Journal List > J Korean Med Sci > v.35(47) > 1146245

Kim, Kim, and Pai: Association between Antibiotic Consumption and Incidence of Clostridioides difficile Infection in a Hospital

Abstract

Previous exposure to antimicrobials is a major risk factor for Clostridioides difficile infection (CDI). Antibiotic prescription and C. difficile toxin assay records of patients admitted to a tertiary hospital in Korea from 2009 to 2013 were collected to investigate the association between antibiotic consumption and CDI incidence. A Spearman's correlation analysis between CDI incidence (positive result of toxin assay/10,000 admissions) and antibiotic consumption (defined daily dose/1,000 patient-days) was performed on a monthly basis. Using the matched month approach, we found a significant correlation between CDI rate and moxifloxacin consumption (Spearman's r = 0.351, P < 0.001). Furthermore, using the one-month delay approach, we found that the consumption of clindamycin (Spearman's r = 0.272, P = 0.037) and moxifloxacin (Spearman's r = 0.297, P = 0.022) was significantly correlated with CDI incidence. Extended-spectrum cephalosporins did not have any effect on CDI incidence.

Graphical Abstract

jkms-35-e407-abf001.jpg

Clostridioides difficile infection (CDI) is one of the most common hospital-acquired infections, with symptoms ranging from mild diarrhea to life-threatening pseudomembranous colitis.1 In the US, approximately 223,900 CDI cases occur and more than 12,500 patients with CDI die annually.2 Antibiotics have a significant and long-lasting effect on the intestinal microbiota and reduce colonization resistance against pathogens, including C. difficile.3 One of the most important predisposing factors for CDI is exposure to high-risk antimicrobial agents including fluoroquinolone (FQ), extended-spectrum cephalosporins (ESC), and clindamycin.14 In addition, the use of any antibiotic has been associated with CDI development, and even short-term antibiotic use may increase the risk of CDI.56 Patients are prone to developing CDI three months after cessation of antibiotic therapy, and the risk is the highest during the first month after stopping antibiotic use.7
Domestic data on high-risk antibiotics for treating CDI in Korean hospitals are limited.8 Because any antibiotic can predispose an individual to CDI, it is important to identify high-risk antimicrobial agents in Korean hospitals to develop a proper strategy to reduce CDI.4 To this end, we conducted the present study to define the association between antibiotic consumption and CDI incidence at the hospital level.
A single-center retrospective study was conducted at a tertiary-care hospital with 859 beds in Korea. Positive results for C. difficile toxin genes (tcdA or tcd B, cdtA, or cdt B) using multiplex PCR, positive results for C. difficile toxin A & B assay (VIDAS C. difficile Toxin A & B; Biomerieux SA, Marcy I’Etoile, France), antibiotic prescriptions, patient days, and number of admissions were collected from inpatients between 2009 and 2013. Antimicrobial stewardship programs remained largely unchanged during the study period. The most prominent strategy for antimicrobial stewardship programs in the study hospital was restrictive measures for designated antimicrobials.
We defined CDI when a patient showed positive results for C. difficile toxin genes and/or C. difficile toxin A & B assay while having unformed stools more than three times a day on consecutive days.5 We included multiple CDI episodes from one patient, but only one CDI episode was included per hospitalization. In addition, among patients with CDI, we included only hospital-acquired CDI (HA-CDI) for the analysis. Patients who developed diarrhea at least 72 hours after hospitalization or within 2 months from the last discharge and did not reside in a long-term care facility were diagnosed with HA-CDI.9 CDI incidence was defined as the number of cases per 10,000 admissions.
Prescription records for antibiotic classes such as clindamycin, FQ, beta-lactam/beta-lactamase inhibitor (BL/BLI), 1st generation cephalosporin (1st CEP), 2nd generation cephalosporin (2nd CEP), ESC, penicillin, macrolide, trimethoprim/sulfamethoxazole (SXT), glycopeptide, rifampicin, aminoglycoside, and carbapenem were collected. In addition, we collected data for levofloxacin, moxifloxacin, and piperacillin/tazobactam (TZP) for a detailed evaluation of the effect of FQ and BL/BLI. Only systemic agents with oral or parenteral administration routes were included, while topical agents were excluded. ESC comprised 3rd and 4th generation cephalosporins. The amount of antibiotic consumption was calculated by defined daily dose (DDD) using the World Health Organization's Anatomical Therapeutic Chemical classification,10 and this was then standardized for 1,000 patient-days.
We classified clindamycin, FQ, BL/BLI, 1st CEP, 2nd CEP, ESC, penicillin, macrolide, and SXT as antibiotics frequently associated with CDI and others as antibiotics rarely associated with CDI.4 Spearman's rank correlation analysis was used to describe the relationship between antibiotic consumption and HA-CDI incidence. Matched-month and one-month delay approaches were applied to evaluate both the immediate and delayed effects of antibiotics on CDI occurrence, respectively. Statistical significance was defined as P < 0.05. All analyses were performed using SPSS 24.0 (IBM Corporation, Armonk, NY, USA).
