Author response: "Missed opportunity related to statistical methods"

"We thank MrGilder for his considered comments and suggestions for alternative analyses of our data. We also appreciate Mr Gilder’s support of our call for larger studies to contribute to the evidence base for preoperative loading with high-carbohydrate fluids..."

Prevalence and predictors of giving birth in health facilities in Bugesera District, Rwanda.

BACKGROUND: The proportion of births attended by skilled health personnel is one of two indicators used to measure progress towards Millennium Development Goal 5, which aims for a 75% reduction in global maternal mortality ratios by 2015. Rwanda has one of the highest maternal mortality ratios in the world, estimated between 249-584 maternal deaths per 100,000 live births. The objectives of this study were to quantify secular trends in health facility delivery and to identify factors that affect the uptake of intrapartum healthcare services among women living in rural villages in Bugesera District, Eastern Province, Rwanda. METHODS: Using census data and probability proportional to size cluster sampling methodology, 30 villages were selected for community-based, cross-sectional surveys of women aged 18-50 who had given birth in the previous three years. Complete obstetric histories and detailed demographic data were elicited from respondents using iPad technology. Geospatial coordinates were used to calculate the path distances between each village and its designated health center and district hospital. Bivariate and multivariate logistic regressions were used to identify factors associated with delivery in health facilities. RESULTS: Analysis of 3106 lifetime deliveries from 859 respondents shows a sharp increase in the percentage of health facility deliveries in recent years. Delivering a penultimate baby at a health facility (OR = 4.681 [3.204 - 6.839]), possessing health insurance (OR = 3.812 [1.795 - 8.097]), managing household finances (OR = 1.897 [1.046 - 3.439]), attending more antenatal care visits (OR = 1.567 [1.163 - 2.112]), delivering more recently (OR = 1.438 [1.120 - 1.847] annually), and living closer to a health center (OR = 0.909 [0.846 - 0.976] per km) were independently associated with facility delivery. CONCLUSIONS: The strongest correlates of facility-based delivery in Bugesera District include previous delivery at a health facility, possession of health insurance, greater financial autonomy, more recent interactions with the health system, and proximity to a health center. Recent structural interventions in Rwanda, including the rapid scale-up of community-financed health insurance, likely contributed to the dramatic improvement in the health facility delivery rate observed in our study.

Recent developments in statistical methods for detecting genetic loci affecting phenotypic variability

A number of recent works have introduced statistical methods for detecting genetic loci that affect phenotypic variability, which we refer to as variability-controlling quantitative trait loci (vQTL). These are genetic variants whose allelic state predicts how much phenotype values will vary about their expected means. Such loci are of great potential interest in both human and non-human genetic studies, one reason being that a detected vQTL could represent a previously undetected interaction with other genes or environmental factors. The simultaneous publication of these new methods in different journals has in many cases precluded opportunity for comparison. We survey some of these methods, the respective trade-offs they imply, and the connections between them. The methods fall into three main groups: classical non-parametric, fully parametric, and semi-parametric two-stage approximations. Choosing between alternatives involves balancing the need for robustness, flexibility, and speed. For each method, we identify important assumptions and limitations, including those of practical importance, such as their scope for including covariates and random effects. We show in simulations that both parametric methods and their semi-parametric approximations can give elevated false positive rates when they ignore mean-variance relationships intrinsic to the data generation process. We conclude that choice of method depends on the trait distribution, the need to include non-genetic covariates, and the population size and structure, coupled with a critical evaluation of how these fit with the assumptions of the statistical model.

Comparison of two statistical methods for rare variant association analysis

Studies have shown that rare genetic variants have stronger effects in predisposing common diseases, and several statistical methods have been developed for association studies involving rare variants. In order to better understand how these statistical methods perform, we seek to compare two recently developed rare variant statistical methods (VT and C-alpha) on 10,000 simulated re-sequencing data sets with disease status and the corresponding 10,000 simulated null data sets. The SLC1A1 gene has been suggested to be associated with diastolic blood pressure (DBP) in previous studies. In the current study, we applied VT and C-alpha methods to the empirical re-sequencing data for the SLC1A1 gene from 300 whites and 200 blacks. We found that VT method obtains higher power and performs better than C-alpha method with the simulated data we used. The type I errors were well-controlled for both methods. In addition, both VT and C-alpha methods suggested no statistical evidence for the association between the SLC1A1 gene and DBP. Overall, our findings provided an important comparison of the two statistical methods for future reference and provided preliminary and pioneer findings on the association between the SLC1A1 gene and blood pressure.^

Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^

Applying logic forms and statistical methods to CL-SR performance

This paper describes a CL-SR system that employs two different techniques: the first one is based on NLP rules that consist on applying logic forms to the topic processing while the second one basically consists on applying the IR-n statistical search engine to the spoken document collection. The application of logic forms to the topics allows to increase the weight of topic terms according to a set of syntactic rules. Thus, the weights of the topic terms are used by IR-n system in the information retrieval process.

