Predictive factors for vaginal douching and tampon use among US women: Are these behaviors risk factors for bacterial vaginosis and trichomonas?

The use of feminine products such as vaginal douches, tampons, and sanitary napkins are common among women. Despite the results of some studies that suggest an association between douching and bacterial vaginosis, douching remains a topic that is understudied. The possibility of an association between tampon use and infection has not been significantly investigated since the toxic shock outbreak in the 1980s. The first objective of our study was to evaluate demographic, reproductive health, and sexual behavior variables to establish an epidemiologic profile of menstruating women who reported douching and women who reported using sanitary napkins only. The second objective of our study was to evaluate whether the behaviors of douching and using tampons were associated with an increased risk of bacterial vaginosis or trichomonas. We analyzed these factors, using logistic regression, among the 3,174 women from the NHANES cross sectional data from 2001-2004, who met the inclusion criteria determined for our study. We established an epidemiologic profile for women who had the highest frequency of douching reported as women who were age 36-49, had a high school education or GED, black race, not taking oral contraceptives, reported vaginal symptoms in the last month, two or more sexual partners in the last year, or tested positive for bacterial vaginosis or trichomonas. The profile for those who had the highest frequency of exclusive sanitary napkin use included women with less than a high school education, married women, women classified as black or "other" in race, and women who were not on oral contraceptives. While we were able to establish a significant increase in the odds of douching among women who tested positive for bacterial vaginosis or trichomonas, we did not find any significant difference in the odds of exclusive napkin use and testing negative for bacterial vaginosis or trichomonas.^

RESPIRATORY COMPENSATION MECHANISMS IN THE UPPER AND LOWER RESPIRATORY TRACTS OF AN ANIMAL MODEL AFTER SUBCHRONIC INHALATION EXPOSURE TO FORMALDEHYDE: IMPLICATIONS FOR TOXICOLOGY RISK ASSESSMENT (DEPOSITION, DOSE RECEIVED, RESPONSE)

The potential for significant human populations to experience long-term inhalation of formaldehyde and reports of symptomatology due to this exposure has led to a considerable interest in the toxicologic assessment of risk from subchronic formaldehyde exposures using animal models. Since formaldehyde inhalation depresses certain respiratory parameters in addition to its other forms of toxicity, there is a potential for the alteration of the actual dose received by the exposed individual (and the resulting toxicity) due to this respiratory effect. The respiratory responses to formaldehyde inhalation and the subsequent pattern of deposition were therefore investigated in animals that had received subchronic exposure to the compound, and the potential for changes in the formaldehyde dose received due to long-term inhalation evaluated. Male Sprague-Dawley rats were exposed to either 0, 0.5, 3, or 15 ppm formaldehyde for 6 hours/day, 5 days/week for up to 6 months. The patterns of respiratory response, deposition and the compensation mechanisms involved were then determined in a series of formaldehyde test challenges to both the upper and to the lower respiratory tracts in separate groups of subchronically exposed animals and age-specific controls (four concentration groups, two time points). In both the control and pre-exposed animals, there was a characteristic recovery of respiratory parameters initially depressed by formaldehyde inhalation to at or approaching pre-exposure levels within 10 minutes of the initiation of exposure. Also, formaldehyde deposition was found to remain very high in the upper and lower tracts after long-term exposure. Therefore, there was probably little subsequent effect on the dose received by the exposed individual that was attributable to the repeated exposures. There was a diminished initial minute volume response in test challenges of both the upper and lower tracts of animals that had received at least 16 weeks of exposure to 15 ppm, with compensatory increases in tidal volume in the upper tract and respiratory rate in the lower tract. However, this dose-related effect was probably not relevant to human risk estimation because this formaldehyde dose is in excess of that experienced by human populations. ^

