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Original Contribution |

Statin Use and Hospitalization for Sepsis in Patients With Chronic Kidney Disease FREE

Rajesh Gupta, MD; Laura C. Plantinga, ScM; Nancy E. Fink, MPH; Michal L. Melamed, MD, MHS; Josef Coresh, MD, PhD; Caroline S. Fox, MD, MPH; Nathan W. Levin, MD; Neil R. Powe, MD, MPH, MBA
[+] Author Affiliations

Author Affiliations: Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Md (Drs Gupta, Coresh, and Powe and Mss Plantinga and Fink); Department of Epidemiology (Ms Fink and Drs Coresh and Powe), Department of Biostatistics (Dr Coresh), and Department of Health Policy and Management (Dr Powe), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md; Departments of Medicine and Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY (Dr Melamed); National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, Mass (Dr Fox); and Renal Research Institute, New York, NY (Dr Levin). Dr Gupta is now with the Division of Cardiology, Northwestern University, Chicago, Ill.

More Author Information
JAMA. 2007;297(13):1455-1464. doi:10.1001/jama.297.13.1455.
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Published online

Context Patients with chronic kidney disease are at high risk for sepsis and sepsis-related mortality.

Objective To assess whether statin use is associated with a reduction in hospitalizations for sepsis in dialysis patients.

Design, Setting, and Patients National prospective cohort study that enrolled 1041 incident dialysis patients at 81 US not-for-profit outpatient dialysis clinics from October 1995 to June 1998, with follow-up to January 2005. Statin use was determined by medical record review. Rates of hospitalization for sepsis between statin users and control patients were compared using multivariate regression models, with adjustment for potential confounders in the overall cohort and in a subcohort in which control patients were matched to statin users according to their likelihood (propensity) to have been prescribed a statin.

Main Outcome Measure Hospitalizations for sepsis were determined through hospital records from the United States Renal Data System (mean follow-up, 3.4 years).

Results There were 303 hospitalizations for sepsis. Rates of sepsis-related hospitalizations were significantly lower in patients receiving statins (crude incidence rate, 41/1000 patient-years) than in those not receiving statins (crude incidence rate, 110/1000 patient-years) (P<.001). With adjustment for demographics and dialysis modality, statin users were substantially less likely to be subsequently hospitalized for sepsis (incidence rate ratio, 0.41; 95% confidence interval [CI], 0.25-0.68). Further adjustment for comorbidities and laboratory values continued to show this protective association (incidence rate ratio, 0.38; 95% CI, 0.21-0.67). In the propensity-matched subcohort, statin use was even more protective (incidence rate ratio, 0.24; 95% CI, 0.11-0.49).

Conclusions Use of statins was strongly and independently associated with a reduction in the risk of hospitalization for sepsis in patients who had chronic kidney disease and were receiving dialysis. Randomized trials of statins in patients with chronic kidney disease should examine the prevention of sepsis as a potentially important benefit.

Sepsis is a major cause of morbidity and mortality in patients who have chronic kidney disease and are receiving dialysis. Patients receiving dialysis have rates of sepsis that are significantly higher than those of patients without kidney disease, and dialysis patients have higher rates of mortality from sepsis.1 In addition, rates of sepsis have been increasing during the last few decades.2 Although studies have attempted to identify risk factors associated with sepsis in the general population3 and in patients with kidney disease,4,5 no preventive treatment has been identified.

Statins are cholesterol-reducing medications that have become a cornerstone of primary and secondary prevention of cardiovascular disease. In recent years, pleiotropic effects of statins have been highlighted.68 Statins have been found to reduce cardiovascular events regardless of baseline low-density lipoprotein (LDL) cholesterol level,9 and they have been shown to reduce inflammatory factors such as C-reactive protein, which is also associated with a reduction in the rate of cardiovascular events.10,11

Experimental evidence in animals has indicated that statins may prevent sepsis and modulate the severity of sepsis.1214 Two smaller observational studies in humans have shown lower rates of sepsis-related mortality among patients being treated with statins and a reduction in the incidence and severity of sepsis among patients treated with statins.15,16 A recent larger, population-based cohort study found a reduction in the incidence of sepsis among patients who were prescribed a statin after being hospitalized for a cardiovascular event.17

Therefore, our aim was to assess the effect of treatment with statin medications on the rates of sepsis in a prospective cohort study of patients who had chronic kidney disease and were receiving dialysis. We hypothesized that statins would reduce the incidence of sepsis among these high-risk patients.

