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Risk factors for Clostridium difficile infection in pediatric inpatients: A meta-analysis and systematic review

Published online by Cambridge University Press:  07 March 2019

Scott Anjewierden
Affiliation:
Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
Zheyi Han
Affiliation:
Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
Charles B. Foster
Affiliation:
Center for Pediatric Infectious Diseases, Cleveland Clinic Children’s, Cleveland, Ohio, USA
Chaitanya Pant
Affiliation:
Division of Gastroenterology, Hepatology and Motility, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas, USA
Abhishek Deshpande*
Affiliation:
Medicine Institute Center for Value Based Care Research, Cleveland Clinic, Cleveland, Ohio, USA Department of Infectious Diseases, Cleveland Clinic, Cleveland, Ohio, USA
*
Author for correspondence: Abhishek Deshpande, Email: abhishekdp@gmail.com
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Abstract

Objective:

To summarize risk factors for Clostridioides (formerly Clostridium) difficile infection (CDI) in hospitalized pediatric patients as determined by previous observational studies.

Design:

Meta-analysis and systematic review.

Patients:

Studies evaluating risk factors for CDI in pediatric inpatients were eligible for inclusion.

Method:

We systematically searched MEDLINE, Web of Science, Scopus, and EMBASE for subject headings and text words related to CDI and pediatrics from 1975 to 2017. Two of the investigators independently screened studies, extracted and compiled data, assessed study quality, and performed the meta-analysis.

Results:

Of the 2,033 articles screened, 14 studies reporting 10,531,669 children met the inclusion criteria. Prior antibiotic exposure (odds ratio [OR], 2.14; 95% confidence interval [CI], 1.31–3.52) and proton pump inhibitor (PPI) use (OR, 1.33; 95% CI, 1.07–1.64) were associated with an increased risk of CDI in children. Subgroup analyses using studies reporting only adjusted results suggested that prior antibiotic exposure is not a significant risk factor for CDI. H2 receptor antagonist (H2RA) use (OR, 1.36; 95% CI, 0.31–5.98) and that female gender (OR, 0.87; 95% CI, 0.74–1.03) did not play a significant role as a risk factor for developing CDI.

Conclusion:

Prior antibiotic exposure appears to be an important risk factor for CDI based on the combined analysis but not significant using adjusted studies. PPI use was associated with an increased risk of CDI. Judicious and appropriate use of antibiotics and PPIs may help reduce the risk of CDI in this vulnerable population.

Type
Original Article
Copyright
© 2019 by The Society for Healthcare Epidemiology of America. All rights reserved. 

Clostridioides (formerly Clostridium) difficile is one of the most frequent causes of hospital-acquired infections in both adult and pediatric patients.Reference Langley, LeBlanc, Hanakowski and Goloubeva1, Reference Magill, Edwards and Bamberg2 The incidence and healthcare burden of C. difficile infection (CDI) in the hospitalized pediatric population has increased in the past 20 years,Reference Nylund, Goudie, Garza, Fairbrother and Cohen3Reference Zilberberg, Tillotson and McDonald6 mostly attributed to the emergence of the new, hypervirulent strain B1/NAP1/027.Reference Toltzis, Kim, Dul, Zoltanski, Smathers and Zaoutis7 Although most children recover without long-term sequelae, CDI in hospitalized children is associated with increased mortality, length of stay, and hospital cost,Reference Sammons, Localio, Xiao, Coffin and Zaoutis5 and it is an independent predictor of subsequent colectomy and discharge to short- or long-term care facility.Reference Gupta, Pardi, Baddour and Khanna8

In adult patients, CDI is associated with discrete risk factors including advanced age, antibiotic exposure, prolonged hospitalization, proton-pump inhibitor use, immunocompromised state, and other medical comorbidities.Reference McDonald, Gerding and Johnson9 In comparison, risk factors for CDI in children are less well-defined. Notably, antibiotic and proton pump inhibitor (PPI) use have only been variably associated with CDI risk in children.Reference Sandora, Fung and Flaherty10Reference Turco, Martinelli and Miele12 Additionally, current understanding of pediatric CDI is further complicated by the fact that up to 70% of infants <1 month and up to 2 years of age are colonized with C. difficile but do not develop clinical illness until 12–24 months of age.Reference McFarland, Brandmarker and Guandalini13 Therefore, closer examination of currently available evidence is needed to better understand the significance and implications of potential risk factors for pediatric CDI. The aim of this meta-analysis and systematic review was to evaluate the association of previously identified risk factors with CDI in hospitalized children.

