Development of a bedside tool to predict the probability of drug-resistant pathogens among hospitalized adult patients with gram-negative infections

Table 1 Independent predictors of ≥1 type of resistant infection included in the multivariate analysis^a

	Predictor	CRE		3GC-R		MDRP
	Predictor	Hospital	Community	Hospital	Community	Hospital	Community
Other	Infection site ^b	✓	✓	✓	✓	✓	✓
	ICU vs non-ICU	✓		✓		✓
	Hospital prevalence	✓	✓	✓	✓	✓	✓
Patient	Age			✓	✓
	Transfer	✓	✓	✓	✓	✓	✓
	Admission in prior 6 months	✓	✓	✓	✓	✓	✓
	Prior number of antibiotics ^c	✓		✓		✓
	Infection in prior 3 months		✓		✓	✓	✓
Comorbidities^d	Cancer			✓			✓
	Cerebrovascular disease	✓		✓
	Chronic pulmonary disease					✓	✓
	Heart failure			✓
	Diabetes with complications	✓		✓	✓
	Diabetes without complications		✓		✓		✓
	Dialysis	✓	✓	✓	✓	✓
	Mild liver disease	✓		✓
	Myocardial infarction	✓				✓	✓
	Para/hemiplegia		✓		✓	✓	✓
	Peripheral vascular disease			✓

3GC-R third-generation cephalosporin-resistant Enterobacteriaceae, CRE carbapenem-resistant Enterobacteriaceae, ICU intensive care unit, MDRP multidrug-resistant Pseudomonas aeruginosa
^aBoldface cells = most important predictors across most models (predictors incurring the highest level of risk compared with the reference value).
^bComplicated urinary tract infection, complicated intra-abdominal infection, bloodstream infection, or hospital-acquired/ventilator-associated pneumonia.
^cPrior number of antibiotics was not included for community-acquired infection because of the difficulty of recovering accurate data
^dPrimary and secondary diagnoses were based on International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] codes

ISSN: 1471-2334