Study Design and Population

We conducted a national prospective cohort study of incident dialysis patients by examining the association of statin use with the occurrence of sepsis. The CHOICE (Choices for Healthy Outcomes in Caring for ESRD) study was initiated in 1995 to investigate treatment choices and outcomes of dialysis care. Eligibility criteria for enrollment included initiation of long-term outpatient dialysis in the preceding 3 months, ability to provide informed consent, age older than 17 years, and ability to speak English or Spanish. The Johns Hopkins School of Medicine institutional review board and the review boards for the clinical centers approved the study protocol.

From October 1995 to June 1998, 1041 participants from 19 states were enrolled at 81 dialysis clinics associated with Dialysis Clinic Inc (Nashville, Tenn; n = 923), New Haven CAPD (New Haven, Conn; n = 86), or Saint Raphael's Hospital (New Haven, Conn; n = 32). A specimen bank was established to store blood samples from the Dialysis Clinic Inc enrollees, and specimens were obtained for 895 (97.0%) of the Dialysis Clinic Inc participants.

Measurements

Statin use at baseline was determined by review of dialysis clinic notes, hospital discharge summaries, and computerized order entry records.18 Statin medications used by patients included lovastatin, fluvastatin, pravastatin, simvastatin, and atorvastatin.

Data about patient demographics, health behaviors, work history, medical history, preparation for dialysis, and history of sepsis were collected from a baseline self-report questionnaire. Race/ethnicity was initially assessed in CHOICE because dialysis patient outcomes (including sepsis) were known to differ by race.4 Race/ethnicity was self-reported by patients, with the following investigator-defined categories: white not Hispanic, Hispanic, African American, Asian or Pacific Islander, and other. For the purposes of analyses and because of small numbers in certain groups, we categorized race as white, black, or other. Height and weight were obtained from the Centers for Medicare & Medicaid Medical Evidence Report (form 2728). Dialysis modality at baseline was defined as the modality at 4 weeks after study enrollment. Late referral was defined as a first visit with a nephrologist less than 4 months before onset of dialysis.19 Vascular access information was obtained through review of discharge summaries, dialysis flow sheets, and dialysis clinic progress notes.20 Rates of calcitriol treatment were obtained from Medicare billing data through the United States Renal Data System. Frequency of sit-down rounds at the dialysis unit, a process measure of the quality of care associated with outcomes, was based on clinic surveys and categorized as monthly, more often than monthly, or less than monthly.21

Comorbidity was assessed using the Index of Coexistent Disease, an instrument that has been validated as a predictor of death in dialysis populations. The Index of Coexistent Disease score ranges from 0 to 3, with 3 as the highest severity level, and is a composite measure of both the presence and severity of different comorbid conditions.22,23 Individual comorbidities, except history of sepsis, were abstracted from dialysis unit records, hospital discharge summaries, medication lists, consultation notes, diagnostic imaging, and cardiac imaging reports, which were collected at each dialysis unit, photocopied, and sent to New England Medical Center for abstraction and scoring. Two dialysis nurses, with previous training and experience in using the Index of Coexistent Disease, reviewed and scored all records. The reliability of data abstraction and severity scoring was assessed with a masked recoding of 45 medical records. Interrater reliability for Index of Coexistent Disease score was high (κ = 0.93).

Baseline nonfasting venous blood specimens were routinely collected at the Dialysis Clinic Inc facilities just before a dialysis session. Laboratory values for albumin, creatinine, and hematocrit were obtained from monthly laboratory tests at dialysis clinics. For patients in the specimen bank, specimens were also sent overnight to the central laboratory, where they were stored at −80°C. More than 95% of samples were frozen within 48 hours of venipuncture. Total and LDL cholesterol levels were obtained from aliquoted samples sent to Quest Diagnostics (Baltimore, Md). C-reactive protein and interleukin 6 values were obtained from analysis at the University of Vermont, Colchester.