Methods

All procedures used in this study were consistent with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.Reference Moher, Liberati, Tetzlaff and Altman14

Data sources and searches

Two investigators (S.A. and Z.H.) systematically searched the literature independently using the following predetermined inclusion criteria: (1) observational studies (including case control and cohort) evaluating risk factors for primary CDI, (2) pediatric patients (≤19 years), (3) study population includes >10 pediatric patients, (4) in-patients admitted to a hospital, and (5) studies evaluated >1 CDI risk factor. Studies were excluded if (1) they exclusively studied CDI in children <2 years, in which the role of C. difficile was unclear and testing was not routinely recommended,Reference McDonald, Gerding and Johnson9 and (2) if they exclusively studied CDI patients in an outpatient setting. The following databases were searched from January 1975 to August 2017: MEDLINE (PubMed), EMBASE, Web of Science, and Scopus. The following search terms were used: C. diff infection, Clostridium difficile infection, CDI, Clostridium difficile associated infection, CDAD, pediatric, paediatric, children, infants, adolescents, risk, risk factors, predictor, and marker. We also conducted a modified search from September 2016 to August 2017 including Clostridioides difficile in our search criteria, but we did not find any additional eligible studies (data not shown). The electronic PubMed search strategy is available in the supplemental appendix online.

Study selection and data extraction

A list of retrieved articles that met the inclusion criteria was reviewed by 2 investigators independently (S.A. and Z.H.). These investigators also independently extracted data from the full text of the included studies. The data collected included study design, study population, patient demographics, clinical characteristics, and identified risk factors for CDI. Any disagreement was resolved in consensus with a third investigator (A.D.). Authors were contacted if relevant information was not available for a particular study. The Cohen’s interrater κ statistics for inclusion agreement and data extraction were 0.85 and 0.90 respectively, which indicated excellent interrater agreement.

Quality assessment

The quality of the observational studies (including cohort and case-control) was assessed independently by 2 investigators (S.A. and Z.H.) using the Newcastle-Ottawa Scale (NOS).Reference Wells, Shea and O’Connell15 Studies with NOS scores >7 were considered high-quality studies, and those with NOS scores of 5–7 were considered moderate-quality studies. Any disagreements or discrepancies were resolved by consensus with a third investigator (A.D.). The Cohen’s interrater κ statistic for study quality assessment was 0.90, which indicated excellent interrater agreement.

Data synthesis and analysis

Due to the diversity of risk factors evaluated in studies of C. difficile, we decided a priori that all risk factors reported in ≥3 studies were eligible for inclusion in the meta-analysis.

For all studies, when possible, we extracted the adjusted odds ratios (ORs) and relative risks. When adjusted data were not available, crude odds ratios and relative risks with their 95% confidence intervals (CIs) were calculated from the number of events.

We decided a priori that adjusted data would be used for all meta-analyses with ≥3 studies. When adjusted data were not available for ≥3 studies, we combined the adjusted and unadjusted data. DerSimonian and Laird random-effects models were used for all meta-analyses.Reference DerSimonian and Laird16 The meta-analysis was performed using the inverse variance method to obtain pooled ORs and 95% confidence intervals (CIs). We assumed similarity between the OR and other relative measures, such as relative risk or rate ratios, because of low disease frequency and prevalence of CDI in this population. We evaluated statistical heterogeneity using the Cochran χ2 (Cochran Q) and the I2 statistic. We defined significant heterogeneity as a χ2 <0.10 or an I 2 statistic >66%.Reference Deeks, Higgins, Altman, Higgins and Green17 Moderate heterogeneity was defined as an I2 statistic between 33% and 66%. Low heterogeneity was defined as an I2 statistic <33%.

Assessment of publication bias

To check for publication bias, we generated funnel plots and used Egger’s regression asymmetry test. Where asymmetry was detected, we assessed the potential impact of the publication bias using the Duval and Tweedie nonparametric “trim-and-fill” method.Reference Duval and Tweedie18

We used Review Manager software (RevMan, version 5.3 for Windows, Oxford, UK; The Cochrane Collaboration, 2014) for our statistical analyses.

Results

Study characteristics

The preliminary literature search identified 2,032 publications (Fig. 1). After removing duplicates and screening titles for potentially relevant articles, 127 studies were considered relevant. On further screening of the abstracts of these potentially relevant studies, 56 were selected for full text review. Finally, a total of 14 articles met the full inclusion criteria and were included in the systematic review. The reasons for excluding the remaining 42 articles are listed in Figure 1.

