in Harris County by formulating better educational programs and literature for medical professionals and other personnel who are in contact with children. ^

UNDERSTANDING NURSE CREATED COGNITIVE ARTIFACTS: PERSONALLY-CREATED-COGNITIVE-ARTIFACTS AS EXTERNAL REPRESENTATIONS OF DISTRIBUTED COGNITION

Manuscript 1: “Conceptual Analysis: Externalizing Nursing Knowledge” We use concept analysis to establish that the report tool nurses prepare, carry, reference, amend, and use as a temporary data repository are examples of cognitive artifacts. This tool, integrally woven throughout the work and practice of nurses, is important to cognition and clinical decision-making. Establishing the tool as a cognitive artifact will support new dimensions of study. Such studies can characterize how this report tool supports cognition, internal representation of knowledge and skills, and external representation of knowledge of the nurse. Manuscript 2: “Research Methods: Exploring Cognitive Work” The purpose of this paper is to describe a complex, cross-sectional, multi-method approach to study of personal cognitive artifacts in the clinical environment. The complex data arrays present in these cognitive artifacts warrant the use of multiple methods of data collection. Use of a less robust research design may result in an incomplete understanding of the meaning, value, content, and relationships between personal cognitive artifacts in the clinical environment and the cognitive work of the user. Manuscript 3: “Making the Cognitive Work of Registered Nurses Visible” Purpose: Knowledge representations and structures are created and used by registered nurses to guide patient care. Understanding is limited regarding how these knowledge representations, or cognitive artifacts, contribute to working memory, prioritization, organization, cognition, and decision-making. The purpose of this study was to identify and characterize the role a specific cognitive artifact knowledge representation and structure as it contributed to the cognitive work of the registered nurse. Methods: Data collection was completed, using qualitative research methods, by shadowing and interviewing 25 registered nurses. Data analysis employed triangulation and iterative analytic processes. Results: Nurse cognitive artifacts support recall, data evaluation, decision-making, organization, and prioritization. These cognitive artifacts demonstrated spatial, longitudinal, chronologic, visual, and personal cues to support the cognitive work of nurses. Conclusions: Nurse cognitive artifacts are an important adjunct to the cognitive work of nurses, and directly support patient care. Nurses need to be able to configure their cognitive artifact in ways that are meaningful and support their internal knowledge representations.

Using incomplete citation data for MEDLINE results ranking.

Information overload is a significant problem for modern medicine. Searching MEDLINE for common topics often retrieves more relevant documents than users can review. Therefore, we must identify documents that are not only relevant, but also important. Our system ranks articles using citation counts and the PageRank algorithm, incorporating data from the Science Citation Index. However, citation data is usually incomplete. Therefore, we explore the relationship between the quantity of citation information available to the system and the quality of the result ranking. Specifically, we test the ability of citation count and PageRank to identify "important articles" as defined by experts from large result sets with decreasing citation information. We found that PageRank performs better than simple citation counts, but both algorithms are surprisingly robust to information loss. We conclude that even an incomplete citation database is likely to be effective for importance ranking.

Using incomplete citation data for MEDLINE results ranking.

Information overload is a significant problem for modern medicine. Searching MEDLINE for common topics often retrieves more relevant documents than users can review. Therefore, we must identify documents that are not only relevant, but also important. Our system ranks articles using citation counts and the PageRank algorithm, incorporating data from the Science Citation Index. However, citation data is usually incomplete. Therefore, we explore the relationship between the quantity of citation information available to the system and the quality of the result ranking. Specifically, we test the ability of citation count and PageRank to identify "important articles" as defined by experts from large result sets with decreasing citation information. We found that PageRank performs better than simple citation counts, but both algorithms are surprisingly robust to information loss. We conclude that even an incomplete citation database is likely to be effective for importance ranking.