HA-CDI was diagnosed at 45.33-58.10 cases per 10,000 admissions at the hospital during the study period. Table 1 shows the correlation between HA-CDI incidence and antibiotic consumption. When analysis was performed using the matched-month approach, moxifloxacin consumption (r = 0.351, P < 0.001) displayed a significant positive correlation with HA-CDI incidence. Contrarily, levofloxacin consumption (r = −0.365, P = 0.004) was negatively correlated with HA-CDI incidence; BL/BLI consumption (r = −0.250, P = 0.054) displayed a negative correlation with HA-CDI incidence with marginal significance. Other antibiotics known to be frequently associated with CDI, such as clindamycin, ESC, penicillin, macrolide, and SXT, did not have any effect on HA-CDI incidence. None of the antibiotics known to be rarely associated with CDI showed a significant correlation with HA-CDI incidence.
Using the one-month delay approach, we found that clindamycin (r = 0.272, P = 0.037) and moxifloxacin consumption (r = 0.297, P = 0.022) displayed significant positive correlation with HA-CDI incidence. Levofloxacin consumption presented a negative correlation with HA-CDI incidence (r = −0.265, P = 0.043). None of the other antibiotics presented any significant effect on HA-CDI incidence in the one-month delay analysis (Fig. 1).
Although previous studies in other countries have reported the association of FQ, ESC, and carbapenem consumption with CDI incidence, we found that clindamycin and moxifloxacin consumption affected CDI incidence in the study hospital.1112 Possibly, these antibiotics imposed strong selective pressures on C. difficile, considering the high rates of resistance of large-cluster isolates to clindamycin and moxifloxacin reported in our previous study.8 The development of C. difficile resistance appears to play an important role in CDI due to the presence of strains with increased virulence.1314 A strain of clindamycin-resistant C. difficile was implicated in a large outbreak in the early 1990s, and FQ-resistant hypervirulent NAP1/BI/O27 was an important factor in outbreaks in the 2000s.1314 Our study showed that levofloxacin consumption had a negative correlation with CDI incidence. One plausible reason for this finding might be a trade-off phenomenon between levofloxacin and moxifloxacin. Many physicians may consider them as having the same spectrum and effects. Similarly, the negative correlation between BL/BLI consumption and CDI incidence might be attributable to the trade-off effect between other risky antibiotics such as clindamycin and moxifloxacin throughout the hospital. Further studies are necessary to clarify the effect of levofloxacin and BL/BLI on the incidence of CDI.
Several studies have reported that HA-CDI incidence can be successfully controlled by restricting the use of these high-risk antibiotics.151617 Given that restricting high-risk antimicrobial agents has been more effective in reducing CDI incidence than other measures, such as improvements in hospital infection control, antimicrobial stewardship for high-risk agents has been considered to be a central component of CDI control.616 Unfortunately, very few Korean hospitals perform monitoring and intervention for high-risk antimicrobials for CDI.18 Therefore, it is necessary to implement antimicrobial stewardship program interventions targeting high-risk antibiotics for CDI in Korean hospitals.
There are some potential limitations to our study. First, we evaluated the correlation between antibiotic use and CDI incidence at the hospital level; therefore, the results cannot be extrapolated to the patient level. In addition to individual antibiotic usage patterns, other important risk factors for individuals, such as age, underlying comorbidities, and chemotherapeutic agent use, were not analyzed. Second, this study was performed in a single center; thus, the findings cannot be generalized. Third, antibiotic consumption was measured by DDD instead of days of therapy. The antibiotic use of pediatric patients or patients with renal impairment might not be calculated correctly.19 Finally, because CDI was diagnosed by stool culture or toxin assay only when requested, CDI incidence may have been underestimated.
In conclusion, CDI incidence was positively correlated with clindamycin and moxifloxacin use. It is necessary to implement proper antimicrobial stewardship programs targeting high-risk antibiotics for CDI in Korean hospitals.

Ethics statement

The study protocol was approved by the Institutional Review Boards of the Hanyang University Hospital (2015-01-015), and the requirement for written informed consent from patients was waived due to the retrospective nature of the study and its impracticability.

Notes

Funding: This work was supported by the research fund of BCWorld Pharm. Co., Ltd. (2019).

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

  • Conceptualization: Pai H.

  • Data curation: Kim B.

