Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-05T05:11:46.708Z Has data issue: false hasContentIssue false
  • English
  • Français

Clostridium difficile infection increases acute and chronic morbidity and mortality

Published online by Cambridge University Press:  09 November 2018

Margaret A. Olsen ,
Dustin Stwalley ,
Clarisse Demont  and
Erik R. Dubberke
Margaret A. Olsen*
Affiliation:
Department of Medicine, Washington University School of Medicine, St Louis, Missouri Department of Surgery, Washington University School of Medicine, St Louis, Missouri
Dustin Stwalley
Affiliation:
Department of Medicine, Washington University School of Medicine, St Louis, Missouri
Clarisse Demont
Affiliation:
Sanofi Pasteur, Lyon, France
Erik R. Dubberke*
Affiliation:
Department of Medicine, Washington University School of Medicine, St Louis, Missouri
*
Authors for correspondence: Margaret A. Olsen, PhD, MPH, Division of Infectious Diseases, Campus Box 8051, Washington University School of Medicine, 4523 Clayton Ave, St Louis, MO 63110. E-mail: [email protected] or Erik R. Dubberke, MD, MSPH, Division of Infectious Diseases, Campus Box 8051, Washington University School of Medicine, 4523 Clayton Ave, St Louis, MO 63110. E-mail: [email protected]
Authors for correspondence: Margaret A. Olsen, PhD, MPH, Division of Infectious Diseases, Campus Box 8051, Washington University School of Medicine, 4523 Clayton Ave, St Louis, MO 63110. E-mail: [email protected] or Erik R. Dubberke, MD, MSPH, Division of Infectious Diseases, Campus Box 8051, Washington University School of Medicine, 4523 Clayton Ave, St Louis, MO 63110. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective

In this study, we aimed to quantify short- and long-term outcomes of Clostridium difficile infection (CDI) in the elderly, including all-cause mortality, transfer to a facility, and hospitalizations.

Design

Retrospective study using 2011 Medicare claims data, including all elderly persons coded for CDI and a sample of uninfected persons. Analysis of propensity score-matched pairs and the entire population stratified by the propensity score was used to determine the risk of all-cause mortality, new transfer to a long-term care facility (LTCF), and short-term skilled nursing facility (SNF), and subsequent hospitalizations within 30, 90, and 365 days.

Results

The claims records of 174,903 patients coded for CDI were compared with those of 1,318,538 control patients. CDI was associated with increased risk of death (odds ratio [OR], 1.77; 95% confidence interval [CI], 1.74–1.81; attributable mortality, 10.9%), new LTCF transfer (OR, 1.74; 95% CI, 1.67–1.82), and new SNF transfer (OR, 2.52; 95% CI, 2.46–2.58) within 30 days in matched-pairs analyses. In a stratified analysis, CDI was associated with greatest risk of 30-day all-cause mortality in persons with lowest baseline probability of CDI (hazard ratio [HR], 3.04; 95% CI, 2.83–3.26); the risk progressively decreased as the baseline probability of CDI increased. CDI was also associated with increased risk of subsequent 30-day, 90-day, and 1-year hospitalization.

Conclusions

CDI was associated with increased risk of short- and long-term adverse outcomes, including transfer to short- and long-term care facilities, hospitalization, and all-cause mortality. The magnitude of mortality risk varied depending on baseline probability of CDI, suggesting that even lower-risk patients may benefit from interventions to prevent CDI.

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 40 , Issue 1 , January 2019 , pp. 65 - 71
Copyright
© 2018 by The Society for Healthcare Epidemiology of America. All rights reserved. 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

PREVIOUS PRESENTATION: The preliminary findings of this study were presented at the European Congress of Clinical Microbiology and Infectious Diseases (ECCMID) conference on April 10, 2016 in Amsterdam, Netherlands.

Cite this article: Olsen MA, et al. (2019). Clostridium difficile infection increases acute and chronic morbidity and mortality. Infection Control & Hospital Epidemiology 2019, 40, 65–71. doi: 10.1017/ice.2018.280