NETWORK TOPOLOGY IN HUMAN PROTEIN INTERACTION DATA PREDICTS FUNCTIONAL ASSOCIATION

High-throughput assays, such as yeast two-hybrid system, have generated a huge amount of protein-protein interaction (PPI) data in the past decade. This tremendously increases the need for developing reliable methods to systematically and automatically suggest protein functions and relationships between them. With the available PPI data, it is now possible to study the functions and relationships in the context of a large-scale network. To data, several network-based schemes have been provided to effectively annotate protein functions on a large scale. However, due to those inherent noises in high-throughput data generation, new methods and algorithms should be developed to increase the reliability of functional annotations. Previous work in a yeast PPI network (Samanta and Liang, 2003) has shown that the local connection topology, particularly for two proteins sharing an unusually large number of neighbors, can predict functional associations between proteins, and hence suggest their functions. One advantage of the work is that their algorithm is not sensitive to noises (false positives) in high-throughput PPI data. In this study, we improved their prediction scheme by developing a new algorithm and new methods which we applied on a human PPI network to make a genome-wide functional inference. We used the new algorithm to measure and reduce the influence of hub proteins on detecting functionally associated proteins. We used the annotations of the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) as independent and unbiased benchmarks to evaluate our algorithms and methods within the human PPI network. We showed that, compared with the previous work from Samanta and Liang, our algorithm and methods developed in this study improved the overall quality of functional inferences for human proteins. By applying the algorithms to the human PPI network, we obtained 4,233 significant functional associations among 1,754 proteins. Further comparisons of their KEGG and GO annotations allowed us to assign 466 KEGG pathway annotations to 274 proteins and 123 GO annotations to 114 proteins with estimated false discovery rates of <21% for KEGG and <30% for GO. We clustered 1,729 proteins by their functional associations and made pathway analysis to identify several subclusters that are highly enriched in certain signaling pathways. Particularly, we performed a detailed analysis on a subcluster enriched in the transforming growth factor β signaling pathway (P<10-50) which is important in cell proliferation and tumorigenesis. Analysis of another four subclusters also suggested potential new players in six signaling pathways worthy of further experimental investigations. Our study gives clear insight into the common neighbor-based prediction scheme and provides a reliable method for large-scale functional annotations in this post-genomic era.

Can prospective usability evaluation predict data errors?

Increasing amounts of clinical research data are collected by manual data entry into electronic source systems and directly from research subjects. For this manual entered source data, common methods of data cleaning such as post-entry identification and resolution of discrepancies and double data entry are not feasible. However data accuracy rates achieved without these mechanisms may be higher than desired for a particular research use. We evaluated a heuristic usability method for utility as a tool to independently and prospectively identify data collection form questions associated with data errors. The method evaluated had a promising sensitivity of 64% and a specificity of 67%. The method was used as described in the literature for usability with no further adaptations or specialization for predicting data errors. We conclude that usability evaluation methodology should be further investigated for use in data quality assurance.

EVALUATION OF INTENSITY MODULATED RADIATION THERAPY (IMRT) DELIVERY ERROR DUE TO IMRT TREATMENT PLAN COMPLEXITY AND IMPROPERLY MATCHED DOSIMETRY DATA