  • Formal analysis: Kim B.

  • Investigation: Kim B, Kim J, Pai H.

  • Methodology: Kim B, Kim J, Pai H.

  • Resources: Kim B, Kim J, Pai H.

  • Supervision: Kim B, Kim J, Pai H.

  • Writing - original draft: Kim B.

  • Writing - review & editing: Kim B, Pai H.

References

1. Freeman J, Bauer MP, Baines SD, Corver J, Fawley WN, Goorhuis B, et al. The changing epidemiology of Clostridium difficile infections. Clin Microbiol Rev. 2010; 23(3):529–549. PMID: 20610822.
crossref
2. Centers for Disease Control and Prevention. Antibiotic resistance threats in the United States. Updated 2020. Accessed May 23, 2020. https://www.multivu.com/players/English/8627551-cdc-antibiotic-resistance-threat-report-2019.
3. Brown K, Valenta K, Fisman D, Simor A, Daneman N. Hospital ward antibiotic prescribing and the risks of Clostridium difficile infection. JAMA Intern Med. 2015; 175(4):626–633. PMID: 25705994.
4. Leffler DA, Lamont JT, Lamont JT. Clostridium difficile infection. N Engl J Med. 2015; 372(16):1539–1548. PMID: 25875259.
crossref
5. McDonald LC, Gerding DN, Johnson S, Bakken JS, Carroll KC, Coffin SE, et al. Clinical practice guidelines for Clostridium difficile infection in adults and children: 2017 update by the Infectious Diseases Society of America (IDSA) and Society for Healthcare Epidemiology of America (SHEA). Clin Infect Dis. 2018; 66(7):e1–e48. PMID: 29462280.
crossref
6. Owens RC Jr, Donskey CJ, Gaynes RP, Loo VG, Muto CA. Antimicrobial-associated risk factors for Clostridium difficile infection. Clin Infect Dis. 2008; 46(s1):Suppl 1. S19–S31. PMID: 18177218.
7. Hensgens MP, Goorhuis A, Dekkers OM, Kuijper EJ. Time interval of increased risk for Clostridium difficile infection after exposure to antibiotics. J Antimicrob Chemother. 2012; 67(3):742–748. PMID: 22146873.
crossref
8. Kim J, Kang JO, Kim H, Seo MR, Choi TY, Pai H, et al. Epidemiology of Clostridium difficile infections in a tertiary-care hospital in Korea. Clin Microbiol Infect. 2013; 19(6):521–527. PMID: 22712697.
crossref
9. McDonald LC, Coignard B, Dubberke E, Song X, Horan T, Kutty PK, et al. Recommendations for surveillance of Clostridium difficile-associated disease. Infect Control Hosp Epidemiol. 2007; 28(2):140–145. PMID: 17265394.
crossref
10. World Health Organization. Definition and general considerations of defined daily dose (DDD). Updated 2020. Accessed April 7, 2020. http://www.whocc.no/ddd/definition_and_general_considera/.
11. Kazakova SV, Baggs J, McDonald LC, Yi SH, Hatfield KM, Guh A, et al. Association between antibiotic use and hospital-onset Clostridioides difficile infection in US acute care hospitals, 2006–2012: an ecologic analysis. Clin Infect Dis. 2020; 70(1):11–18. PMID: 30820545.
crossref
12. Pereira JB, Farragher TM, Tully MP, Jonathan Cooke J. Association between Clostridium difficile infection and antimicrobial usage in a large group of English hospitals. Br J Clin Pharmacol. 2014; 77(5):896–903. PMID: 24868578.
13. Johnson S, Samore MH, Farrow KA, Killgore GE, Tenover FC, Lyras D, et al. Epidemics of diarrhea caused by a clindamycin-resistant strain of Clostridium difficile in four hospitals. N Engl J Med. 1999; 341(22):1645–1651. PMID: 10572152.
14. Pépin J, Saheb N, Coulombe MA, Alary ME, Corriveau MP, Authier S, et al. Emergence of fluoroquinolones as the predominant risk factor for Clostridium difficile-associated diarrhea: a cohort study during an epidemic in Quebec. Clin Infect Dis. 2005; 41(9):1254–1260. PMID: 16206099.
15. Pear SM, Williamson TH, Bettin KM, Gerding DN, Galgiani JN. Decrease in nosocomial Clostridium difficile-associated diarrhea by restricting clindamycin use. Ann Intern Med. 1994; 120(4):272–277. PMID: 8080497.
crossref
16. Dingle KE, Didelot X, Quan TP, Eyre DW, Stoesser N, Golubchik T, et al. Effects of control interventions on Clostridium difficile infection in England: an observational study. Lancet Infect Dis. 2017; 17(4):411–421. PMID: 28130063.
17. Aldeyab MA, Devine MJ, Flanagan P, Mannion M, Craig A, Scott MG, et al. Multihospital outbreak of Clostridium difficile ribotype 027 infection: epidemiology and analysis of control measures. Infect Control Hosp Epidemiol. 2011; 32(3):210–219. PMID: 21460505.
18. Kim B, Lee MJ, Moon SM, Park SY, Song KH, Lee H, et al. Current status of antimicrobial stewardship programmes in Korean hospitals: results of a 2018 nationwide survey. J Hosp Infect. 2020; 104(2):172–180. PMID: 31513880.
crossref
19. Sinnott SJ, Polinski JM, Byrne S, Gagne JJ. Measuring drug exposure: concordance between defined daily dose and days' supply depended on drug class. J Clin Epidemiol. 2016; 69:107–113. PMID: 26146090.
Fig. 1

