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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Liver Transpl. Author manuscript; available in PMC 2013 August 1.
Published in final edited form as:
PMCID: PMC3405162

Clostridium difficile Infection in Hospitalized Liver Transplant Patients: A Nationwide Analysis



Incidence of Clostridium difficile infection (CDI) is increasing among hospitalized patients. Liver transplant patients are at higher risk for acquiring CDI. Small, single-center studies, but no nation-wide analyses, have assessed this association.


We used the Healthcare Cost and Utilization Project- Nationwide Inpatient Sample (HCUP-NIS) from years 2004–2008 for this retrospective cross sectional study. Patients with any discharge diagnosis of liver transplant comprised the study population and were identified using ICD-9-CM codes. Those with a discharge diagnosis of CDI were considered cases. Our primary outcomes were prevalence of CDI and effect of CDI on inpatient mortality. Our secondary outcomes included length of stay and hospitalization charges. Regression analysis was used to derive odds ratios adjusted for potential confounders.


There were 193,714 discharges with a diagnosis of liver transplant from 2004–2008. Prevalence of CDI was 2.7% in liver transplant population compared to 0.9% in non liver transplant population (p <0.001). Most of the liver transplant patients were in the 50–64 age group. Liver transplant patients were at higher odds of developing CDI (OR 2.88, 95% CI 2.68–3.10). Increasing age, increasing comorbidity, IBD and NG tube placement were also independent risk factors for CDI. CDI in liver transplant was associated with a higher mortality, 5.5% as compared to 2.3% in liver transplant only population (adjusted OR 1.7, 95% CI 1.3–2.2).


Liver transplant patients have a higher prevalence of CDI as compared to non liver transplant patients (2.7% vs. 0.9%).CDI was an independent risk factor for mortality in liver transplant population.

Keywords: Solid organ transplant, complications, outcomes research, cross sectional


Clostridium difficile infection (CDI) is an important cause of morbidity and mortality in hospitalized patients (1, 2). The past decades have seen an increasing incidence of CDI in North America (3, 4). Clostridium difficile is a gram positive spore forming anaerobe and causes toxin mediated invasive infection (5, 6). Its clinical presentation varies from asymptomatic carriage to life threatening colitis requiring surgical resection (6). Established risk factors for CDI include older age, increased comorbidity and recent antibiotic or healthcare exposure, whereas immunosuppression, organ transplantation, and gastric acid suppression have been recently implicated (7, 8). There is increasing recognition of newer at-risk subgroups include those with IBD, pregnant women, and community acquired CDI.

Liver transplant patients are predisposed to CDI due to a decrease in patient defense mechanisms resulting from a combination of debilitating disease, operative stress, immunosuppresants and an imbalance in gut flora due antibiotic use (911). Various retrospective, single center studies have placed the incidence of CDI in liver transplant ranging from 3% to 8% (1214). Some studies have shown liver transplant patients as a high risk population for CDI (10). Jeffery et al retrospectively studied charts from 467 liver transplants and found the prevalence to be about 8% and established that the early post operative period (<28 days post transplant) is associated with a higher risk of developing CDI(12). Other risk factors established in the study were high MELD score, inability to bypass ICU post-op as well as post operative vascular, biliary or incisional complications. Masao et al retrospectively studied 242 living donor liver transplant patients and identified age >55, male gender and serum creatinine >1.5 as risk factors for CDI. Their reported prevalence was 5% (13). Stelzmueller et al studied solid organ transplant patients with CDI in a single center study and found the prevalence of CDI to be 3.45% among liver transplant patients. This was the highest prevalence in their cohort of single organ recipients; only multi visceral transplant had a higher prevalence of 20% (14).

There is paucity of nationwide data on prevalence of CDI in liver transplant patients and its effect on inpatient mortality and its impact on healthcare resources. Our study aims were: 1) to determine the prevalence of CDI in hospitalized patients with liver transplant, 2) to determine if liver transplant is independently associated with CDI in hospitalized patients, 3) to examine the effect of CDI on mortality in hospitalized liver transplant patients; and to 4) compare CDI prevalence in liver transplant population with other solid organ transplant population (renal transplant).


