1218 infection control & hospital epidemiology october 2017, vol. 38, no. 10


aminoglycosides, fluoroquinolones (levofloxacin or cipro- floxacin), antipseudomonal penicillins (ticarcillin-clavunalic


acid or piperacillin-tazobactam), and carbapenems (imipenem or meropenem).1,23


Data Collection


For all study patients, the following clinical data were pro- spectively collected: age, gender, living arrangements prior to the ED visit, pre-existing comorbidities, predisposing factors for infection, and antibiotic exposure history within the 3 months prior to study enrollment. Records of previous microbiological study results for the patientwere also reviewed to assess the colonization status of MRSA and/or VRE in the 12 months prior to enrollment. Results of the microbiological assessments performed, including active surveillance cultures and clinical cultures obtained at the ED and after hospitaliza- tion, were also recorded. For all patients in the second stage of the study, the same


clinical and previous microbiological data were collected as for the patients in the first stage of the study, with the exception of the active surveillance cultures. Patients were observed for any positive clinical culture of MDR-GNB and the occurrence of culture-confirmed MDR-GNB infection during the hospitali- zation treatment course. The diagnosis of a MDR-GNB infection of a study patient was independently judged by 2 investigators based on clinical and microbiological findings. A third investigator made the final decision if these 2 investi- gators did not reach an agreement on the primary site ofMDR- GNB infection.


Model Development, Validation, and Usefulness in Clinical Application


The patients in the first stage of the study were randomly assigned to the derivation or validation sets in a 2:1 ratio using a simple randomization method that used computer- generated random numbers. The COP model was developed from the derivation patient set and was tested independently using the validation patient set. We then used the data set collected from the patients in the second stage of the study to evaluate the usefulness of the COP model in stratifying MDR- GNB infection risk among ED patients.


Statistical Analyses


Means (± standard deviation) were calculated for continuous variables, and percentages were used for categorical variables. An independent Student t test was used to compare con- tinuous variables, whereas categorical variables were analyzed using a χ2 test or the Fisher exact test. Because records of previous microbiological test results were not usually available at the time of the initial ED evaluation, only the demographic and clinical variables were included in the logistic regression analysis. Potential predictors for MDR-GNB colonization with


P<.05 on univariate analysis were investigated using multi- variate logistic regression analysis with a backward selection method. The colinearity of the covariates was assessed, and model fitting was explored based on the Hosmer–Lemeshow goodness-of-fit test. The discriminatory ability of each model was assessed using the area under the receiver operating characteristic (ROC) curve method.24 To develop an easy-to-use clinical risk score, we assigned a


point value to each independent predictor selected by the final logistic regression model by multiplying the value of the corresponding natural logarithm (β-coefficient) of the odds ratio by 2 and rounding to the nearest integer.25 The overall score was the sum of the individual point values for each predictor. Sensitivity, specificity, positive predictive value, and negative predictive value with an associated 95% confidence interval (CI) for the prediction model at different cutoff values, were evaluated using a standard definition and methods.26 The best cutoff value for prediction of the final model was chosen based on the Youden index statistics and stratified patients into low and high MDR-GNB colonization risk groups. For the patients in the second stage of the study, the cumulative probability of developing a MDR-GNB infection, calculated from the date of ED visit, was plotted using the Kaplan-Meier method. Differences between low and high MDR-GNB colonization risk categories were tested using the log-rank test. All statistically analyses were performed using SPSS version 16.0 software (SPSS, Chicago, IL).


results


Development of the MDR-GNB Colonization Prediction Model


In first stage of this study, 995 patients received active surveillance cultures. Of these patients, 122 (12.3%) were identified as being colonized with MDR-GNB by either the surveillance or clinical cultures. Moreover, the active surveil- lance cultures detected 95 patients, and the early clinical cultures identified an additional 27 patients. Without con- sidering the surveillance culture results, early clinical cultures identified only 72 of 122 (59.0%) MDR-GNB colonized


patients (Online Appendix Figure A). The bacteriological findings and culture sites of the MDR-GNB isolates identified from the 122 MDR-GNB colonized patients are shown in Table 1. Escherichia coli was the predominant MDR-GNB species, with the respiratory tract being the most frequent anatomical site with a positive MDR-GNB culture. Stage 1 patients were randomly assigned to the derivation


and validation sets. There were 77 (11.6%) and 45 (13.6%) MDR-GNB colonizers in the derivation and validation sets, respectively (P=.379). With the exception of the percentage of patients that resided in a long-term care facility (LTCF) (4.4% vs 7.8%; P=.024), the derivation and validation set patients had similar demographic distributions, clinical characteristics, and previous recovery rates of MRSA (Table 2).


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64  |  Page 65  |  Page 66  |  Page 67  |  Page 68  |  Page 69  |  Page 70  |  Page 71  |  Page 72  |  Page 73  |  Page 74  |  Page 75  |  Page 76  |  Page 77  |  Page 78  |  Page 79  |  Page 80  |  Page 81  |  Page 82  |  Page 83  |  Page 84  |  Page 85  |  Page 86  |  Page 87  |  Page 88  |  Page 89  |  Page 90  |  Page 91  |  Page 92  |  Page 93  |  Page 94  |  Page 95  |  Page 96  |  Page 97  |  Page 98  |  Page 99  |  Page 100  |  Page 101  |  Page 102  |  Page 103  |  Page 104  |  Page 105  |  Page 106  |  Page 107  |  Page 108  |  Page 109  |  Page 110  |  Page 111  |  Page 112  |  Page 113  |  Page 114  |  Page 115  |  Page 116  |  Page 117  |  Page 118  |  Page 119  |  Page 120  |  Page 121  |  Page 122  |  Page 123  |  Page 124  |  Page 125  |  Page 126  |  Page 127  |  Page 128  |  Page 129  |  Page 130  |  Page 131  |  Page 132  |  Page 133  |  Page 134  |  Page 135  |  Page 136  |  Page 137  |  Page 138  |  Page 139  |  Page 140  |  Page 141  |  Page 142  |  Page 143  |  Page 144