Analytical statistics : statistical methods, testing for significance /

Mode of access: Internet.

The Pratt Pouch Provides a Three-Fold Access Increase to Antiretroviral Medication for Births outside Health Facilities in Southern Zambia.

INTRODUCTION: Modern day antiretroviral therapy allows HIV+ pregnant women to lower the likelihood of viral transmission to their infants before, during, and after birth from 20-45% to less than 5%. In developing countries, where non-facility births may outnumber facility births, infant access to safe antiretroviral medication during the critical first three days after birth is often limited. A single-dose, polyethylene pouch ("Pratt Pouch") addresses this challenge by allowing the medication to be distributed to mothers during antenatal care. METHODS: The Pratt Pouch was introduced as part of a one year clinical feasibility study in two districts in Southern Province, Zambia. Participating nurses, community health workers, and pharmacists were trained before implementation. Success in achieving improved antiretroviral medication access was assessed via pre intervention and post intervention survey responses by HIV+ mothers. RESULTS: Access to medication for HIV-exposed infants born outside of a health facility increased from 35% (17/51) before the introduction of the pouch to 94% (15/16) after (p<0.05). A non-significant increase in homebirth rates from 33% (pre intervention cohort) to 50% (post intervention cohort) was observed (p>0.05). Results remained below the national average homebirth rate of 52%. Users reported minimal spillage and a high level of satisfaction with the Pratt Pouch. CONCLUSION: The Pratt Pouch enhances access to infant antiretroviral medication in a rural, non-facility birth setting. Wide scale implementation could have a substantial global impact on HIV transmission rates from mother to child.

ART attrition across health facilities implementing Option B+ in Haiti

Thesis (Master's)--University of Washington, 2016-08

Seeing the Wood for the Trees: A Critical Evaluation of Methods to Estimate the Parameters of Stochastic Differential Equations

Maximum-likelihood estimates of the parameters of stochastic differential equations are consistent and asymptotically efficient, but unfortunately difficult to obtain if a closed-form expression for the transitional probability density function of the process is not available. As a result, a large number of competing estimation procedures have been proposed. This article provides a critical evaluation of the various estimation techniques. Special attention is given to the ease of implementation and comparative performance of the procedures when estimating the parameters of the Cox–Ingersoll–Ross and Ornstein–Uhlenbeck equations respectively.

Book review: "Qualitative Health Psychology. Theories and Methods" Michael Murray and Kerry Chamberlain (Eds.)

Qualitative Health Psychology aims to contribute to the debate about the nature of psychology and of science through ‘an examination of the role of qualitative research within health psychology’ (p. 3). The editors, in bringing together contributors from the UK, Ireland, Canada, Brazil, New Zealand and Australia, have compiled a text that reflects different uses of qualitative health research in diverse social and cultural contexts. Structured into three parts, the book encompasses key theoretical and methodological issues in qualitative research in its attempt to encourage broad epistemological debate within health psychology.

Characteristics of chemotherapy practice in rural and remote area health facilities in Queensland

Objective The overall objective of this study was to document the nature of the chemotherapy nursing practice of rural and remote area nurses in Queensland. Design A questionnaire survey that elicited descriptive quantitative and qualitative data. Setting Forty-seven rural and remote area health facilities in Queensland involved in the administration of chemotherapy. Subjects Sixty-seven Queensland rural and remote area nurses involved in the administration of cytotoxic drugs. Main outcome measures: Characteristics of chemotherapy practice including context of practice, amount and type of chemotherapy administered, logistical problems, level of support from referral centres, policies and procedures, safety issues. Results The results indicate that the risks to nursing staff and the potential for poor patient outcomes are higher than in specialist chemotherapy facilities. This is largely due to the human and material resource constraints characteristic of rural practice. These include a lack of understanding on the part of metropolitan-based health departments and the specialist cancer centres that refer patients to rural areas of the constraints that may adversely influence patient outcomes. Conclusions It is essential that steps are taken to ensure that rural and remote area cancer patients have equitable access to safe and competent chemotherapy care delivered in their choice of context, and the results of this study provide guidance on ways that this can be achieved.

Why nurses are resigning from rural and remote Queensland health facilities

This paper presents a selection of the results reported in the study “Factors Influencing the Recruitment and Retention of Rural and Remote Area Nurses in Queensland” (Hegney et al 2001). The main aim of this study was to determine why nurses in those rural and remote areas of Queensland that reported higher than State average turnover rates between February 1999 and May 2000, chose to leave their employment. The study therefore investigated the factors that influenced nurses' decisions to leave rural and remote area practice, the factors that influenced them to remain in practice and those factors nurses considered irrelevant to leaving or staying in rural/remote area nursing. This paper reports those factors the participants believed influenced them to leave rural and remote area nursing in Queensland. While the findings cannot be generalised to the Australian nursing workforce or to nurses not employed by Queensland Health, the study does confirm the findings of previous Australian research and formulates recommendations to assist future nursing workforce planning and policy.