Background
The incidence and severity of Clostridium difficile infections are increasing. Acid-suppressive therapy has been suggested as a risk factor for C difficile, but this remains controversial.
Methods
We conducted a pharmacoepidemiologic cohort study, performing a secondary analysis of data collected prospectively on 101 796 discharges from a tertiary care medical center during a 5-year period. The primary exposure of interest was acid suppression therapy, classified by the most intense acid suppression therapy received (no acid suppression, histamine2-receptor antagonist [H2RA] therapy, daily proton pump inhibitor [PPI], and PPI more frequently than daily).
Results
As the level of acid suppression increased, the risk of nosocomial C difficile infection increased, from 0.3% (95% confidence interval [CI], 0.21%-0.31%) in patients not receiving acid suppressive therapy to 0.6% (95% CI, 0.49%-0.79%) in those receiving H2RA therapy, to 0.9% (95% CI, 0.80%-0.98%) in those receiving daily PPI treatment, and to 1.4% (1.15%-1.71%) in those receiving more frequent PPI therapy. After adjustment for comorbid conditions, age, antibiotics, and propensity score–based likelihood of receipt of acid-suppression therapy, the association persisted, increasing from an odds ratio of 1 (no acid suppression [reference]) to 1.53 (95% CI, 1.12-2.10) (H2RA), to 1.74 (95% CI, 1.39-2.18) (daily PPI), and to 2.36 (95% CI, 1.79-3.11) (more frequent PPI). Similar estimates were found with a matched cohort analysis and with nested case-control techniques.
Conclusions
Increasing levels of pharmacologic acid suppression are associated with increased risks of nosocomial C difficile infection. This evidence of a dose-response effect provides further support for the potentially causal nature of iatrogenic acid suppression in the development of nosocomial C difficile infection.
Clostridium difficile infection poses a clear and escalating threat to public health. Incidence and severity of disease are increasing,1,2 and costs total more than $1 billion in the United States annually.3 Although other populations are at risk,4 most cases remain both nosocomial and iatrogenic.2 Prevention is therefore paramount, but preventive measures have generally focused on isolation of infected patients, hand hygiene, and antibiotic stewardship.5
Recently, attention has turned to the possible contribution of proton pump inhibitor (PPI) use to the acquisition of C difficile. This association is biologically plausible. More than 2 decades ago, Gurian et al6 showed that more-acidic gastric juices were more effective than less-acidic gastric juices in killing C difficile and neutralizing its toxin. Mice receiving PPIs have similar susceptibility to C difficile infection as mice receiving antibiotics.7 More recently, some,8-11 but not all,11-15 epidemiologic studies have suggested an association between C difficile infection and PPI use, both in the inpatient and outpatient setting. However, a recent review summarized the state of the literature regarding PPI and C difficile infection as remaining “controversial1”; another recent prominent C difficile review did not mention PPIs at all.2
Moreover, little work has addressed whether a dose-response effect exists between acid suppression and C difficile infection,16 in spite of the fact that this is often viewed as one of the epidemiologic pillars of causal inference.17-19 Therefore, we sought to examine the relationship between increasing levels of pharmacologic acid suppression and nosocomial acquisition of C difficile in a large pharmacoepidemiologic cohort.
This was a pharmacoepidemiologic cohort study, in which we performed a secondary analysis of data prospectively collected for other reasons on patients discharged between January 1, 2004, and January 31, 2008, at the Beth Israel Deaconess Medical Center, a large, urban, tertiary care center in Boston, Massachusetts. The hospital's institutional review board approved the study with a waiver of informed consent.
Data were obtained from electronic medical databases created as part of usual care. These databases contain information from each admission, such as demographics, discharge diagnosis codes, medication orders, microbiologic results, length of stay, and inpatient mortality.
All patients who were at least 18 years old and had a length of stay of 3 or more days were included. The outcome of interest, nosocomial C difficile infection, was defined as a newly positive C difficile toxin assay result on or after the third hospital day, a definition used by others.8 Only a first diagnosis of C difficile was included; subsequent admissions of patients with index C difficile infection were excluded.