Outcomes Ascertainment

The observation period for each patient began on the date of enrollment and continued until January 1, 2005. The primary outcome was hospitalization for sepsis. We used the United States Renal Data System hospitalization data to determine the primary cause for each hospitalization. We defined hospitalization for sepsis as any hospitalization in which the primary International Classification of Diseases, Ninth Revision (ICD-9) code was 038.0 to 038.9 (septicemia) or 790.7 (bacteremia).3International Classification of Diseases coding information for sepsis has been used widely in other studies of sepsis.2,17 The sensitivity and specificity of ICD-9 codes for sepsis have been evaluated by comparing ICD-9 information with medical record review, using clinical consensus definitions of sepsis. The sensitivity of ICD-9 codes was found to be 75.4% to 87.7%, depending on the specific ICD-9 codes used.24 The positive predictive value of 038.x codes for sepsis was found to be 88.9% to 97.7%, depending on the clinical definition of sepsis.2 Only episodes in which the primary cause of hospitalization was sepsis were included in our analysis to avoid including cases in which infection was acquired during hospitalization.

Statistical Analysis

To assess the presence, direction, strength, and statistical significance of an association between statin use and sepsis, we performed 2 analyses: a multivariate Poisson regression analysis on the entire CHOICE cohort, comparing occurrence of sepsis in statin users vs all other patients; and an analysis comparing occurrence of sepsis in statin users vs a control group identified through propensity-score matching. For both analyses, we compared patients initially receiving a statin vs control patients who were not receiving a statin. Baseline characteristics of the study groups were compared with the χ2 test for categorical variables and t test for continuous variables. Crude incidence rates of sepsis were calculated by dividing the total number of hospitalizations for sepsis by the cumulative time at risk for each group. Time at risk for sepsis started with enrollment or the Medicare eligibility date, if the patient was not Medicare eligible at the start of the study. Time during hospitalization was excluded from time at risk. Patients were censored at death or kidney transplantation.

In the first analysis, multivariate Poisson regression models were used to obtain incidence rate ratios adjusted for potential cofounders. Potential confounders were identified by assessing the relation between each variable and use of statins and risk of hospitalization for sepsis (P≤.20 for both associations). Also, clinically relevant variables that did not meet these statistical criteria were still included to derive a full nonparsimonious model. By these criteria, the confounders included in the models were demographic information (age, sex, race, education level, and employment status), dialysis modality, comorbidities (history of myocardial infarction, cerebrovascular disease or transient ischemic attack, peripheral vascular disease, diabetes mellitus, sepsis, and Index of Coexistent Disease score), and laboratory measures (albumin, total cholesterol, hematocrit, C-reactive protein, and interleukin 6). No pairs of covariates with correlations greater than or equal to 0.7 were added to the models to avoid issues of collinearity. Subgroup analyses by age, sex, dialysis modality, diabetic status, malignancy history, sepsis history, C-reactive protein, LDL, and comorbidity were also performed.

In the second analysis, we also calculated incidence rates of sepsis and the incidence rate ratios in a propensity-matched subcohort. Propensity score matching is an established method to address a major limitation of observational studies, namely, confounding by indication.25,26 A propensity score is calculated as the estimated probability from logistic regression of a patient's being assigned to a given intervention, in this case, a statin. The following variables were used in the regression model to derive this propensity score for each patient: age, sex, race, history of myocardial infarction, cerebrovascular accident, peripheral vascular disease, diabetes mellitus, total cholesterol level, baseline dialysis modality, education level, and employment status. Variables were chosen because they were a clinical indication for statin use, clinically related to statin use, or statistically associated with statin use. Total cholesterol was treated as a categorical variable by dividing total cholesterol levels into 2 groups, less than 200 and greater than or equal to 200 mg/dL. Of the initial 143 statin users, 107 had complete information on all variables necessary to generate propensity scores. Using a greedy algorithm with a 5-digit match, each of these patients was matched to a control patient who had a similar probability of receiving a statin.27 The 5-digit algorithm proceeds sequentially through 5-, 4-, 3-, 2-, and 1-digit matches on possible controls' propensity scores for each case, and once a control is selected, it is out of the pool, making the algorithm “greedy.”