Fig. 1. Flow chart for study inclusion in the systematic review and meta-analysis.

The main characteristics of the included studies are summarized in Supplemental Table 2. The final study population consisted of 10,531,669 children, of which 22,320 patients developed CDI. In analyzing the 14 included studies, 7 were retrospective cohort studies and 6 were retrospective case-control studies, while the remaining study was a prospective cohort study. Six of the studies were conducted in the United States, 2 were conducted in Italy, with a single study was conducted in each of the following countries: Canada, China, Croatia, Japan, Spain, and Turkey. The testing methodology for CDI consisted of a C. difficile toxin assay for 10 studies. Clostridium difficile culture and/or toxin assay for 2 studies and the use of the International Classification of Diseases Ninth Edition (ICD-9) code 008.45 or other billing codes were used in the remaining 3 studies.

Quality assessment

Using the NOS scale, all included studies were identified as moderate or high in quality (Supplemental Table 1 online). Most included studies clearly identified the study population and defined the outcome and outcome assessment. Most studies identified important confounders that were used for adjustment of the association exposures and risk of CDI. We found considerable variation in the selection of available confounding variables for adjustment. A few confounding variables may not have been fully identified and recorded. The most common confounders adjusted were age, gender, and antibiotic exposure. Information on the dose and duration of antibiotic therapy prior to the diagnosis of CDI was limited. Various methods were used to identify antibiotic use, including review of patient medical records, patient prescription records, and ICD-9 codes.

Meta-analyses of risk factors for CDI

Exposure to antibiotics

A total of 7 studies reported data on prior antibiotic exposure (5 unadjusted and 2 adjusted studies). Because <3 studies provided adjusted data, we combined studies reporting the adjusted and unadjusted data. Meta-analysis of the 7 studies demonstrated a significantly increased risk of CDI with prior exposure to any antibiotic class (OR, 2.14; 95% CI, 1.31–3.52; P = .003) (Fig. 2). There was moderate heterogeneity among these studies (I2 = 57%). We also performed subgroup analysis for the adjusted and unadjusted studies. The meta-analysis of the unadjusted studies showed a significantly increased risk of CDI with prior exposure to any antibiotic class (OR, 2.34; 95% CI, 1.27–4.31; P = .006). There was significant heterogeneity among these studies (I2 = 68%). The meta-analysis of the adjusted studies also showed an increased risk of CDI with prior exposure to antibiotics, but the results were not statistically significant (OR, 1.49; 95% CI, 0.66–3.34; P = .34). There was low heterogeneity between the 2 adjusted studies (I2 = 1%). Risk factors for CDI with individual antibiotic subclasses were not reported by >2 studies and were therefore not included in the meta-analysis.

Fig. 2. Forest plot of the association between antibiotic use and CDI. Vertical line corresponds to no difference point between the 2 groups. Squares correspond to risk ratios. Horizontal lines represent the 95% confidence intervals. The diamond indicates the pooled relative risk ratios. Note. df, degrees of freedom; M-H, Mantel-Haenszel.

Gastric acid suppression

We identified 4 studies that reported adjusted data on PPI use as a risk factor for CDI. Meta-analysis of the 4 studies showed increased risk of CDI with PPI use (OR, 1.33; 95% CI, 1.07–1.64; P = .01) (Fig. 3). There was moderate heterogeneity among these studies (I2 = 36%). Adjusted data for the risk of CDI with H2 receptor antagonist (H2RA) use was obtained from 3 studies. Meta-analysis of the 3 studies examining H2RA use also showed increased risk of CDI associated with H2RA use, but the result was not statistically significant (OR, 1.36; 95% CI, 0.31–5.98; P = .68) (Fig. 4). There was significant heterogeneity among these studies (I2 = 68%).

Fig. 3. Forest plot of the association between PPI use and CDI. Vertical line corresponds to no difference point between the 2 groups. Squares correspond to risk ratios. Horizontal lines represent the 95% confidence intervals. The diamond indicates the pooled relative risk ratios. Note. df, degrees of freedom; M-H, Mantel-Haenszel.

Gender

We identified 4 studies that reported adjusted data on gender as a risk factor for CDI. Meta-analysis of the 4 adjusted studies did not show a significantly increased risk of CDI associated with female gender (OR, 0.87; 95% CI, 0.74–1.03; P = .10) (Fig. 5). There was significant heterogeneity among these studies (I2 = 76%).