The primary exposure of interest was receipt of acid suppression therapy. Exposure was classified by the most intense acid suppression therapy received before a positive C difficile test result or hospital discharge, whichever was earlier. The 4 a priori acid suppression groups were no acid suppression therapy, histamine2-receptor antagonist (H2RA) therapy, daily PPI, and PPI more frequently than daily. We used these classifications because they result in stepwise increases in gastric acid suppression20 and because they represent common clinical therapeutic approaches. Because of formulary selections in our hospital, clinical dosing of PPIs closely parallels the defined daily dose21; more than 98% of daily PPIs were equivalent to the defined daily dose.
We collected other potentially important predictors of C difficile infection. We assessed antibiotics received during the hospitalization before a diagnosis of C difficile infection or discharge, categorizing patients as having received no antibiotics, low-risk antibiotics, or high-risk antibiotics. High-risk antibiotics were identified based on the medical literature and included fluoroquinolones, cephalosporins, intravenous β-lactam/β-lactamase inhibitors, macrolides, clindamycin, and carbapenems.13,22,23 Other antibiotics were classified as low risk. To classify patients' comorbidity status, we used the method of Elixhauser et al24 for classification of specific comorbid conditions; we used the Charlson Comorbidity Index25,26 to represent the cumulative burden of comorbid illness.
We performed unadjusted comparisons using the t test, the Mann-Whitney test, the χ2 test, or the Fisher exact test, as appropriate. We used the Kaplan-Meier method to assess time to the C difficile diagnosis. Statistical analyses were performed with SAS software, version 9.1 (SAS Institute Inc, Cary, North Carolina) and SPSS, version 16.0.1 (SPSS Inc, Chicago, Illinois).
Patients for whom physicians prescribe acid-suppressive medications are likely to differ systematically from those who do not receive the medications, resulting in potential selection bias. Thus, in addition to multivariable adjustment for comorbidities, we applied a propensity score adjustment technique. Since the method for propensity score construction for multilevel variables is less well established, as a first step we created a binary propensity score to reflect the probability of receiving the strongest level of acid suppression (PPI more often than daily) compared with no acid suppression therapy. The propensity score was derived from a logistic generalized estimating equation (GEE) model, which included 19 clinical and demographic variables. We then applied the propensity score equation to the rest of the study cohort (the H2RA only and daily PPI groups). Finally, we verified that the mean propensity scores of the 4 exposure groups were correctly ordered (ie, that there was a linear increase from the lowest level of acid-suppressive therapy to the highest). The propensity score was then included in the final logistic GEE regression model, with C difficile infection as the dependent variable.
Because each patient could have been admitted to the hospital more than once during the study period, we used a GEE model to address patient-level clustering, with a dependent variable of nosocomial C difficile infection. To avoid model overfitting, forward stepwise selection was used to identify potentially significant predictors (P < .10) for retention in the model. Model discrimination was assessed using the area under the receiver operating characteristics curve; model fit was tested using the Hosmer-Lemeshow statistic (calculated under the assumption of independent correlation structure of the model). The model included exposure to acid suppression, exposure to prior antibiotics, age, sex, comorbid illness, propensity score, and log-transformed length of stay as an offset variable. Since acquiring C difficile infection results in a longer length of stay, for C difficile–positive patients, length of stay was substituted with time to the diagnosis.
Additional analytic approaches
Because true findings should be resilient to the analytic technique applied, we also analyzed the relationship between acid suppression and C difficile infection using 2 additional approaches.
Cohort Propensity Score Matching
We defined patients with no acid suppression therapy as a reference group. Then all other patients (those with varying acid suppression therapy levels) were matched 1:1 with the reference cohort using a propensity score with caliper of 0.10.27,28 A nearest-neighbor–matching algorithm with a “greedy” heuristic (one that always implements the best immediate or local solution) was applied. In greedy nearest-neighbor matching, a patient from the treatment cohort was randomly selected, and matching was attempted with the “nearest” patient from the reference group. This process was repeated until matches had been attempted for all patients in each acid suppression group. Each matched pair was unique, and data for unmatched patients were not used in subsequent analyses. By this approach, we created 3 matched cohorts: no acid suppression/H2RA; no acid suppression/daily PPI; and no acid suppression/PPI more frequently than daily. We applied a logistic GEE regression in each of the matched cohort pairs.