Spearman's correlation and consumption-over-time plots by one-month delay analysis, (A) for lincosamide consumption and CDI incidence (Spearman's r = 0.272, P = 0.037), (B) for moxifloxacin consumption and CDI incidence (Spearman's r = 0.297, P = 0.022), and (C) for extended-spectrum cephalosporin consumption and CDI incidence (Spearman's r = 0.075, P = 0.573).

CDI = Clostridioides difficile infection, DDD = defined daily dose.
jkms-35-e407-g001
Table 1

Correlation between hospital-acquired Clostridioides difficile infection incidence and antibiotic consumption

jkms-35-e407-i001
Variables Year Matched montha One-month delayb
2009 2010 2011 2012 2013 Spearman's r P value Spearman's r P value
HA-CDI/104 admissions 54.36 58.10 51.94 57.04 45.33 - - - -
Antibiotics, DDD/103 patient-days
Frequently associated with CDI
Clindamycin 17.08 20.08 16.62 16.31 13.61 0.220 0.091 0.272 0.037
Fluoroquinolone 119.17 109.11 124.49 122.77 129.66 −0.070 0.597 −0.009 0.944
Moxifloxacin 20.24 21.11 25.09 15.54 15.77 0.351 < 0.001 0.297 0.022
Levofloxacin 48.56 38.02 45.37 41.24 52.70 −0.365 0.004 −0.265 0.043
BL/BLI 86.70 80.65 84.97 88.43 104.86 −0.250 0.054 −0.176 0.182
Piperacillin/tazobactam 23.18 25.87 30.31 39.65 42.11 −0.146 0.266 −0.193 0.144
1st generation cephalosporin 140.20 136.46 134.39 130.17 112.59 −0.010 0.939 −0.025 0.851
2nd generation cephalosporin 94.70 91.11 86.70 90.67 94.11 −0.176 0.177 −0.067 0.617
Extended-spectrum cephalosporinc 187.63 192.84 176.90 180.30 184.20 0.041 0.758 0.075 0.573
Penicillin 7.56 15.34 20.87 22.88 22.32 −0.127 0.335 −0.231 0.078
Macrolide 49.11 29.68 51.55 45.97 39.22 −0.040 0.759 −0.016 0.904
Trimethoprim/sulfamethoxazole 23.40 40.54 34.56 32.53 19.78 0.175 0.182 0.125 0.346
Total 725.53 715.82 731.12 730.03 720.36 −0.077 0.559 −0.085 0.520
Rarely associated with CDI
Glycopeptide 15.81 21.24 18.27 21.05 22.66 0.100 0.448 −0.059 0.660
Metronidazole 44.15 44.82 48.21 46.55 43.29 0.102 0.437 −0.136 0.305
Rifampicin 27.94 33.12 31.47 30.53 31.79 0.218 0.094 0.154 0.246
Aminoglycoside 54.39 38.13 32.38 30.45 25.04 −0.017 0.898 0.073 0.581
Carbapenem 9.25 12.02 10.31 10.96 13.91 −0.112 0.392 −0.203 0.124
Total 151.54 149.33 140.65 139.55 136.68 0.157 0.230 0.062 0.641
aSpearman's correlation method between antibiotic consumption and HA-CDI incidence on a monthly basis. The incidence of HA-CDI in a certain month was paired with antibiotic consumption in the same month; bSpearmans correlation method between antibiotic consumption and HA-CDI incidence on a monthly basis. The incidence of HA-CDI in a certain month was paired with antibiotic consumption in the previous month; cComprises 3rd generation and 4th generation cephalosporins.
HA-CDI = hospital-acquired Clostridioides difficile infection, DDD = defined daily dose, BL/BLIs = beta-lactam/beta-lactamase inhibitor.
TOOLS
Similar articles