Epidemiological Characteristics of Carbapenemase Producing Carbapenem-Resistant Enterobacteriaceae Colonization.

PURPOSE: This study identified the epidemiological characteristics, including the size and major strains, of carbapenemase-producing carbapenem-resistant Enterobacteriaceae (CP-CRE) and CP-CRE-related factors by comparing the characteristics of patients in the CP-CRE and non-CP-CRE groups and the CP-CRE and non-CRE groups. METHODS: This secondary data analysis study included 24 patients in the CP-CRE group, 113 patients in the non-CP-CRE group, and 113 in the non-CRE group. The size and type of CP-CRE were analyzed in terms of frequency and percentage, and CP-CRE risk factors were identified using multiple logistic regression analysis. RESULTS: The rate of CP-CRE positivity among patients with CRE was 17.5%, and the most common causative organism in the CP-CRE group was Klebsiella pneumoniae (81.8%). There were no significant differences between patients in the CP-CRE and non-CP-CRE groups. When compared with the non-CRE group, the isolation of multidrug-resistant organisms except for CRE, particularly vancomycin-resistant Enterococcus, was confirmed as a major risk factor. CONCLUSION: To prevent CP-CRE acquisition, patients with multidrug-resistant organisms require treatment with more thorough adherence to CRE prevention and management guidelines.

Controlling an Outbreak of Multidrug-resistant Acinetobacter baumannii in a Pediatric Intensive Care Unit: a Retrospective Analysis.

BACKGROUND: Multidrug-resistant Acinetobacter baumannii (MDRAB) is widespread among intensive care units worldwide, posing a threat to patients and the health system. We describe the successful management of a MDRAB outbreak by implementing an infection-control strategy in a pediatric intensive care unit (PICU). METHODS: This retrospective study investigated the patients admitted to the PICU in periods 1 (8 months) and 2 (7 months), from the index MDRAB case to intervention implementation, and from intervention implementation to cessation of MDRAB spread. An infection-control strategy was designed following six concepts: 1) cohort isolation of colonized patients, 2) enforcement of hand hygiene, 3) universal contact precautions, 4) environmental management, 5) periodic surveillance culture study, and 6) monitoring and feedback. RESULTS: Of the 427 patients, 29 were confirmed to have MDRAB colonization, of which 18 had MDRAB infections. Overall incidence per 1,000 patient days decreased from 7.8 (period 1) to 5.8 (period 2). The MDRAB outbreak was declared terminated after the 6-month follow-up following period 2. MDRAB was detected on the computer keyboard and in condensed water inside the ventilator circuits. The rate of hand hygiene performance was the lowest in the three months before and after index case admission and increased from 84% (period 1) to 95% (period 2). Patients with higher severity, indicated by a higher Pediatric Risk of Mortality III score, were more likely to develop colonization (P = 0.030), because they had invasive devices and required more contact with healthcare workers. MDRAB colonization contributed to an increase in the duration of mechanical ventilation and PICU stay (P < 0.001), but did not affect mortality (P = 0.273). CONCLUSION: The MDRAB outbreak was successfully terminated by the implementation of a comprehensive infection-control strategy focused on the promotion of hand hygiene, universal contact precautions, and environmental management through multidisciplinary teamwork.

Development of a Nomogram for Carbapenem-Resistant Enterobacteriaceae Acquisition Risk Prediction Among Patients in the Intensive Care Unit of a Secondary Referral Hospital.

PURPOSE: This study aimed to identify the risk factors of carbapenem-resistant Enterobacteriaceae (CRE) acquisition to build a nomogram for CRE acquisition risk prediction and evaluate its performance. METHODS: This unmatched case-control study included 352 adult patients (55 patients and 297 controls) admitted to the intensive care unit (ICU) of a 453-bed secondary referral hospital between January 1, 2018, and September 31, 2019, in Busan, South Korea. The nomogram was built with the identified risk factors using multiple logistic regression analysis. Its performance was analyzed using calibration-in-the-large, the slope of the calibration plot, concordance statistic (c-statistic), and the sensitivity and specificity of the training set, subsets, and a new test set. RESULTS: The risk factors of CRE acquisition among ICU patients at a secondary referral hospital were Acute Physiology and Chronic Health Evaluation II score at the time of admission, use of a central venous catheter and a nasogastric tube, as well as use of cephalosporin antibiotics. At 20.0% of the predicted CRE acquisition risk in the training set, the calibration-in-the-large was 0, slope of the calibration plot was 1, c-statistic was .93, sensitivity was 85.5%, and specificity was 84.8%. The performance was relatively good in the subsets and new test set. CONCLUSION: The nomogram can be used to monitor the CRE acquisition risk for ICU patients who have a similar case mix to patients in the study hospitals. Future studies need to involve more rigorous methodology and larger samples.

Validation of a carbapenem-resistant Enterobacteriaceae colonization risk prediction model: A retrospective cohort study in Korean intensive care units.

BACKGROUND: To assess the external validity of a carbapenem-resistant Enterobacteriaceae colonization risk prediction model (CREP-model). METHODS: This retrospective cohort study included 414 patients admitted to the intensive care units of a tertiary hospital from November 1, 2017 to May 31, 2018. Data were collected via medical record review, and we analyzed the performance of the CREP-model by assessment of calibration, discrimination, clinical usefulness, and uniformity-of-fit. RESULTS: The validation subjects showed differences in age, Acute Physiology and Chronic Health Evaluation II score, mechanical ventilation days, and carbapenem-resistant Enterobacteriaceae colonization rate from those of the CREP-model development subjects. The calibration-in-the-large was 0.069 (95% confidence interval [CI], 0.065-0.074), and calibration slope was 1.114 (95% CI, 1.091-1.136). The area under the receiver operating characteristic curve was 0.883 (95% CI, 0.838-0.928). At the predicted risk of 0.25, the sensitivity, specificity, and correct classification rates were 81.3%, 79.8%, and 80.0%, respectively, and the net benefit according to the model was 0.035 with 64 fewer false-positive results per 100 patients. The calibration, discrimination, and clinical usefulness showed similar results among subjects stratified according to sex, age group, medical department, and admission source. CONCLUSIONS: The CREP-model showed good performance in the validation sample; therefore, we recommend introducing the CREP-model into intensive care units of tertiary hospitals to improve decision-making.