13 resultados para Multiple Baseline Design

em DigitalCommons@The Texas Medical Center


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Cross-sectional designs, longitudinal designs in which a single cohort is followed over time, and mixed-longitudinal designs in which several cohorts are followed for a shorter period are compared by their precision, potential for bias due to age, time and cohort effects, and feasibility. Mixed longitudinal studies have two advantages over longitudinal studies: isolation of time and age effects and shorter completion time. Though the advantages of mixed-longitudinal studies are clear, choosing an optimal design is difficult, especially given the number of possible combinations of the number of cohorts and number of overlapping intervals between cohorts. The purpose of this paper is to determine the optimal design for detecting differences in group growth rates.^ The type of mixed-longitudinal study appropriate for modeling both individual and group growth rates is called a "multiple-longitudinal" design. A multiple-longitudinal study typically requires uniform or simultaneous entry of subjects, who are each observed till the end of the study.^ While recommendations for designing pure-longitudinal studies have been made by Schlesselman (1973b), Lefant (1990) and Helms (1991), design recommendations for multiple-longitudinal studies have never been published. It is shown that by using power analyses to determine the minimum number of occasions per cohort and minimum number of overlapping occasions between cohorts, in conjunction with a cost model, an optimal multiple-longitudinal design can be determined. An example of systolic blood pressure values for cohorts of males and cohorts of females, ages 8 to 18 years, is given. ^

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Treatment for cancer often involves combination therapies used both in medical practice and clinical trials. Korn and Simon listed three reasons for the utility of combinations: 1) biochemical synergism, 2) differential susceptibility of tumor cells to different agents, and 3) higher achievable dose intensity by exploiting non-overlapping toxicities to the host. Even if the toxicity profile of each agent of a given combination is known, the toxicity profile of the agents used in combination must be established. Thus, caution is required when designing and evaluating trials with combination therapies. Traditional clinical design is based on the consideration of a single drug. However, a trial of drugs in combination requires a dose-selection procedure that is vastly different than that needed for a single-drug trial. When two drugs are combined in a phase I trial, an important trial objective is to determine the maximum tolerated dose (MTD). The MTD is defined as the dose level below the dose at which two of six patients experience drug-related dose-limiting toxicity (DLT). In phase I trials that combine two agents, more than one MTD generally exists, although all are rarely determined. For example, there may be an MTD that includes high doses of drug A with lower doses of drug B, another one for high doses of drug B with lower doses of drug A, and yet another for intermediate doses of both drugs administered together. With classic phase I trial designs, only one MTD is identified. Our new trial design allows identification of more than one MTD efficiently, within the context of a single protocol. The two drugs combined in our phase I trial are temsirolimus and bevacizumab. Bevacizumab is a monoclonal antibody targeting the vascular endothelial growth factor (VEGF) pathway which is fundamental for tumor growth and metastasis. One mechanism of tumor resistance to antiangiogenic therapy is upregulation of hypoxia inducible factor 1α (HIF-1α) which mediates responses to hypoxic conditions. Temsirolimus has resulted in reduced levels of HIF-1α making this an ideal combination therapy. Dr. Donald Berry developed a trial design schema for evaluating low, intermediate and high dose levels of two drugs given in combination as illustrated in a recently published paper in Biometrics entitled “A Parallel Phase I/II Clinical Trial Design for Combination Therapies.” His trial design utilized cytotoxic chemotherapy. We adapted this design schema by incorporating greater numbers of dose levels for each drug. Additional dose levels are being examined because it has been the experience of phase I trials that targeted agents, when given in combination, are often effective at dosing levels lower than the FDA-approved dose of said drugs. A total of thirteen dose levels including representative high, intermediate and low dose levels of temsirolimus with representative high, intermediate, and low dose levels of bevacizumab will be evaluated. We hypothesize that our new trial design will facilitate identification of more than one MTD, if they exist, efficiently and within the context of a single protocol. Doses gleaned from this approach could potentially allow for a more personalized approach in dose selection from among the MTDs obtained that can be based upon a patient’s specific co-morbid conditions or anticipated toxicities.