Attitudes About Predictive MEN1 Genetic Testing in Minors

Multiple Endocrine Neoplasia type 1 (MEN1) is a hereditary cancer syndrome characterized by tumors of the endocrine system. Tumors most commonly develop in the parathyroid glands, pituitary gland, and the gastro-entero pancreatic tract. MEN1 is a highly penetrant condition and age of onset is variable. Most patients are diagnosed in early adulthood; however, rare cases of MEN1 present in early childhood. Expert consensus opinion is that predictive genetic testing should be offered at age 5 years, however there are no evidence-based studies that clearly establish that predictive genetic testing at this age would be beneficial since most symptoms do not present until later in life. This study was designed to explore attitudes about the most appropriate age for predictive genetic testing from individuals at risk of having a child with MEN1. Participants who had an MEN1 mutation were invited to complete a survey and were asked to invite their spouses to participate as well. The survey included several validated measures designed to assess participants’ attitudes about predictive testing in minors. Fifty-eight affected participants and twenty-two spouses/partners completed the survey. Most participants felt that MEN1 genetic testing was appropriate in healthy minors. Younger age and increased knowledge of MEN1 genetics and inheritance predicted genetic testing at a younger age. Additionally, participants who saw more positive than negative general outcomes from genetic testing were more likely to favor genetic testing at younger ages. Overall, participants felt genetic testing should be offered at a younger age than most adult onset conditions and most felt the appropriate time for testing was when a child could understand and participate in the testing process. Psychological concerns seemed to be the primary focus of participants who favored later ages for genetic testing, while medical benefits were more commonly cited for younger age. This exploratory study has implications for counseling patients whose children are at risk of developing MEN1 and illustrates issues that are important to patients and their spouses when considering testing in children.

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

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

ATTITUDES AND PRACTICES OF GENETIC COUNSELORS IN PROVIDING PREDICTIVE TESTING TO MINORS AT RISK FOR LI-FRAUMENI SYNDROME

Li- Fraumeni Syndrome (LFS) is a rare autosomal dominant hereditary cancer syndrome caused by mutations in the TP53 gene that predisposes individuals to a wide variety of cancers, including breast cancer, soft tissue sarcomas, osteosarcomas, brain tumors, and adrenocortical carcinomas. Individuals found to carry germline mutations in TP53 have a 90% lifetime cancer risk, with a 20% chance to develop cancer under the age of 20. Despite the significant risk of childhood cancer, predictive testing for unaffected minors at risk for LFS historically has not been recommended, largely due to the lack of available and effective screening for the types of cancers involved. A recently developed screening protocol suggests an advantage to identifying and screening children at risk for LFS and we therefore hypothesized that this alongside with the availability of new screening modalities may substantiate a shift in recommendations for predictive genetic testing in minors at risk for LFS. We aimed to describe current screening recommendations that genetic counselors provide to this population as well as explore factors that may have influenced genetic counselors attitude and practice in regards to this issue. An online survey was emailed to members of the National Society of Genetic Counselors (NSGC) and the Canadian Association of Genetic Counsellors (CAGC). Of an estimated 1000 eligible participants, 172 completed surveys that were analyzed. Genetic counselors in this study were more likely to support predictive genetic testing for this population as the minor aged (p

Predictive validity of the personal background and preparation survey and effectiveness of targeted interventions among health science community college students

Existing data, collected from 1st-year students enrolled in a major Health Science Community College in the south central United States, for Fall 2010, Spring 2011, Fall 2011 and Spring 2012 semesters as part of the "Online Navigational Assessment Vehicle, Intervention Guidance, and Targeting of Risks (NAVIGATOR) for Undergraduate Minority Student Success" with CPHS approval number HSC-GEN-07-0158, was used for this thesis. The Personal Background and Preparation Survey (PBPS) and a two-question risk self-assessment subscale were administered to students during their 1st-year orientation. The PBPS total risk score, risk self-assessment total and overall scores, and Under Representative Minority Student (URMS) status were recorded. The purpose of this study is to evaluate and report the predictive validity of the indicators identified above for Adverse Academic Status Events (AASE) and Nonadvancement Adverse Academic Status Events (NAASE) as well as the effectiveness of interventions targeted using the PBPS among a diverse population of health science community college students. The predictive validity of the PBPS for AASE has previously been demonstrated among health science professions and graduate students (Johnson, Johnson, Kim, & McKee, 2009a; Johnson, Johnson, McKee, & Kim, 2009b). Data will be analyzed using binary logistic regression and correlation using SPSS 19 statistical package. Independent variables will include baseline- versus intervention-year treatments, PBPS, risk self-assessment, and URMS status. The dependent variables will be binary AASE and NAASE status. ^ The PBPS was the first reliable diagnostic and prescriptive instrument to establish documented predictive validity for student Adverse Academic Status Events (AASE) among students attending health science professional schools. These results extend the documented validity for the PBPS in predicting AASE to a health science community college student population. Results further demonstrated that interventions introduced using the PBPS were followed by approximately one-third reduction in the odds of Nonadvancement Adverse Academic Status Events (NAASE), controlling for URMS status and risk self-assessment scores. These results indicate interventions introduced using the PBPS may have potential to reduce AASE or attrition among URMS and nonURMS attending health science community colleges on a broader scale; positively impacting costs, shortages, and diversity of health science professionals.^