Nested Matched Case Control
Patients with C difficile infection were matched at a 1:2 ratio by a nearest-neighbor–matching algorithm with a “greedy” heuristic to patients without C difficile infection on the basis of their diagnosis related group, Charlson index with caliper of 1 point, age with caliper of 5 years, and propensity score with caliper of 0.10.27,28 Only cases with 2 controls matched were included in the analysis. Only the first admission for each patient was included. Multivariable conditional logistic regression analysis was then performed with inclusion of 4 groups of acid suppression therapy and adjustment for sex and number of comorbidities.
Lastly, because some hospital services are often believed to be very low risk for C difficile infection, we performed a sensitivity analysis that excluded patients admitted to the obstetrics and psychiatric services.
The study period included 174 224 admissions and 1344 cases of toxin-positive C difficile infection. Of these admissions, 72 428 did not meet inclusion criteria: 72 013 had a length of stay less than 3 days, 447 involved patients who were younger than 18 years, and 177 involved patients who had been diagnosed as having C difficile during prior admissions. Some patients had more than 1 exclusion criterion. Thus, 101 796 admissions were eligible for analysis. Nosocomial C difficile infection occurred in 665 cases (0.7% of admissions). Patients with nosocomial C difficile infection were older, more likely to be male, and more likely to have comorbid conditions such congestive heart failure, renal failure, and cancer. Exposure to antibiotics was strongly associated with development of C difficile, and nosocomial C difficile infection was associated with higher mortality rates (Table 1). Length of stay was strongly associated with the rate of nosocomial C difficile infection (Figure 1): patients hospitalized for less than 7 days had a lower rate of C difficile infection than patients with longer stays (0.4% vs 1.1%; P < .001).
The final propensity score included 19 variables that differentiated between the probability of receiving maximal acid suppression therapy and no acid suppression: age, sex, history of heart failure, chronic lung disease, diabetes mellitus, hypothyroidism, neurologic disorders, chronic liver diseases, gastric ulcer, malignancy, connective tissue diseases, coagulation disorders, AIDS/human immunodeficiency virus, chronic renal failure, obesity, history of weight loss, anemia, alcohol abuse, and history of blood loss. Applying the propensity score formula to all 4 acid suppression exposure groups, from lowest to highest, yielded mean propensity scores of 0.15, 0.19, 0.26, and 0.32. Simple regression demonstrated a strong linear trend based on propensity score analysis, further underscoring the adequacy of our approach.
RISK OF NOSOCOMIAL C DIFFICILE INFECTION
In unadjusted analyses, increasing levels of acid-suppressive therapy were associated with increasing rates of nosocomial C difficile infection. As the level of acid suppression increased, the risk of developing nosocomial C difficile infection increased, from 0.3% (95% confidence interval [CI], 0.21%-0.31%) to 0.6% (95% CI, 0.49%-0.79%), to 0.9% (0.80%-0.98%), to 1.4% (1.15%-1.71%). Antibiotic therapy strongly predicted C difficile infection: 0.2% in patients who did not receive antibiotics, 0.4% in patients treated with low-risk antibiotics, and 1.1% in patients who received high-risk antibiotics (P < .001). Figure 2 shows the risk of C difficile infection, simultaneously stratified by acid suppression therapy and antibiotics.
After adjustment for comorbid conditions, age, receipt of antibiotics, and propensity score–based likelihood of receipt of acid suppression therapy, the association persisted. In our main analysis, which adjusted for propensity score as a continuous variable, we found that as the level of acid suppression increased, the adjusted odds of developing C difficile infection also increased, from an odds ratio (OR) of 1 (reference) to 1.53 (95% CI, 1.12-2.10) for H2RA only, to 1.74 (95% CI, 1.39-2.18) for daily PPI, and to 2.36 (95% CI, 1.79-3.11) for PPI more frequently than daily (Table 2). Because the incidence of C difficile infection in our unexposed cohort is low (0.25%), adjusted ORs are close approximations of adjusted relative risks.29
In addition, receipt of prior antibiotics, age, and comorbid conditions were important risk factors for nosocomial C difficile. Low-risk antibiotics were associated with a near doubling of the odds of C difficile infection, and high-risk antibiotics with a more than 3-fold increase in the odds of disease. The model had good discrimination (area under the receiver operating characteristics curve, 0.77 [95% CI, 0.76-0.79]) and good calibration (P = .64, Hosmer-Lemeshow test).
