Michels Ricarda, Papan Cihan, Boutin Sébastien, Alhussein Farah, Becker Sören L, Nurjadi Dennis, Last Katharina
Center for Infectious Diseases, Institute of Medical Microbiology and Hygiene, Saarland University, Homburg, Germany.
Institute for Hygiene and Public Health, University Hospital Bonn, Venusberg-Campus 1, Bonn, Germany.
Infection. 2025 Feb;53(1):145-153. doi: 10.1007/s15010-024-02334-6. Epub 2024 Jul 4.
To characterize the clinical relevance of S. saccharolyticus and to identify criteria to distinguish between infection and contamination.
We retrospectively investigated clinical features of patients with S. saccharolyticus detection between June 2009 and July 2021. Based on six criteria, infection was considered likely for patients with a score from 3 to 6 points, infection was considered unlikely for patients with a score from 0 to 2 points. We performed group comparison and logistic regression to identify factors than are associated with likely infection. In addition, whole genome sequencing (WGS) of 22 isolates was performed.
Of 93 patients in total, 44 were assigned to the group "infection likely" and 49 to the group "infection unlikely". Multiple regression analysis revealed "maximum body temperature during hospital stay" to have the strongest predictive effect on likely infection (adjusted odds ratio 4.40, 95% confidence interval 2.07-9.23). WGS revealed two different clades. Compared to isolates from clade A, isolates from clade B were more frequently associated with implanted medical devices (3/10 vs. 9/12, p = 0.046) and a shorter time to positivity (TTP) (4.5 vs. 3, p = 0.016). Both clades did neither differ significantly in terms of causing a likely infection (clade A 7/10 vs. clade B 5/12, p = 0.23) nor in median length of hospital stay (28 vs. 15.5 days, p = 0.083) and length of stay at the ICU (21 vs. 3.5 days, p = 0.14).
These findings indicate that S. saccharolyticus can cause clinically relevant infections. Differentiation between infection and contamination remains challenging.
描述解糖梭状芽孢杆菌的临床相关性,并确定区分感染和污染的标准。
我们回顾性调查了2009年6月至2021年7月期间检测到解糖梭状芽孢杆菌的患者的临床特征。基于六个标准,得分为3至6分的患者被认为可能感染,得分为0至2分的患者被认为不太可能感染。我们进行了组间比较和逻辑回归分析,以确定与可能感染相关的因素。此外,对22株分离株进行了全基因组测序(WGS)。
在总共93例患者中,44例被归为“可能感染”组,49例被归为“不太可能感染”组。多元回归分析显示,“住院期间最高体温”对可能感染的预测作用最强(调整后的优势比为4.40,95%置信区间为2.07-9.23)。WGS显示出两个不同的进化枝。与进化枝A的分离株相比,进化枝B的分离株与植入式医疗器械的关联更频繁(3/10对9/12,p = 0.)。