We also performed several sensitivity analyses to test the robustness of our results. First, we used multiple methods to control for the possibility that certain patients may have had a disproportionate risk of sepsis. We analyzed patients who had more than 1 hospitalization for sepsis according to their first hospitalization only, ie, if a patient had 2 or more sepsis-related hospitalizations, we changed their total count to 1 but kept the same at-risk time used in the primary analyses. Additionally, Cox proportional hazards models, with stratification by clinic and censoring at patient death, transplant, or last date of follow-up (December 31, 2004), were also used to examine time to first sepsis-related hospitalization. We also excluded patients with a history of sepsis from multivariate and propensity-matched analyses to test whether this affected our results. Second, although drug and alcohol abuse are risk factors for sepsis, we had limited data on these variables. For this reason, we identified the subset of patients for whom these variables were known and then performed sensitivity analyses including all of the potential confounders cited above, with and without the addition of drug and alcohol abuse to assess the effect of these variables. Third, there is experimental evidence that activated 1,25-dihydroxycholecalciferol may modulate the response to infection in endothelial cells.28 We assessed whether treatment for secondary hyperparathyroidism was significantly different between the statin group and the control group, and we added baseline calcitriol treatment information to a multivariate model to test whether it would change the relationship between statin use and sepsis. Fourth, statin use may be a marker of high-quality care. We added quality-of-care markers for predialysis care (late referral to a nephrologist) and for postdialysis care (frequency of dialysis unit sit-down rounds) to a multivariate model to determine whether quality-of-care variables would affect the relationship between statin use and sepsis. Fifth, we accounted for overdispersion in the distribution of our count data by examining the results with negative binomial modeling. Sixth, because we did not have cholesterol values before statin treatment, we excluded cholesterol from the list of variables used to derive the propensity score and then reconstructed a new propensity-matched subcohort comparing the results with the original propensity-matched subcohort. Finally, adjustment in the full cohort analysis for the propensity score was also performed.

The possibility of confounding by clinic was controlled with fixed-effects modeling, clustered on the clinic, which accounted for within-clinic correlation and between-clinic differences in baseline incidence. A 2-sided P<.05 was used as the level of statistical significance for all tests. Statistical analyses were performed using Stata software, version 8.2 (StataCorp, College Station, Tex) and SAS system for Windows, version 9.1 (SAS Institute Inc, Cary, NC).

Patient Characteristics

Almost 14% of patients were receiving a statin at baseline and 86% were not (Table 1). Patients receiving a statin were more likely to be white; less likely to have ever used street drugs; more likely to receive peritoneal dialysis; more likely to have a higher hematocrit level; less likely to have a late referral to a nephrologist; more likely to have a higher total and LDL cholesterol level; more likely to have a history of diabetes mellitus (or diabetes as an assigned cause of end-stage renal disease), myocardial infarction, cerebrovascular accident, or peripheral vascular disease; and more likely to have a history of sepsis. Statin users tended to consume less alcohol per week and had higher education levels and employment rates, although these characteristics were not statistically significant.

Table Graphic Jump LocationTable 1. Baseline Characteristics of Patients in the CHOICE Cohort, by Statin Use

In the propensity-matched subcohort, the only variable that was significantly different between statin users and control patients was history of sepsis (Table 2), with statin users more likely to have a history of sepsis.

Table Graphic Jump LocationTable 2. Baseline Characteristics of Patients in the Propensity-Matched Subcohort, by Statin Use
Risk of Sepsis by Statin Use in the Entire Cohort

Among all 1041 patients, there were a total of 303 hospitalizations for sepsis during follow-up (mean, 3.4 years). The crude incidence rate of sepsis among statin users was 41 per 1000 patient-years exposed compared with 110 per 1000 patient-years exposed in the control group. The crude incidence rate ratio of sepsis was 0.37 (95% confidence interval [CI], 0.22-0.61) (Table 3) or 63% lower in the statin group compared with the control group. After adjustment for demographic characteristics, dialysis modality, comorbidities, and laboratory values, the risk of hospitalization for sepsis remained statistically significantly lower by 62% among statin users (Table 3, Model 3).

Table Graphic Jump LocationTable 3. Ratio of the Rate of Hospitalization for Sepsis (Statin Group vs Control Group) in the Entire CHOICE Cohort and the Propensity-Matched Subcohort

The protective association of statin use on rates of sepsis was present in nearly all subgroups analyzed (Table 4).

Table Graphic Jump LocationTable 4. Ratio of the Rate of Hospitalization for Sepsis (Statin Group vs Control Group) in Subgroups of the Entire CHOICE Cohort: Unadjusted, Multivariate, and Propensity Score–Adjusted Analyses
Risk of Sepsis by Statin Use in the Propensity-Matched Subcohort

Among the 214 patients who were matched according to their propensity to have been prescribed a statin, there were 54 hospitalizations during follow-up. The relative risk of sepsis per 1000 patient-years was 0.24 (95% CI, 0.11-0.49) for statin users compared with nonusers (Table 3), or 76% lower among statin users. There was evidence of possible interactions between subgroup characteristics and statin use in the propensity-matched subcohort by age (P = .06), dialysis modality (P = .08), and C-reactive protein (P = .05).