Data Source and Study Design

The Healthcare Cost and Utilization Project (HCUP)-Nationwide Inpatient Sample (NIS) from years 2004 to 2008 was used for this analysis (15). The NIS is the largest all payer inpatient discharge database. The patients are 20% stratified sample of all the discharges occurring in that year from about 1000 hospitals in 32–37 states (dependent on year of study) and contains information on about 8 million discharges per year. The patients have listed a primary discharge diagnosis and up to 14 secondary discharges diagnoses. The patients can also have up to 15 procedure codes associated with the discharges. We utilized a retrospective cross-sectional study design.

Study population

International Classification of Diseases, Clinical Modification 9th Edition (ICD-9-CM) codes were used to identify patients from the database (Table 1). Study population consisted of patients with any discharge diagnosis code of liver transplant whereas the liver transplant patients with a concomitant discharge diagnosis code of CDI were considered cases. The use of ICD-9-CM codes for identifying patients with CDI has been validated in other studies and demonstrated good accuracy (16, 17). Patients without any transplant codes were used as non-transplant controls. These codes have been validated in the literature for such analysis (1822). The subgroup of patients carrying a procedure code of liver transplant was also studied to look at CDI in the admission related to the primary surgery. To examine if the risk of CDI was specific for liver transplant or common across all transplant related immunosuppression, we selected a control population with a discharge diagnosis of renal transplant.

Table 1
ICD-9-CM codes used in analysis

Definition of Variables

The NIS contains demographic information on all hospitalizations, including age, gender, race, primary and secondary insurance. Patient’s comorbidity was adjusted using the Deyo modification of Charlson index, is a tool that has been validated for use in administrative databases (23, 23, 24). We defined a new variable ‘any infection’ for adjustment purposes as a surrogate for antibiotic use. For this variable, we included all ICD-9-CM codes used for a wide variety of infections (other than CDI and viral illnesses) that can potentially be treated with antibiotics. A similar coding was used by Martin et al for study of sepsis (25). The ICD-9-CM codes used for this variable are listed in Appendix 1. Disposition from hospital was also included in the analysis. Known risk factors for CDI i.e. NG tube placement, IBD and critical illness, as indicated by mechanical ventilation, were used for the adjusted analysis (2629). We could not determine antibiotic or PPI use from the database due to lack of information on medication administration within NIS.


We analyzed the following outcomes: 1) prevalence of CDI in hospitalized patients with liver transplant, 2) in-hospital mortality in patients admitted with liver transplant, 3) secondary outcomes that included length of stay and hospitalization charges associated with liver transplant plus CDI, and discharge disposition when leaving hospital. The various discharge dispositions available from the database were home, home with care, facility and hospital discharge.

Data analysis

Categorical variables were compared using Chi-square test and t-test was used for continuous variables. Logistic regression was used to determine association of liver transplantation with CDI as well as to determine effect of CDI on mortality in this cohort. The analysis was adjusted for variables such as age, gender, race, insurance and comorbidities including general comorbidity using the Charlson index and any infection. Analyzed outcomes included mortality, length of stay, hospitalization charges as well as discharge disposition. For comparison purposes, we performed a similar analysis for hospitalized renal transplant discharges in the same years. We also performed a subgroup multivariate analysis including only liver and renal transplant related admissions in the data. All analysis was done using STATA 10 (Stata Corp, College Station, Texas) using appropriate survey estimation command and strata weights provided in each NIS file. The study was approved by the Medical College of Wisconsin Institutional Review Board (IRB).


Prevalence of CDI in liver transplant patients

There were 193,714 discharges for liver transplant from year 2004–2008. Out of these, 5,159 were associated with CDI (Prevalence of 2.7%). In the non-transplant population, the prevalence of CDI was 0.9% (p < 0.001) (Figure 1). The prevalence of CDI in patients with the index admission for liver transplant procedure was 2.9%, which was not significantly different than CDI and any liver transplant related admission population. 7.6% of liver transplant patients also had a kidney transplant. CDI prevalence in patients with both liver and kidney transplant was 2.3%. CDI prevalence in liver transplant patients with a concomitant code for acute rejection was 3.2% as compared to 2.5% in admissions not related to acute rejection (p<0.001).

