Infection Control & Hospital Epidemiology
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Fig. 2. Stratified hazard ratios and rates of hospitalization within 30 days after Clostridium difficile infection (CDI) or control index date. The total number of patient included in the hospitalization analyses was 1,475,045 (158,558 CDI case patients and 1,316,487 control patients) after excluding 18,396 persons who died during the index hospitalization. The bars represent the hospitalization rates in control patients (open bars) and CDI case patients (grey bars). Hazard ratio and 95% confidence interval. The null hazard ratio of 1.0 is indicated by the horizontal dashed line.
makes clinical sense because patients at very high risk of CDI also have very high underlying severity of illness, with 60% 1-year mortality among the control uninfected patient population in the highest stratum. In contrast, patients in the lowest baseline CDI stratum had a 3-fold increased risk of 1-year all-cause mortality if they developed CDI. The stratified analysis demonstrates that the increased risk of mortality associated with CDI is not uniform in all elderly persons. In matched-pairs analysis, the attributable risk of 30-day LTCF
transfer due to CDI was 2.7%, and the attributable risk of 30-day SNF transfer due to CDI was much higher at 15.8%. In contrast to prior studies, we developed algorithms to distinguish long-term care residence (ie, nursing home) from short-term care stays to determine the impact of CDI on these distinct outcomes. SNF stays (median, 29 days), which reflect acute-care events requiring additional medical care before patients can return home, are reimbursed by Medicare for the purpose of rehabilitation fol- lowing a hospitalization.27 In contrast, LTCF implies continual residence with no transition back to the community. The increased risk of 30-day SNF admission is suggestive of acute CDI-attributable morbidity and is further supported by the increased risk of 30- and 90-day hospitalizations in CDI patients. The increased risk of LTCF transfer suggests that CDI also con- tributes to chronic morbidity from which patients are unable to fully recover. This increased risk of transition to a LTCF has additional implications in terms of quality of life and economics; these costs are largely borne out of pocket or by the Medicaid program. The reduced impact of effect modification on these outcomes suggests that CDI-attributable morbidity impacts patients regardless of their underlying CDI risk. The pooled CDI attributable mortality of 10.9% we calculated using propensity score matched pairs is similar to the results
reported by Nanwa et al28 in a Canadian population. In that study, the attributable risk of mortality due to community-onset CDI was 13% at 1 year, although they did not report mortality specifically in the elderly. In contrast, Kuntz et al11 reported much lower attributable mortality risk of 4% due to nonrecurrent CDI in adult Kaiser Health Plan members. One possible explanation for the lower CDI mortality risk in the Kuntz et al study was the requirement of a negative CDI test in control patients, thus selecting for control patients suspected of having CDI with likely higher underlying severity of illness than a nontested group. Our results also differ from those of Shorr et al9 in theMedicare
elderly population, in which they reported higher attributable mortality due to CDI of 10% at 30 days and 19% at 1 year.9 Although Shorr et al also used propensity scores and matched pairs, they included fewer variables in their model and less stringent methods for matching than we did in this study. Because we were able to match only 73% of CDI cases to controls (vs 99% by Shorr), our analysis consisted of patients likely more similar in baseline characteristics, resulting in lower attributable risk than that reported by Shorr et al. The limitations of this study include use of administrative
data, which lack clinical detail concerning some CDI risk factors (eg, antibiotic utilization), CDI verification, and medications used to treat CDI in the hospital. Previously, we found the CDI ICD-9- CM diagnosis code reported by hospitals to have a sensitivity of 78% and a specificity of 99.7% compared to C. difficile toxin assay results.29 Although identification of CDI using claims data is imperfect, the impact on our findings should be minimal because the net effect of this misclassification results in bias toward the null hypothesis. The use of older Medicare data is also a limita- tion, and our results should be confirmed with more recent data in which the incidence of CDI is lower. Despite the imperfection
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