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预测建模用于确定脊柱手术后的感染风险:优化患者管理

Ruiyu Wang^1,2, Jie Xiao¹, Qi Gao²

¹Department of Anesthesiology, Weifang Medical University, Weifang, Shandong 261041, P.R. China.

Experimental and therapeutic medicine

|May 27, 2024

概括

一个预测模型确定了脊椎病后手术感染的关键风险因素. 这种工具有助于识别风险较高的患者,改善手术结果和患者护理.

科学领域:

整形外科手术整形外科手术
传染病流行病学传染病流行病学
临床预测建模临床预测建模

背景情况:

脊柱外科手术后的感染是影响患者预后的重大并发症.
预测建模可以识别高风险患者以优化管理.
脊椎形手术带来了所有原因的术后感染的显著风险.

研究的目的:

为了调查所有原因感染的发生在接受脊椎病手术的患者中.
开发和验证一种预测模型,用于在脊椎形手术后的医院感染.

主要方法:

对370名脊椎形手术患者的回顾性分析 (2016年1月 - 2022年10月).
感染者和非感染者群体之间的临床人口统计学,手术和实验室变量的比较.
后勤回归用于构建和内部验证感染预测模型.

主要成果:

所有原因的医院感染发生在17.8% (66/370) 的患者中.
确定了关键预测因素:性别,ASA分类,BMI,糖尿病,高血压,手术前白细胞,手术前CRP和手术持续时间.
在内部验证中,预测模型在曲线下的面积 (AUC) 达到0.776.

结论:

结合已识别的变量,动态名图可以预测脊椎形手术后的全因感染风险.
开发的模型提供了实时风险评估和临床决策支持的潜力.
这种预测工具可以增强脊柱病患者的术前和术后管理策略.

关键词:

动态名字图 (dynamic nomogram) 是一个动态名字图.感染的感染感染.预测模型预测模型脊柱体脊椎病是什么?脊柱体脊椎病是什么?脊柱外科手术脊柱外科手术

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