Figure 1
Prevalence of CDI in study population

Characteristics of patients

On unadjusted analysis, liver transplant patients with and without CDI were of similar age distribution with most patients falling in the 50–64 age group. They were similar in terms of gender, race and insurance provider. There were more liver transplant plus CDI patients admitted to teaching hospitals (Table 2).

Table 2
Characteristics of study population

Factors associated with CDI

On adjusted analysis, liver transplant was associated with almost 3 times the odds of having CDI as compared to non liver transplant patients (OR 2.88, 95% CI 2.68–3.10). This analysis was adjusted for any infection in the patients. Other risk factors for CDI were found to be increasing age, comorbidities including mechanical ventilation, NG tube placement, IBD and any infection. Race other than White was associated with a lower risk on unadjusted analysis (Table 3).

Table 3
Multivariate analysis of associated factors with Clostridium Difficile infection in hospitalized patients from 2004–2008


Mortality in hospitalized patients with liver transplant and CDI was 5.5%, which was higher than the non liver transplant mortality of 3.2% (p <0.001). There was no difference in mortality in CDI patients during the index admission for the liver transplant surgery as compared to admissions not associated with the liver transplant surgery (6.7% vs. 5.2% p=0.43). Teaching hospitals had a higher mortality in liver transplant and liver transplant plus CDI patients. CDI was an independent predictor of mortality in liver transplant patients with an adjusted odds ratio (OR) of 1.7 (95% CI 1.3–2.2). Patients with liver transplant who had CDI were also more likely to be on mechanical ventilation. Length of stay increased from a mean 7.7 days (95% CI 7.1–8.3) to a mean of 17.8 days (95% CI 15.6–20.0) in liver transplant with CDI group (mean difference 9.9 days, 95% CI 9.2–10.7). CDI with liver transplant was also associated with almost twice the hospitalization charges (mean difference $69,131, 95% CI $60,652–$77,610). Restricting our analysis to patients who survived hospitalization, we found similar increases for length of stay and hospitalization charges (Table 2). The liver transplant plus CDI patients were more likely to be discharged to a facility and require home care as compared to liver transplant patients alone.

Comparison with renal transplant patients

We did a comparative analysis of patients with renal transplant to determine if the association of CDI with liver transplant is exclusive to liver transplant or is associated with a transplant state. The prevalence of CDI in renal transplant population was 2.1% which was significantly lower than the liver transplant population (p <0.001). Renal transplant state was also independently associated with risk of developing CDI (OR 2.81, 95% CI 2.70–2.93). Mortality in renal transplant patients with CDI was 5.0%, which was not significantly lower than the liver transplant population with CDI (5.5%) (p= 0.150). In our subgroup multivariate analysis including only liver and kidney transplant patients, liver transplant remained independently associated with CDI (OR 1.28, 95% CI 1.11–1.48).


Clostridium difficile incidence is increasing among hospitalized patients. Recent single center studies have shown an increased predisposition in liver transplant patients (7, 12, 14) but are limited by their sample size and single center perspective. Using a nationally representative database, we demonstrate that (1) CDI occurred more commonly in liver transplant patients than in non-transplant controls as well as renal transplant patients; and (2) CDI was an independent risk factor for mortality in patients with liver transplant, and was associated with a significant increase in length of stay and hospitalization charges.

