An augmented reality mobile application for weight estimation in paediatric patients: A prospective single-blinded cross-sectional study.

IF 2.5 Q1 MEDICINE, GENERAL & INTERNAL Annals of the Academy of Medicine, Singapore Pub Date : 2023-12-28 DOI:10.47102/annals-acadmedsg.20238
Sangun Nah, Sungwoo Choi, Nayeon Kang, Kyung Yoon Bae, Ye Rim Kim, Minsol Kim, Ji Eun Moon, Sangsoo Han
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Abstract

Introduction: Determining the exact weight of children is a challenging task during emergency situations. Current guidelines recommend the use of length-based weight-estimating tapes. However, healthcare providers must either always carry the tapes or take time to locate them. Moreover, they may not know how to use them. To address these issues, we developed an augmented reality smartphone application for length-based weight estimation called the Paediatric Augmented Reality Scale (PARS). We evaluated its performance and compared it to that of the Broselow tape (BT) and Paediatric Advanced Weight Prediction in the Emergency Room extra-long and extra-large (PAWPER-XL) tape methods.

Method: A prospective, single-blinded cross-sectional study was conducted with children aged 1 month to 12 years who visited the emergency department of the tertiary university hospital in Bucheon, South Korea between July 2021 and February 2022. This study aimed to evaluate the measurement agreement and performance of 3 methods: BT, PAWPER-XL and PARS.

Results: In all, 1090 participants were enrolled, and 639 (58.6%) were male. The mean age of the participants was 4.1 ± 2.8 years, with a mean height of 102.7 ± 21.7 cm and mean weight of 18.8 ± 9.5 kg. Compared to BT and PAWPER-XL, PARS exhibited lower mean absolute percentage error (9.60%) and root mean square percentage error (3.02%). PARS achieved a higher proportion of weights estimated within 10% of the actual weight (63.21%), outperform-ing BT (57.25%) and PAWPER-XL (62.47%). The intraclass correlation coefficients for the actual and estimated weights of BT, PAWPER-XL and PARS were 0.952, 0.969 and 0.973, respectively (P<0.001).

Conclusion: PARS exhibited a modestly better performance than BT and PAWPER-XL in estimating body weight. PARS-estimated body weights correlated fairly accurately with the actual body weights. PARS holds potential utility in paediatric emergencies.

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用于估算儿科患者体重的增强现实移动应用:前瞻性单盲横断面研究。
简介在紧急情况下,确定儿童的确切体重是一项具有挑战性的任务。现行指南建议使用基于长度的体重估测带。但是,医疗服务提供者要么必须随身携带,要么必须花时间去寻找。此外,他们可能不知道如何使用它们。为了解决这些问题,我们开发了一款基于长度估算体重的增强现实智能手机应用程序,名为儿科增强现实体重计(PARS)。我们对其性能进行了评估,并将其与布罗塞罗(Broselow)尺(BT)和儿科急诊室超长超大尺(PAWPER-XL)高级体重预测方法进行了比较:这项前瞻性、单盲横断面研究的对象是2021年7月至2022年2月期间在韩国富川市三级大学医院急诊科就诊的1个月至12岁儿童。该研究旨在评估三种方法的测量一致性和性能:结果:总共有 1090 名参与者,其中 639 名(58.6%)为男性。参与者的平均年龄为(4.1±2.8)岁,平均身高为(102.7±21.7)厘米,平均体重为(18.8±9.5)公斤。与 BT 和 PAWPER-XL 相比,PARS 的平均绝对百分比误差(9.60%)和均方根百分比误差(3.02%)更低。在实际重量的 10%以内,PARS 估算的重量比例更高(63.21%),超过了 BT(57.25%)和 PAWPER-XL(62.47%)。BT、PAWPER-XL 和 PARS 的实际权重和估算权重的类内相关系数分别为 0.952、0.969 和 0.973(PC 结论:PARS 的实际权重和估算权重的类内相关系数分别为 0.952、0.969 和 0.973):PARS 在估计体重方面的表现略好于 BT 和 PAWPER-XL。PARS 估算的体重与实际体重的相关性相当准确。PARS 在儿科急诊中具有潜在的实用性。
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