Daily chlorhexidine bathing to reduce bacteraemia in critically ill children: a multicentre, cluster-randomised, crossover trial.

BACKGROUND: Bacteraemia is an important cause of morbidity and mortality in critically ill children. Our objective was to assess whether daily bathing in chlorhexidine gluconate (CHG) compared with standard bathing practices would reduce bacteraemia in critically ill children. METHODS: In an unmasked, cluster-randomised, two-period crossover trial, ten paediatric intensive-care units at five hospitals in the USA were randomly assigned a daily bathing routine for admitted patients older than 2 months, either standard bathing practices or using a cloth impregnated with 2% CHG, for a 6-month period. Units switched to the alternative bathing method for a second 6-month period. 6482 admissions were screened for eligibility. The primary outcome was an episode of bacteraemia. We did intention-to-treat (ITT) and per-protocol (PP) analyses. This study is registered with ClinicalTrials.gov (identifier NCT00549393). FINDINGS: 1521 admitted patients were excluded because their length of stay was less than 2 days, and 14 refused to participate. 4947 admissions were eligible for analysis. In the ITT population, a non-significant reduction in incidence of bacteraemia was noted with CHG bathing (3·52 per 1000 days, 95% CI 2·64-4·61) compared with standard practices (4·93 per 1000 days, 3·91-6·15; adjusted incidence rate ratio [aIRR] 0·71, 95% CI 0·42-1·20). In the PP population, incidence of bacteraemia was lower in patients receiving CHG bathing (3·28 per 1000 days, 2·27-4·58) compared with standard practices (4·93 per 1000 days, 3·91-6·15; aIRR 0·64, 0·42-0·98). No serious study-related adverse events were recorded, and the incidence of CHG-associated skin reactions was 1·2 per 1000 days (95% CI 0·60-2·02). INTERPRETATION: Critically ill children receiving daily CHG bathing had a lower incidence of bacteraemia compared with those receiving a standard bathing routine. Furthermore, the treatment was well tolerated. FUNDING: Sage Products, US National Institutes of Health.

Understanding the relationship between road users and the roadway infrastructure in Ghana.

Ghana exemplifies the contribution of road crashes to mortality and morbidity in Africa, partly due to a growing population and increasing car ownership, where fatalities have increased by 12 to 15 % annually since 2008 (National Road Safety Authority (NRSA), 2017). The study described in this paper focused on understanding driver behavior at unsignalized junctions in the Ashanti Region of Ghana. Understanding driver behavior at unsignalized junctions is particularly important since failure to stop or yield can seriously affect vulnerable road users. The study's objectives were to develop relationships between driver behavior and junction characteristics. Understanding the characteristics that lead to determining what factors influence a driver's behavioral response at rural junctions provides information for policy makers to determine the best strategies to address these behaviors. The study evaluated stopping behavior at rural junctions. Driver behavior was extracted from video views of ten junctions in the Ashanti Region of Ghana. A total of 3,420 vehicles were observed across all ten junctions during data collection before any analysis was conducted. The type of stop was selected as a surrogate measure of safety. Logistic regression was used to model stopping behavior at the selected junctions. The analysis showed drivers were more likely to stop when going straight (versus a left turn) and left turning vehicles were more likely to stop than right turning vehicles. Additionally, single unit trucks and tro-tros were more likely to stop than other vehicle types. Drivers were also much more likely to stop when channelization, intersection lighting, or speed humps were present. Drivers at junctions with 4-approaches were also more likely to stop than those with 3 approaches. The results from this research contribute valuable information about what factors contribute to positive safety behaviors at rural junctions. This provides guidance for safety professionals to select solutions and can be a valuable tool to predict the economical effectiveness of solutions to addressing junction safety in low- and middle-income countries (LMIC) such as Ghana. The results can also provide insight and recommendations to Ghanaian road safety agencies and launch sustainable efforts to raise community awareness toward decreasing road crash fatalities in Ghana.

Pedestrians safety perceptions on midblock crosswalk utilization along urban corridors of developing countries.

In Ghana, road crossing accidents account for more than 70% of all pedestrian fatalities as the task of road crossing is challenging, even in so-called 'protected' midblock crosswalks. This paper assesses pedestrians perception of midblock crosswalks safety along major arterials in the Sunyani municipality. Following the identification and ranking of twenty-four (24) pedestrian crash-prone locations using the MAAP IV software, identified pedestrian crosswalks were inventorized, their degree of utilization were investigated and some active pedestrians were interviewed. There is a strong correlation between pedestrian perceptions and use behavior behaviour as over 90% of pedestrians stated they did not use the midblock crosswalks, and about 77% stated the location of the facility influenced their crossing behaviour. In the strict use of designated midblock crosswalks, only 8.7% of active pedestrians complied. Findings suggest that the incorporation of pedestrian views into the design and construction of pedestrian facilities could significantly improve the use of these facilities and consequently the occurrence of crashes. These findings have implication particularly for transport managers in developing countries with limited budgets for infrastructure provision.

Modifying the SERVPERF to assess paratransit minibus taxis trotro in Ghana and the relevance of mobility-as-a-service features to the service.