Fig. 4. Forest plot of the association between H2RA use and CDI. Vertical line corresponds to no difference point between the 2 groups. Squares correspond to risk ratios. Horizontal lines represent the 95% confidence intervals. The diamond indicates the pooled relative risk ratios. Note. df, degrees of freedom; M-H, Mantel-Haenszel.

Fig. 5. Forest plot of the association between gender and CDI. Vertical line corresponds to no difference point between the 2 groups. Squares correspond to risk ratios. Horizontal lines represent the 95% confidence intervals. The diamond indicates the pooled relative risk ratios. Note. df, degrees of freedom; M-H, Mantel-Haenszel.

Other risk factors

Several additional risk factors associated with pediatric CDI were not included in the meta-analysis because they were reported in <3 studies. These risk factors and their corresponding estimated effect sizes have been listed in Supplemental Table 2 (online). Notably, underlying comorbidities that have been previously reported such as inflammatory bowel disease (IBD), solid organ transplant, and malignanciesReference Sandora, Fung and Flaherty10, Reference Kim, Smathers, Prasad, Leckerman, Coffin and Zaoutis19,Reference Pant, Anderson and Deshpande20 were also reported by multiple studies included in this review (Supplemental Table 2 online).

Publication bias

We did not assess publication bias because there were <10 included studies (for each risk factor that was meta-analyzed). A minimum number of 10 studies is suggested when assessing publication bias using a funnel plot or other more advanced regression-based methods. However, we constructed a funnel plot for 2 of the variables, antibiotic exposure and PPI use, because these risk factors had a large number of patients included from 7 and 4 studies, respectively (Supplemental Fig. 1 online).

Discussion

In this meta-analysis of 14 studies, prior antibiotic exposure and PPI use were significantly associated with increased risk of developing CDI. Children with prior antibiotic exposure have approximately twice the risk of developing CDI compared to patients without a recent history of antibiotic exposure. However, the association was not statistically significant after pooling studies providing adjusted data.

Antibiotic exposure was a significant risk factor in the pediatric inpatient population in our meta-analysis. This finding is consistent with results from the adult population, where antibiotic exposure has been observed to be the most important modifiable risk factor for the development of CDI.Reference McDonald, Gerding and Johnson9 These findings are consistent with the observation that usage of antibiotics can eliminate the natural gut microbiota and establish a favorable environment for C. difficile.Reference Dethlefsen, Huse, Sogin and Relman21 Multiple classes of antibiotics have been independently associated with CDI in the adult population.Reference Slimings and Riley22 In hospitalized pediatric patients, several antibiotic classes were independently associated with CDI. Specifically, carbapenems were identified as a significant risk factor by 2 studies,Reference Adams, Eberly, Rajnik and Nylund23, Reference Hojsak, Ferenc and Bojanić24 while aminoglycosides and cephalosporins were identified by only 1 study.Reference Hojsak, Ferenc and Bojanić24 Individual studies included in this systematic review demonstrated significant risks with use of carbapenems, aminoglycosides, and thrd- or fourth-generation cephalosporins (Supplemental Table 2 online). However, none of the individual antibiotic classes were evaluated by at least 3 different studies and were therefore deemed ineligible for the meta-analysis. Although certain antibiotic classes may in fact be independently associated with increased risk for CDI, more studies performed in the pediatric population are needed to further evaluate these associations. Specifically, design of future studies should clarify on the duration of antibiotic or gastric acid suppression treatment and identify specific antibiotic classes used.

Although our findings are consistent with current acceptance of antibiotic exposure as a risk factor for pediatric CDI, the significance of our results should be considered with caution. Due to the limited availability of studies on the risk factors of CDI in pediatric inpatients, our meta-analysis of antibiotic exposure included <10 studies for antibiotic exposure. Additionally, our analysis of antibiotic exposure is subject to confounding due to the inclusion of unadjusted studies because few studies provided adjusted data. Furthermore, the 2 studies that provided adjusted data for antibiotic exposure did not demonstrate a significant association. The loss of significance may be attributed to adjustments for age, sex, chemotherapy, and use of PPIs, H2Ras, and steroids.

