There were 2,049 intra-abdominal infections treated during the period of study; 789 infections were treated without culture, 78 had cultures without growth (usually obtained after antibiotics had been started), and 1,182 had positive cultures. Comparing the infections treated without culture with those treated with positive cultures, the former were more likely to be community-acquired (407/789 [52%] vs. 395/1182 [33%]; p

<

0.0001) and were associated with a lower Acute Physiology and Chronic Health Evaluation (APACHE) II score [
4] at the time of presentation (11.2

±

0.3 vs. 13.3

±

0.3 points; p

<

0.0001). Because the focus of this paper is patients at high risk of having infections caused by resistant pathogens, the rest of the analysis will be limited to the 1,182 infections with positive cultures. Of these cases, 1,074 were complicated intra-abdominal infections, as defined by the U.S. Centers for Disease Control and Prevention (CDC), and 108 were organ/space surgical site infections.
Because health care-associated and community-acquired infections tend to have different microbiology findings, these groups were compared first. gives the ORs with 95% confidence intervals for the isolation of specific pathogens from healthcare-associated infections compared to community-acquired infections. The enterococci and
Candida spp. were the two groups of pathogens more likely to be isolated from health care-associated infections to a clinically relevant extent. Other pathogens, such as MRSA and
Serratia spp., were statistically more likely to be isolated from health care-associated infections, yet still occurred relatively infrequently (<

6% of infections) and might not affect the choice of empiric antimicrobial therapy. Surprisingly, several pathogens commonly believed to be associated with health care-associated infections were isolated with similar frequency from the two groups, including
P. aeruginosa, Citrobacter spp., and coagulase-negative staphylococci. Because the inclusion of solid organ transplant recipients could be a factor in the rate of recovery of certain pathogens, the report of pathogens is repeated in , excluding these patients. Surprisingly, although the frequency of some pathogens is altered after the exclusion of transplant patients; e. g., VRE, the ORs are changed minimally, and the most important differences clinically are again for enterococci and fungi.
| Table 1.Odds Ratios of Isolation of Common Bacteria from Health-Care Associated vs. Community-Acquired Intra-Abdominal Infections |
| Table 2.Odds Ratios of Isolation of Common Bacteria from Health-Care Associated vs. Community-Acquired Intra-Abdominal Infections, Excluding Patients with Solid Organ Allografts |
To help define demographics and outcomes related to intra-abdominal infections with resistant pathogens, presents an analysis of associations between multiple clinical variables and the isolation of pathogens considered to be resistant or potentially resistant to standard empiric antimicrobial therapy. The means for continuous variables are given with p values for the differences between infections caused by resistant and non-resistant pathogens. For dichotomous variables, the frequency is given for resistant and non-resistant infections, and ORs with 95% CI are given for their comparison. Outcomes for these infections also are presented. These data confirm that resistant pathogens occur more commonly in hospitalized patients, particularly in the intensive care unit (ICU), and are associated with underlying diseases. Although the mean APACHE II score was significantly higher in patients with resistant infections, the difference of less than three points may be clinically trivial and probably prevents this parameter from being a useful discriminating factor. Gastroduodenal source infections created the highest risk and appendiceal source infections the lowest risk for involvement of resistant organisms. As would be expected, infections with the pathogens of interest were associated with a longer stay and a higher in-hospital mortality rate.
| Table 3.Patient Characteristics and Outcomes, Resistant vs. Non-Resistant Pathogens, for All Intra-Abdominal Infections |
A logistic regression analysis investigating the influence of potential predictors listed in on subsequent finding of a resistant organism was performed. The model demonstrated only marginal statistical performance (c statistic 0.674; R
2
=

0.096), giving credence to the idea that predicting these cases is difficult. independent statistically significant effects were seen for age

