Predicting Which Species of Bacteria Will Cause an Infection After Fracture Surgery

Author:

Rane Ajinkya,Ghulam Qasim M.,Hannan Zachary D.,McKegg Phillip C.,Fisher Kalin,Joshi Manjari,O'Hara Nathan N.,O'Toole Robert V.

Abstract

The aim of this study was to develop and validate risk prediction models for deep surgical site infection (SSI) caused by specific bacterial pathogens after fracture fixation. A retrospective case-control study was conducted at a level I trauma center. Fifteen candidate predictors of the bacterial pathogens in deep SSI were evaluated to develop models of bacterial risk. The study included 441 patients with orthopedic trauma with deep SSI after fracture fixation and 576 control patients. The main outcome measurement was deep SSI cultures positive for methicillin-sensitive Staphylococcus aureus (MSSA), methicillin-resistant S aureus (MRSA), gram-negative rods (GNRs), anaerobes, or polymicrobial infection within 1 year of injury. Prognostic models were developed for five bacterial pathogen outcomes. Mean area under the curve ranged from 0.70 (GNRs) to 0.74 (polymicrobial). Strong predictors of MRSA were American Society of Anesthesiologists (ASA) classification of III or greater (odds ratio [OR], 3.4; 95% CI, 1.6–8.0) and time to fixation greater than 7 days (OR, 3.4; 95% CI, 1.9–5.9). Gustilo type III fracture was the strongest predictor of MSSA (OR, 2.5; 95% CI, 1.6–3.9) and GNRs (OR, 3.4; 95% CI, 2.3–5.0). ASA classification of III or greater was the strongest predictor of polymicrobial infection (OR, 5.9; 95% CI, 2.7–15.5) and was associated with increased odds of GNRs (OR, 2.7; 95% CI, 1.5–5.5). Our models predict the risk of MRSA, MSSA, GNR, anaerobe, and polymicrobial infections in patients with fractures. The models might allow for modification of preoperative antibiotic selection based on the particular pathogen posing greatest risk for this patient population. [ Orthopedics . 2024;47(1):e19–e25.]

Publisher

SLACK, Inc.

Subject

Orthopedics and Sports Medicine,Surgery

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3