Impact of active surveillance and infection control measures on carbapenem-resistant Gram-negative bacterial colonization and infections in intensive care

Κarampatakis, Theodoros; Tsergouli, Katerina; Iosifidis, Εlias; Antachopoulos, Charalampos; Karapanagiotou, A.; Karyoti, Aggeliki; Gritsi-Gerogianni, N.; Tsakris, Athanassios; Roilides, Emmanuel

doi:10.1016/j.jhin.2018.05.010

Cited by 50 publications

(32 citation statements)

References 33 publications

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“…Before the current pandemic, the emergence of antimicrobial resistance among bacteria and fungi has been one of the worldwide leading threats [5][6][7][8][9]. To minimize the impact of antimicrobial resistance, adequate antimicrobial stewardship programs have been recommended, as well as implementation of infection control measures, based on active screening for colonization with resistant pathogens and strict contact isolation precautions for carriers to avoid horizontal spread among patients [10]. Optimizing antimicrobial prescription might be challenging among COVID-19 patients, especially critical ones, since clinical severity, imaging features and laboratory parameters make it difficult to differentiate bacterial co-infection from the mere effects of SARS-CoV-2.…”

Section: Introductionmentioning

confidence: 99%

Spread of Carbapenem-Resistant Gram-Negatives and Candida auris during the COVID-19 Pandemic in Critically Ill Patients: One Step Back in Antimicrobial Stewardship?

et al. 2021

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The possible negative impact of severe adult respiratory distress caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection (COVID-19) on antimicrobial stewardship and infection control has been postulated, but few real-life data are available. The aim of this study was to report our experience with colonization/infection of carbapenem-resistant Pseudomonas aeruginosa (CRPA), carbapenem-resistant Klebsiella pneumoniae (CR-Kp) and Candida auris among critically ill COVID-19 patients admitted to the intensive care unit (ICU). All COVID-19 patients admitted to the ICUs at San Martino Policlinico Hospital–IRCCS in Genoa, Italy, were screened from 28 February to 31 May 2020. One-hundred and eighteen patients admitted to COVID-19 ICUs were included in the study. Among them, 12 (10.2%) became colonized/infected with CRPA, 6 (5.1%) with C. auris and 2 (1.6%) with CR-Kp. All patients with CRPA received prior treatment with meropenem, and in 11 (91.7%) infection was not preceded by colonization. Four patients (66.7%) developed C. auris candidemia. A significant spread of resistant pathogens was observed among critically ill COVID-19 patients. Dedicated strategies are warranted to prevent horizontal spread and maintain effective antimicrobial stewardship programs in the setting of COVID-19 care.

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Section: Introductionmentioning

confidence: 99%

Spread of Carbapenem-Resistant Gram-Negatives and Candida auris during the COVID-19 Pandemic in Critically Ill Patients: One Step Back in Antimicrobial Stewardship?

et al. 2021

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“…CRKP has become a global health problem and is listed in the critical priority category of the 2019 WHO global priority pathogens list for the research and development of new antibiotics. The incidence of ICU-acquired CRKP colonization/infection varies between 3.7 to 8.1 cases per 1000 patient-days, according to different studies worldwide ( 25 , 26 ). Data from the China Antimicrobial Surveillance Network (CHINET) showed that the prevalence of CRKP has been markedly increasing in China, from 2.6% in 2005 to 28.6% in 2018.…”