To ascertain whether our results might be an artifact of the analytic method chosen, we used additional analytic approaches to verify our findings. In our main analysis, we used the entire cohort and adjusted for propensity to receive high-level acid suppression, treating this as a continuous variable. In our first additional approach, we conducted a cohort analysis matched by propensity score. In our second additional approach, we conducted a nested, matched case-control analysis. The results of these different approaches yielded results very similar to the main analysis (Figure 3).
We performed a sensitivity analysis, excluding patients admitted to the psychiatric and obstetrics services, which have low risks of nosocomial C difficile infection. The C difficile infection rate in the remaining cohort of 80 906 admissions was 0.8%. Multivariable GEE analysis demonstrated that the association between acid suppression and C difficile persisted. Compared with no acid suppression, H2RA treatment was associated with an OR of 1.29 (95% CI, 0.94-1.67); daily PPI, with an OR of 1.47 (95% CI, 1.18-1.84); and PPI more frequently than daily, with an OR of 1.98 (95% CI, 1.51-2.59).
This study demonstrates that increasing levels of pharmacologic acid suppression are independently associated with an increased risk of nosocomial C difficile infection. The strength of the association is both clinically and statistically meaningful. Compared with no acid suppression, receipt of a daily PPI was associated with a more than 70% increase in the odds of developing C difficile; patients who received more frequent PPIs had a more than doubling of risk.
We attempted to design a study that would contribute meaningfully to the debate about whether acid suppression contributes causally to nosocomial C difficile infection or is simply a confounder. Although a substantial number of studies have assessed the relationship between PPI use and C difficile infection, with findings on both sides of the issue,8-15 we found none that addressed the question of dose-response effect (biological gradient). In fact, a recent editorial applied all of the commonly used causal criteria first laid out by Sir Austin Bradford Hill17 to the question and found that “none of the studies published to date . . . have yet demonstrated a dose-response curve, whereby a stronger association between PPI exposure and the development of colitis was noted in individuals receiving higher doses of PPIs (biological gradient).”16(p2315) We therefore focused on a key element of the epidemiologic ascertainment of causality—biological gradient.19 Our study provides clear evidence of just such a dose-response effect: more intense acid suppression is associated with increased risks of C difficile infection. In addition to addressing the issue of biological gradient, our results also provide further evidence in support of the temporality, consistency, and strength of the association.
Our study has several additional strengths. First, our cohort is large and includes all consecutive adults meeting inclusion criteria, limiting the likelihood of selection bias. Second, we ensured that acid suppression and antibiotic exposure occurred before development of C difficile, addressing the temporality criterion of Bradford Hill.17 Third, we adjusted for the burden of comorbid disease, a criticism of some prior studies.30,31 Fourth, we controlled for the likelihood of administration of more-intense acid suppression therapy using techniques commonly recommended in pharmacoepidemiology.32 Finally, our results were resilient to the specific analytic technique applied, with remarkably similar estimates of the dose-response relationship.
Our study also has several key limitations. First, it remains an observational study. A randomized design would provide greater confidence in our findings. However, conducting a randomized controlled trial to assess whether a therapy causes C difficile infection would ethically be problematic. In addition, because the acquisition of C difficile is a relatively rare event, such a trial would be very large and therefore costly. Second, there may be residual confounding. We attempted to control for selection bias using careful application of propensity score–based techniques and further adjusted for significant confounders, but unmeasured variables may still cause residual confounding. Effect estimates, as expected, moved closer to the null as we adjusted for covariates, but the magnitude of effect still remains plausibly large. Third, we were unable to collect information about use of acid-suppressive medications or antibiotics before admission, which could be an important effect modifier.