Previous investigations of gastric acid suppression as a risk factor for pediatric CDI have been conflicting. Biologically, there is strong plausibility for gastric acid suppression as a risk factor for CDI because the loss of acidity may disrupt the normal gastrointestinal microbial diversityReference Seto, Jeraldo, Orenstein, Chia and DiBaise25 and prolong the survival of spores,Reference Jump, Pultz and Donskey26 both of which may predispose the host to susceptibility for C. difficile. PPI use was significantly associated with development of CDI in the pediatric inpatient population in this meta-analysis, although the effect size was small. Most recently, Oshima et alReference Oshima, Wu, Li, Fukui, Watari and Miwa27 reported a 3-fold increase in risk of CDI with PPI use in their meta-analysis of pediatric patients. The discrepancies between our results may be explained by differences in our study methodologies. Specifically, Oshima et al included studies that examined community acquired CDI in the outpatient setting and exclusively used raw data from chosen studies that were not adjusted for potential confounding factors. In contrast, we avoided unadjusted data in our analysis of PPI use, and we used only data that had been adjusted by multivariable logistic regression in the original studies. In particular, we obtained unpublished multivariate data for the association of PPI use with CDI from the authors of Brown et alReference Brown, Knoderer, Nichols and Crumby28 to include in this meta-analysis, whereas Oshima et al used unadjusted data from the same study. Nonetheless, the 2 meta-analyses are consistent in demonstrating some degree of association between PPI use and CDI in the pediatric population.

For many of the risk factors assessed by the included studies, we were unable to pool the data due to either an insufficient number of studies or variability in reporting. For example, the presence of IBD as an underlying comorbidity was reported to be a statistically significant risk factor, but was reported by only 2 studies.Reference Nylund, Goudie, Garza, Fairbrother and Cohen3, Reference Pascarella, Martinelli, Miele, Del Pezzo, Roscetto and Staiano29 The association between IBD and CDI might be mediated by the increased use of immunosuppressive agents, antibiotics, and healthcare services, as well as the disruption of the gut mucosal barrier and flora that underlie the pathophysiology of IBD.Reference Sinh, Barrett and Yun30 Similarly, solid organ transplantation was also reported to be an independent risk factor by 2 separate studies, potentially due to the chronic immunosuppressive therapy in these patients.Reference Nylund, Goudie, Garza, Fairbrother and Cohen3, Reference Pant, Deshpande and Desai31 Malignancies in general as well as specific subtypes of tumors were reported to be independent risk factors in several studies. Again, the association may be mediated by the immunosuppressive and antimicrobial effects of chemotherapy, which was reported to be a statistically significant risk factor itself in 1 study.Reference de Blank, Zaoutis, Fisher, Troxel, Kim and Aplenc32 In general, additional studies examining these risk factors in the hospitalized pediatric population are needed to validate these findings.

Our meta-analysis has several limitations. First, relatively few studies were identified for our meta-analysis, and they were exclusively observational. To address this limitation, we searched 4 separate databases and included >2,000 articles in our original search. Unfortunately, studies of risk factors for CDI in the pediatric population are limited in nature, and they often include community acquired-CDI in combination to hospital acquired-CDI. Due to differences in the acquisition of these 2 conditions, we did not feel that using studies of exclusively outpatient CDI infections would be representative of the risk factors for hospitalized patients. As a result, the number of eligible studies was limited in our analysis. Second, contemporary practice guidelines recommend the use of nucleic acid amplification test over the use of other modalities in the diagnosis of CDI.Reference McDonald, Gerding and Johnson9 Due to the paucity of new studies of CDI in pediatric patients, however, most of the studies included in this meta-analysis are older and utilized previously accepted methods such as toxin EIA (Table 1). Third, we evaluated antibiotic exposure as a composite variable without clarifying the specific antibiotics used and duration of treatment because few studies had reported this information. In reality, select antibiotics may have greater effects on CDI compared to others.Reference Adams, Eberly, Rajnik and Nylund23 Fourth, although our meta-analysis incorporated studies representing >10 million patients overall, several studies with large sample size, particularly that of Nylund et alReference Nylund, Goudie, Garza, Fairbrother and Cohen3 did not provide data on important risk factors such as antibiotic exposure and PPI use. A final limitation is the utilization of unadjusted studies that are especially prone to bias and confounding by additional variables. We performed subgroup analyses with only adjusted studies where possible, but we felt the limited number of studies justified the use of unadjusted studies for a preliminary examination of these risk factors. Additional adjusted studies of risk factors for pediatric inpatient CDI would provide the data for a more robust meta-analysis of these risk factors in the future.

Table 1. Characteristics of Included Studies

Note. N/A, not available; RCC, retrospective case-control; RC, retrospective cohort; NCC, nested case-control; EIA, enzyme immunoassay; DRG, Diagnosis-Related Group; ICD-9, International Classification of Disease, 9th edition; PCR, polymerase chain reaction; CTA, cytotoxicity assay; LAMP, loop-mediated isothermal amplification; qPCR, quantitative polymerase chain reaction.

a Presence of billing codes for Toxin A/B EIA and/or PCR, as well as metronidazole (PO or IV) or vancomycin (PO) within the period of 1 day before or 2 days after diagnostic test.

