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Despite a reported worldwide increase, the incidence of extended-spectrum β-lactamase (ESBL) Escherichia coli and Klebsiella infections in the United States is unknown. Understanding the incidence and trends of ESBL infections will aid in directing research and prevention efforts.
To perform a literature review to identify the incidence of ESBL-producing E. coli and Klebsiella infections in the United States.
Systematic literature review.
MEDLINE via Ovid, CINAHL, Cochrane library, NHS Economic Evaluation Database, Web of Science, and Scopus were searched for multicenter (≥2 sites), US studies published between 2000 and 2015 that evaluated the incidence of ESBL-E. coli or ESBL-Klebsiella infections. We excluded studies that examined resistance rates alone or did not have a denominator that included uninfected patients such as patient days, device days, number of admissions, or number of discharges. Additionally, articles that were not written in English, contained duplicated data, or pertained to ESBL organisms from food, animals, or the environment were excluded.
Among 51,419 studies examined, 9 were included for review. Incidence rates differed by patient population, time, and ESBL definition and ranged from 0 infections per 100,000 patient days to 16.64 infections per 10,000 discharges and incidence rates increased over time from 1997 to 2011. Rates were slightly higher for ESBL-Klebsiella infections than for ESBL-E. coli infections.
The incidence of ESBL-E. coli and ESBL-Klebsiella infections in the United States has increased, with slightly higher rates of ESBL-Klebsiella infections. Appropriate estimates of ESBL infections when coupled with other mechanisms of resistance will allow for the appropriate targeting of resources toward research, drug discovery, antimicrobial stewardship, and infection prevention.
The purpose of this study was to quantify the effect of multidrug-resistant (MDR) gram-negative bacteria and methicillin-resistant Staphylococcus aureus (MRSA) healthcare-associated infections (HAIs) on mortality following infection, regardless of patient location.
We conducted a retrospective cohort study of patients with an inpatient admission in the US Department of Veterans Affairs (VA) system between October 1, 2007, and November 30, 2010. We constructed multivariate log-binomial regressions to assess the impact of a positive culture on mortality in the 30- and 90-day periods following the first positive culture, using a propensity-score–matched subsample.
Patients identified with positive cultures due to MDR Acinetobacter (n=218), MDR Pseudomonas aeruginosa (n=1,026), and MDR Enterobacteriaceae (n=3,498) were propensity-score matched to 14,591 patients without positive cultures due to these organisms. In addition, 3,471 patients with positive cultures due to MRSA were propensity-score matched to 12,499 patients without positive MRSA cultures. Multidrug-resistant gram-negative bacteria were associated with a significantly elevated risk of mortality both for invasive (RR, 2.32; 95% CI, 1.85–2.92) and noninvasive cultures (RR, 1.33; 95% CI, 1.22–1.44) during the 30-day period. Similarly, patients with MRSA HAIs (RR, 2.77; 95% CI, 2.39–3.21) and colonizations (RR, 1.32; 95% CI, 1.22–1.50) had an increased risk of death at 30 days.
We found that HAIs due to gram-negative bacteria and MRSA conferred significantly elevated 30- and 90-day risks of mortality. This finding held true both for invasive cultures, which are likely to be true infections, and noninvasive infections, which are possibly colonizations.
Information about the health and economic impact of infections caused by vancomycin-resistant enterococci (VRE) can inform investments in infection prevention and development of novel therapeutics.
To systematically review the incidence of VRE infection in the United States and the clinical and economic outcomes.
We searched various databases for US studies published from January 1, 2000, through June 8, 2015, that evaluated incidence, mortality, length of stay, discharge to a long-term care facility, readmission, recurrence, or costs attributable to VRE infections. We included multicenter studies that evaluated incidence and single-center and multicenter studies that evaluated outcomes. We kept studies that did not have a denominator or uninfected controls only if they assessed postinfection length of stay, costs, or recurrence. We performed meta-analysis to pool the mortality data.
Five studies provided incidence data and 13 studies evaluated outcomes or costs. The incidence of VRE infections increased in Atlanta and Detroit but did not increase in national samples. Compared with uninfected controls, VRE infection was associated with increased mortality (pooled odds ratio, 2.55), longer length of stay (3-4.6 days longer or 1.4 times longer), increased risk of discharge to a long-term care facility (2.8- to 6.5-fold) or readmission (2.9-fold), and higher costs ($9,949 higher or 1.6-fold more).