In Ghana, minibus taxis (trotros) are an important mode of transport that commute about 60% of the traveling public. In spite of their popularity, minibuses are generally inefficient, disorganized and have low service quality. In an attempt to assess service quality of the service, a modified SERVPERF tool was developed. Differences in perceptions of service quality between male and female respondents were also assessed, and the attractiveness of certain technological features as possible remedies to service quality issues were determined. Using an online Google forms version of the modified SERVPERF, responses from nearly one thousand commuters were collected. The link to the questionnaire was dispersed via social media (Whatsapp and Telegram) since the data was collected during the outbreak of COVID-19 in Ghana. Following a factor reduction, the most important service quality factors determined to affect trotro users were (i) Reliability of the service, (ii) Variability in cost and (iii) Responsiveness. Respondents also identified technologies that could help them (a) book, (b) report driver misbehavior, (c) make safe e-payments and (d) track the location of trotros, as most likely to improve their trotro service quality. The findings suggest that some mobility as a service features could have possible benefit for the trotro. The study is however limited in its ability to determine the exact impact of these technologies since it uses a stated preference approach. Future research could explore the willingness of other stakeholder groups such as operators in adopting these technologies since their participation would be key to the success of any such scheme.

Lifecycle management in pharmaceutical analysis: How to establish an efficient and relevant continued performance monitoring program.

It is the objective of a systematic and holistic Quality-by-Design approach to demonstrate and ensure that an analytical procedure is fit for its intended purpose over its entire lifecycle. Such a lifecycle approach, as proposed for a new USP General Information Chapter includes the three stages Procedure Design and Development, Procedure Performance Qualification, and Continued Procedure Performance Verification, in alignment to manufacturing process validation. A decisive component of this approach is the Analytical Target Profile, which defines the performance requirements for the measurement of a Quality Attribute as the target for selection, development and optimization of the respective analytical procedures. Although the most benefit can be gained by a comprehensive Quality-by-Design approach establishing the Analytical Target Profile in the very beginning of a drug development project, it may also be established retrospectively for analytical procedures long in routine use, in order to facilitate future lifecycle activities such as continual improvements, transfers, monitoring and periodic performance evaluations. In contrast to the first two stages of the analytical lifecycle with usually limited amount of data, the Continued Procedure Performance Verification stage offers the possibility to utilize a much more reliable data base to collect, analyze, and evaluate data that relate to analytical procedure performance. This monitoring program should be aligned as far as possible with other quality systems already in place and may include performance indicators such as Conformity (i.e. out-of specification test results with analytical root-cause), Validity (i.e. failure to meet method acceptance criteria, e.g. system suitability tests), and (numerical) analytical performance parameters (e.g. ranges for replicate determinations, control sample results, etc). In addition to the monitoring of analytical control parameters by means of control charts, average (pooled) performance parameters can be calculated. Over time, a large number of data can be included and thus the reliability of these estimates is increased tremendously. Such reliable estimates for the true performance parameters, e.g. repeatability or intermediate precision are essential to identify systematic effects (also called special cause variation) with good confidence. The intent of the analytical procedure performance evaluation is to identify substandard performance, identify root cause through investigations, and determine when additional activities are required to improve it. Examples are provided for the monitoring and evaluation of performance parameters for the compendial drug substance Furosemide and for biopharmaceutical applications.

Evaluating manufacturing process profile comparability with multivariate equivalence testing: Case study of cell-culture small scale model transfer.

This article studies the Generalized Mahalanobis Distance (GMD) approach proposed by Hoffelder which measures the dissimilarity of two multivariate Gaussian distributions with arbitrary covariance matrices and unequal sample sizes. This investigation demonstrated that, with appropriate adjustment, the GMD approach can achieve the targeted nominal Type I error and provide sufficient power for testing equivalence between two profile populations. The adjusted GMD approach was applied to examine the equivalence of harvest profiles between a 12L small scale model and 2000L manufacturing scale in a transfer study performed at Sanofi Specialty Care Framingham Biologics. The harvest profiles were evaluated based on three critical parameters (Productivity, Lactate Production, and Total Cell Density) and deemed practically equivalent using a pre-defined equivalence margin per the adjusted GMD approach. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 34:187-195, 2018.

Empirical power and sample size calculations for cluster-randomized and cluster-randomized crossover studies.

In recent years, the number of studies using a cluster-randomized design has grown dramatically. In addition, the cluster-randomized crossover design has been touted as a methodological advance that can increase efficiency of cluster-randomized studies in certain situations. While the cluster-randomized crossover trial has become a popular tool, standards of design, analysis, reporting and implementation have not been established for this emergent design. We address one particular aspect of cluster-randomized and cluster-randomized crossover trial design: estimating statistical power. We present a general framework for estimating power via simulation in cluster-randomized studies with or without one or more crossover periods. We have implemented this framework in the clusterPower software package for R, freely available online from the Comprehensive R Archive Network. Our simulation framework is easy to implement and users may customize the methods used for data analysis. We give four examples of using the software in practice. The clusterPower package could play an important role in the design of future cluster-randomized and cluster-randomized crossover studies. This work is the first to establish a universal method for calculating power for both cluster-randomized and cluster-randomized clinical trials. More research is needed to develop standardized and recommended methodology for cluster-randomized crossover studies.