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Context: Despite tremendous strides in HIV treatment over the past decade, resistance remains a major problem. A growing number of patients develop resistance and require new therapies to suppress viral replication. ^ Objective: To assess the safety of multiple administrations of the anti-CD4 receptor (anti-CD4) monoclonal antibody ibalizumab given as intravenous (IV) infusions, in three dosage regimens, in subjects infected with human immunodeficiency virus (HIV-1). ^ Design: Phase 1, multi-center, open-label, randomized clinical trial comparing the safety, pharmacokinetics and antiviral activity of three dosages of ibalizumab. ^ Setting: Six clinical trial sites in the United States. ^ Participants: A total of twenty-two HIV-positive patients on no anti-retroviral therapy or a stable failing regimen. ^ Intervention: Randomized to one of two treatment groups in Arms A and B followed by non-randomized enrollment in Arm C. Patients randomized to Arm A received 10 mg/kg of ibalizumab every 7 days, for a total of 10 doses; patients randomized to Arm B received a total of six doses of ibalizumab; a single loading dose of 10 mg/kg on Day 1 followed by five maintenance doses of 6 mg/kg every 14 days, starting at Week 1. Patients assigned to Arm C received 25 mg/kg of ibalizumab every 14 days for a total of 5 doses. All patients were followed for safety for an additional 7 to 8 weeks. ^ Main Outcome Measures: Clinical and laboratory assessments of safety and tolerability of multiple administrations of ibalizumab in HIV-infected patients. Secondary measures of efficacy include HIV-1 RNA (viral load) measurements. ^ Results: 21 patients were treatment-experienced and 1 was naïve to HIV therapy. Six patients were failing despite therapy and 15 were on no current HIV treatment. Mean baseline viral load (4.78 log 10; range 3.7-5.9) and CD4+ cell counts (332/μL; range 89-494) were similar across cohorts. Mean peak decreases in viral load from baseline of 0.99 log10(1.11 log10, and 0.96 log 10 occurred by Wk 2 in Cohorts A, B and C, respectively. Viral loads decreased by >1.0 log10 in 64%; 4 patients viral loads were suppressed to < 400 copies/mL. Viral loads returned towards baseline by Week 9 with reduced susceptibility to ibalizumab. CD4+ cell counts rose transiently and returned toward baseline. Maximum median elevations above BL in CD4+ cell counts for Cohorts A, B and C were +257, +198 and +103 cells/μL, respectively and occurred within 3 Wks in 16 of 22 subjects. The half-life of ibalizumab was 3-3.5 days and elimination was characteristic of capacity-limited kinetics. Administration of ibalizumab was well tolerated. Four serious adverse events were reported during the study. None of these events were related to study drug. Headache, nausea and cough were the most frequently reported treatment emergent adverse events and there were no laboratory abnormalities related to study drug. ^ Conclusions: Ibalizumab administered either weekly or bi-weekly was safe, well tolerated, and demonstrated antiviral activity. Further studies with ibalizumab in combination with standard antiretroviral treatments are warranted.^

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A two-pronged approach for the automatic quantitation of multiple sclerosis (MS) lesions on magnetic resonance (MR) images has been developed. This method includes the design and use of a pulse sequence for improved lesion-to-tissue contrast (LTC) and seeks to identify and minimize the sources of false lesion classifications in segmented images. The new pulse sequence, referred to as AFFIRMATIVE (Attenuation of Fluid by Fast Inversion Recovery with MAgnetization Transfer Imaging with Variable Echoes), improves the LTC, relative to spin-echo images, by combining Fluid-Attenuated Inversion Recovery (FLAIR) and Magnetization Transfer Contrast (MTC). In addition to acquiring fast FLAIR/MTC images, the AFFIRMATIVE sequence simultaneously acquires fast spin-echo (FSE) images for spatial registration of images, which is necessary for accurate lesion quantitation. Flow has been found to be a primary source of false lesion classifications. Therefore, an imaging protocol and reconstruction methods are developed to generate "flow images" which depict both coherent (vascular) and incoherent (CSF) flow. An automatic technique is designed for the removal of extra-meningeal tissues, since these are known to be sources of false lesion classifications. A retrospective, three-dimensional (3D) registration algorithm is implemented to correct for patient movement which may have occurred between AFFIRMATIVE and flow imaging scans. Following application of these pre-processing steps, images are segmented into white matter, gray matter, cerebrospinal fluid, and MS lesions based on AFFIRMATIVE and flow images using an automatic algorithm. All algorithms are seamlessly integrated into a single MR image analysis software package. Lesion quantitation has been performed on images from 15 patient volunteers. The total processing time is less than two hours per patient on a SPARCstation 20. The automated nature of this approach should provide an objective means of monitoring the progression, stabilization, and/or regression of MS lesions in large-scale, multi-center clinical trials. ^

