Part 2: Identifying Research MethodologiesAfter reading each of the four peer-reviewed articles you selected, use the Matrix Worksheet template to analyze the methodologies applied in each of the four

Original Article Risk factors forClostridium difficileinfection in pediatric inpatients:

A meta-analysis and systematic review Scott Anjewierden BS 1,a , Zheyi Han BS 1,a, Charles B. Foster MD 2, Chaitanya Pant MD 3 and Abhishek Deshpande MD, PhD 4,5 1Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, Ohio, USA, 2Center for Pediatric Infectious Diseases, Cleveland Clinic Children’s, Cleveland, Ohio, USA, 3Division of Gastroenterology, Hepatology and Motility, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas, USA, 4Medicine Institute Center for Value Based Care Research, Cleveland Clinic, Cleveland, Ohio, USA and 5Department of Infectious Diseases, Cleveland Clinic, Cleveland, Ohio, USA Abstract Objective: To summarize risk factors forClostridioides(formerlyClostridium)difficileinfection (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.

(Received 20 November 2018; accepted 19 January 2019) Clostridioides(formerlyClostridium)difficileis one of the most fre- quent causes of hospital-acquired infections in both adult and pedi- atric patients. 1,2 The incidence and healthcare burden ofC. difficile infection (CDI) in the hospitalized pediatric population has increased in the past 20 years, 3–6 mostly attributed to the emergence of the new, hypervirulent strain B1/NAP1/027. 7Although most chil- dren recover without long-term sequelae, CDI in hospitalized chil- dren is associated with increased mortality, length of stay, and hospital cost, 5and it is an independent predictor of subsequent colectomy and discharge to short- or long-term care facility. 8 In adult patients, CDI is associated with discrete risk factors including advanced age, antibiotic exposure, prolongedhospitalization, proton-pump inhibitor use, immunocompromised state, and other medical comorbidities. 9In 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. 10–12 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 withC. difficilebut do not develop clinical illness until 12–24 months of age. 13Therefore, closer examination of currently avail- able 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. 14 aAuthors of equal contribution.

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

Author for correspondence:Abhishek Deshpande, Email:[email protected] Cite this article:Anjewierden S,et al. (2019). Risk factors forClostridium difficile infection in pediatric inpatients: A meta-analysis and systematic review.Infection Control & Hospital Epidemiology, 40: 420–426, © 2019 by The Society for Healthcare Epidemiology of America. All rights reserved. Infection Control & Hospital Epidemiology(2019),40,420–426 doi:10.1017/ice.2019.23 Data sources and searches Two investigators (S.A. and Z.H.) systematically searched the literature independently using the following predetermined inclu- sion 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 evalu- ated>1 CDI risk factor. Studies were excluded if (1) they exclusively studied CDI in children<2 years, in which the role ofC. difficilewas unclear and testing was not routinely recommended, 9and (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 difficileinfection, CDI,Clostridium difficileassociated 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 includingClostridioides difficilein 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 character- istics, 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 interraterκstatistics 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). 15Studies 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 interraterκstatistic 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 ofC. 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 avail- able, 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 avail- able for≥3 studies, we combined the adjusted and unadjusted data.

DerSimonian and Laird random-effects models were used for all meta-analyses. 16 The meta-analysis was performed using the inverse variance method to obtain pooled ORs and 95% confidenceintervals (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 Cochranχ 2 (Cochran Q) and the I 2 statistic. We defined significant heterogeneity as aχ 2<0.10 or anI 2statistic>66%. 17Moderate heterogeneity was defined as an I 2statistic between 33% and 66%. Low heterogeneity was defined as an I 2statistic<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. 18 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 poten- tially relevant articles, 127 studies were considered relevant. On further screening of the abstracts of these potentially relevant stud- ies, 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 Figure1.

The main characteristics of the included studies are summarized in Supplemental Table2. 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 sin- gle study was conducted in each of the following countries: Canada, China, Croatia, Japan, Spain, and Turkey. The testing methodology for CDI consisted of aC. difficiletoxin assay for 10 studies.

Clostridium difficileculture and/or toxin assay for 2 studies and the use of theInternational 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 Table1online).

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 consider- able 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 diagno- sis of CDI was limited. Various methods were used to identify anti- biotic use, including review of patient medical records, patient prescription records, and ICD-9 codes. Infection Control & Hospital Epidemiology421 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 sig- nificantly increased risk of CDI with prior exposure to any antibi- otic class (OR, 2.14; 95% CI, 1.31–3.52;P=.003) (Fig.2). There was moderate heterogeneity among these studies (I 2=57%). We also performed subgroup analysis for the adjusted and unadjusted stud- ies. The meta-analysis of the unadjusted studies showed a signifi- cantly 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 (I 2=68%). The meta-analysis of the adjusted studies also showed an increased risk of CDI withprior 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 (I 2=1%). Risk factors for CDI with individual antibiotic subclasses were not reported by >2 studies and were therefore not included in the meta-analysis.

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 (I 2=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 Records identified through database searching (n = 2032) Screening Included Eligibility Identification Additional records identified through other sources (n = 1) Records after duplicates removed (n = 1373) Records screened (n = 127)Records excluded (n = 72) Full-text articles assessed for eligibility (n=56)Full-text articles excluded: 42 • Includes outpatient data: 13 • Combined adult and pediatric data: 13 • Primarily children < 1: 4 • ≤ 10 cases of C. diff: 3 • Appropriate data missing: 4 • CDI recurrence only: 2 • Duplicate data source: 2 • Studied 1 risk factor: 1 Studies that met inclusion criteria (n = 14) Studies included in quantitative synthesis (meta-analysis) (n = 9) Figure 1.Flow chart for study inclusion in the systematic review and meta-analysis.