We found the prevalence of CDI in liver transplant patients to be 2.7%. Various studies have placed the prevalence anywhere from 3% to 8% (1214, 30). Stelzmueller et al retrospectively studied solid organ transplants in a single center and found the prevalence of CDI in liver transplant patients to be 3.45% (14). A multi-year retrospective study by Albright from the Mayo Clinic found the prevalence CDI in liver transplant patients to be 8%. They also found that the early post transplant period (<28 days) was highest risk for developing CDI (12). Hashimoto et al reported a prevalence of 5% and median time of onset of CDI as 19 days (13). The fact that our study showed prevalence near the lower end of previous study estimates may be explained by the fact that studies from single centers may more likely reflect referral populations with greater co-morbidity and higher risk for CDI. Although our study lacks data on timing of infection, the subgroup analysis, which shows prevalence slightly higher for the index admission (2.9%) corroborates reports from other studies that the early post operative period has the highest risk for developing CDI. The earlier onset of CDI may be related to the more potent immunosuppression used in the immediate post operative period (31) and the debilitated state of patients prior to transplant (10). The admissions related to acute rejection had significantly higher prevalence of CDI as compared to admissions not associated with acute rejection, which is likely due to increased immunosuppression required to treat acute rejection.

Increasing age was found to be a risk factor for CDI in our study; this is in line with the literature, where advanced age is a well-established risk factor for CDI (26, 32, 33, 33). Although race was not a significant factor on unadjusted analysis, in the final model, White race was found to be a risk factor for CDI in liver transplant patients. There is no correlating data in the literature that indicates White race is a risk factor for CDI. Female gender was at slightly higher risk of developing CDI among liver transplant patients. Studies are mixed in terms of gender based risk for CDI, as some have shown males whereas others have shown females as more likely to develop CDI (13, 34, 35). The significance of these contrasting findings is unclear. More liver transplant patients with CDI were admitted to teaching hospitals as compared to non teaching hospitals, which is possibly due to the fact that due to their inherent complexity, these patients are referred to transplant centers or teaching hospitals.

On adjusted analysis, we found liver transplant to be independently associated with CDI. This was after adjusting for various variables such as age, race, and general comorbidity (Charlson index) as well as known risk factors for CDI that could be used from the database, including NG tube placement, mechanical ventilation and IBD. PPI use and antibiotic use were not used in the analysis due to lack of information on medications. The variable ‘any infection’ was also used in this adjustment as a proxy for antibiotic use. A similar variable has been used by Martin et al but that list was less comprehensive than the set of infections included in our study (25). The use of this variable only makes the association between liver transplant and CDI stronger, as we hypothesize that if this variable was not used, the association would likely be weaker due to not being adjusted for these multiple infections.

CDI was found to be an independent risk factor for mortality in hospitalized liver transplant patients, emphasizing the importance of having a high index of suspicion for early diagnosis and appropriate initiation of treatment. In addition to being a risk factor for mortality in this population, CDI also was a burden on healthcare as it increased the length of stay and hospital cost by almost two fold. It also altered the discharge disposition for patients. Fewer CDI patients were able to be discharged home and required discharges to facility or home with care. This highlights the burden on the healthcare system posed by this complex cohort of patients. One reason could be that this cohort of patients already has multiple comorbidities and the added need for isolation and antibiotic treatment alters the disposition towards a care facility or home with care.

Most liver transplant patients have underlying pre-transplant cirrhosis and studies have shown cirrhotics to be at a higher risk of developing CDI. Bajaj et al analyzed a nationwide database as well as a tertiary care center data and found that CDI is associated with higher mortality, LOS and hospital charges (18). This underlying or pre-transplant comorbidity likely contributes to the risk of CDI in the liver transplant population.

We compared the risk of developing CDI with renal transplant patients and found renal transplant also to be a risk factor for developing CDI, although the prevalence of CDI was higher in liver transplant patients as compared to renal transplant patients. In the Stelzmueller et al study, prevalence of CDI was also higher among liver transplant patients as compared to renal transplant patients (14). The exact reason for this finding is unclear as liver is considered less immunogenic in comparison to the kidney and requires less immunosuppression after transplant. This finding could be due to difference in patient demographics or differential use of antibiotics due to other comorbidities among the two populations. Our subgroup multivariate analysis with liver and kidney transplant patients only indicated that LT patients have a higher risk of CDI than KT patients. The reasons for this could be multifactorial and include ‘residual’ effect of pre-transplant cirrhosis, different immunosuppression regimen post-LT compared to post-KT, and different use of antibiotics (that predispose to CDI) post-LT compared to post-KT. These findings emphasize that the co-morbid state and immunosuppresants play a role in risk for CDI (10, 14, 34).