Inappropriate imaging utilization in Texas: Geographic variation and predictive factors

Objective::Describe and understand regional differences and associated multilevel factors (patient, provider and regional) to inappropriate utilization of advance imaging tests in the privately insured population of Texas. Methods: We analyzed Blue Cross Blue Shield of Texas claims dataset to study the advance imaging utilization during 2008-2010 in the PPO/PPO+ plans. We used three of CMS "Hospital Outpatient Quality Reporting" imaging efficiency measures. These included ordering MRI for low back pain without prior conservative management (OP-8) and utilization of combined with and without contrast abdominal CT (OP-10) and thorax CT (OP-11). Means and variation by hospital referral regions (HRR) in Texas were measured and a multilevel logistic regression for being a provider with high values for any the three OP measures was used in the analysis. We also analyzed OP-8 at the individual level. A multilevel logistic regression was used to identify predictive factors for having an inappropriate MRI for low back pain. Results: Mean OP-8 for Texas providers was 37.89%, OP-10 was 29.94% and OP-11 was 9.24%. Variation was higher for CT measure. And certain HRRs were consistently above the mean. Hospital providers had higher odds of high OP-8 values (OP-8: OR, 1.34; CI, 1.12-1.60) but had smaller odds of having high OP-10 and OP-11 values (OP-10: OR, 0.15; CI, 0.12-0.18; OP-11: OR, 0.43; CI, 0.34-0.53). Providers with the highest volume of imaging studies performed, were less likely to have high OP-8 measures (OP-8: OR, 0.58; CI, 0.48-0.70) but more likely to perform combined thoracic CT scans (OP-11: OR, 1.62; CI, 1.34-1.95). Males had higher odds of inappropriate MRI (OR, 1.21; CI, 1.16-1.26). Pattern of care in the six months prior to the MRI event was significantly associated with having an inappropriate MRI. Conclusion::We identified a significant variation in advance imaging utilization across Texas. Type of facility was associated with measure performance, but the associations differ according to the type of study. Last, certain individual characteristics such as gender, age and pattern of care were found to be predictors of inappropriate MRIs.^

Accumulation rates, carbon composition and Eocene carbonate compensation depths of ODP Sites 199-1218 and 199-1219

CaCO3, Corg, and biogenic SiO2 were measured in Eocene equatorial Pacific sediments from Sites 1218 and 1219, and bulk oxygen and carbon isotopes were measured on selected intervals from Site 1219. These data delineate a series of CaCO3 events that first appeared at ~48 Ma and continued to the Eocene/Oligocene boundary. Each event lasted 1-2 m.y. and is separated from the next by a low CaCO3 interval of a similar time span. The largest of these carbonate accumulation events (CAE-3) is in Magnetochron 18. It began at ~42.2 Ma, lasted until ~40.3 Ma, and was marked by higher than average productivity. The end of CAE-3 was abrupt and was associated with a large-scale carbon transfer to the oceans prior to warming of high-latitude regions. Changes in carbonate compensation depth associated with CAE excursions were small in the early part of the middle Eocene but increased to as much as 800 m by the late middle Eocene before decreasing into the late Eocene. Oxygen isotope data indicate that the carbonate events are associated with cooling conditions and may mark small glaciations in the Eocene.

The gap between recognition and the 'compensation business' : the claim against Britain for compensation by Kenya's former Mau Mau fighters

During the first Kibaki administration (2002-2007), a movement by the former Mau Mau fighters demanded recognition for the role that they had played in the achievement of independence. They began to demand, also, monetary compensation for past injustices. Why had it taken over 40 years (from independence in 1963) for the former Mau Mau fighters to initiate this movement? What can be observed as the outcome of their movement? To answer these questions, three different historical currents need to be taken into account. These were, respectively, changing trends in the government of Kenya, progress in historical research into the actual circumstances of colonial control, and a realization, based on mounting experience, that launching a legal action against Britain could turn out to be a lucrative initiative. This paper concludes that, regardless of the actual purpose of the legal case, neither of their objectives was certain to be achieved. Two inescapable realities remain: the doubts cast on the reputation of the government by its decision to lift the Mau Mau‟s outlaw status – a decision that was widely seen as a latter-day example of the „Kikuyu favouritism‟ policy followed by the first Kibaki administration – and the popular interpretation of the involvement of Leigh Day, well known in Kenya ever since the unexploded bombs case for its success in obtaining substantial compensation payments, as a vehicle for squeezing large amounts of money from the British government for the benefit of the Kikuyu people.

