基于GM(1,1)模型中国常见耐碳青霉烯类细菌耐药率预测

王婷; 管廷英; 郑超; 沈立岩; 阴佳; 孙强

doi:10.11847/zgggws1141915

基于GM(1,1)模型中国常见耐碳青霉烯类细菌耐药率预测

Establishment, evaluation and application of GM(1,1) models for predict-ing prevalence of common carbapenem-resistant bacteria in China

摘要

摘要:
目的探讨GM(1,1)模型在中国常见耐碳青霉烯类细菌中的预测价值，为细菌耐药防控措施的制定以及卫生资源的合理分配提供参考依据。
方法收集中国细菌耐药监测网2015年1月 — 2021年12月全国细菌耐药监测报告中耐碳青霉烯类大肠埃希杆菌（CR-E.coli）、耐碳青霉烯类肺炎克雷伯菌（CRKP）、耐碳青霉烯类铜绿假单胞菌（CRPA）和耐碳青霉烯类鲍曼不动杆菌（CRAB）的细菌耐药率数据，以2015年 — 2019年的数据构建灰色预测GM(1,1)模型，采用后验差比值C、小误差概率P评估模型拟合精度以及相对误差和残差评估预测模型拟合效果，采用2020 — 2021年的数据验证模型的预测效果，并应用构建的GM(1,1)模型预测2022 — 2025年CR-E.coli、CRKP、CRPA和CRAB的耐药率。
结果本研究构建的CR-E.coli、CRKP、CRPA和CRAB 4种常见耐碳青霉烯类细菌的GM(1,1)预测模型的后验差比值C均 < 0.50，小概率误差P均接近1.0，相对误差和残差均 < 10%，模型对CR-E.coli、CRKP、CRPA、CRAB 4种细菌耐药率的预测效果均较好，可应用于外推预测；预计到2025年，中国CR-E.coli、CRKP、CRPA和CRAB 4种常见耐碳青霉烯类细菌2022年预测的耐药率分别为1.668%、12.208%、16.663%和52.507%，2023年预测的耐药率分别为1.698%、12.886%、15.930%和51.549%，2024年预测的耐药率分别为1.729%、13.601%、15.229%和50.608%，2025年预测的耐药率分别为1.761%、14.355%、14.559%和49.685%，CR-E.coli和CRKP的耐药率呈现逐步上升趋势，而CRPA和CRAB的耐药率呈稳步下降趋势。
结论 GM(1,1)模型能够较好地预测中国耐碳青霉烯类细菌的耐药率的变化趋势，可为卫生健康部门调整细菌耐药防控策略提供数据支持和参考依据。

Abstract:
Objective To establish, evaluate and preliminarily apply grey model (1,1) GM(1,1) models for predicting the prevalence of common carbapenem-resistant bacteria in China.
Methods We extracted the national data of 2015 – 2021 on detection rate of carbapenem-resistant Escherichia coli (CR-E.coli), carbapenem-resistant Klebsiella pneumoniae (CRKP), carbapenem-resistant Pseudomonas aeruginosa (CRPA), and carbapenem-resistant Acinetobacter baumannii (CRAB) from the China Bacterial Drug Resistance Surveillance Network. Four GM(1,1) models were constructed using the data of 2015 – 2019. Posterior difference ratio C, small error probability P, and relative error and residual error were used to assess the accuracy of the established models in predicting prevalence of common carbapenem-resistant bacteria with the data of 2020 – 2021. The prevalence of CR-E.coli, CRKP, CRPA and CRAB for years from 2022 to 2025 in China were predicted using the four GM(1,1) models established.
Results For the four established GM(1,1) models, the values of posterior difference ratio C were less than 0.50, the small probability error P were close to 1.0, and the relative errors and residual errors were less than 10%, indicating good efficacies in predicting the prevalence of CR-E.coli, CRKP, CRPA and CRAB. Based on the four established GM(1,1) models, the predicted yearly prevalence of CR-E.coli, CRKP, CRPA, and CRAB in China are 1.668%, 12.208%, 16.663%, and 52.507% for 2022; 1.698%, 12.886%, 15.930%, and 1.549% for 2023; 1.729%, 13.601%, 15.229%, and 50.608% for 2024; and 1.761%, 14.355%, 14.559%, and 49.685% for 2025, respectively, with a upward trend for the prevalence of CR-E.coli and CRKP but a downward trend for the prevalence of CRPA and CRAB.
Conclusion In this study, four GM(1,1) models were established for predicting the prevalence of common carbapenem-resistant bacteria and the predictions based on the models could be used in developing strategies on the prevention and control the prevalence of CR-E.coli, CRKP, CRPA and CRAB in China.

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