Figure 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.

422Scott Anjewierdenet al significant (OR, 1.36; 95% CI, 0.31–5.98;P=.68) (Fig.4). There was significant heterogeneity among these studies (I 2=68%).

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 (I 2=76%).

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 Table2(online). Notably, underlying comorbidities that have been previously reported such as inflammatory bowel disease (IBD), solid organ transplant, and malignancies 10,19 ,20were also reported by multiple studies included in this review (Supplemental Table2online).

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.1online).

Discussion In this meta-analysis of 14 studies, prior antibiotic exposure and PPI use were significantly associated with increased risk of devel- oping CDI. Children with prior antibiotic exposure have approx- imately twice the risk of developing CDI compared to patients without a recent history of antibiotic exposure. However, the asso- ciation was not statistically significant after pooling studies provid- ing adjusted data.Antibiotic exposure was a significant risk factor in the pediatric inpatient population in our meta-analysis. This finding is consis- tent with results from the adult population, where antibiotic expo- sure has been observed to be the most important modifiable risk factor for the development of CDI. 9These findings are consistent with the observation that usage of antibiotics can eliminate the natural gut microbiota and establish a favorable environment forC. difficile. 21Multiple classes of antibiotics have been independ- ently associated with CDI in the adult population. 22In hospitalized pediatric patients, several antibiotic classes were independently associated with CDI. Specifically, carbapenems were identified as a significant risk factor by 2 studies, 23,24 while aminoglycosides and cephalosporins were identified by only 1 study. 24Individual studies included in this systematic review demonstrated significant risks with use of carbapenems, aminoglycosides, and thrd- or fourth-generation cephalosporins (Supplemental Table2online).

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 suppres- sion 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 signifi- cance of our results should be considered with caution. Due to the limited availability of studies on the risk factors of CDI in pedi- atric 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 antibi- otic 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 fac- tor 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 Figure 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 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.

Infection Control & Hospital Epidemiology423 gastrointestinal microbial diversity 25and prolong the survival of spores, 26both of which may predispose the host to susceptibility forC. difficile. PPI use was significantly associated with develop- ment of CDI in the pediatric inpatient population in this meta- analysis, although the effect size was small. Most recently, Oshima et al 27 reported a 3-fold increase in risk of CDI with PPI use in their meta-analysis of pediatric patients. The discrepan- cies 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 multivari- ate data for the association of PPI use with CDI from the authors of Brown et al 28to 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 statisticallysignificant risk factor, but was reported by only 2 studies. 3,29 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. 30 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. 3,31 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. 32In 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 exclu- sively observational. To address this limitation, we searched 4 sep- arate databases and included>2,000 articles in our original search.

Unfortunately, studies of risk factors for CDI in the pediatric pop- ulation 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 Figure 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.

Table 1.Characteristics of Included Studies First Author,Year PublishedStudy LocationStudy PeriodStudy DesignSample Size, No.Boys, No. (%)Age Range, yDiagnostic Test/Criteria Pascarella F, 292009 Italy 2005–2007 RCC 193 107 (55.4) 1–18 Toxin A/B EIA Turco R, 122010 Italy 2005–2009 RCC 136 86 (63.2) 1–18 Toxin A/B EIA Nylund CM, 32011 USA 1997–2006 RC 10,495,728 4,198,965 (40.0) 1–17 ICD9 Code (008.45) Guo S, 332012 China 2010–2011 PC 140 98 (70.0) 0–18 Toxin A/B PCR Hojsak I, 242012 Croatia 2006–2011 RC 744 379 (51.0) 0–18 Toxin A/B EIA De Blank P, 322013 USA 1999–2011 RC 33,059 18,479 (55.9) 1–18 ICD9 code (008.45), billing codes a Price V, 342013 Canada 1995–2004 RC 341 168 (49.3) 1–18 Culture Brown KE, 282015 USA 2008–2012 RCC 458 227 (49.6) 1–17 Toxin B qPCR Santiago B, 352015 Spain 2010–2011 RC 250 140 (56.0) 0–15 Culture, Toxin A/B PCR Ciricillo J, 362016 USA 2010–2013 RC 55 N/A 0–18 Toxin A/B EIA, LAMP Finnerty C, 372016 USA 1997–2008 RCC 85 57 (67.0) 0–18 Toxin A/B EIA Karaaslan A, 382016 Turkey 2012–2014 RCC 986 552 (56.0) 0–18 Toxin A/B EIA, CTA Pant C, 312016 USA 2012–2012 RC 12,797 6,760 (52.8) 1–17 ICD9 Code (008.45) Daida A, 392017 Japan 2003–2012 RCC 108 64 (59.3) 0–19 Toxin A/B EIA 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.

aPresence 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.

424Scott Anjewierdenet al 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. 9Due 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 (Table1). Third, we evaluated antibi- otic 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. 23 Fourth, although our meta-analysis incorporated studies representing>10 million patients overall, several studies with large sample size, particularly that of Nylund et al 3did 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.

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 judi- ciously in hospitalized patients to minimize the risk for CDI, and similar considerations may be beneficial prior to administra- tion of PPIs. Higher-quality adjusted studies of risk factors in the pediatric population with better defined study parameters and def- initions for risk factors are needed to validate these results and to further explore other potential risk factors, including the risk asso- ciated with specific antibiotic classes. Supplementary material.To view supplementary material for this article, please visit 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.

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