These results may have important public health implications. Our results suggest that, compared with no acid suppression, we should expect at least 1 additional case of nosocomial C difficile infection for every 533 patients who receive a daily PPI, after controlling for other risk factors. (This is based on a nosocomial C difficile infection incidence of 0.3% in patients receiving no acid suppression and an adjusted increase of 70% in odds of disease in patients receiving daily PPIs.) Although this seems like a relatively large number-needed-to-harm, the magnitude of exposure is large. We found that 60% of patients received acid-suppressive therapy, similar to others' estimates.33-35 Since there are about 32.7 million annual adult discharges in the United States annually,36 the number of potentially attributable nosocomial C difficile cases in the United States numbers in the tens of thousands per year. This is particularly important, since prior work has found that more than two-thirds of inpatient acid-suppressive prescriptions are not strictly indicated.33-35
In conclusion, we found that the intensity of acid-suppressive therapy was strongly and independently associated with the development of nosocomial C difficile infection. Although determining causality is an extremely complex process,18 it seems unlikely that a randomized controlled trial of acid suppressive therapy, with a primary outcome of nosocomial C difficile infection, will ever be conducted. Our study therefore adds new key information about the dose-response relationship between acid-suppressive medications and nosocomial C difficile infection. Given the importance of nosocomial C difficile infection to individual patient outcomes, hospitals, health systems, and physicians can take several reasonable, important steps even in the absence of randomized controlled trials. First, physicians should ensure that each patient receives the least-intense acid-suppressive therapy that is appropriate for his or her clinical condition. In particular, unless and until there is clear evidence that low-risk, noncritically ill patients receive benefit from stress ulcer prophylaxis,37 we should strive to minimize exposure to acid-suppressive medications in this group. Many intensive care unit patients are also at low risk for clinically significant gastrointestinal tract bleeding,38 and guidelines have not recommend prophylaxis for these patients.39 Hospitals can also take an important step in this regard by re-examining any standing protocols for low-risk patients that include stress ulcer prophylaxis by default and by ensuring that prophylactic medications are not continued beyond discharge.40-42 Finally, future interventional trials of acid-suppressive medications in inpatients should actively collect information about incident C difficile infection and other adverse events. Researchers can also further help reduce uncertainty in this field by using risk-benefit analysis to create tools that help select patients in whom stress ulcer prophylaxis may be clearly beneficial or clearly harmful.
Correspondence: Michael D. Howell, MD, MPH, Critical Care Quality, Silverman Institute for Healthcare Quality and Safety, Beth Israel Deaconess Medical Center, 330 Brookline Ave, Boston, MA 02215 (mhowell@bidmc.harvard.edu).
Accepted for Publication: February 10, 2010.
Author Contributions:Study concept and design: Howell, V. Novack, Grgurich, Soulliard, L. Novack, and Talmor. Acquisition of data: Howell. Analysis and interpretation of data: Howell, V. Novack, L. Novack, Pencina, and Talmor. Drafting of the manuscript: Howell, V. Novack, Grgurich, Soulliard, and Talmor. Critical revision of the manuscript for important intellectual content: V. Novack, Grgurich, Pencina, and Talmor. Statistical analysis: Howell, V. Novack, L. Novack, and Pencina. Administrative, technical, and material support: Grgurich, Soulliard, and Talmor. Study supervision: Howell.
1.Blossom
DBMcDonald
LC The challenges posed by reemerging
Clostridium difficile infection.
Clin Infect Dis 2007;45
(2)
222- 227
PubMedGoogle Scholar 2.Kelly
CPLaMont
JT
Clostridium difficile—more difficult than ever.
N Engl J Med 2008;359
(18)
1932- 1940
PubMedGoogle Scholar 3.Kyne
LHamel
MBPolavaram
RKelly
CP Health care costs and mortality associated with nosocomial diarrhea due to
Clostridium difficile.
Clin Infect Dis 2002;34
(3)
346- 353
PubMedGoogle Scholar 4.Centers for Disease Control and Prevention (CDC), Severe
Clostridium difficile–associated disease in populations previously at low risk—four states, 2005.
MMWR Morb Mortal Wkly Rep 2005;54
(47)
1201- 1205
PubMedGoogle Scholar 5.Vonberg
RPKuijper
EJWilcox
MH
et al. European C difficile–Infection Control Group; European Centre for Disease Prevention and Control (ECDC), Infection control measures to limit the spread of
Clostridium difficile.
Clin Microbiol Infect 2008;14
((suppl 5))
2- 20
PubMedGoogle Scholar 6.Gurian
LWard
TTKaton
RM Possible foodborne transmission in a case of pseudomembranous colitis due to
Clostridium difficile: influence of gastrointestinal secretions on Clostridium difficile infection.