Nonrigid Motion Compensation of Free Breathing Acquired Myocardial Perfusion Data

In this work, we present a novel method to compensate the movement in images acquired during free breathing using first-pass gadolinium enhanced, myocardial perfusion magnetic resonance imaging (MRI). First, we use independent component analysis (ICA) to identify the optimal number of independent components (ICs) that separate the breathing motion from the intensity change induced by the contrast agent. Then, synthetic images are created by recombining the ICs, but other then in previously published work (Milles et al. 2008), we omit the component related to motion, and therefore, the resulting reference image series is free of motion. Motion compensation is then achieved by using a multi-pass non-rigid image registration scheme. We tested our method on 15 distinct image series (5 patients) consisting of 58 images each and we validated our method by comparing manually tracked intensity profiles of the myocardial sections to automatically generated ones before and after registration. The average correlation to the manually obtained curves before registration 0:89 0:11 was increased to 0:98 0:02

Advanced predictive quality control strategy involving different facilities

There are many industries that use highly technological solutions to improve quality in all of their products. The steel industry is one example. Several automatic surface-inspection systems are used in the steel industry to identify various types of defects and to help operators decide whether to accept, reroute, or downgrade the material, subject to the assessment process. This paper focuses on promoting a strategy that considers all defects in an integrated fashion. It does this by managing the uncertainty about the exact position of a defect due to different process conditions by means of Gaussian additive influence functions. The relevance of the approach is in making possible consistency and reliability between surface inspection systems. The results obtained are an increase in confidence in the automatic inspection system and an ability to introduce improved prediction and advanced routing models. The prediction is provided to technical operators to help them in their decision-making process. It shows the increase in improvement gained by reducing the 40 % of coils that are downgraded at the hot strip mill because of specific defects. In addition, this technology facilitates an increase of 50 % in the accuracy of the estimate of defect survival after the cleaning facility in comparison to the former approach. The proposed technology is implemented by means of software-based, multi-agent solutions. It makes possible the independent treatment of information, presentation, quality analysis, and other relevant functions.

Automatic motion compensation of free breathing acquired myocardial perfusion data by using independent component analysis

Images acquired during free breathing using first-pass gadolinium-enhanced myocardial perfusion magnetic resonance imaging (MRI) exhibit a quasiperiodic motion pattern that needs to be compensated for if a further automatic analysis of the perfusion is to be executed. In this work, we present a method to compensate this movement by combining independent component analysis (ICA) and image registration: First, we use ICA and a time?frequency analysis to identify the motion and separate it from the intensity change induced by the contrast agent. Then, synthetic reference images are created by recombining all the independent components but the one related to the motion. Therefore, the resulting image series does not exhibit motion and its images have intensities similar to those of their original counterparts. Motion compensation is then achieved by using a multi-pass image registration procedure. We tested our method on 39 image series acquired from 13 patients, covering the basal, mid and apical areas of the left heart ventricle and consisting of 58 perfusion images each. We validated our method by comparing manually tracked intensity profiles of the myocardial sections to automatically generated ones before and after registration of 13 patient data sets (39 distinct slices). We compared linear, non-linear, and combined ICA based registration approaches and previously published motion compensation schemes. Considering run-time and accuracy, a two-step ICA based motion compensation scheme that first optimizes a translation and then for non-linear transformation performed best and achieves registration of the whole series in 32 ± 12 s on a recent workstation. The proposed scheme improves the Pearsons correlation coefficient between manually and automatically obtained time?intensity curves from .84 ± .19 before registration to .96 ± .06 after registration

Magneto-optic current sensor with Faraday mirror for linear birefringence compensation

Fiber optic sensors have some advantages in subjects related with electrical current and magnetic field measurement. In spite of the optical fiber utilization advantages we have to take into account undesirable effects, which are present in real non-ideal optical fibers. In telecommunication and sensor application fields the presence of inherent and induced birefringence is crucial. The presence of birefringence may cause an undesirable change in the polarization state. In order to compensate the linear birefringence a promising method has been chosen. This method employs orthogonal polarization conjugation in the back propagation direction of the light wave in the fiber. A study and a simulation of an experimental setup are realized with the advantage of a significant sensitivity improvement.