Prediction of congenital heart disease for newborns: comparative analysis of Holt-Winters exponential smoothing and autoregressive integrated moving average models

Weize Xu; Zehua Shao; Hongliang Lou; Jianchuan Qi; Jihua Zhu; Die Li; Qiang Shu

doi:10.1186/s12874-022-01719-1

Prediction of congenital heart disease for newborns: comparative analysis of Holt-Winters exponential smoothing and autoregressive integrated moving average models

BMC Med Res Methodol. 2022 Oct 1;22(1):257. doi: 10.1186/s12874-022-01719-1.

Authors

Weize Xu^#¹, Zehua Shao^#², Hongliang Lou^#³, Jianchuan Qi¹, Jihua Zhu⁴, Die Li¹, Qiang Shu⁵

Affiliations

¹ Department of Cardiac Surgery, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, No. 3333 Binsheng Road, Binjiang District, Hangzhou, 310000, Zhejiang, China.
² Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, 450003, China.
³ Jinhua Maternal and Child Health Care Hospital, Jinhua, 321000, China.
⁴ Department of Nursing, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, 310000, China.
⁵ Department of Cardiac Surgery, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, No. 3333 Binsheng Road, Binjiang District, Hangzhou, 310000, Zhejiang, China. shuqiang@zju.edu.cn.

^# Contributed equally.

Abstract

Objective: To describe the temporal trend of the number of new congenital heart disease (CHD) cases among newborns in Jinhua from 2019 to 2020 and explored an appropriate model to fit and forecast the tendency of CHD.

Methods: Data on CHD from 2019 to 2020 was collected from a health information system. We counted the number of newborns with CHD weekly and separately used the additive Holt-Winters ES method and ARIMA model to fit and predict the number of CHD for newborns in Jinhua. By comparing the mean square error, rooted mean square error and mean absolute percentage error of each approach, we evaluated the effects of different approaches for predicting the number of CHD in newborns.

Results: A total of 1135 newborns, including 601 baby girls and 534 baby boys, were admitted for CHD from HIS in Jinhua during the 2-year study period. The prevalence of CHD among newborns in Jinhua in 2019 was 0.96%. Atrial septal defect was diagnosed the most frequently among all newborns with CHD. The number of CHD cases among newborns remained stable in 2019 and 2020. There were fewer cases in spring and summer, while cases peaked in November and December. The ARIMA(2,1,1) model relatively offered advantages over the additive Holt-winters ES method in predicting the number of newborns with CHD, while the accuracy of ARIMA(2,1,1) was not very ideal.

Conclusions: The diagnosis of CHD is related to many risk factors, therefore, when using temporal models to fit and predict the data, we must consider such factors' influence and try to incorporate them into the models.

Keywords: Autoregressive integrated moving average model; Congenital heart disease; Holt-Winters exponential smoothing; Newborns; Time series.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Forecasting
Heart Defects, Congenital* / diagnosis
Heart Defects, Congenital* / epidemiology
Humans
Infant, Newborn
Models, Statistical
Research Design*
Risk Factors
Seasons