>

70 years (OR

=

0.65; p

=

0.02), premorbid pulmonary diagnosis (OR

=

1.70; p

=

0.001), treatment more than 10 days after admission (OR

=

1.70; p

=

0.002), stomach as the source (OR

=

2.86; p

=

0.005), duodenum as the source (OR

=

4.62; p

<

0.0001), small bowel as the source (OR

=

1.70; p

=

0.04), and appendix as the source (OR

=

0.34; p

=

0.014). It is possible that other factors exist that are independently predictive of specific pathogens but not all resistant pathogens in general. Because it is possible that the presence of patients with allografts might have skewed the results significantly, provides data similar to that found in , but excludes transplant recipients. With the exception of a decrease in the number of infections from a hepatobiliary source, there are minimal differences between the overall cohort and the cohort excluding transplant patients.
| Table 4.Patient Characteristics and Outcomes, Resistant vs. Non-Resistant Pathogens, for All Intra-Abdominal Infections Excluding Patients with Solid Organ Allografts |
Because many if not most community-acquired infections are treated without cultures, a separate analysis of the risk factors for the isolation of resistant pathogens from these infections was compiled (). Although less frequently than for health care-associated infections, one quarter of the community-acquired infections nevertheless had the organisms of interest recovered. The resistant pathogens recovered from these patients included
P. aeruginosa (N

=

12),
S. maltophilia (N

=

3), MRSA (N

=

10), coagulase-negative staphylococci (N

=

15), VRE (N

=

5),
C. albicans (N

=

42), non-
albicans Candida spp. (N

=

17), and non-speciated yeast (N

=

13). Risk factors for the isolation of resistant pathogens were similar to those for all infections, and included corticosteroid use, organ (especially liver) transplantation, pulmonary disease, a gastroduodenal source, and a clinically trivial APACHE II score difference of two points. The length of stay after the initiation of treatment was higher with resistant pathogens, but the in-hospital mortality rates were nearly identical in the two groups.
| Table 5.Patient Characteristics and Outcomes, Resistant vs. Non-Resistant Pathogens, for Community-Acquired Infections |
Because prediction of the presence of specific resistant pathogens might be valuable when choosing antimicrobials empirically, for example, administering fluconazole to patients at risk for candidal infection or linezolid to patients at risk for VRE infections, gives data regarding specific clinical characteristics and outcomes for the resistant pathogens of interest, including non-fermenting gram-negative bacilli, resistant staphylococci, VRE, and fungi, as well as for all enterococci. The ORs and 95% CI are from comparisons with infections where no resistant pathogens were isolated (see the third column of ), except for all enterococcal infections, which were compared with all other infections not caused by enterococci or resistant pathogens. Not surprisingly, the isolation of resistant pathogens was associated with acquisition in a health care setting, particularly in the ICU. Differences among the specific pathogens or classes were noted. Non-fermenting gram-negative bacilli were associated with underlying lung disease, perhaps secondary to oral or pulmonary colonization. Resistant staphylococcal infections were associated with a pancreatic source and ventilator dependence, perhaps likewise secondary to colonization by this organism. Analysis of MRSA infections alone gave similar results. Infections with any Enterococcus were associated with liver disease, including prior liver transplantation, and a hepatobiliary or duodenal source, probably because of the ability of these organisms to grow in bile. Vancomycin-resistant enterococci were even more closely associated with immunosuppression, liver disease, and a hepatobiliary source. Finally, the isolation of fungi was associated with steroid use, pulmonary disease, and a gastro-duodenal or small bowel source. In general, outcomes were worse for resistant pathogens, with the highest mortality rate observed after infections caused by fungi or VRE.
| Table 6.Patient Characteristics and Odds Ratios (85% Confidence Intervals) of Finding that Characteristic among Patients with Specific Resistant Pathogens Compared with Intra-Abdominal Infections with No Resistant Pathogens |
gives results of a multivariable analysis of risk factors for death after intra-abdominal infections to analyze the importance of resistance in outcome. When developing the model, a strong interaction between solid organ transplantation and death after infections with resistant organisms was revealed. In terms of crude mortality rate, the following observations were made: Mortality rate for non-transplant patients with non-resistant infections 49/584 (8.4%) vs. 54/386 (14.0%) for non-transplant patients with resistant infections (p

=

0.008); mortality rate for solid organ transplant patients with non-resistant infections 10/105 (9.5%) vs. 30/107 (28.0%) for solid organ transplant patients with resistant infections (p

=

0.001). Therefore, the final model included the interaction term “Resistant organism

+

solid organ transplant.” The logistic regression model demonstrated excellent statistical performance (c statistic 0.887; R
2
=

0.226). Not surprisingly, multiple measures of acute and chronic illness were associated with death, although after APACHE II score, the strongest predictor was intra-abdominal infection with a resistant organism in the setting of solid organ transplantation. These data suggest that after adjusting for other variables, the added burden of resistance affects immunosuppressed transplant patients disproportionately.
| Table 7.Results of Logistic Regression Analysis Examining Influence of Clinical Factors on In-Hospital Death |