Intensity modulated radiation therapy (IMRT) is a technique that delivers a highly conformal dose distribution to a target volume while attempting to maximally spare the surrounding normal tissues. IMRT is a common treatment modality used for treating head and neck (H&N) cancers, and the presence of many critical structures in this region requires accurate treatment delivery. The Radiological Physics Center (RPC) acts as both a remote and on-site quality assurance agency that credentials institutions participating in clinical trials. To date, about 30% of all IMRT participants have failed the RPC’s remote audit using the IMRT H&N phantom. The purpose of this project is to evaluate possible causes of H&N IMRT delivery errors observed by the RPC, specifically IMRT treatment plan complexity and the use of improper dosimetry data from machines that were thought to be matched but in reality were not. Eight H&N IMRT plans with a range of complexity defined by total MU (1460-3466), number of segments (54-225), and modulation complexity scores (MCS) (0.181-0.609) were created in Pinnacle v.8m. These plans were delivered to the RPC’s H&N phantom on a single Varian Clinac. One of the IMRT plans (1851 MU, 88 segments, and MCS=0.469) was equivalent to the median H&N plan from 130 previous RPC H&N phantom irradiations. This average IMRT plan was also delivered on four matched Varian Clinac machines and the dose distribution calculated using a different 6MV beam model. Radiochromic film and TLD within the phantom were used to analyze the dose profiles and absolute doses, respectively. The measured and calculated were compared to evaluate the dosimetric accuracy. All deliveries met the RPC acceptance criteria of ±7% absolute dose difference and 4 mm distance-to-agreement (DTA). Additionally, gamma index analysis was performed for all deliveries using a ±7%/4mm and ±5%/3mm criteria. Increasing the treatment plan complexity by varying the MU, number of segments, or varying the MCS resulted in no clear trend toward an increase in dosimetric error determined by the absolute dose difference, DTA, or gamma index. Varying the delivery machines as well as the beam model (use of a Clinac 6EX 6MV beam model vs. Clinac 21EX 6MV model), also did not show any clear trend towards an increased dosimetric error using the same criteria indicated above.

BMP-SIGNALING REGULATES A COMMON TRANSCRIPTIONAL PROGRAM TO CONTROL FACIAL FORM AND SKELETAL MORPHOGENESIS

Much of the craniofacial skeleton, such as the skull vault, mandible and midface, develops through direct, intramembranous ossification of the cranial neural crest (CNC) derived progenitor cells. Bmp-signaling plays critical roles in normal craniofacial development, and Bmp4 deficiency results in craniofacial abnormalities, such as cleft lip and palate. We performed an in depth analysis of Bmp4, a critical regulator of development, disease, and evolution, in the CNC. Conditional Bmp4 overexpression, using a tetracycline regulated Bmp4 gain of function allele, resulted in facial form changes that were most dramatic after an E10.5 Bmp4 induction. Expression profiling uncovered a signature of Bmp4 induced genes (BIG) composed predominantly of transcriptional regulators controlling self-renewal, osteoblast differentiation, and negative Bmp autoregulation. The complimentary experiment, CNC inactivation of Bmp2, Bmp4, and Bmp7, resulted in complete or partial loss of multiple CNC derived skeletal elements revealing a critical requirement for Bmp-signaling in membranous bone and cartilage development. Importantly, the BIG signature was reduced in Bmp loss of function mutants indicating similar Bmp-regulated target genes underlying facial form modulation and normal skeletal morphogenesis. Chromatin immunoprecipitation (ChIP) revealed a subset of the BIG signature, including Satb2, Smad6, Hand1, Gadd45g and Gata3 that was bound by Smad1/5 in the developing mandible revealing direct, Smad-mediated regulation. These data indicate that Bmp-signaling regulates craniofacial skeletal development and facial form by balancing self-renewal and differentiation pathways in CNC progenitors.

Gastric cancer survival amongst Hispanics- A Hispanic paradox? A case series study using the SEER 1973--2005 data registry

Stomach cancer is the fourth most common cancer in the world, and ranked 16th in the US in 2008. The age-adjusted rates among Hispanics were 2.8 times that of non-Hispanic Whites in 1998-2002. In spite of that, previous research has found that Hispanics with non-cardia adenocarcinoma of the stomach have a slightly better survival than non-Hispanic Whites. However, such previous research did not include a comparison with African-Americans, and it was limited to data released for the years 1973-2000 in the nine original Surveillance, Epidemiology, and End Results Cancer Registries. This finding was interpreted as related to the Hispanic Paradox, a phenomenon that refers to the fact that Hispanics in the USA tend to paradoxically have substantially better health than other ethnic groups in spite of what their aggregate socio-economic indicators would predict. We extended such research to the SEER 17 Registry, 1973-2005, with varying years of diagnosis per registry, and compared the survival of non-cardia adenocarcinoma of the stomach according to ethnicity (Hispanics, non-Hispanic Whites and African-Americans), while controlling for age, gender, marital status, stage of disease and treatment using Cox regression survival analysis. We found that Hispanic ethnicity by itself did not confer an advantage on survival from non-cardia adenocarcinoma of the stomach, but that being born abroad was independently associated with the apparent 'Hispanic Paradox' previously reported, and that such advantage was seen among foreign born persons across all race/ethnic groups.^

