导出和验证长期COVID的风险预测模型:苏格兰的一项基于人口的回顾性队列研究
Karen Jeffrey1, Vicky Hammersley1, Rishma Maini2
1Usher Institute, University of Edinburgh, Edinburgh EH16 4UX, UK.
Journal of the Royal Society of Medicine
|November 18, 2024
概括
高龄,高BMI和严重的COVID-19增加了长期COVID的风险. 接种疫苗和新的变种降低了风险. 这项研究确定了长期COVID的关键预测因素.
科学领域:
- 流行病学 流行病学
- 传染性疾病 传染性疾病
- 公共卫生 公共卫生
背景情况:
- 长期COVID,是COVID-19复杂的后急性后续,对全球健康构成重大挑战.
- 识别患有长期COVID的高风险个体对于有针对性的预防和管理策略至关重要.
研究的目的:
- 使用电子健康记录开发和验证长期COVID风险的预测模型.
- 确定与长期COVID发展相关的关键风险因素和保护因素.
主要方法:
- 在苏格兰进行了一项以人口为基础的回顾性队列研究.
- 分析了2020年3月至2022年10月期间出现COVID-19阳性测试的成年人 (≥18岁) 的电子健康记录.
- 统计模型用于计算长期COVID的预测指标的调整几率比率 (aOR) 和95%置信区间 (CI).
主要成果:
- 共有68,486名患者 (5.6%) 患有长期COVID.
- 长期COVID风险增加的预测因素包括年龄较大,身体质量指数 (BMI) 较高,严重的COVID-19感染,女性性别,贫困和先前存在的健康状况.
- 长期COVID的风险降低与Delta或Omicron变种占主导地位和COVID-19疫苗接种期间的感染有关.
结论:
- 高龄,高BMI,严重的COVID-19,女性性别,贫困和并发症是长期COVID的重要预测因素.
- 接种COVID-19疫苗和感染较新的变种 (三角形,欧米克朗) 与患长期COVID的风险降低有关.
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