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

Risk factors for in-hospital acquisition of carbapenem-resistant Enterobacterales in patients with severe burns

BACKGROUND

Although patients with severe burns are prone to severe infections with antibiotic-resistant bacteria and inevitably have some risk factors for carbapenem-resistant Enterobacterales (CRE) acquisition, risk factors for CRE infection or colonization in these patients have not been investigated.

AIM

To identify the independent risk factors for CRE acquisition in patients with severe burns.

METHODS

Patients admitted to the burn intensive care unit (BICU) for acute burn care were categorized based on culture results during BICU care into the CRE group and non-CRE group, which included the carbapenem-susceptible Enterobacterales (CSE) and control groups. Clinical and microbiological factors were compared between the CRE and non-CRE groups, and between the CRE and CSE groups to identify independent risk factors for in-hospital CRE acquisition.

FINDINGS

Among the included 489 patients, 101 (20.7%) and 388 (79.3%) patients were classified in the CRE and non-CRE groups, respectively. The non-CRE group included 91 (18.6%) and 297 (60.7%) patients in the CSE and control groups, respectively. In multivariate analysis between the CRE and non-CRE groups, exposure to other CRE-acquired patients (P = 0.018), abbreviated burn severity index score ≥9 (P = 0.012), and mechanical ventilation (P < 0.001) were associated with CRE acquisition. In multivariate analysis between the CRE and CSE groups, exposure to other CRE-acquired patients was associated with CRE acquisition (P = 0.048).

CONCLUSION

Considering the limitation of controlling the burn severity in hospitalized patients, enhanced infection control measures for preventing in-hospital CRE transmission among patients with severe burns should be emphasized.

A deep learning model for predicting multidrug-resistant organism infection in critically ill patients

BACKGROUND

This study aimed to apply the backpropagation neural network (BPNN) to develop a model for predicting multidrug-resistant organism (MDRO) infection in critically ill patients.

METHODS

This study collected patient information admitted to the intensive care unit (ICU) of the Affiliated Hospital of Qingdao University from August 2021 to January 2022. All patients enrolled were divided randomly into a training set (80%) and a test set (20%). The least absolute shrinkage and selection operator and stepwise regression analysis were used to determine the independent risk factors for MDRO infection. A BPNN model was constructed based on these factors. Then, we externally validated this model in patients from May 2022 to July 2022 over the same center. The model performance was evaluated by the calibration curve, the area under the curve (AUC), sensitivity, specificity, and accuracy.

RESULTS

In the primary cohort, 688 patients were enrolled, including 109 (15.84%) MDRO infection patients. Risk factors for MDRO infection, as determined by the primary cohort, included length of hospitalization, length of ICU stay, long-term bed rest, antibiotics use before ICU, acute physiology and chronic health evaluation II, invasive operation before ICU, quantity of antibiotics, chronic lung disease, and hypoproteinemia. There were 238 patients in the validation set, including 31 (13.03%) MDRO infection patients. This BPNN model yielded good calibration. The AUC of the training set, the test set and the validation set were 0.889 (95% CI 0.852-0.925), 0.919 (95% CI 0.856-0.983), and 0.811 (95% CI 0.731-0.891), respectively.

CONCLUSIONS

This study confirmed nine independent risk factors for MDRO infection. The BPNN model performed well and was potentially used to predict MDRO infection in ICU patients.

Epidemiological characteristics of carbapenem-resistant Enterobacteriaceae and carbapenem-resistant Acinetobacter baumannii in a tertiary referral hospital in Korea

Objectives

This study aimed to identify the epidemiological characteristics of patients with carbapenem-resistant Enterobacteriaceae and Acinetobacter baumannii (CRE/CRAB) isolates in a tertiary referral hospital in Korea.

Methods

We collected and analyzed data from 528 adults admitted to a tertiary referral hospital from August 1, 2018 to February 29, 2020. The CRE/CRAB isolates were confirmed as being present at the time of patients’ admission or acquired during hospitalization based on their medical records. The t-test, chi-square test, or Fisher exact test and stepwise multiple logistic regression were performed.

Results

While the proportion of community-acquired CRE/CRAB was low (6%), 20% of CRE/CRAB isolates were identified in patients at the time of hospitalization. The risk of CRAB isolation was positively associated with mechanical ventilator use (odds ratio [OR], 3.52; 95% confidence interval [CI], 1.96−6.33) and total parenteral nutrition use (OR, 3.64; 95% CI, 1.87−7.08).

Conclusion

Over 20% of CRE/CRAB isolates in a tertiary referral hospital in Korea were found at the time of patients’ admission. Furthermore, patients with mechanical ventilation and/or total parenteral nutrition tended to acquire CRAB more frequently. Thus, active surveillance for CRE/CRAB at the time of hospitalization is strongly required, particularly for patients who are expected to require mechanical ventilation or total parenteral nutrition.

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.

A Nomogram With Six Variables Is Useful to Predict the Risk of Acquiring Carbapenem-Resistant Microorganism Infection in ICU Patients

Background

Carbapenem-resistant microorganism (CRO) transmission in the medical setting confers a global threat to public health. However, there is no established risk prediction model for infection due to CRO in ICU patients. This study aimed to develop a nomogram to predict the risk of acquiring CRO infection in patients with the first ICU admission and to determine the length of ICU stay (ICU-LOS) and 28-day survival.

Methods

Patient data were retrieved from the Medical Information Mart for Intensive Care (MIMIC-IV) database based on predetermined inclusion and exclusion criteria. A CRO was defined as a bacterium isolated from any humoral microbial culture that showed insensitivity or resistance to carbapenems. The characteristics of CRO and non-CRO patients in the first ICU admission were compared. Propensity score matching was applied to balance the differences between the CRO and non-CRO cohorts. Kaplan–Meier curves were constructed to determine the 28-day survival rate and ICU-LOS. Furthermore, after randomization of the CRO cohort into the training and validation sets, a predictive nomogram was constructed based on LASSO regression and Logistic regression analysis, and its performance was verified by internal validation.

Results

Overall, 4531 patients who had first ICU admission as recorded in MIMIC-IV were enrolled, 183 (4.04%) of whom were diagnosed with CRO infection. Moreover, CRO infection was independently associated with 28-day survival and ICU-LOS in ICU patients. Parameters eligible for inclusion in this nomogram were male sex, hemoglobin-min, temperature-max, use of a peripherally inserted central catheter line, dialysis treatment, and use of carbapenems. This nomogram showed a better performance as indicated by the area under the receiver operating characteristic curve values of 0.776 (95% confidence interval [CI] 0.667-0.750) and 0.723 (95% CI 0.556-0.855) in the training and validation sets, respectively, in terms of predicting the risk of acquiring CRO infection.

Conclusions

CRO infection was independently associated with ICU-LOS and 28-day survival in patients with first ICU admission. The nomogram showed the best prediction of the risk of acquiring CRO infection in ICU patients. Based on the nomogram-based scoring, we can management the risk factors and guide individualized prevention and control of CRO.