Supporting clinical decision making in the emergency department for paediatric patients using machine learning: A scoping review protocol.

INTRODUCTION: Machine learning as a clinical decision support system tool has the potential to assist clinicians who must make complex and accurate medical decisions in fast paced environments such as the emergency department. This paper presents a protocol for a scoping review, with the objective of summarising the existing research on machine learning clinical decision support system tools in the emergency department, focusing on models that can be used for paediatric patients, where a knowledge gap exists. MATERIALS AND METHODS: The methodology used will follow the scoping study framework of Arksey and O'Malley, along with other guidelines. Machine learning clinical decision support system tools for any outcome and population (paediatric/adult/mixed) for use in the emergency department will be included. Articles such as grey literature, letters, pre-prints, editorials, scoping/literature/narrative reviews, non-English full text papers, protocols, surveys, abstract or full text not available and models based on synthesised data will be excluded. Articles from the last five years will be included. Four databases will be searched: Medline (EBSCO), CINAHL (EBSCO), EMBASE and Cochrane Central. Independent reviewers will perform the screening in two sequential stages (stage 1: clinician expertise and stage 2: computer science expertise), disagreements will be resolved by discussion. Data relevant to the research question will be collected. Quantitative analysis will be performed to generate the results. DISCUSSION: The study results will summarise the existing research on machine learning clinical decision support tools in the emergency department, focusing on models that can be used for paediatric patients. This holds the promise to identify opportunities to both incorporate models in clinical practice and to develop future models by utilising reviewers from diverse backgrounds and relevant expertise.

Comparing the outcomes of tubularized incised plate urethroplasty and dorsal inlay graft urethroplasty in children with hypospadias: a systematic review and meta-analysis.

BACKGROUND: Excellent outcomes have been reported following the widely accepted tubularized incised plate urethroplasty (TIPU) and its relatively recent modification, the dorsal inlay graft urethroplasty (DIGU). However, there is a lack of consensus on which technique offers more favorable postoperative outcomes. AIMS: To systematically compare the reported outcomes of the TIPU and DIGU techniques in children undergoing primary hypospadias repair. DESIGN: A systematic review and meta-analysis of randomized and observational studies. METHODS: An electronic database search was conducted up to May 2018. Sources included Medline, Embase, Cochrane library, CINAHL, Web of Science, and Google Scholar as well as trial registries and grey literature sources. Studies were selected if they compared the postoperative complications of TIPU and DIGU in children. Secondary outcomes included standardized cosmetic scores and urinary flow studies. A meta-analysis of reported complications was performed using a random-effects model. RESULTS: Two randomized, two prospective, and two retrospective studies met the inclusion criteria. TIPU and DIGU were performed in 350 and 267 patients, respectively. Pooled analysis did not demonstrate a significant difference regarding postoperative urethrocutaneous fistula, meatal/urethral stenosis, wound dehiscence, or total complications. Subgroup analysis according to hypospadias severity did not alter initial findings. Statistical analysis of secondary outcomes was not feasible due to insufficient data. Most studies were of low methodological quality with a high risk of bias. CONCLUSIONS: There is no strong evidence to suggest that either technique offers more favorable outcomes. Until more robust randomized trials exist, decisions regarding the appropriate repair should be based on the surgeon's experience and outcomes.