Dataset Information

Forecasting and predicting intussusception in children younger than 48 months in Suzhou using a seasonal autoregressive integrated moving average model.

ABSTRACT:

Objective

The aims of this study were to highlight some epidemiological aspects of intussusception cases younger than 48 months and to develop a forecasting model for the occurrence of intussusception in children younger than 48 months in Suzhou.

Design

A retrospective study of intussusception cases that occurred between January 2007 and December 2017.

Setting

Retrospective chart reviews of intussusception paediatric patients in a large Children's hospital in South-East China were performed.

Participants

The hospital records of 13?887 intussusception cases in patients younger than 48 months were included in this study.

Interventions

The modelling process was conducted using the appropriate module in SPSS V.23.0.

Methods

The Box-Jenkins approach was used to fit a seasonal autoregressive integrated moving average (ARIMA) model to the monthly recorded intussusception cases in patients younger than 48 months in Suzhou from 2007 to 2016.

Results

Epidemiological analysis revealed that intussusception younger than 48 months was reported continuously throughout the year, with peaks in the late spring and early summer months. The most affected age group was younger than 36 months. The time-series analysis showed that an ARIMA (1,0,1 1,1,1)₁₂ model offered the best fit for surveillance data of intussusception younger than 48 months. This model was used to predict intussusception younger than 48 months for the year 2017, and the fitted data showed considerable agreement with the actual data.

Conclusion

ARIMA models are useful for monitoring intussusception in patients younger than 48 months and provide an estimate of the variability to be expected in future cases in Suzhou. The models are helpful for predicting intussusception cases in Suzhou and could be useful for developing early warning systems. They may also play a key role in early detection, timely treatment and prevention of serious complications in cases of intussusception.

SUBMITTER: Guo WL

PROVIDER: S-EPMC6340449 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Forecasting and predicting intussusception in children younger than 48 months in Suzhou using a seasonal autoregressive integrated moving average model.

Guo Wan-Liang WL Geng Jia J Zhan Yang Y Tan Ya-Lan YL Hu Zhang-Chun ZC Pan Peng P Sheng Mao M Wang Jian J Huang Shun-Gen SG

BMJ open 20190117 1

<h4>Objective</h4>The aims of this study were to highlight some epidemiological aspects of intussusception cases younger than 48 months and to develop a forecasting model for the occurrence of intussusception in children younger than 48 months in Suzhou.<h4>Design</h4>A retrospective study of intussusception cases that occurred between January 2007 and December 2017.<h4>Setting</h4>Retrospective chart reviews of intussusception paediatric patients in a large Children's hospital in South-East Chi ...[more]

PMID: 30782741

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Dataset Information

Forecasting and predicting intussusception in children younger than 48 months in Suzhou using a seasonal autoregressive integrated moving average model.

Objective

Design

Setting

Participants

Interventions

Methods

Results

Conclusion

Publications

Forecasting and predicting intussusception in children younger than 48 months in Suzhou using a seasonal autoregressive integrated moving average model.

Similar Datasets

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