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Low parental monitoring is related to youth risk behaviors such as delinquency and aggression. The purpose of this dissertation was to describe the development and evaluation of a parent education intervention to increase parental monitoring in Hispanic parents of middle school children.^ The first study described the process of intervention mapping as used to develop Padres Trabajando por la Paz, a newsletter intervention for parents. Using theory, empirical literature, and information from the target population, performance objectives and determinants for monitoring were defined. Learning objectives were specified and a staged social-cognitive approach was used to develop methods and strategies delivered through newsletters.^ The second study examined the outcomes of a randomized trial of the newsletter intervention. Outcome measures consisted of a general measure of monitoring, parent and child reports of monitoring behaviors targeted by the intervention, and psychosocial determinants of monitoring (self-efficacy, norms, outcome expectancies, knowledge, and beliefs). Seventy-seven parents completed the randomized trial, half of which received four newsletters over an eight-week period. Results revealed a significant interaction effect for baseline and treatment for parent's reports of norms for monitoring (p =.009). Parents in the experimental condition who scored low at baseline reported increased norms for monitoring at follow-up. A significant interaction effect for child reports of parental monitoring behaviors (p =.04) reflected an small increase across baseline levels in the experimental condition and decreases for the control condition at higher baseline scores. Both groups of parents reported increased levels of monitoring at follow-up. No other outcome measures varied significantly by condition.^ The third study examined the relationship between the psychosocial determinants of parental monitoring and parental monitoring behaviors in the study population. Weak evidence for a relationship between outcome expectancies and parental monitoring behaviors suggests further research in the area utilizing stronger empirical models such as longitudinal design and structural equation modeling.^ The low-cost, minimal newsletter intervention showed promise for changing norms among Hispanic parents for parental monitoring. In light of the importance of parental monitoring as a protective factor for youth health risk behaviors, more research needs to be done to develop and evaluate interventions to increase parental monitoring. ^

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Using stress and coping as a unifying theoretical concept, a series of five models was developed in order to synthesize the survey questions and to classify information. These models identified the question, listed the research study, described measurements, listed workplace data, and listed industry and national reference data.^ A set of 38 instrument questions was developed within the five coping correlate categories. In addition, a set of 22 stress symptoms was also developed. The study was conducted within two groups, police and professors, on a large university campus. The groups were selected because their occupations were diverse, but they were a part of the same macroenvironment. The premise was that police officers would be more highly stressed than professors.^ Of a total study group of 80, there were 37 respondents. The difference in the mean stress responses was observable between the two groups. Not only were the responses similar within each group, but the stress level of response was also similar within each group. While the response to the survey instrument was good, only 3 respondents answered the stress symptom survey properly. It was determined that none of the 37 respondents believed that they were ill. This perception of being well was also evidenced by the grand mean of the stress scores of 2.76 (3.0 = moderate stress). This also caused fewer independent variables to be entered in the multiple regression model.^ The survey instrument was carefully designed to be universal. Universality is the ability to transcend occupational or regional definitions as applied to stress. It is the ability to measure responses within broad categories such as physiological, emotional, behavioral, social, and cognitive functions without losing the ability to measure the detail within the individual questions, or the relationships between questions and categories.^ Replication is much easier to achieve with standardized categories, questions, and measurement procedures such as those developed for the universal survey instrument. Because the survey instrument is universal it can be used as an analytical device, an assessment device, a basic tool for planning and a follow-up instrument to measure individual response to planned reductions in occupational stress. (Abstract shortened with permission of author.) ^

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Retroviruses are RNA viruses that replicate through a double-stranded DNA intermediate. The viral enzyme reverse transcriptase copies the retroviral genomic RNA into this DNA intermediate through the process of reverse transcription. Many variables can affect the fidelity of reverse transcriptase during reverse transcription, including specific sequences within the retroviral genome. ^ Previous studies have observed that multiple cloning sites (MCS) and sequences predicted to form stable hairpin structures are hotspots for deletion during retroviral replication. The studies described in this dissertation were performed to elucidate the variables that affect the stability of MCS and hairpin structures in retroviral vectors. Two series of retroviral vectors were constructed and characterized in these studies. ^ Spleen necrosis virus-based vectors were constructed containing separate MCS insertions of varying length, orientation, and symmetry. The only MCS that was a hotspot for deletion formed a stable hairpin structure. Upon more detailed study, the MCS previously reported as a hotspot for deletion was found to contain a tandem linker insertion that formed a hairpin structure. Murine leukemia virus-based vectors were constructed containing separate sequence insertions of either inverted repeat symmetry (122IR) that could form a hairpin structure, or little symmetry (122c) that would form a less stable structure. These insertions were made into either the neomycin resistance marker ( neo) or the hygromycin resistance marker (hyg) of the vector. 122c was stable in both neo and hyg, while 122IR was preferentially deleted in neo and was remarkably unstable in hyg. ^ These results suggest that MCS are hotspots for deletion in retroviral vectors if they can form hairpin structures, and that hairpin structures can be highly unstable at certain locations in retroviral vectors. This information may contribute to improved design of retroviral vectors for such uses as human gene therapy, and will contribute to a greater understanding of the basic science of retroviral reverse transcription. ^

