Robin Walker

Changes in the rates of awareness, treatment and control of hypertension in Canada over the past two decades.

Background Analyses of medication databases indicate marked increases in prescribing of antihypertensive drugs in Canada over the past decade. This study was done to examine the trends in the prevalence of hypertension and in control rates in Canada between 1992 and 2009. Methods Three population-based surveys, the 1986–1992 Canadian Heart Health Surveys, the 2006 Ontario Survey on the Prevalence and Control of Hypertension and the 2007–2009 Canadian Health Measures Survey, collected self-reported health information from, and measured blood pressure among, community-dwelling adults. Results The population prevalence of hypertension was stable between 1992 and 2009 at 19.7%–21.6%. Hypertension control improved from 13.2% (95% confidence interval [CI] 10.7%–15.7%) in 1992 to 64.6% (95% CI 60.0%–69.2%) in 2009, reflecting improvements in awareness (from 56.9% [95% CI 53.1%–60.5%] in 1992 to 82.5% [95% CI 78.5%–86.0%] in 2009) and treatment (from 34.6% [95% CI 29.2%–40.0%] in 1992 to 79.0% [95% CI 71.3%–86.7%] in 2009) among people with hypertension. The size of improvements in awareness, treatment and control were similar among people who had or did not have cardiovascular comorbidities Although systolic blood pressures among patients with untreated hypertension were similar between 1992 and 2009 (ranging from 146 [95% CI 145–147] mm Hg to 148 [95% CI 144–151] mm Hg), people who did not have hypertension and patients with hypertension that was being treated showed substantially lower systolic pressures in 2009 than in 1992 (113 [95% CI 112–114] v. 117 [95% CI 117–117] mm Hg and 128 [95% CI 126–130] v. 145 [95% CI 143–147] mm Hg). Interpretation The prevalence of hypertension has remained stable among community-dwelling adults in Canada over the past two decades, but the rates for treatment and control of hypertension have improved markedly during this time.

Diagnosed hypertension in Canada: incidence, prevalence and associated mortality

Background: Hypertension is a leading risk factor for cardiovascular diseases. Our objectives were to examine the prevalence and incidence of diagnosed hypertension in Canada and compare mortality among people with and without diagnosed hypertension. Methods: We obtained data from linked health administrative databases from each province and territory for adults aged 20 years and older. We used a validated case definition to identify people with hypertension diagnosed between 1998/99 and 2007/08. We excluded pregnant women from the analysis. Results: This retrospective population-based study included more than 26 million people. In 2007/08, about 6 million adults (23.0%) were living with diagnosed hypertension and about 418 000 had a new diagnosis. The age-standardized prevalence increased significantly from 12.5% in 1998/99 to 19.6% in 2007/08, and the incidence decreased from 2.7 to 2.4 per 100. Among people aged 60 years and older, the prevalence was higher among women than among men, as was the incidence among people aged 75 years and older. The prevalence and incidence were highest in the Atlantic region. For all age groups, all-cause mortality was higher among adults with diagnosed hypertension than among those without diagnosed hypertension. Interpretation: The overall prevalence of diagnosed hypertension in Canada from 1998 to 2008 was high and increasing, whereas the incidence declined during the same period. These findings highlight the need to continue monitoring the effectiveness of efforts for managing hypertension and to enhance public health programs aimed at preventing hypertension.

Improving the quality of care for infants: a cluster randomized controlled trial.

Background: We developed and tested a new method, called the Evidence-based Practice for Improving Quality method, for continuous quality improvement. Methods: We used cluster randomization to assign 6 neonatal intensive care units (ICUs) to reduce nosocomial infection (infection group) and 6 ICUs to reduce bronchopulmonary dysplasia (pulmonary group). We included all infants born at 32 or fewer weeks gestation. We collected baseline data for 1 year. Practice change interventions were implemented using rapid-change cycles for 2 years. Results: The difference in incidence trends (slopes of trend lines) between the ICUs in the infection and pulmonary groups was − 0.0020 (95% confidence interval [CI] − 0.0007 to 0.0004) for nosocomial infection and − 0.0006 (95% CI − 0.0011 to − 0.0001) for bronchopulmonary dysplasia. Interpretation: The results suggest that the Evidence-based Practice for Improving Quality method reduced bronchopulmonary dysplasia in the neonatal ICU and that it may reduce nosocomial infection.

The Age of Red Blood Cells in Premature Infants (ARIPI) Randomized Controlled Trial: Study Design

Despite recent trends in decreasing transfusion thresholds and the development of technologies designed to avoid allogeneic exposure, allogeneic red blood cell (RBC) transfusions remain an important supportive and life-saving measure for neonatal intensive care patients experiencing illness and anemia. Reluctantly, a number of laboratory and observational studies have indicated that the amount of time RBCs are stored can affect oxygen delivery to tissues. Consequently, older RBCs may result in higher rates of organ dysfunction, nosocomial infection, and lengths of stay. Because of such harmful effects, an evaluation of the association between age of blood and nosocomial infection and organ dysfunction is warranted. The aim of the study was to determine if RBCs stored for 7 days or less (fresh RBCs) compared to current standard transfusion practice decreases major nosocomial infection and organ dysfunction in neonates admitted to the neonatal intensive care unit and requiring at least one RBC transfusion. This study is a double-blind, multicenter, randomized controlled trial design. The trial will be an effectiveness study evaluating the effectiveness of stored vs fresh RBCs in neonates requiring transfusion. Neonatal patients requiring at least one unit of RBCs will be randomized to receive either (1) RBCs stored no longer than 7 days or (2) standard practice. The study was conducted in Canadian university-affiliated level III (tertiary) neonatal intensive care units. The primary outcome for this study will be a composite measure of major neonatal morbidities (necrotizing enterocolitis, retinopathy of prematurity, bronchopulmonary dysplasia, intraventricular hemorrhage, and mortality). Secondary outcomes include individual items of the composite measure and nosocomial infection (bacteremia, septic shock, and pneumonia). The sample size calculations have been estimated based on the formula for 2 independent proportions using an alpha of .05, a (1-beta) of .80, and a 10% noncompliance factor. The baseline rate for our composite measure is estimated to be 65% as indicated by the literature. Assuming a 15% absolute risk reduction with the use of RBCs stored 7 days or less, our estimated total sample size required will be 450 (225 patients per treatment arm). The Age of Red Blood Cells in Premature Infants (ARIPI) trial is registered at the US National Institutes of Health (ClinicalTrials.gov) no. NCT00326924 and current controlled trials ISRCTN65939658.

