Active Surveillance of Multidrug-Resistant Organisms with Rapid Detection Methods for Infection Control

[External Validation of Carbapenem-Resistant Enterobacteriaceae Acquisition Risk Prediction Model in a Medium Sized Hospital]

PURPOSE

This study was aimed to evaluate the external validity of a carbapenem-resistant Enterobacteriaceae (CRE) acquisition risk prediction model (the CREP-model) in a medium-sized hospital.

METHODS

This retrospective cohort study included 613 patients (CRE group: 69, no-CRE group: 544) admitted to the intensive care units of a 453-beds secondary referral general hospital from March 1, 2017 to September 30, 2019 in South Korea. The performance of the CREP-model was analyzed with calibration, discrimination, and clinical usefulness.

RESULTS

The results showed that those higher in age had lower presence of multidrug resistant organisms (MDROs), cephalosporin use ≥ 15 days, Acute Physiology and Chronic Health Evaluation II (APACHE II) score ≥ 21 points, and lower CRE acquisition rates than those of CREP-model development subjects. The calibration-in-the-large was 0.12 (95% CI: - 0.16~0.39), while the calibration slope was 0.87 (95% CI: 0.63~1.12), and the concordance statistic was .71 (95% CI: .63~.78). At the predicted risk of .10, the sensitivity, specificity, and correct classification rates were 43.5%, 84.2%, and 79.6%, respectively. The net true positive according to the CREP-model were 3 per 100 subjects. After adjusting the predictors' cutting points, the concordance statistic increased to .84 (95% CI: .79~.89), and the sensitivity and net true positive was improved to 75.4%. and 6 per 100 subjects, respectively.

CONCLUSION

The CREP-model's discrimination and clinical usefulness are low in a medium sized general hospital but are improved after adjusting for the predictors. Therefore, we suggest that institutions should only use the CREP-model after assessing the distribution of the predictors and adjusting their cutting points.

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.

Development of a risk prediction model of carbapenem-resistant Enterobacteriaceae colonization among patients in intensive care units

BACKGROUND

Few hospitals have conducted surveillance cultures to identity carbapenem-resistant Enterobacteriaceae (CRE) colonization in Korea because of high test costs, long wait time to get results, and lack of personnel. This study aimed to identify risk factors of CRE colonization and to develop a model for predicting the risk of CRE colonization.

METHODS

This retrospective cohort study was done with medical record review at a tertiary hospital between October 1, 2016, and October 31, 2017, in 444 adult patients admitted to the intensive care unit. The identification of risk factors and risk model development were done by multiple logistic regression. The area under the receiver operator characteristic curve and correct classification were measured.

RESULTS

The risk prediction logistic model for CRE colonization was composed of 4 factors among 22 significant variables on univariate analysis and 1 interaction term; E (logit of CRE colonization) = -2.821 + 1.606 (isolation of multidrug-resistant organisms) + 1.347 (≥15 days of cephalosporin administration) + 0.980 (≥15 days of carbapenem administration) + 0.544 (score ≥21 on Acute Physiology and Chronic Health Evaluation II). The risk prediction model showed 0.80 (95% confidence interval, 0.74-0.85) for the area under the curve, and 68.9% correct classification.

CONCLUSIONS

It is recommended to utilize the risk prediction model to screen out for the colonization of CRE, and to do validation studies for verifying the generalizability.