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用于通报法国莱姆病发病率的计算机化决策支持系统。

Computerised decision support system towards informing Lyme borreliosis incidence in France.

作者信息

Suhanda Ilona Eveline, Le Bel Josselin, Bonnet Camille, Launay Titouan, Kim Younjung, Delory Tristan, Métras Raphaëlle

机构信息

Sorbonne Université, INSERM, Institut Pierre Louis d'Épidémiologie et de Santé Publique, F75012, Paris, France.

Antibioclic Steering Committee, Paris, France.

出版信息

Sci Rep. 2025 May 3;15(1):15506. doi: 10.1038/s41598-025-99896-8.

DOI:10.1038/s41598-025-99896-8
PMID:40319191
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12049454/
Abstract

In Europe, the estimation of Lyme borreliosis (LB) incidence is challenged by its heterogeneous reporting. In France, LB incidence is estimated from cases reported voluntarily to the Sentinelles network through general practitioners (GPs). Here, we explored how a computerised decision support system (CDSS), Antibioclic, with higher GPs participation and country-wide coverage, can inform further LB incidence. We derived the incidence of LB Antibioclic indicators (with either erythema migrans or disseminated disease), surveyed Antibioclic usage for suspect cases seen in GP consultations, and compared those estimates with the Sentinelles network estimations. In 2023, the incidence of Antibioclic LB indicators (290 per 100,000 inhabitants; CI95%, 277-303) was almost five times higher than LB incidence from the Sentinelles network, but sharing similar higher-incidence regions. Antibioclic LB indicators under-estimated the incidence of suspect cases seen in higher-incidence regions, while in lower-risk regions, Antibioclic estimation was closer to observed suspect cases. Refine estimates would benefit from improved follow up over time and space while improving case definition.

摘要

在欧洲,莱姆病(LB)发病率的估算因报告的异质性而面临挑战。在法国,LB发病率是根据全科医生(GP)自愿向哨兵网络报告的病例估算得出的。在此,我们探讨了一个具有更高全科医生参与度和全国覆盖范围的计算机化决策支持系统(CDSS)——抗生素点击系统(Antibioclic)如何为进一步了解LB发病率提供信息。我们得出了抗生素点击系统中LB指标(伴有游走性红斑或播散性疾病)的发病率,调查了在全科医生会诊中见到的疑似病例使用抗生素点击系统的情况,并将这些估算值与哨兵网络的估算值进行比较。2023年,抗生素点击系统LB指标的发病率(每10万居民290例;95%置信区间,277 - 303)几乎是哨兵网络LB发病率的五倍,但高发病率地区相似。抗生素点击系统LB指标低估了高发病率地区所见疑似病例的发病率,而在低风险地区,抗生素点击系统的估算值更接近观察到的疑似病例。随着时间推移和空间范围的扩大,通过改进病例定义并加强随访,将有助于完善估算值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe1a/12049454/3799dba5e640/41598_2025_99896_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe1a/12049454/b12347e81f4f/41598_2025_99896_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe1a/12049454/a9f1ba2afda0/41598_2025_99896_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe1a/12049454/a4a322a8fbfb/41598_2025_99896_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe1a/12049454/8db9a27763f4/41598_2025_99896_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe1a/12049454/3799dba5e640/41598_2025_99896_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe1a/12049454/b12347e81f4f/41598_2025_99896_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe1a/12049454/a9f1ba2afda0/41598_2025_99896_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe1a/12049454/a4a322a8fbfb/41598_2025_99896_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe1a/12049454/8db9a27763f4/41598_2025_99896_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe1a/12049454/3799dba5e640/41598_2025_99896_Fig5_HTML.jpg

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本文引用的文献

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