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Forecasting and predicting intussusception in children younger than 48 months in Suzhou using a seasonal autoregressive integrated moving average model
  1. Wan-liang Guo1,
  2. Jia Geng2,
  3. Yang Zhan1,
  4. Ya-lan Tan1,
  5. Zhang-chun Hu1,
  6. Peng Pan1,
  7. Mao Sheng1,
  8. Jian Wang3,
  9. Shun-gen Huang3
  1. 1 Department of Radiology, Children’s Hospital of Soochow University, Suzhou, China
  2. 2 Clinical Laboratory, The 3rd hospital of Yulin, Yulin, China
  3. 3 Department of Pediatric Surgery, Children’s Hospital of Soochow University, Suzhou, China
  1. Correspondence to Shun-gen Huang; drhuang01{at}163.com

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.

  • intussusception
  • epidemiology
  • forecasting
  • time series

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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Footnotes

  • Patient consent for publication Not required.

  • W-G and JG contributed equally.

  • MS and S-H contributed equally.

  • Contributors SH and MS designed the study. WG, JG, YT, ZH, PP and JW, collected data. WG, JW, YT, JG and YZ analysed data. WG, SH and MS wrote the manuscript, and all authors read and approved the final version of the manuscript.

  • Funding This work was supported by Jiangsu Province Health and Family Planning Projects (H201519), Fundamental and Application Research in Health Care of Suzhou (SYS201762).

  • Competing interests None declared.

  • Ethics approval This study was approved by the Institutional Review Board of the Children’s Hospital of Soochow University.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement No additional data are available.

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