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A systematic review and meta-analysis of the accuracy of weight estimation systems used in paediatric emergency care in developing countries.

ABSTRACT: Introduction:When weight cannot be measured during the management of medical emergencies in children, a convenient, quick and accurate method of weight estimation is required, as many drug doses and other interventions are based on body weight. Many weight estimation methodologies in current use have been shown to be inaccurate, especially in low- and middle-income countries with a high prevalence of underweight children. This meta-analysis evaluated the accuracy of weight estimation systems in children from studies from low- and middle-income countries. Methods:Articles from low- and middle-income countries were screened for inclusion to evaluate and compare the accuracy of existing systems and the newer dual length- and habitus-based methods, using standard meta-analysis techniques. Results:The 2D systems and parental estimates performed best overall. The PAWPER tape, parental estimates, the Wozniak method and the Mercy method were the most accurate systems with percentage of weight estimates within 10% of actual weight (PW10) accuracies of 86.9%, 80.4%, 72.1% and 71.4% respectively. The Broselow tape (PW10 47.1%) achieved a moderate accuracy and age-based estimates a very low accuracy (PW10 11.8-47.5%). Conclusions:The PAWPER tape, the Wozniak method and the Mercy method achieved an acceptable level of accuracy in studies from low- and middle-income countries and should preferentially be used and further advanced for clinical emergency medicine practice. Parental estimates may be considered if the regular caregiver of the child is present and a recent measured weight is known. The Broselow tape and age-based formulas should be abandoned in low- and middle-income country populations as they are potentially dangerously inaccurate.

SUBMITTER: Wells M

PROVIDER: S-EPMC6246873 | biostudies-other | 2017

REPOSITORIES: biostudies-other

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A systematic review and meta-analysis of the accuracy of weight estimation systems used in paediatric emergency care in developing countries.

Wells Mike M Goldstein Lara Nicole LN Bentley Alison A

African journal of emergency medicine : Revue africaine de la medecine d'urgence 20170922 Suppl

<h4>Introduction</h4>When weight cannot be measured during the management of medical emergencies in children, a convenient, quick and accurate method of weight estimation is required, as many drug doses and other interventions are based on body weight. Many weight estimation methodologies in current use have been shown to be inaccurate, especially in low- and middle-income countries with a high prevalence of underweight children. This meta-analysis evaluated the accuracy of weight estimation sys ...[more]

PMID: 30505673

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Project description:The safe and effective administration of fluids and medications during the management of medical emergencies in children depends on an appropriately determined dose, based on body weight. Weight can often not be measured in these circumstances and a convenient, quick and accurate method of weight estimation is required. Most methods in current use are not accurate enough, but the newer length-based, habitus-modified (two-dimensional) systems have shown significantly higher accuracy. This meta-analysis evaluated the accuracy of weight estimation systems in children. Articles were screened for inclusion into two study arms: to determine an appropriate accuracy target for weight estimation systems; and to evaluate the accuracy of existing systems using standard meta-analysis techniques. There was no evidence found to support any specific goal of accuracy. Based on the findings of this study, a proposed minimum accuracy of 70% of estimations within 10% of actual weight (PW10 > 70%), and 95% within 20% of actual weight (PW20 > 95%) should be demonstrated by a weight estimation system before being considered to be accurate. In the meta-analysis, the two-dimensional systems performed best. The Mercy method (PW10 70.9%, PW20 95.3%), the PAWPER tape (PW10 78.0%, PW20 96.6%) and parental estimates (PW10 69.8%, PW20 87.1%) were the most accurate systems investigated, with the Broselow tape (PW10 55.6%, PW20 81.2%) achieving a lesser accuracy. Age-based estimates achieved a very low accuracy. Age- and length-based systems had a substantial difference in over- and underestimation of weight in high-income and low- and middle-income populations. A benchmark for minimum accuracy is recommended for weight estimation studies and a PW10 > 70% with PW20 > 95% is suggested. The Mercy method, the PAWPER tape and parental estimates were the most accurate weight estimation systems followed by length-based and age-based systems. The use of age-based formulas should be abandoned because of their poor accuracy.