Gastroenterology 1982;83
(2)
465- 469
PubMedGoogle Scholar 7.Kaur
SVaishnavi
CPrasad
KKRay
PKochhar
R Comparative role of antibiotic and proton pump inhibitor in experimental
Clostridium difficile infection in mice.
Microbiol Immunol 2007;51
(12)
1209- 1214
PubMedGoogle Scholar 8.Aseeri
MSchroeder
TKramer
JZackula
R Gastric acid suppression by proton pump inhibitors as a risk factor for
Clostridium difficile–associated diarrhea in hospitalized patients.
Am J Gastroenterol 2008;103
(9)
2308- 2313
PubMedGoogle Scholar 9.Choudhry
MNSoran
HZiglam
HM Overuse and inappropriate prescribing of proton pump inhibitors in patients with
Clostridium difficile–associated disease.
QJM 2008;101
(6)
445- 448
PubMedGoogle Scholar 10.Dial
SAlrasadi
KManoukian
CHuang
AMenzies
D Risk of
Clostridium difficile diarrhea among hospital inpatients prescribed proton pump inhibitors: cohort and case-control studies.
CMAJ 2004;171
(1)
33- 38
PubMedGoogle Scholar 11.Lowe
DOMamdani
MMKopp
ALow
DEJuurlink
DN Proton pump inhibitors and hospitalization for
Clostridium difficile–associated disease: a population-based study.
Clin Infect Dis 2006;43
(10)
1272- 1276
PubMedGoogle Scholar 12.Beaulieu
MWilliamson
DPichette
GLachaine
J Risk of
Clostridium difficile–associated disease among patients receiving proton-pump inhibitors in a Quebec medical intensive care unit.
Infect Control Hosp Epidemiol 2007;28
(11)
1305- 1307
PubMedGoogle Scholar 13.Pépin
JSaheb
NCoulombe
MA
et al. Emergence of fluoroquinolones as the predominant risk factor for
Clostridium difficile–associated diarrhea: a cohort study during an epidemic in Quebec.
Clin Infect Dis 2005;41
(9)
1254- 1260
PubMedGoogle Scholar 14.Shah
SLewis
ALeopold
DDunstan
FWoodhouse
K Gastric acid suppression does not promote clostridial diarrhoea in the elderly.
QJM 2000;93
(3)
175- 181
PubMedGoogle Scholar 15.Wilcox
MHMooney
LBendall
RSettle
CDFawley
WN A case-control study of community-associated
Clostridium difficile infection.
J Antimicrob Chemother 2008;62
(2)
388- 396
PubMedGoogle Scholar 16.Metz
DC
Clostridium difficile colitis: wash your hands before stopping the proton pump inhibitor.
Am J Gastroenterol 2008;103
(9)
2314- 2316
PubMedGoogle Scholar 17.Hill
AB The environment and disease: association or causation?
Proc R Soc Med 1965;58295- 300
PubMedGoogle Scholar 18.Rothman
KJGreenland
S Causation and causal inference in epidemiology.
Am J Public Health 2005;95
((suppl 1))
S144- S150
PubMedGoogle Scholar 19.Swaen
Gvan Amelsvoort
L A weight of evidence approach to causal inference.
J Clin Epidemiol 2009;62
(3)
270- 277
PubMedGoogle Scholar 20.Huang
JQHunt
RH Pharmacological and pharmacodynamic essentials of H(2)-receptor antagonists and proton pump inhibitors for the practising physician.
Best Pract Res Clin Gastroenterol 2001;15
(3)
355- 370
PubMedGoogle Scholar 21.World Health Organization, International language for drug utilization research. 2009;
http://www.whocc.no/. Accessed January 30, 2010
22.Baxter
RRay
GTFireman
BH Case-control study of antibiotic use and subsequent
Clostridium difficile–associated diarrhea in hospitalized patients.
Infect Control Hosp Epidemiol 2008;29
(1)
44- 50
PubMedGoogle Scholar 23.Winston
DJLazarus
HMBeveridge
RA
et al. Randomized, double-blind, multicenter trial comparing clinafloxacin with imipenem as empirical monotherapy for febrile granulocytopenic patients.
Clin Infect Dis 2001;32
(3)
381- 390
PubMedGoogle Scholar 24.Elixhauser
ASteiner
CHarris
DRCoffey
RM Comorbidity measures for use with administrative data.