In conclusion, we found that antibiotic exposure and PPI use may be risk factors for CDI infection in hospitalized pediatric patients. Clinicians should continue to utilize antibiotics judiciously in hospitalized patients to minimize the risk for CDI, and similar considerations may be beneficial prior to administration of PPIs. Higher-quality adjusted studies of risk factors in the pediatric population with better defined study parameters and definitions for risk factors are needed to validate these results and to further explore other potential risk factors, including the risk associated with specific antibiotic classes.

Supplementary material

To view supplementary material for this article, please visit https://doi.org/10.1017/ice.2019.23.

Author ORCIDs

Scott Anjewierden, 0000-0001-5542-1599; Chaitanya Pant, 0000-0003-4599-7644; Abhishek Deshpande, 0000-0001-5522-2995

Acknowledgments

None.

Financial support

No financial support was provided relevant to this article.

Conflicts of interest

Abhishek Deshpande has received research support from 3M, Clorox, and STERIS unrelated to this study. All other authors report no conflicts of interest relevant to this article to disclose.

Footnotes

a

Authors of equal contribution.

PREVIOUS PRESENTATION: An abstract containing data used in this study was presented at the 2018 CSCTR Midwest Clinical and Translational Research Meeting on April 26, 2018, in Chicago, Illinois.