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Despite of the proven efficacy of the Pap test, Asian populations still have low Pap screening compliance. The purpose of this dissertation was to investigate factors that influencing women's decision to obtain a Pap test, and to describe the development and evaluation of a cervical cancer educational program promoting the Pap screening behavior among women in Taiwan. ^ The first study examined factors associated with Pap screening compliance. Psychometric properties of measurement instruments were also assessed. The scale reliabilities were as the follows: Cronbach alpha 0.70 for knowledge scale, 0.88 for pros scale, 0.68 for cons scale, and 0.72 for perceived norms scale. Results from multiple logistic regression analysis, after adjusted for marital status, showed women who compliant to Pap screening guidelines had significantly higher knowledge, higher perceived benefits (pros), lower perceived barriers (cons), and higher perceived norms to receive a Pap test. ^ The second study described the development of a program called “Love yourself before you take care of your family”, designed to increase Pap screening behavior among women in Taiwan. The development of this program was guided by Intervention Mapping (IM), an innovative process of intervention design. The program used methods such as information transmission, modeling, persuasion, and facilitation. Strategies included direct mail campaigns, role model stories with women's testimonials, and phone intervention. ^ The third study examined the effectiveness of a randomized trial of the carefully-designed intervention (N = 424). Participants were female family members of inpatients admitted to one of the major teaching hospitals in Taiwan during August and September 1999. Women in the intervention group reported a higher rate of receiving a Pap test than women in the control group (50% versus 32%) after a three-month intervention (p = 0.002). Women in the intervention group showed increased knowledge (p = .016), perceived pros (p = 0.008), and susceptibility (p = .011) between baseline and follow-up. They also showed higher perceived pros of Pap tests than women in control group at follow-up (p = .031). This result suggested that program development based on theories and evidences could maximize the intervention impact for a specific target population. ^

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Mixed longitudinal designs are important study designs for many areas of medical research. Mixed longitudinal studies have several advantages over cross-sectional or pure longitudinal studies, including shorter study completion time and ability to separate time and age effects, thus are an attractive choice. Statistical methodology used in general longitudinal studies has been rapidly developing within the last few decades. Common approaches for statistical modeling in studies with mixed longitudinal designs have been the linear mixed-effects model incorporating an age or time effect. The general linear mixed-effects model is considered an appropriate choice to analyze repeated measurements data in longitudinal studies. However, common use of linear mixed-effects model on mixed longitudinal studies often incorporates age as the only random-effect but fails to take into consideration the cohort effect in conducting statistical inferences on age-related trajectories of outcome measurements. We believe special attention should be paid to cohort effects when analyzing data in mixed longitudinal designs with multiple overlapping cohorts. Thus, this has become an important statistical issue to address. ^ This research aims to address statistical issues related to mixed longitudinal studies. The proposed study examined the existing statistical analysis methods for the mixed longitudinal designs and developed an alternative analytic method to incorporate effects from multiple overlapping cohorts as well as from different aged subjects. The proposed study used simulation to evaluate the performance of the proposed analytic method by comparing it with the commonly-used model. Finally, the study applied the proposed analytic method to the data collected by an existing study Project HeartBeat!, which had been evaluated using traditional analytic techniques. Project HeartBeat! is a longitudinal study of cardiovascular disease (CVD) risk factors in childhood and adolescence using a mixed longitudinal design. The proposed model was used to evaluate four blood lipids adjusting for age, gender, race/ethnicity, and endocrine hormones. The result of this dissertation suggest the proposed analytic model could be a more flexible and reliable choice than the traditional model in terms of fitting data to provide more accurate estimates in mixed longitudinal studies. Conceptually, the proposed model described in this study has useful features, including consideration of effects from multiple overlapping cohorts, and is an attractive approach for analyzing data in mixed longitudinal design studies.^