Clinical and economic outcomes of serious postoperative infections following resection of common respiratory and gastrointestinal solid tumors

Unlike infections occurring during periods of chemotherapy-induced neutropenia, postoperative infections in patients with solid malignancy remain largely understudied. The purpose of this population-based study was to evaluate the clinical and economic burden, as well as the relationship of hospital surgical volume and outcomes associated with serious postoperative infection (SPI) – i.e., bacteremia/sepsis, pneumonia, and wound infection – following resection of common solid tumors.^ From the Texas Discharge Data Research File, we identified all Texas residents who underwent resection of cancer of the lung, esophagus, stomach, pancreas, colon, or rectum between 2002 and 2006. From their billing records, we identified ICD-9 codes indicating SPI and also subsequent SPI-related readmissions occurring within 30 days of surgery. Random-effects logistic regression was used to calculate the impact of SPI on mortality, as well as the association between surgical volume and SPI, adjusting for case-mix, hospital characteristics, and clustering of multiple surgical admissions within the same patient and patients within the same hospital. Excess bed days and costs were calculated by subtracting values for patients without infections from those with infections computed using multilevel mixed-effects generalized linear model by fitting a gamma distribution to the data using log link.^ Serious postoperative infection occurred following 9.4% of the 37,582 eligible tumor resections and was independently associated with an 11-fold increase in the odds of in-hospital mortality (95% Confidence Interval [95% CI], 6.7-18.5, P < 0.001). Patients with SPI required 6.3 additional hospital days (95% CI, 6.1 - 6.5) at an incremental cost of $16,396 (95% CI, $15,927–$16,875). There was a significant trend toward lower overall rates of SPI with higher surgical volume (P=0.037). ^ Due to the substantial morbidity, mortality, and excess costs associated with SPI following solid tumor resections and given that, under current reimbursement practices, most of this heavy burden is borne by acute care providers, it is imperative for hospitals to identify more effective prophylactic measures, so that these potentially preventable infections and their associated expenditures can be averted. Additional volume-outcomes research is also needed to identify infection prevention processes that can be transferred from higher- to lower-volume providers.^

Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

Early identification of symptomatic aortic stenosis using echocardiographic data

Background: Heart failure (CHF) is the most frequent and prognostically severe symptom of aortic stenosis (AS), and the most common indication for surgery. The mainstay of treatment for AS is aortic valve replacement (AVR), and the main indication for an AVR is development of symptomatic disease. ACC/AHA guidelines define severe AS as an aortic valve area (AVA) ≤1cm², but there is little data correlating echocardiogram AVA with the onset of symptomatic CHF. We evaluated the risk of developing CHF with progressively decreasing echocardiographic AVA. We also compared echocardiographic AVA with Jet velocity (V2) and indexed AVA (AVAI) to assess the best predictor of development of symptomatic CHF.^ Methods and Results: This retrospective cohort study evaluated 518 patients with asymptomatic moderate or severe AS from a single community based cardiology practice. A total of 925 echocardiograms were performed over an 11-year period. Each echocardiogram was correlated with concurrent clinical assessments while the investigator was blinded to the echocardiogram severity of AS. The Cox Proportional hazards model was used to analyze the relationship between AVA and the development of CHF. The median age of patients at entry was 76.1 years, with 54% males. A total of 116 patients (21.8%) developed new onset CHF during follow-up. Compared to patients with AVA >1.0cm², patients with lower AVA had an exponentially increasing risk of developing CHF for each 0.2cm² decrement in AVA, becoming statistically significant only at an AVA less than 0.8 cm². Also, compared to V2 and AVAI, AVA added more information to assessing risk for development of CHF (p=0.041). ^ Conclusion: In patients with normal or mildly impaired LVEF, the risk of CHF rises exponentially with decreasing valve area and becomes statistically significant after AVA falls below 0.8cm². AVA is a better predictor of CHF when compared to V2 or AVAI.^