Project description:ObjectivesTo update the current evidence base on paediatric postdischarge mortality (PDM) in developing countries. Secondary objectives included an evaluation of risk factors, timing and location of PDM.DesignSystematic literature review without meta-analysis.Data sourcesSearches of Medline and EMBASE were conducted from October 2012 to July 2017.Eligibility criteriaStudies were included if they were conducted in developing countries and examined paediatric PDM. 1238 articles were screened, yielding 11 eligible studies. These were added to 13 studies identified in a previous systematic review including studies prior to October 2012. In total, 24 studies were included for analysis.Data extraction and synthesisTwo independent reviewers extracted and synthesised data using Microsoft Excel.ResultsStudies were conducted mostly within African countries (19 of 24) and looked at all admissions or specific subsets of admissions. The primary subpopulations included malnutrition, respiratory infections, diarrhoeal diseases, malaria and anaemia. The anaemia and malaria subpopulations had the lowest PDM rates (typically 1%-2%), while those with malnutrition and respiratory infections had the highest (typically 3%-20%). Although there was significant heterogeneity between study populations and follow-up periods, studies consistently found rates of PDM to be similar, or to exceed, in-hospital mortality. Furthermore, over two-thirds of deaths after discharge occurred at home. Highly significant risk factors for PDM across all infectious admissions included HIV status, young age, pneumonia, malnutrition, anthropometric variables, hypoxia, anaemia, leaving hospital against medical advice and previous hospitalisations.ConclusionsPostdischarge mortality rates are often as high as in-hospital mortality, yet remain largely unaddressed. Most children who die following discharge do so at home, suggesting that interventions applied prior to discharge are ideal to addressing this neglected cause of mortality. The development, therefore, of evidence-based, risk-guided, interventions must be a focus to achieve the sustainable development goals.

Project description:IntroductionThe effect of patient position and patient cooperation on the accuracy of emergency weight estimation systems has not been evaluated previously. The objective of this study was to evaluate weight estimation accuracy of the Broselow tape, the PAWPER XL tape, the Mercy method, and a custom-designed mobile phone App in a variety of realistic simulated paediatric emergencies.MethodsThis was a prospective study in which 32 emergency medicine volunteers participated in eight simulations of common paediatric emergency conditions, using children models. The participants used each of the four methods to estimate the children's weight. The accuracy of and time taken for the weight estimations were evaluated for each method. A regression analysis determined the effects of patient position and cooperation on weight estimation accuracy. Evaluation of subgroups of best-performers and worst-performers among the participants provided information on the effects of human user-error on weight estimation accuracy.ResultsThe Broselow tape, Mercy method, App and the PAWPER XL tape achieved percentages of weight estimation within 10% of actual weight in 47.7, 57.3, 68.1, and 73.0% of estimations, respectively. Patient position and cooperation strongly impacted the accuracy of the Broselow tape, had a minimal effect on the Mercy method and the App, and had no effect on the PAWPER XL tape. The best performing participants achieved very high accuracy with all methods except the Broselow tape.DiscussionThe Mercy method, the App, and the PAWPER XL tape achieved exceptionally high accuracy even in uncooperative and sub-optimally positioned children when used by the best-performing participants. Human error, from inexperience and inadequate training, had the most significant impact on accuracy. The Mercy method was the most subject to human error, and the PAWPER XL tape, the least. Adequate training in using weight estimation systems is essential for paediatric patient safety.

Project description:Software development effort estimation (SDEE) is recognized as vital activity for effective project management since under or over estimating can lead to unsuccessful utilization of project resources. Machine learning (ML) algorithms are largely contributing in SDEE domain, particularly ensemble effort estimation (EEE) works well in rectifying bias and subjectivity to solo ML learners. Performance of EEE significantly depends on hyperparameter composition as well as weight assignment mechanism of solo learners. However, in EEE domain, impact of optimization in terms of hyperparameter tunning as well as weight assignment is explored by few researchers. This study aims in improving SDEE performance by incorporating metaheuristic hyperparameter and weight optimization in EEE, which enables accuracy and diversity to the ensemble model. The study proposed Metaheuristic-optimized Multi-dimensional bagging scheme and Weighted Ensemble (MoMdbWE) approach. This is achieved by proposed search space division and hyperparameter optimization method named as Multi-dimensional bagging (Mdb). Metaheuristic algorithm considered for this work is Firefly algorithm (FFA), to get best hyperparameters of three base ML algorithms (Random Forest, Support vector machine and Deep Neural network) since FFA has shown promising results of fitness in terms of MAE. Further enhancement in performance is achieved by incorporating FFA-based weight optimization to construct Metaheuristic-optimized weighted ensemble (MoWE) of individual multi-dimensional bagging schemes. Proposed scheme is implemented on eight frequently utilized effort estimation datasets and results are evaluated by 5 error metrices (MAE, RMSE, MMRE, MdMRE, Pred), standard accuracy and effect size along with Wilcox statistical test. Findings confirmed that the use of FFA optimization for hyperparameter (with search space sub-division) and for ensemble weights, has significantly enhanced performance in comparison with individual base algorithms as well as other homogeneous and heterogenous EEE techniques.

Dataset Information

A systematic review and meta-analysis of the accuracy of weight estimation systems used in paediatric emergency care in developing countries.

Publications

A systematic review and meta-analysis of the accuracy of weight estimation systems used in paediatric emergency care in developing countries.

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