在法国5岁出生队伍中使用机器学习进行RSV严重感染风险分层
Côme Horvat1, Cécile Chauvel2, Jean-Sebastien Casalegno3,4
1From the Hospices Civils de Lyon, Hôpital Femme Mère Enfant, Service de Réanimation Pédiatrique et d'Accueil des Urgences, Bron, France.
The Pediatric infectious disease journal
|May 7, 2024
概括
10月或11月出生的婴儿面临严重呼吸道同胞病毒 (RSV) 感染的高风险. 这一发现有助于优先考虑在RSV季节对脆弱婴儿的预防措施.
科学领域:
- 儿科 儿科 儿科
- 传染性疾病 传染性疾病
- 公共卫生 公共卫生
背景情况:
- 呼吸道同胞性病毒 (RSV) 对婴儿健康和医院资源产生重大影响.
- 新的产前和产周药物干预需要识别患有严重RSV疾病高风险的婴儿.
- 风险分层对于管理1岁以下婴儿的RSV负担至关重要.
研究的目的:
- 在1岁以下的婴儿中分层发展严重RSV感染的风险.
- 为了确定特定的婴儿群体在RSV相关的严重住院住院的风险较高.
- 为预防RSV提供有针对性的公共卫生干预措施和资源分配的信息.
主要方法:
- 对2014-2018年间出生于法国里昂民事医院的婴儿进行了回顾性观察性研究.
- 专注于与RSV (SARI-WI) 相关的严重急性下呼吸道感染住院的婴儿.
- 利用机器学习算法来分析围产期和临床数据以预测风险.
主要成果:
- 在42,069名婴儿中,有555人患上了SARI-WI.
- 11月份出生的婴儿具有>80%的SARI-WI预测风险.
- 10月份出生的婴儿有很高的预测风险,除了满期,阴道分娩的婴儿没有兄弟姐妹. 非常低的风险 (<10%) 观察到婴儿出生在其他月份,到期,通过阴道分娩,没有兄弟姐妹.
结论:
- 在RSV疫情爆发前或在疫情爆发前几周出生的婴儿是关键的风险群体.
- 当资源有限时,可能需要优先考虑RSV预防措施.
- 了解相对于RSV季节的出生时间对于风险评估至关重要.
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