Section: Discussionmentioning

confidence: 99%

Validation and Extrapolation of a Multimodal Infection Prevention and Control Intervention on Carbapenem-Resistant Klebsiella pneumoniae in an Epidemic Region: A Historical Control Quasi-Experimental Study

et al. 2021

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Objective: To verify the effects of comprehensive infection prevention and control (IPC) interventions for the prevention of the cross-transmission of carbapenem-resistant Klebsiella pneumoniae (CRKP) within intensive care units (ICUs) in an epidemic region.Methods: A historical control, quasi-experimental design was performed. The study was conducted between January 2017 and December 2019, following the implementation of a multimodal IPC bundle. The baseline period was established from January 2013 to June 2013, when only basic IPC measures were applied.Results: A total of 748 patients were enrolled during the entire study. The incidence of ICU-acquired CRKP colonization/infection was 1.16 per 1,000 patient-days during the intervention period, compared with 10.19 per 1,000 patient-days during the baseline period (p = 0.002). The slope of the monthly incidence of CRKP at admission showed an increasing trend (p = 0.03). The incidence of ICU-acquired catheter-related bloodstream infections caused by CRKP decreased from 2.54 to 0.96 per 1,000 central-line-days (p = 0.08). Compliance with contact precautions and terminal room disinfection improved during the intervention period. All environmental surface culture samples acquired after terminal room disinfection were negative for CRKP.Conclusion: Our findings suggest that in epidemic settings, multimodal IPC intervention strategies and consistent monitoring of compliance, may limit the spread of CRKP in ICUs.

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“…The route of transmission also has more possibility of analysis with the assistance of next-generation sequencing 19 . Many pieces of researches focus on Protecting susceptible people because of its simplicity and effectiveness 5,20,21 . Some studies pay attention to the identi cation of high-risk factors, which are determined by building models [21][22][23][24] .…”

Section: Prospective Studymentioning

confidence: 99%

Early Prediction of the Carbapenem Resistance Gram-negative Bacteria Carriage in Intensive Care Unit using Machine-Learning

Liang

Zhao²,

et al. 2020

Preprint

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Background The prevention and control of carbapenem-resistance gram-negative bacteria (CR-GNB) is the difficulty and focus for clinicians in the intensive care unit (ICU). This study construct a CR-GNB carriage prediction model in order to predict the CR-GNB incidence in one week. Methods The database is comprised of nearly 10,000 patients. the model is constructed by the multivariate logistic regression model and three machine learning algorithms. Then we choose the optimal model and verify the accuracy by daily predicted and recorded the occurrence of CR-GNB of all patients admitted for 4 months. Results There are 1385 patients with positive CR-GNB cultures and 1535 negative patients in this study. Forty-five variables have statistical significant differences. We include the 17 variables in the multivariate logistic regression model and build three machine learning models for all variables. In terms of accuracy and the area under the receiver operating characteristic (AUROC) curve, the random forest is better than XGBoost and multivariate logistic regression model, and better than decision tree model (accuracy: 84% >82%>81%>72%), (AUROC: 0.9089 > 0.8947 ≈ 0.8987 > 0.7845). In the 4-month prospective study, 81 cases were predicted to be positive in CR-GNB culture within 7 days, 146 cases were predicted to be negative, 86 cases were positive, and 120 cases were negative, with an overall accuracy of 84% and AUROC of 91.98%. Conclusions Prediction models by machine learning can predict the occurrence of CR-GNB colonization or infection within a week period, and can real-time predict and guide medical staff to identify high-risk groups more accurately.

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Impact of active surveillance and infection control measures on carbapenem-resistant Gram-negative bacterial colonization and infections in intensive care

Cited by 50 publications

References 33 publications

Spread of Carbapenem-Resistant Gram-Negatives and Candida auris during the COVID-19 Pandemic in Critically Ill Patients: One Step Back in Antimicrobial Stewardship?

Spread of Carbapenem-Resistant Gram-Negatives and Candida auris during the COVID-19 Pandemic in Critically Ill Patients: One Step Back in Antimicrobial Stewardship?

Validation and Extrapolation of a Multimodal Infection Prevention and Control Intervention on Carbapenem-Resistant Klebsiella pneumoniae in an Epidemic Region: A Historical Control Quasi-Experimental Study

Early Prediction of the Carbapenem Resistance Gram-negative Bacteria Carriage in Intensive Care Unit using Machine-Learning

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