854 infection control & hospital epidemiology july 2017, vol. 38, no. 7


table 4. Risk Ratios for Mortality 30 and 90 Days After Culture for Patients With Positive Cultures Relative to Patients Without Positive Cultures, Regardless of Location Status (Hospitalized or Postdischarge)


30 Days 95% CI Organism


MDR Gram-negative bacteria Combined Invasivea


Noninvasiveb


MDR Acinetobacter Combined Invasive


Noninvasive


MDR Pseudomonas Combined Invasive


Noninvasive


MDR Enterobacteriaceae Combined Invasive


MRSA


Noninvasive Combined


HAIc Colonizationd RR


1.42 2.32 1.33


2.21 3.34 1.98


1.70 2.08 1.62


1.18 2.07 1.09


1.55 2.77 1.35


Lower


1.31 1.85 1.22


1.78 1.97 1.53


1.50 1.22 1.42


1.07 1.64 0.99


1.42 2.39 1.22


Upper


1.54 2.92 1.44


2.74 5.66 2.57


1.93 3.56 1.85


1.29 2.60 1.21


1.70 3.21 1.50


P Value


<.0001 <.0001 <.0001


<.0001 <.0001 <.0001


<.0001 .007


<.0001 <.0001


<.0001 .074


<.0001 <.0001 <.0001


RR


1.48 1.93 1.39


1.91 2.39 1.72


1.65 1.99 1.59


1.28 1.88 1.21


1.44 2.24 1.31


Lower


1.39 1.59 1.30


1.61 1.49 1.40


1.51 1.34 1.44


1.20 1.57 1.12


1.34 1.99 1.21


90 Days 95% CI Upper


1.57 2.33 1.48


2.27 3.84 2.12


1.82 2.96 1.75


1.37 2.26 1.30


1.54 2.53 1.42


P Value


<.0001 <.0001 <.0001


<.0001 <.0001 <.0001


<.0001 .001


<.0001 <.0001


<.0001 <.0001


<.0001 <.0001 <.0001


NOTE. MDR, multidrug resistant; RR, risk ratio; CI, confidence interval; HAI, healthcare-associated infection; MRSA, methicillin-resistant


Staphylococcus aureus. aCulture obtained from a typically sterile site including blood, bone, bone marrow, cerebrospinal fluid, pleural fluid, peritoneal fluid, synovial


fluid, lymph node. bCulture obtained from a site other than those listed for invasive cultures. cUsing algorithm developed by Branch-Elliman et al (2014), culture obtained from sterile site (blood, bone, or device) or patient was treated


with MRSA-active antimicrobials in the 5 days prior to or following the positive culture. dPositive culture not classified as HAI by Branch-Elliman algorithm.


This study has several limitations to. First, our exposure of


interest was a positive clinical culture for 1 of several MDR organisms. While these cultures may not all be indicative of true infections, we identified whether the cultures were obtained from a site that is usually considered sterile (eg, blood, bone, bone marrow, cerebrospinal fluid, pleural fluid, synovial fluid, and lymph node) or unsterile. Positive cultures from sterile sites are much more likely to be infections. Second, our analyses used administrative and clinical data from the VA. These data were not produced for the purposes of research but in the process of providing care to patients in the VA system. Thus, these results may not be generalizable to other settings to the extent that differences exist between patients and healthcare delivery systems. Also, our analyses may include residual confounding related to severity of illness during the index hospitalization, which we were unable to control for using administrative data. Third, for the purposes of this analysis, we focused solely on a patient’s first hospita- lization during our time period of interest. And finally, patients receiving care in the VA system may not be representative of


healthcare overall in the United States. A similar analysis using non-VA data would be useful and may yield more general- izable results. Our study has several strengths. First, this is the largest study


to estimate the attributable mortality associated with HAIs due to MDR gram-negative bacteria with patients from more than 100 hospitals in the United States. Second, we used a propensity-score matching approach to select control patients in which we matched patients based on the length of stay prior to infection. Thus, we avoided introducing time-dependent bias to our estimates that would have occurred in an analysis and did not explicitly take into account the time-varying nature of HAIs.28 By incorporating important postadmission confounders (eg, indicators for surgery, mechanical ventila- tion, peritoneal dialysis, and hemodialysis, and days spent in both the medical and surgical ICU) in our propensity score estimation, our mortality estimates are likely to more accu- rately represent the true mortality effect. Third, unlike other data sources, the VA dataset allowed us to follow patients beyond discharge to ascertain whether they died within 30 or


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