Clinical decision-support systems for intensive care units using case-based reasoning

The artificial intelligence approach used in this work focusses on case-based reasoning techniques for the estimation of medical outcomes and resource utilization. The systems were designed with a view to help medical and nursing personnel to assess patient status, assist in making a diagnosis, and facilitate the selection of a course of therapy. The initial prototype provided information on the closest-matching patient cases to the newest patient admission in an adult intensive care unit (ICU). The system was subsequently re-designed for use in a neonatal ICU. The results of a short clinical pilot evaluation performed in both adult and neonatal units are reported and have led to substantial improvement of the prototype. Future work will include longer-term clinical trials for both adult and neonatal ICUs, once all the software changes have been made to both prototypes in response to the comments of the users made during the preliminary evaluations. To date, the results are very encouraging and physician interest in the potential clinical usefulness of these two systems remains high, and particularly so in the new testing environment in Ottawa.

Extending ventilation duration estimations approach from adult to neonatal intensive care patients using artificial neural networks

In earlier work, the research group successfully used artificial neural networks (ANNs) to estimate ventilation duration for adult intensive care unit (ICU) patients. The ANNs performed well in terms of correct classification rate (CCR) and average squared error (ASE) classifying the outcome into two classes: whether patients were ventilated for less than/equal to or for more than 8 h (/spl les/ or >). The objective of new work was to apply this adult model to the estimation of ventilation with neonatal ICU (NICU) patient records. The performance obtained with the neonatal patients was comparable to that previously found with the adult database, again as measured in terms of a maximum CCR and a minimum ASE. The effectiveness of using the weight-elimination technique in controlling overfitting was again validated for the neonatal patients as it had been for our adult patients. It was concluded that the approach developed for ICU adult patients was also successfully applied to a different medical environment: neonatal ICU patients.

Towards Ethical Decision Support and Knowledge Management in Neonatal Intensive Care

Recent studies in neonatal medicine, clinical nursing, and cognitive psychology have indicated the need to augment current decision-making practice in neonatal intensive care units with computerized, intelligent decision support systems. Rapid progress in artificial intelligence and knowledge management facilitates the design of collaborative ethical decision-support tools that allow clinicians to provide better support for parents facing inherently difficult choices, such as when to withdraw aggressive treatment. The appropriateness of using computers to support ethical decision-making is critically analyzed through research and literature review. In ethical dilemmas, multiple diverse participants need to communicate and function as a team to select the best treatment plan. In order to do this, physicians require reliable estimations of prognosis, while parents need a highly useable tool to help them assimilate complex medical issues and address their own value system. Our goal is to improve and structuralize the ethical decision-making that has become an inevitable part of modern neonatal care units. The paper contributes to clinical decision support by outlining the needs and basis for ethical decision support and justifying the proposed development efforts.

Healthcare Knowledge Management: Knowledge Management in the Perinatal Care Environment

The chapter presents four key steps in the knowledge management process: access to quality clinical data; knowledge discovery; knowledge translation; and knowledge integration and sharing. Examples are provided for each of these steps for the perinatal care clinical environment and a number of artificial intelligence tools and analyses results are described. The usefulness of this approach for clinical decision support is discussed and the chapter concludes with suggestions on knowledge integration and sharing using Web services.

Risk factors for Apgar score using artificial neural networks.

Artificial Neural Networks (ANNs) have been used in identifying the risk factors for many medical outcomes. In this paper, the risk factors for low Apgar score are introduced. This is the first time, to our knowledge, that the ANNs are used for Apgar score prediction. The medical domain of interest used is the perinatal database provided by the Perinatal Partnership Program of Eastern and Southeastern Ontario (PPPESO). The ability of the feed forward back propagation ANNs to generate strong predictive model with the most influential variables is tested. Finally, minimal sets of variables (risk factors) that are important in predicting Apgar score outcome without degrading the ANN performance are identified

Predicting preterm birth using artificial neural networks

This paper has three contributions: 1) to evaluate how changing the a priori distribution of the training set affects the performance of a back-propagation feed-forward artificial neural network (ANN) in predicting PreTerm Birth (PTB) for obstetrical patients, 2) to assess the effectiveness of the weight elimination cost function in improving the ANNs classification of PTB and in identifying a new minimal dataset, and (3) to determine if PTB can be predicted outside of clinical trial situations using data readily available to the physician during obstetrical care. The ANN was trained and tested on cases with 8 input variables describing the patients obstetrical history; the output variable was PTB before 37 weeks gestation. To observe the impact of training with a higher-than-normal prevalence, an artificial training set with a PTB rate of 23% was created. Networks trained on higher-than-normal prevalence achieved higher sensitivity rates and greater C-index values, at the cost of slightly lower specificity and correct classification rates.