References

1. Hall, AJ, Curns, AT, McDonald, LC, Parashar, UD, Lopman, BA. The roles of Clostridium difficile and norovirus among gastroenteritis-associated deaths in the United States, 1999–2007. Clin Infect Dis 2012;55:216–223.Google Scholar
2. Lessa, FC, Mu, Y, Bamberg, WM, et al. Burden of Clostridium difficile infection in the United States. N Engl J Med 2015;372:825–834.Google Scholar
3. Magill, SS, Edwards, JR, Bamberg, W, et al. Multistate point-prevalence survey of health care-associated infections. N Engl J Med 2014;370:1198–1208.Google Scholar
4. Kwon, JH, Olsen, MA, Dubberke, ER. The morbidity, mortality, and costs associated with Clostridium difficile infection. Infect Dis Clin North Am 2015;29:123–134.Google Scholar
5. Wiegand, PN, Nathwani, D, Wilcox, MH, Stephens, J, Shelbaya, A, Haider, S. Clinical and economic burden of Clostridium difficile infection in Europe: a systematic review of healthcare-facility–acquired infection. J Hosp Infect 2012;81:1–14.Google Scholar
6. Abou Chakra, CN, McGeer, A, Labbe, AC, et al. Factors associated with complications of Clostridium difficile infection in a multicenter prospective cohort. Clin Infect Dis 2015;61:1781–1788.Google Scholar
7. Abou Chakra, CN, Pepin, J, Sirard, S, Valiquette, L. Risk factors for recurrence, complications and mortality in Clostridium difficile infection: a systematic review. PLoS One. 2014;9:e98400.Google Scholar
8. Drozd, EM, Inocencio, TJ, Braithwaite, S, et al. Mortality, hospital costs, payments, and readmissions associated with Clostridium difficile infection among Medicare beneficiaries. Infect Dis Clin Pract (Baltimore) 2015;23:318–323.Google Scholar
9. Shorr, AF, Zilberberg, MD, Wang, L, Baser, O, Yu, H. Mortality and costs in clostridium difficile infection among the elderly in the United States. Infect Control Hosp Epidemiol 2016;37:1331–1336.Google Scholar
10. Rothman, KJ, Lash, TL. Modern Epidemiology, 3d ed. Philadelphia, PA: Lippincott Williams & Wilkins; 2008.Google Scholar
11. Kuntz, JL, Baker, JM, Kipnis, P, et al. Utilization of health services among adults with recurrent Clostridium difficile infection: a 12-year population-based study. Infect Control Hosp Epidemiol 2017;38:45–52.Google Scholar
12. Nanwa, N, Kwong, JC, Krahn, M, et al. The economic burden of hospital-acquired Clostridium difficile infection: a population-based matched cohort study. Infect Control Hosp Epidemiol 2016;37:1068–1078.Google Scholar
13. Magee, G, Strauss, ME, Thomas, SM, Brown, H, Baumer, D, Broderick, KC. Impact of Clostridium difficile-associated diarrhea on acute-care length of stay, hospital costs, and readmission: a multicenter retrospective study of inpatients, 2009–2011. Am J Infect Control 2015;43:1148–1153.Google Scholar
14. Barbut, F, Bouee, S, Longepierre, L, Goldberg, M, Bensoussan, C, Levy-Bachelot, L. Excess mortality between 2007 and 2014 among patients with Clostridium difficile infection: a French health insurance database analysis. J Hosp Infect 2018;98:21–28.Google Scholar
15. Khanna, S, Gupta, A, Baddour, LM, Pardi, DS. Epidemiology, outcomes, and predictors of mortality in hospitalized adults with Clostridium difficile infection. Intern Emerg Med 2016;11:657–665.Google Scholar
16. Center RDA. Chronic Conditions Data Warehouse website. https://www.ccwdata.org/web/guest/home. Published 2017. Accessed July 2, 2017.Google Scholar
17. Intrator, O, Hiris, J, Berg, K, Miller, SC, Mor, V. The residential history file: studying nursing home residents’ long-term care histories(*). Health Serv Res 2011;46:120–137.Google Scholar
18. Olsen, MA, Young-Xu, Y, Stwalley, D, et al. The burden of Clostridium difficile infection: estimates of the incidence of CDI from US administrative databases. BMC Infect Dis 2016;16:177.Google Scholar
19. Dubberke, ER, Olsen, MA, Stwalley, D, et al. Identification of Medicare recipients at highest risk for Clostridium difficile infection in the US by population attributable risk analysis. PLoS One 2016;11:e0146822.Google Scholar
20. Goodwin, JS, Li, S, Zhou, J, Graham, JE, Karmarkar, A, Ottenbacher, K. Comparison of methods to identify long-term care nursing home residence with administrative data. BMC Health Serv Res 2017;17:376.Google Scholar
21. Klabunde, CN, Potosky, AL, Legler, JM, Warren, JL. Development of a comorbidity index using physician claims data. J Clin Epidemiol 2000;53:1258–1267.Google Scholar
22. Austin, PC. Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies. Pharm Stat 2011;10:150–161.Google Scholar
23. Coca-Perraillon, M. Local and global propensity score matching. SAS Global Forum website. http://www2.sas.com/proceedings/forum2007/185-2007.pdf. Published 2007. Accessed June 8, 2015.Google Scholar
24. Austin, PC. Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Stat Med 2009;28:3083–3107.Google Scholar
25. Yang, D, Dalton, J. A unified approach to measuring the effect size between two groups using SAS. SAS Global Forum website. http://www.lerner.ccf.org/qhs/software/lib/stddiff.pdf. Published 2012. Accessed June 8, 2015.Google Scholar
26. Austin, PC. The use of propensity score methods with survival or time-to-event outcomes: eporting measures of effect similar to those used in randomized experiments. Stat Med 2014;33:1242–1258.Google Scholar
27. Bowblis, JR, Horowitz, J, Brunt, CS. Ownership status and length of stay in skilled nursing facilities: Does endogeneity matter? J Appl Gerontol 2016;35:303–320.Google Scholar
28. Nanwa, N, Sander, B, Krahn, M, et al. A population-based matched cohort study examining the mortality and costs of patients with community-onset Clostridium difficile infection identified using emergency department visits and hospital admissions. PLoS One 2017;12:e0172410.Google Scholar
29. Dubberke, ER, Butler, AM, Yokoe, DS, et al. Multicenter study of surveillance for hospital-onset Clostridium difficile infection by the use of ICD-9-CM diagnosis codes. Infect Control Hosp Epidemiol 2010;31:262–268.Google Scholar
Supplementary material: File

Olsen et al. supplementary material

Appendix

Download Olsen et al. supplementary material(File)
File 169.6 KB