VRE infection is associated with large attributable burdens, including excess mortality, prolonged in-hospital stay, and increased treatment costs. Multicenter studies that use suitable controls and adjust for time at risk or confounders are needed to estimate the burden of VRE infections.
Our objective was to estimate the per-infection and cumulative mortality and cost burden of multidrug-resistant (MDR) Acinetobacter healthcare-associated infections (HAIs) in the United States using data from published studies.
We identified studies that estimated the excess cost, length of stay (LOS), or mortality attributable to MDR Acinetobacter HAIs. We generated estimates of the cost per HAI using 3 methods: (1) overall cost estimates, (2) multiplying LOS estimates by a cost per inpatient-day ($4,350) from the payer perspective, and (3) multiplying LOS estimates by a cost per inpatient-day from the hospital ($2,030) perspective. We deflated our estimates for time-dependent bias using an adjustment factor derived from studies that estimated attributable LOS using both time-fixed methods and either multistate models (70.4% decrease) or matching patients with and without HAIs using the timing of infection (47.4% decrease). Finally, we used the incidence rate of MDR Acinetobacter HAIs to generate cumulative incidence, cost, and mortality associated with these infections.
Our estimates of the cost per infection were $129,917 (method 1), $72,025 (method 2), and $33,510 (method 3). The pooled relative risk of mortality was 4.51 (95% CI, 1.10–32.65), which yielded a mortality rate of 10.6% (95% CI, 2.5%–29.4%). With an incidence rate of 0.141 (95% CI, 0.136–0.161) per 1,000 patient-days at risk, we estimated an annual cumulative incidence of 12,524 (95% CI, 11,509–13,625) in the United States.
The estimates presented here are relevant to understanding the expenditures and lives that could be saved by preventing MDR Acinetobacter HAIs.
Estimates of the excess length of stay (LOS) attributable to healthcare-associated infections (HAIs) in which total LOS of patients with and without HAIs are biased because of failure to account for the timing of infection. Alternate methods that appropriately treat HAI as a time-varying exposure are multistate models and cohort studies, which match regarding the time of infection. We examined the magnitude of this time-dependent bias in published studies that compared different methodological approaches.
We conducted a systematic review of the published literature to identify studies that report attributable LOS estimates using both total LOS (time-fixed) methods and either multistate models or matching patients with and without HAIs using the timing of infection.
Of the 7 studies that compared time-fixed methods to multistate models, conventional methods resulted in estimates of the LOS to HAIs that were, on average, 9.4 days longer or 238% greater than those generated using multistate models. Of the 5 studies that compared time-fixed methods to matching on timing of infection, conventional methods resulted in estimates of the LOS to HAIs that were, on average, 12.6 days longer or 139% greater than those generated by matching on timing of infection.
Our results suggest that estimates of the attributable LOS due to HAIs depend heavily on the methods used to generate those estimates. Overestimation of this effect can lead to incorrect assumptions of the likely cost savings from HAI prevention measures.
Infect. Control Hosp. Epidemiol. 2015;36(9):1089–1094
Standard estimates of the impact of Clostridium difficile infections (CDI) on inpatient lengths of stay (LOS) may overstate inpatient care costs attributable to CDI. In this study, we used multistate modeling (MSM) of CDI timing to reduce bias in estimates of excess LOS.
A retrospective cohort study of all hospitalizations at any of 120 acute care facilities within the US Department of Veterans Affairs (VA) between 2005 and 2012 was conducted. We estimated the excess LOS attributable to CDI using an MSM to address time-dependent bias. Bootstrapping was used to generate 95% confidence intervals (CI). These estimates were compared to unadjusted differences in mean LOS for hospitalizations with and without CDI.
During the study period, there were 3.96 million hospitalizations and 43,540 CDIs. A comparison of unadjusted means suggested an excess LOS of 14.0 days (19.4 vs 5.4 days). In contrast, the MSM estimated an attributable LOS of only 2.27 days (95% CI, 2.14–2.40). The excess LOS for mild-to-moderate CDI was 0.75 days (95% CI, 0.59–0.89), and for severe CDI, it was 4.11 days (95% CI, 3.90–4.32). Substantial variation across the Veteran Integrated Services Networks (VISN) was observed.
CDI significantly contributes to LOS, but the magnitude of its estimated impact is smaller when methods are used that account for the time-varying nature of infection. The greatest impact on LOS occurred among patients with severe CDI. Significant geographic variability was observed. MSM is a useful tool for obtaining more accurate estimates of the inpatient care costs of CDI.
Infect. Control Hosp. Epidemiol. 2015;36(9):1024–1030
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