References

Langley, JM, LeBlanc, JC, Hanakowski, M, Goloubeva, O. The role of Clostridium difficile and viruses as causes of nosocomial diarrhea in children. Infect Control Hosp Epidemiol 2002;23:660664.10.1086/501990CrossRefGoogle ScholarPubMed
Magill, SS, Edwards, JR, Bamberg, W, et al. Multistate point-prevalence survey of health care–associated infections. N Engl J Med 2014;370:11981208.10.1056/NEJMoa1306801CrossRefGoogle ScholarPubMed
Nylund, CM, Goudie, A, Garza, JM, Fairbrother, G, Cohen, MB. Clostridium difficile infection in hospitalized children in the United States. Arch Pediatr Adolesc Med 2011;165:451457.10.1001/archpediatrics.2010.282CrossRefGoogle ScholarPubMed
Khanna, S, Baddour, LM, Huskins, WC, et al. The epidemiology of Clostridium difficile infection in children: a population-based study. Clin Infect Dis 2013;56:14011406.10.1093/cid/cit075CrossRefGoogle ScholarPubMed
Sammons, JS, Localio, R, Xiao, R, Coffin, SE, Zaoutis, T. Clostridium difficile infection is associated with increased risk of death and prolonged hospitalization in children. Clin Infect Dis 2013;57:18.10.1093/cid/cit155CrossRefGoogle ScholarPubMed
Zilberberg, MD, Tillotson, GS, McDonald, LC. Clostridium difficile infections among hospitalized children, United States, 1997–2006. Emerg Infect Dis 2010;16:604609.10.3201/eid1604.090680CrossRefGoogle ScholarPubMed
Toltzis, P, Kim, J, Dul, M, Zoltanski, J, Smathers, S, Zaoutis, T. Presence of the epidemic North American pulsed-field type 1 Clostridium difficile strain in hospitalized children. J Pediatr 2009;154:607608.10.1016/j.jpeds.2008.10.016CrossRefGoogle ScholarPubMed
Gupta, A, Pardi, DS, Baddour, LM, Khanna, S. Outcomes in children with Clostridium difficile infection: results from a nationwide survey. Gastroenterol Rep 2016;4:293298.Google ScholarPubMed
McDonald, LC, Gerding, DN, Johnson, S, 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):e1e48.10.1093/cid/cix1085CrossRefGoogle Scholar
Sandora, TJ, Fung, M, Flaherty, K, et al. Epidemiology and risk factors for Clostridium difficile infection in children. Pediatr Infect Dis J 2011;30:580584.10.1097/INF.0b013e31820bfb29CrossRefGoogle ScholarPubMed
Dulęba, K, Pawłowska, M, Wietlicka-Piszcz, M. Clostridium difficile infection in children hospitalized due to diarrhea. Eur J Clin Microbiol Infect Dis 2014;33:201209.10.1007/s10096-013-1946-1CrossRefGoogle ScholarPubMed
Turco, R, Martinelli, M, Miele, E, et al. Proton pump inhibitors as a risk factor for paediatric Clostridium difficile infection. Aliment Pharmacol Ther 2010;31:754759.10.1111/j.1365-2036.2009.04229.xCrossRefGoogle ScholarPubMed
McFarland, LV, Brandmarker, SA, Guandalini, S. Pediatric Clostridium difficile: a phantom menace or clinical reality? J Pediatr Gastroenterol Nutr 2000;31:220231.10.1097/00005176-200009000-00004CrossRefGoogle ScholarPubMed
Moher, D, Liberati, A, Tetzlaff, J, Altman, DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med 2009;151:264269.10.7326/0003-4819-151-4-200908180-00135CrossRefGoogle ScholarPubMed
Wells, G, Shea, B, O’Connell, D, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Ottawa Health Research website. http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp. Published 2000. Accessed January 23, 2019.Google Scholar
DerSimonian, R, Laird, N. Meta-analysis in clinical trials. Control Clin Trial 1986;7:177188.10.1016/0197-2456(86)90046-2CrossRefGoogle ScholarPubMed
Deeks, JJ, Higgins, JP, Altman, DG. Analysing data and undertaking meta-analyses. In: Higgins, JPT and Green, S (editors). Cochrane Handbook for Systematic Reviews of Interventions. New York: John Wiley & Sons; 2008. Pp. 243296.10.1002/9780470712184.ch9CrossRefGoogle Scholar
Duval, S, Tweedie, R. Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics 2000;56:455463.10.1111/j.0006-341X.2000.00455.xCrossRefGoogle ScholarPubMed
Kim, J, Smathers, SA, Prasad, P, Leckerman, KH, Coffin, S, Zaoutis, T. Epidemiological features of Clostridium difficile-associated disease among inpatients at children’s hospitals in the United States, 2001–2006. Pediatrics 2008;122:12661270.10.1542/peds.2008-0469CrossRefGoogle ScholarPubMed
Pant, C, Anderson, MP, Deshpande, A, et al. Health care burden of Clostridium difficile infection in hospitalized children with inflammatory bowel disease. Inflamm Bowel Dis 2013;19:10801085.10.1097/MIB.0b013e3182807563CrossRefGoogle ScholarPubMed
Dethlefsen, L, Huse, S, Sogin, ML, Relman, DA. The pervasive effects of an antibiotic on the human gut microbiota, as revealed by deep 16S rRNA sequencing. PLOS Biol 2008;6(11):e280.10.1371/journal.pbio.0060280CrossRefGoogle ScholarPubMed
Slimings, C, Riley, TV. Antibiotics and hospital-acquired Clostridium difficile infection: update of systematic review and meta-analysis. J Antimicrob Chemother 2014;69:881891.10.1093/jac/dkt477CrossRefGoogle ScholarPubMed
Adams, DJ, Eberly, MD, Rajnik, M, Nylund, CM. Risk factors for community-associated Clostridium difficile infection in children. J Pediatr 2017;186:105109.10.1016/j.jpeds.2017.03.032CrossRefGoogle ScholarPubMed
Hojsak, I, Ferenc, T, Bojanić, K, et al. Incidence of Clostridium difficile infection in children with inflammatory bowel disease compared to oncology and immunocompetent patients. Digestion 2012;86:611.10.1159/000337357CrossRefGoogle ScholarPubMed
Seto, CT, Jeraldo, P, Orenstein, R, Chia, N, DiBaise, JK. Prolonged use of a proton pump inhibitor reduces microbial diversity: implications for Clostridium difficile susceptibility. Microbiome 2014;2:42.10.1186/2049-2618-2-42CrossRefGoogle ScholarPubMed
Jump, RLP, Pultz, MJ, Donskey, CJ. Vegetative Clostridium difficile survives in room air on moist surfaces and in gastric contents with reduced acidity: a potential mechanism to explain the association between proton pump inhibitors and C. difficile-associated diarrhea? Antimicrob Agents Chemother 2007;51:28832887.10.1128/AAC.01443-06CrossRefGoogle ScholarPubMed
Oshima, T, Wu, L, Li, M, Fukui, H, Watari, J, Miwa, H. Magnitude and direction of the association between Clostridium difficile infection and proton pump inhibitors in adults and pediatric patients: a systematic review and meta-analysis. J Gastroenterol 2018;53:8494.10.1007/s00535-017-1369-3CrossRefGoogle ScholarPubMed
Brown, KE, Knoderer, CA, Nichols, KR, Crumby, AS. Acid-suppressing agents and risk for Clostridium difficile infection in pediatric patients. Clin Pediatr (Phila) 2015;54:11021106.10.1177/0009922815569201CrossRefGoogle ScholarPubMed
Pascarella, F, Martinelli, M, Miele, E, Del Pezzo, M, Roscetto, E, Staiano, A. Impact of Clostridium difficile infection on pediatric inflammatory bowel disease. J Pediatr 2009;154:854858.10.1016/j.jpeds.2008.12.039CrossRefGoogle ScholarPubMed
Sinh, P, Barrett, TA, Yun, L. Clostridium difficile infection and inflammatory bowel disease: a review. Gastroenterol Res Pract 2011;2011:136064.CrossRefGoogle ScholarPubMed
Pant, C, Deshpande, A, Desai, M, et al. Outcomes of Clostridium difficile infection in pediatric solid organ transplant recipients. Transpl Infect Dis 2016;18:3136.10.1111/tid.12477CrossRefGoogle ScholarPubMed
de Blank, P, Zaoutis, T, Fisher, B, Troxel, A, Kim, J, Aplenc, R. Trends in Clostridium difficile infection and risk factors for hospital acquisition of Clostridium difficile among children with cancer. J Pediatr 2013;163:699705.e1.CrossRefGoogle ScholarPubMed
Guo, S, Xu, X, Dong, F. Risk factors of Clostridium difficile-associated diarrhea in children. Zhonghua Yi Xue Za Zhi 2012;92:18361840.Google ScholarPubMed
Price, V, Portwine, C, Zelcer, S, et al. Clostridium difficile infection in pediatric acute myeloid leukemia: from the Canadian Infections in Acute Myeloid Leukemia Research Group. Pediatr Infect Dis J 2013;32:610613.CrossRefGoogle ScholarPubMed
Santiago, B, Guerra, L, García-Morín, M, et al. Clostridium difficile isolation in children hospitalized with diarrhea. An Pediatr 2015;82:417425.CrossRefGoogle ScholarPubMed
Ciricillo, J, Haslam, D, Blum, S, et al. Frequency and risks associated with Clostridium difficile-associated diarrhea after pediatric solid organ transplantation: a single-center retrospective review. Transpl Infect Dis 2016;18:706713.CrossRefGoogle ScholarPubMed
Finnerty, CC, Herndon, DN, Lee, JO, et al. Morbidity and mortality in severely burned children with Clostridium difficile-associated diarrhea. Surgery 2016;159:16311637.CrossRefGoogle ScholarPubMed
Karaaslan, A, Soysal, A, Yakut, N, et al. Hospital-acquired Clostridium difficile infection in pediatric wards: a retrospective case-control study. SpringerPlus 2016;5:1329.CrossRefGoogle ScholarPubMed
Daida, A, Yoshihara, H, Inai, I, et al. Risk factors for hospital-acquired Clostridium difficile infection among pediatric patients with cancer. J Pediatr Hematol Oncol 2017;39:e167e172.CrossRefGoogle ScholarPubMed
Figure 0

