Sagers Luke, Wei Ziming, McKenna Caroline, Chan Christina, Agan Anna A, Pak Theodore R, Rhee Chanu, Klompas Michael, Kanjilal Sanjat
Department of Biomedical Informatics, Harvard Medical School, Boston, MA.
Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Healthcare Institute, Boston, MA.
medRxiv. 2025 Jun 11:2025.06.11.25329430. doi: 10.1101/2025.06.11.25329430.
Hospitalized patients are at risk for developing hospital acquired infections. Active surveillance for bacterial colonization is effective at preventing infection but is resource-intensive and limited to high-risk units and a subset of high-risk pathogens. Colonization pressure (CP) for common pathogens has been associated with hospital acquired infection and can be calculated in real-time using data in the electronic health record. We aimed to assess the impact of CP on nosocomial acquisition for a range of drug susceptible and drug resistant pathogens, across an entire hospital system.
We conducted a retrospective matched cohort study of all inpatients admitted to a large regional integrated healthcare system between May 2015 and July 2024 who stayed in one room during the 30 day observation period. Cases had target organisms detected in any clinical or surveillance culture taken between 3 and 30 days after admission into their first room. Controls were matched on demographics, length of stay, prior surgery and 14 classes of antibiotic exposure. Our outcome was nosocomial acquisition of 11 common pathogens spread across enteric, skin and environmental niches. We applied conditional logistic regression and XGBoost to model nosocomial acquisition using as covariates the Elixhauser comorbidity index and CP, defined as the time-weighted prevalence of an organism in ward co-occupants over the previous 6 months. CP was calculated for 9 organism sets, including the Enterobacterales, ESBL Enterobacterales, vancomycin susceptible and resistant spp, , methicillin susceptible (MSSA), methicillin resistant (MRSA) and drug susceptible and drug resistant (DR) (PsA).
Our pooled cohort included 14,923 cases matched to 28,480 controls. Hospital acquisition occurred four times more frequently for drug susceptible versus drug resistant organisms. Baseline characteristics were well matched between cases and controls. The strongest positive associations were between CP and nosocomial acquisition of (+32.5%, 95% CI +21.9% to +44.0%), CP and ESBL (+29.4%, 95% CI +11.3% to +50.6%), and CP with drug resistant (+28.6%, 95% CI +14.0% to +45.0%). Among the skin flora, CP was associated with a +12.1% (95% CI +9.9% to +14.4%) increase in the odds of nosocomial acquisition of MSSA, CP was associated with a +6.7% (95% CI +1.3% to +12.5%) increase in the odds of MRSA. Negative associations were observed between organisms inhabiting different niches, including CP and ESBL (-7.9%, 95% CI -15.1% to -0.2%), and CP and vancomycin susceptible (-10.0%, 95% CI -15.6% to -4.0%).
A hospitalized patient's odds of nosocomially acquiring a potential pathogen is associated with its prevalence among that patient's ward co-occupants, regardless of the organism's drug resistance profile. Further research is necessary to understand the role of passive surveillance of CP for preventing infection.
LWS was supported by the NLM (2T15LM007092-31). ZW was supported with institutional funding from the Department of Population Medicine. TRP was supported by AHRQ (K08-HS030118). SK was supported by AHRQ (grant no. K08 HS027841-01A1).
住院患者有发生医院获得性感染的风险。对细菌定植进行主动监测可有效预防感染,但资源消耗大,且仅限于高危科室和一部分高危病原体。常见病原体的定植压力(CP)与医院获得性感染有关,可利用电子健康记录中的数据实时计算。我们旨在评估CP对整个医院系统中一系列药敏和耐药病原体的医院内感染获得情况的影响。
我们对2015年5月至2024年7月期间入住一个大型区域综合医疗系统的所有住院患者进行了一项回顾性匹配队列研究,这些患者在30天观察期内住在同一病房。病例在入住首个病房后3至30天内的任何临床或监测培养中检测到目标微生物。对照组在人口统计学、住院时间、既往手术和14类抗生素暴露方面进行匹配。我们的结局是医院内获得11种常见病原体,这些病原体分布在肠道、皮肤和环境生态位。我们应用条件逻辑回归和XGBoost对医院内感染获得情况进行建模,将Elixhauser合并症指数和CP作为协变量,CP定义为前6个月病房同住者中某种微生物的时间加权患病率。计算了9种微生物组的CP,包括肠杆菌科、产超广谱β-内酰胺酶(ESBL)肠杆菌科、对万古霉素敏感和耐药的葡萄球菌、甲氧西林敏感(MSSA)、甲氧西林耐药(MRSA)以及药敏和耐药(DR)(PsA)。
我们的汇总队列包括14923例病例和28480例对照。药敏微生物的医院内感染发生率是耐药微生物的4倍。病例组和对照组的基线特征匹配良好。最强的正相关关系存在于CP与医院内获得[X菌](+32.5%,95%可信区间+21.9%至+44.0%)、CP与ESBL[X菌](+29.4%,95%可信区间+11.3%至+50.6%)以及CP与耐药[X菌](+28.6%,95%可信区间+14.0%至+45.0%)之间。在皮肤菌群中,CP与医院内获得MSSA的几率增加12.1%(95%可信区间+9.9%至+14.4%)相关,CP与医院内获得MRSA的几率增加6.7%(95%可信区间+1.3%至+12.5%)相关。在栖息于不同生态位的微生物之间观察到负相关关系,包括CP与ESBL[X菌](-7.9%,95%可信区间-15.1%至-0.2%)以及CP与对万古霉素敏感[X菌](-10.0%,95%可信区间-15.6%至-4.0%)。
住院患者医院内获得潜在病原体的几率与其病房同住者中的患病率相关,无论该微生物的耐药情况如何。有必要进一步研究以了解对CP进行被动监测在预防感染中的作用。
LWS由美国国立医学图书馆资助(2T15LM007092 - 31)。ZW由人口医学系的机构资金支持。TRP由美国医疗保健研究与质量局资助(K08 - HS030118)。SK由美国医疗保健研究与质量局资助(资助编号K08 HS027841 - 01A1)。