Med Care 1998;36
(1)
8- 27
PubMedGoogle Scholar 25.Charlson
MEPompei
PAles
KLMacKenzie
CR A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.
J Chronic Dis 1987;40
(5)
373- 383
PubMedGoogle Scholar 26.Quan
HSundararajan
VHalfon
P
et al. Coding algorithms for defining comorbidities in
ICD-9-CM and
ICD-10 administrative data.
Med Care 2005;43
(11)
1130- 1139
PubMedGoogle Scholar 27.Moss
RRHumphries
KHGao
M
et al. Outcome of mitral valve repair or replacement: a comparison by propensity score analysis.
Circulation 2003;108
((suppl 1))
II90- II97
PubMedGoogle Scholar 28.Austin
PC Some methods of propensity-score matching had superior performance to others: results of an empirical investigation and Monte Carlo simulations.
Biom J 2009;51
(1)
171- 184
PubMedGoogle Scholar 29.Zhang
JYu
KF What's the relative risk? a method of correcting the odds ratio in cohort studies of common outcomes.
JAMA 1998;280
(19)
1690- 1691
PubMedGoogle Scholar 30.Leffler
DCloud
JWKelly
CP Gastric acid–suppressive agents and risk of
Clostridium difficile–associated disease.
JAMA 2006;295
(22)
2599- 2600
PubMedGoogle Scholar 31.Dial
SDelaney
JACBarkun
ANSuissa
S Gastric acid–suppressive agents and risk of
Clostridium difficile–associated disease [in reply].
JAMA 2006;295
(22)
2600- 2591
Google Scholar 32.Perkins
SMTu
WUnderhill
MGZhou
XHMurray
MD The use of propensity scores in pharmacoepidemiologic research.
Pharmacoepidemiol Drug Saf 2000;9
(2)
93- 101
PubMedGoogle Scholar 33.Pham
CQRegal
REBostwick
TRKnauf
KS Acid suppressive therapy use on an inpatient internal medicine service.
Ann Pharmacother 2006;40
(7-8)
1261- 1266
PubMedGoogle Scholar 34.Parente
FCucino
CGallus
S
et al. Hospital use of acid-suppressive medications and its fall-out on prescribing in general practice: a 1-month survey.
Aliment Pharmacol Ther 2003;17
(12)
1503- 1506
PubMedGoogle Scholar 35.Nardino
RJVender
RJHerbert
PN Overuse of acid-suppressive therapy in hospitalized patients.
Am J Gastroenterol 2000;95
(11)
3118- 3122
PubMedGoogle Scholar 37.Janicki
TStewart
S Stress-ulcer prophylaxis for general medical patients: a review of the evidence.
J Hosp Med 2007;2
(2)
86- 92
PubMedGoogle Scholar 38.Cook
DJFuller
HDGuyatt
GH
et al. Canadian Critical Care Trials Group, Risk factors for gastrointestinal bleeding in critically ill patients.
N Engl J Med 1994;330
(6)
377- 381
PubMedGoogle Scholar 39.ASHP Therapeutic Guidelines on Stress Ulcer Prophylaxis, ASHP Therapeutic Guidelines on Stress Ulcer Prophylaxis: ASHP Commission on Therapeutics and approved by the ASHP Board of Directors on November 14, 1998.
Am J Health Syst Pharm 1999;56
(4)
347- 379
PubMedGoogle Scholar 40.Farrell
CPMercogliano
GKuntz
CL Overuse of stress ulcer prophylaxis in the critical care setting and beyond [published online ahead of print August 14, 2009].
J Crit Care 10.1016/j.jcre.2009.05.014
PubMedGoogle Scholar 41.Murphy
CEStevens
AMFerrentino
N
et al. Frequency of inappropriate continuation of acid suppressive therapy after discharge in patients who began therapy in the surgical intensive care unit.
Pharmacotherapy 2008;28
(8)
968- 976
PubMedGoogle Scholar 42.Wohlt
PDHansen
LAFish
JT Inappropriate continuation of stress ulcer prophylactic therapy after discharge.
Ann Pharmacother 2007;41
(10)
1611- 1616
PubMedGoogle Scholar