Fig. 1. Flow chart for study inclusion in the systematic review and meta-analysis.

Figure 1

Fig. 2. Forest plot of the association between antibiotic use and CDI. Vertical line corresponds to no difference point between the 2 groups. Squares correspond to risk ratios. Horizontal lines represent the 95% confidence intervals. The diamond indicates the pooled relative risk ratios. Note. df, degrees of freedom; M-H, Mantel-Haenszel.

Figure 2

Fig. 3. Forest plot of the association between PPI use and CDI. Vertical line corresponds to no difference point between the 2 groups. Squares correspond to risk ratios. Horizontal lines represent the 95% confidence intervals. The diamond indicates the pooled relative risk ratios. Note. df, degrees of freedom; M-H, Mantel-Haenszel.

Figure 3

Fig. 4. Forest plot of the association between H2RA use and CDI. Vertical line corresponds to no difference point between the 2 groups. Squares correspond to risk ratios. Horizontal lines represent the 95% confidence intervals. The diamond indicates the pooled relative risk ratios. Note. df, degrees of freedom; M-H, Mantel-Haenszel.

Figure 4

Fig. 5. Forest plot of the association between gender and CDI. Vertical line corresponds to no difference point between the 2 groups. Squares correspond to risk ratios. Horizontal lines represent the 95% confidence intervals. The diamond indicates the pooled relative risk ratios. Note. df, degrees of freedom; M-H, Mantel-Haenszel.

Figure 5

Table 1. Characteristics of Included Studies

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