预测出血热与脏综合征严重程度的预测因素
Lihua Huang1, Jun Wu2, Jiao Luo1
1Department of Infection Disease, The First Affiliated Hospital of Dali University, Dali, Yunnan, People's Republic of China.
International journal of general medicine
|April 14, 2025
概括
这项研究确定了前素 (PCT),白素 (ALB),血小板与白素的比率 (PAR) 和肺溢液作为严重出血发烧与脏综合征 (HFRS) 的关键危险因素. 一种预测性诺莫格拉姆模型证明了早期HFRS严重程度识别的临床实用性.
科学领域:
- 腎臟病學 (nephrology) 是一種醫學專業.
- 传染性疾病 传染性疾病
- 流行病学 流行病学
背景情况:
- 带有综合征的出血热 (HFRS) 构成了重大的公共卫生挑战,特别是在中国西南部等地区.
- 识别HFRS严重性的风险因素对于及时干预和改善患者结果至关重要.
研究的目的:
- 调查与HFRS严重程度相关的风险因素.
- 开发和验证一个用于预测严重HFRS病例的诺莫格拉姆模型.
主要方法:
- 对191名HFRS患者进行了回顾性分析,将他们分为重症 (n=42) 和轻症 (n=149) 组.
- 使用LASSO-Logistic回归分析来确定HFRS严重性的独立风险因素.
- 使用曲线下的面积 (AUC),Hosmer-Lemeshow测试和决策曲线分析 (DCA) 构建和验证了一个名ogram模型.
主要成果:
- 严重的HFRS病例表现为长时间住院,增加对连续脏替代疗法 (CRRT) 和呼吸机的需求,以及更高的30天死亡率.
- 确定了前素 (PCT),白蛋白 (ALB),血小板计数与白蛋白比率 (PAR) 和多流液的存在作为独立的危险因素.
- 诺莫格拉姆模型的AUC值为0.890,并表现出良好的校准和临床效用.
结论:
- PCT,ALB,PAR和肺溢液是HFRS严重程度的重要危险因素.
- 开发的诺莫格拉姆模型是一个可靠的,临床上实用的工具,用于早期识别严重的HFRS患者.
- 这种模型有可能改善HFRS流行地区的患者管理和结果.
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