Dataset Information

Validation and human factor analysis study of an infant weight estimation device.

ABSTRACT:

Background

Weight is critical for the medical management of infants; however, scales can be unavailable or inaccessible in some practice settings. We recently developed and validated a robust infant weight estimation method based on chest circumference (CC) and head circumference (HC). This study was designed to determine the human factors (HF) experience with, and predictive performance of, an infant weight estimation device that implements this method.

Methods

Prospective, multi-center, observational, masked study of 486 preterm and term infants (0-90 days) assessed by 15 raters. Raters measured the infant using calibrated scales/measures and masked versions of the device. Raters also evaluated critical tasks associated with device use. Mean error (ME) and mean percentage error (MPE) were used to assess predictive performance.

Result

Among 486 infants enrolled (36.8 ± 4.0 weeks gestational age, 31.5 ± 28.6 days postnatal age), predicted weight correlated highly with actual weight (r = 0.97, ME: - 69 ± 257 g, MPE: - 1.3 ± 6.9%). Predicted weight was within 10 and 15% of actual weight in 86 and 99%, of infants. HF errors were low, 0.1-0.8% depending on task. In all cases raters were confident or very confident in their measurements.

Conclusion

The device was statistically equivalent to the method on which it was based and approximated weight with acceptable variance from the true weight. HF data suggest the device is easy to use. This device can be used to estimate weight in infants when calibrated scales are impractical or unavailable.

SUBMITTER: Abdel-Rahman SM

PROVIDER: S-EPMC6977278 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Publications

Validation and human factor analysis study of an infant weight estimation device.

Abdel-Rahman Susan M SM Paul Ian M IM Delmore Paula P Chen Jia-Yuh JY Mills Mary M Greenberg Rachel G RG

BMC pediatrics 20200122 1

<h4>Background</h4>Weight is critical for the medical management of infants; however, scales can be unavailable or inaccessible in some practice settings. We recently developed and validated a robust infant weight estimation method based on chest circumference (CC) and head circumference (HC). This study was designed to determine the human factors (HF) experience with, and predictive performance of, an infant weight estimation device that implements this method.<h4>Methods</h4>Prospective, multi ...[more]

PMID: 31969129

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Project description:BackgroundParagonimiasis, caused by helminths of the genus Paragonimus spp., is a neglected tropical disease. Human suffering from paragonimiasis is often misunderstood and its quantification by the disability weight of the disability-adjusted life years largely varies in different global burden of disease (GBD) estimates. This paper is to systematically review clinical paragonimiasis cases and requantify the disability weight of human paragonimiasis.MethodsA systematic analysis was conducted using articles from the following databases: PubMed, Institute for Scientific Information Web of Science, China National Knowledge Infrastructure, the Chinese scientific journal databases Wanfang Data and CQVIP, Africa Journal Online, and the System for Information on Grey Literature in Europe. Search terms were the combination of "paragonim*" with "clinical" or "infection". Only articles fulfilling the following conditions were recruited for this study: the occurrence of clinical signs and symptoms of paragonimiasis in human beings were reported; diagnosis was confirmed; no comorbidities were reported; the reviewed clinical cases or epidemiological findings were not already included in any other articles. The information and frequencies of paragonimiasis outcomes from included articles using predefined data fields were extracted two times by two separate individuals. Outcome disability weights were selected mainly from the GBD 2004 and GBD 2013 datasets. Frequencies and disability weights of paragonimiasis outcomes were modelled into a decision tree using the additive approach and multiplicative approach, respectively. Monte Carlo simulations were run 5000 times for an uncertainty analysis.ResultsThe disability weight estimates of paragonimiasis were simulated with 5302 clinical cases from 80 general articles. The overall disability weight was estimated at 0.1927 (median 0.1956) with a 95% uncertainty interval (UI) of 0.1632-0.2378 using the additive approach, and 0.1791 (median 0.1816) with a 95% UI of 0.1530-0.2182 using the multiplicative approach. The simulated disability weights of Paragonimus westermani cases were higher than that of P. skrjabini cases. Lung outcomes and headache were the top two contributors to disability weight for both species.ConclusionsThe use of paragonimiasis disability weight needs to be reconsidered with regard to availability of morbidity data and species variation. Calculating the disease burden of paragonimiasis requires further modification and thus has considerable implications for public health prioritization in research, monitoring, and control.

Dataset Information

Validation and human factor analysis study of an infant weight estimation device.

Background

Methods

Result

Conclusion

Publications

Validation and human factor analysis study of an infant weight estimation device.

Similar Datasets

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