Latent Class Analysis and Phenotypes Identification of Surgical Site Infection in Elderly Patients After Non-cardiac Surgery---Based on a Prediction Model Established by Two Centers Large Sample
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 42,532
- 试验地点
- 1
- 主要终点
- Elderly Patients Surgical Site Infection Phenotypes Identification
研究概览
简要总结
This study utilizes Latent Class Analysis (LCA) to identify phenotypes of Surgical Site Infection (SSI) in elderly patients following non-cardiac surgery. By analyzing data from two large cohorts, the research establishes a predictive model that uncovers independent risk factors for SSI, including age, hyperlipidemia, and surgical characteristics. The model, with AUCs ranging from 0.753 to 0.791 across cohorts, offers a calibrated prediction of SSI risk. Furthermore, LCA delineates four distinct SSI subphenotypes, highlighting a critical subgroup with a higher infection rate. This subgroup presents a complex interplay of risk factors, indicating the need for tailored preventive strategies. The study's findings contribute to a nuanced understanding of SSI in elderly surgical patients and pave the way for more targeted infection control measures.
详细描述
Backgrounds:
With the widespread use of prophylactic antibiotics during perioperative period and the continuous promotion of minimally invasive non-cardiac surgery type such as laparoscopic and thoracoscopic surgery, the incidence of superficial Surgical Site Infection (SSI) has been significantly reduced. Organ/deep SSI has become the dominant type of SSI. Currently, the classification of SSI is limited to the above location from shallow to deep, the epidemiological and clinical characteristics of SSI after non-cardiac surgery in elderly patients are still inadequately defined.
Objectives:
The investigators aimed to determine main risk factors for SSI after non-cardiac surgery among elderly patients in China and to further reveal the clinical attributes of those elderly patients afflicted with SSI.
Methods:
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 65 Years 至 —（Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Age ≥ 65 years;
- •Patients undergoing surgeries not involving local anesthesia.
排除标准
- •Patients undergoing neurosurgery or cardiac surgery;
- •Patients with preoperative infections (including pneumonia, SSIs, UTIs, and bloodstream infections);
- •Uncertain type of operation
结局指标
主要结局
Elderly Patients Surgical Site Infection Phenotypes Identification
时间窗: January 2012 - August 2018
This study applies Latent Class Analysis to identify SSI phenotypes in elderly post-non-cardiac surgery patients, revealing four distinct subgroups with varying infection risks. The predictive model, validated across two cohorts, underscores the importance of tailored preventive strategies for high-risk subgroups, enhancing SSI management in elderly surgical patients.
次要结局
未报告次要终点
研究者
Weidong Mi
Depatment of Anesthesiology, The First Medical Center
Chinese PLA General Hospital