U.S. school based sealant programs: Review of their most common characteristics

In the United States, dental caries is the most common chronic illness in children, occurring five to eight times as frequently as asthma. 11 Dental caries is an unmet health need, disproportionately affecting minority groups and individuals with low socio-economic status.15,34,36 School-Based Sealant Programs were developed to target children at risk, to provide dental services in a closer geographic area, to offer low cost preventive dental services, and to educate families about oral health and prevention.1 There is scientific, evidence based literature that shows the effectiveness of dental sealants preventing dental decay. 13^ Currently, there is no central source for cataloging School-Based Sealant Programs (SBSPs). Information is scattered around publications and documents. For instance, the National Health and Nutrition Examination Survey (NHANES) does not have information about all the existing SBSPs. ^ This literature review determined which are the most common characteristics of SBSPs in the U.S. and determined the extent to which these programs provide sealants to children of low socio-economic status. The method utilized was an electronic database search. Pubmed and EBESCO host databases were searched with Mesh terms like “dental school sealant programs”, “community dentistry”, “school based sealant programs” and “oral preventive programs”. Results were organized in terms of location, population served, providers, funding source and data shared. ^ The searches produced 77 studies, from which 40 were included in this work. Only 18 U.S. states were represented in the results; however these findings are very consistent with the Best Practice Approach – School Based Sealant Programs3. Most of the SBSPs provide their services to children from low income families, and utilized the lower labor cost providers permitted by their state regulations. The author intends that this thesis work will become an aide in the development of future programs, and as evidence for the sustainability of these programs.^

Pathway analysis of genome-wide association study data in primary biliary cirrhosisa

Genome-wide association studies (GWAS) have successfully identified several genetic loci associated with inherited predisposition to primary biliary cirrhosis (PBC), the most common autoimmune disease of the liver. Pathway-based tests constitute a novel paradigm for GWAS analysis. By evaluating genetic variation across a biological pathway (gene set), these tests have the potential to determine the collective impact of variants with subtle effects that are individually too weak to be detected in traditional single variant GWAS analysis. To identify biological pathways associated with the risk of development of PBC, GWAS of PBC from Italy (449 cases and 940 controls) and Canada (530 cases and 398 controls) were independently analyzed. The linear combination test (LCT), a recently developed pathway-level statistical method was used for this analysis. For additional validation, pathways that were replicated at the P <0.05 level of significance in both GWAS on LCT analysis were also tested for association with PBC in each dataset using two complementary GWAS pathway approaches. The complementary approaches included a modification of the gene set enrichment analysis algorithm (i-GSEA4GWAS) and Fisher's exact test for pathway enrichment ratios. Twenty-five pathways were associated with PBC risk on LCT analysis in the Italian dataset at P<0.05, of which eight had an FDR<0.25. The top pathway in the Italian dataset was the TNF/stress related signaling pathway (p=7.38×10 -4, FDR=0.18). Twenty-six pathways were associated with PBC at the P<0.05 level using the LCT in the Canadian dataset with the regulation and function of ChREBP in liver pathway (p=5.68×10-4, FDR=0.285) emerging as the most significant pathway. Two pathways, phosphatidylinositol signaling system (Italian: p=0.016, FDR=0.436; Canadian: p=0.034, FDR=0.693) and hedgehog signaling (Italian: p=0.044, FDR=0.636; Canadian: p=0.041, FDR=0.693), were replicated at LCT P<0.05 in both datasets. Statistically significant association of both pathways with PBC genetic susceptibility was confirmed in the Italian dataset on i-GSEA4GWAS. Results for the phosphatidylinositol signaling system were also significant in both datasets on applying Fisher's exact test for pathway enrichment ratios. This study identified a combination of known and novel pathway-level associations with PBC risk. If functionally validated, the findings may yield fresh insights into the etiology of this complex autoimmune disease with possible preventive and therapeutic application.^