Our study has several limitations. There are no patient identifiers and hence patients cannot be tracked over time and multiple admissions by same patient cannot be accounted for. We could not look at the timing of the infection due to lack of such information and also could not examine the impact of recurrent CDI which may be seen in up to a third of patients. Due to the nature of the database and the resulting lack of laboratory data, MELD score or PPI and antibiotic use could not be determined. Due to the administrative nature of the database, there may be errors of coding leading to missed or erroneous coding of the diagnosis. However, we would expect such errors to be non-differential between the various groups, and would not anticipate any significant alteration in our results. As in many retrospective observational studies, effect sizes reflect association and cannot definitively conclude on causation. Nevertheless, our findings were robust to adjustment for multiple co-morbidities that may likely influence effect sizes. However, the effect of unmeasured confounders is recognized and our findings merit cautious interpretation.

In conclusion, from a nationwide analysis of in liver transplant patients, we identified a prevalence of Clostridium difficile infection in liver transplant patients at 2.7%. Liver transplant was found to be independently associated with CDI in hospitalized patients and CDI was an independent predictor of mortality in hospitalized patients with liver transplant. We suggest vigilance in prevention and a low threshold in assessment for Clostridium difficile infection in hospitalized liver transplant patients particularly in the early post-operative period. We suggest patients with acute rejection, increasing age, White race, mechanical ventilation, IBD and any infection be more vigilantly screened for CDI and possibly considered for more active probiotic prophylaxis during antibiotic therapy.

Table 4
Multivariate analysis for mortality in hospitalized liver transplant patients


This project was presented as a research abstract in Digestive Diseases Week 2011.

Grant Support:

Supported in part by the Clinical & Translational Science Institute of Southeast Wisconsin: NIH UL1RR031973

Abbreviations used

Clostridium Difficile Infection
Healthcare Cost and Utilization Project-Nationwide Inpatient Sample
International Classification of Diseases, Clinical Modification, 9th Revision
Inflammatory Bowel Disease
NG Tube
Nasogastric Tube
Model for End-Stage Liver Disease
Intensive Care Unit
Proton Pump Inhibitor
Length of Stay

Appendix: ICD-9-CM codes for variable ‘any infection’