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Aim To examine the association between the crack cocaine cessation and risky sexual behaviors. Design and setting Between June 2002 and March 2005, a sample of African-American residents of Houston, Texas who were using crack at the time of enrollment participated in a cohort study to evaluate per outreach interventions to reduce HIV risk behaviors. The sample for this study consisted of 351 women and men who completed structured surveys at baseline and at six months about socio-demographic characteristics, drug use, and sexual behaviors. Multivariate logistic regression was used to analyze the association between crack cessation and risky sexual behaviors at follow-up, while controlling for confounding characteristics. Measurements Crack cessation was defined as reporting no crack use in the 30 days prior to the follow-up interview. Possible associated factors included unprotected sex, having multiple sex partners, trading sex for money/drugs, crack use, and socio-demographic variables. Findings At the six-month follow-up interview, 21% of participants reported that they had not used crack in the previous 30 days. For women, crack cessation was significantly associated with having only one sex partner at follow-up; for men, crack cessation was significantly associated with being single, separated, or divorced at baseline, having only one sex partner at follow-up, and initiating protected sex by follow-up. Conclusion These findings support previous research indicating that crack use is associated with unprotected sex and multiple sexual partners, as men and women who ceased crack use were less likely to engage in these risky sexual behaviors. Findings demonstrate that treatment for crack use could have a meaningful effect on risky sexual behaviors and HIV/STI prevention.^

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High-resolution, small-bore PET systems suffer from a tradeoff between system sensitivity, and image quality degradation. In these systems long crystals allow mispositioning of the line of response due to parallax error and this mispositioning causes resolution blurring, but long crystals are necessary for high system sensitivity. One means to allow long crystals without introducing parallax errors is to determine the depth of interaction (DOI) of the gamma ray interaction within the detector module. While DOI has been investigated previously, newly available solid state photomultipliers (SSPMs) well-suited to PET applications and allow new modules for investigation. Depth of interaction in full modules is a relatively new field, and so even if high performance DOI capable modules were available, the appropriate means to characterize and calibrate the modules are not. This work presents an investigation of DOI capable arrays and techniques for characterizing and calibrating those modules. The methods introduced here accurately and reliably characterize and calibrate energy, timing, and event interaction positioning. Additionally presented is a characterization of the spatial resolution of DOI capable modules and a measurement of DOI effects for different angles between detector modules. These arrays have been built into a prototype PET system that delivers better than 2.0 mm resolution with a single-sided-stopping-power in excess of 95% for 511 keV g's. The noise properties of SSPMs scale with the active area of the detector face, and so the best signal-to-noise ratio is possible with parallel readout of each SSPM photodetector pixel rather than multiplexing signals together. This work additionally investigates several algorithms for improving timing performance using timing information from multiple SSPM pixels when light is distributed among several photodetectors.

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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.

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The objectives of this dissertation were to evaluate health outcomes, quality improvement measures, and the long-term cost-effectiveness and impact on diabetes-related microvascular and macrovascular complications of a community health worker-led culturally tailored diabetes education and management intervention provided to uninsured Mexican Americans in an urban faith-based clinic. A prospective, randomized controlled repeated measures design was employed to compare the intervention effects between: (1) an intervention group (n=90) that participated in the Community Diabetes Education (CoDE) program along with usual medical care; and (2) a wait-listed comparison group (n=90) that received only usual medical care. Changes in hemoglobin A1c (HbA1c) and secondary outcomes (lipid status, blood pressure and body mass index) were assessed using linear mixed-models and an intention-to-treat approach. The CoDE group experienced greater reduction in HbA1c (-1.6%, p<.001) than the control group (-.9%, p<.001) over the 12 month study period. After adjusting for group-by-time interaction, antidiabetic medication use at baseline, changes made to the antidiabetic regime over the study period, duration of diabetes and baseline HbA1c, a statistically significant intervention effect on HbA1c (-.7%, p=.02) was observed for CoDE participants. Process and outcome quality measures were evaluated using multiple mixed-effects logistic regression models. Assessment of quality indicators revealed that the CoDE intervention group was significantly more likely to have received a dilated retinal examination than the control group, and 53% achieved a HbA1c below 7% compared with 38% of control group subjects. Long-term cost-effectiveness and impact on diabetes-related health outcomes were estimated through simulation modeling using the rigorously validated Archimedes Model. Over a 20 year time horizon, CoDE participants were forecasted to have less proliferative diabetic retinopathy, fewer foot ulcers, and reduced numbers of foot amputations than control group subjects who received usual medical care. An incremental cost-effectiveness ratio of $355 per quality-adjusted life-year gained was estimated for CoDE intervention participants over the same time period. The results from the three areas of program evaluation: impact on short-term health outcomes, quantification of improvement in quality of diabetes care, and projection of long-term cost-effectiveness and impact on diabetes-related health outcomes provide evidence that a community health worker can be a valuable resource to reduce diabetes disparities for uninsured Mexican Americans. This evidence supports formal integration of community health workers as members of the diabetes care team.^