* septicemia - 038.0,038.10,038.11,038.19,038.2,038.3, 038.40,038.41,038.42,038.43,038.44, 038.49,038.8, 038.9
*SIRS due to infectious process without organ dysfunction 995.91
*Bacteremia 790.7
*Septic shock 785.52
*SIRS due to infectious process with organ dysfunction 995.92
*Disseminated fungal infection 117.9
*Disseminated candidal infection 112.5
*candidal endocarditis 112.81
*fungal endocarditis 115.04, 115.14, 115.94,
*candidal meningitis 112.83
*Fungal meningitis: 114.2,115.01, 115.11, 115.91,
*Fungal pneumonia: 115.05, 115.15, 115.95,
*Rhinosporidiosis 117.0,
*Zygomycosis 117.7
*Aspergillosis 117.3
*other fungal 484.6,484.7,321.0,321.1,
*following codes were unchanged since 2000
*Disseminated fungal infection 117.9
*Disseminated candidal infection 112.5
*candidal endocarditis 112.81
*fungal endocarditis 115.04, 115.14, 115.94,
* Meningococcal septicemia 036.2,
* Waterhouse friedrichson syndrome 036.3
*Gram +ve
     * TSS 040.82
     * scalded skin syndrome 695.81
     * pneumonia - 482.40-482.42,482.49
     * menigitis - 320.3
     * septicemia - 038.10,038.11,038.19,
     * unspecified site - 041.10 - 19,
*Strept: 038.0,041.00-09,482.30-2,482.39,320.2
     * Erysipelas - 035
     * strept throat/scarlet fever - 034.0,034.1
     * rheumatic fever - 390, 391.0-2, 391.8-9, 392
*Pneumo: 038.2, 141.2, 320.1,481, 567.1,
* Gram -ve
     * E coli - 041.4, 038.42,482.82,
     * Hinfluenza - 041.5, 038.41,482.2, 320.0,
     * Proteus - 041.6,
     * klebsiella - 482.0,
     * legionella - 482.84,
     * pseudomonas 041.7,038.43,482.1
     * serratia - 038.44,
     * other gm negative 041.85,038.40,038.49,482.83,320.82
* pseudomonas 041.7,038.43,482.1
     *pneumonia - 482.81
     *meningitis - 320.81
     *bacteriodes - 041.82
     *clostridium perfringens - 041.83
     *unspecified - 041.84
     *septicemia - 038.3
*CNS abscess 324.0,324,1,324.9
*Abscess of pharynx: 478.21,478.22,478.24
*Peritonsillar abscess: 475
*Empyema 510.0,510.9
*Lung abscess 513.0,513.1
*Peritonitis 567.0,567.1,567.21,567.22,567.23,567.29
*Anal and rectal abscess 566
*abdominal abscess: 567.31,567.38,567.39,567.81,567.9
*Intestinal abscess 569.5
*Perforation of intestine 569.83
*Abscess of liver 572.0
*Portal pyemia 572.1
*orchitis with abscess: 604.0
*Pyelo: 590.10,590.11,590.2,590.3,590.80,590.81,590.9
*Other cellulitis or abscess 682.0-9
*Bacterial meningitis 320.0-3,320.7,320.81,320.82,320.89,320.9
*Meningitis due to other organism:321.0-4,321.8
*phlebitis of intracranial sinus 325
*Acute or subacute endocarditis 421.0,421.1,421.9
*Thrombophlebitis 451.0,451.11,451.19,451.2,451.81,4510.82,451.83,451.84,451.89,451.9
*Acute sinusitis 461.0-3,461.8,461.9
*Acute pharyngitis 462
*Acute tonsillitis 463
*Acute URI 465.0,465.8,465.9
*Bronchitis: 466.0,466.11,466.19
*Abscess of pharynx: 478.21,478.22,478.24
*Peritonsillar abscess: 475
*Pneumoncoccal pneumonia 481
*Other bacterial pneumoia 482.0-2, 482.30-32, 482.39,482.40,482.41,482.49,482.81-84,482.89
*Bronchopneumonia - organism not specified 485
*Pneumonia - organism not specified 486
*Acute COPD exacerbation 491.21,491.22
*Bronchiectasis 494.1
*Empyema 510.0,510.9
*Lung abscess 513.0,513.1
*Acute appendicitis 540.0,540.1,540.9
*Appendicitis not 541
*Other appendicitis 542
*Diverticulitis of small intestine without hemorrhage 562.01
*Diverticulitis of small intestine with hemorrhage 562.03
*Diverticulitis of colon without hemorrhage 562.11
*Diverticulitis of colon with hemorrhage 562.13
*Acute cholecystitis 575.0
*Peritonitis 567.0,567.1,567.21,567.22,567.23,567.29
*Anal and rectal abscess 566
*abdominal abscess: 567.31,567.38,567.39,567.81,567.9
*Intestinal abscess 569.5
*Perforation of intestine 569.83
*Abscess of liver 572.0
*Portal pyemia 572.1
*cystitis: 595.0,
*Urethritis/urethral syndrome 597.0
*Urinary tract infection not otherwise specified 599.0,
*Pyelo: 590.10,590.11,590.2,590.3,590.80,590.81,590.9
*Prostatic inflammation 601.0,601.2,601.9,
*Female pelvic inflammation disease 14.0,614.2,614.3,614.5,614.9
*Uterine inflammatory disease 615.0,615.9
*Other female genital inflammation 616.3,616.4,
*orchitis with abscess: 604.0
*Other cellulitis or abscess 682.0-9
*Cellulitis, finger/ toe 681.00,681.01,681.02,681.10,681.11,681.9
*Acute lymphadenitis 683
*Pyogenic arthritis 711.00-09
*Osteomyelitis 730.00-09
*Postoperative infection 998.51,998.59
*Infection or inflammation of device/graft Infection from foleys - 996.64
*Infection from any central line - 999.31
*Infectious complication of medical care not otherwise classified 999.3


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