Sensitivity Analyses

First, we used multiple methods to address the possibility that certain patients may have had a disproportionate risk of sepsis. In the overall cohort, we found that 110 patients had 1 episode of sepsis, 25 patients had 2 episodes, and 30 patients had 3 or more episodes. Limiting the outcomes to include only the first hospitalization, we found that the incidence rate ratio of sepsis was 0.50 (95% CI, 0.26-0.99). Next, Cox models examining time to first sepsis hospitalization gave an adjusted relative hazard of 0.50 (95% CI, 0.25-0.98). When patients with a history of sepsis were excluded from the full multivariate model and the propensity-matched subcohort, the incidence rate ratios were 0.40 (95% CI, 0.22-0.73) and 0.24 (95% CI, 0.11-0.51), respectively. Second, we controlled for baseline reported street drug use and heavy alcohol use by adding these 2 variables to the full multivariate model within the subset of patients for whom these variables were known; incidence rate ratio was 0.31 (95% CI, 0.14-0.69). It was 0.30 (95% CI, 0.13-0.67) within this subset of patients, without the addition of drug and alcohol use variables, showing that rates of sepsis were not materially affected by these variables. Third, when calcitriol use was added to the full multivariate model, the incidence rate ratio was 0.27 (95% CI, 0.11-0.71). Fourth, when we added quality-of-care markers, including late referral to a nephrologist and clinic frequency of sit-down rounds, to the multivariate model, the incidence rate ratio was 0.29 (95% CI, 0.14-0.60). Fifth, the use of a negative binomial model to account for possible overdispersion gave an incidence rate ratio of 0.60 (95% CI, 0.26-0.98). Sixth, when we calculated propensity score without using cholesterol as a predictor, the incidence rate ratio was 0.24 (95% CI, 0.11-0.49). Last, adjustment for propensity scores in the entire cohort also yielded similar results (Table 3, Model 4).

In this national prospective cohort study of patients who had chronic kidney disease and began receiving dialysis, statin use was associated with a large and statistically significant reduction in the incidence of sepsis. After controlling for potential confounding in a multivariate model, this association remained strong and statistically significant. Additionally, the protective association of statins on the incidence of sepsis was present and even stronger in a propensity-matched subcohort analysis.

Several mechanisms may explain the observed protective effect of statins on the occurrence of sepsis. Statins are known to have immunomodulatory properties.2932 Statins may regulate the immune response to infection, thereby minimizing the risk of clinical sepsis in patients with infections. In animal models of sepsis, animals pretreated with statins before induction of sepsis had higher rates of survival.12,14 It is possible that statins reduce the production of cytokines or mitigate the vasodilatory response to cytokines that results in septic shock.13 Statins may also have direct antimicrobial effects, as shown by studies of the effects of statin medications on human immunodeficiency virus, Salmonella, and yeast growth.3336 Indeed, the first statin was originally identified from a fungus, Penicillium citrinum, and it has been postulated that this fungal organism secretes a statin as a selective advantage to prevent replication of competing microorganisms that require cholesterol for growth.37,38

Three clinical studies in nonrenal disease cohorts have compared the rates of sepsis in patients treated with statins to those of control (or untreated) patients. In a retrospective cohort study of 388 patients with bacteremia, Liappis et al15 found a significant reduction in mortality among patients who were taking a statin at their hospitalization. Almog et al16 conducted a prospective cohort study of 361 patients hospitalized with an acute bacterial infection and found a significantly lower rate of severe sepsis and intensive care unit admission among statin users. More recently, a larger study of patients hospitalized for cardiovascular events found that treatment with a statin medication was associated with a lower incidence of sepsis during a mean follow-up of 2.2 years.17 A meta-analysis of 90 056 trial participants39 showed that death from nonvascular causes was reduced in patients who were treated with cholesterol-lowering medications, but infectious causes were not examined separately. Specific to the dialysis population, the Deutsche Diabetes Dialyse Studie trial40 of atorvastatin use in diabetic hemodialysis patients showed that fatal infection was not different between the placebo and atorvastatin groups; however, the nonfatal infection rate and sepsis in particular were not examined. A study recently under way, the Study of Heart and Renal Protection, may have the opportunity to examine the effects of statin use on the incidence and severity of sepsis in patients with chronic kidney disease.41

Our study has certain limitations. This was a prospective, observational study. Observational studies are limited by confounding by indication for treatment because of lack of randomization. We attempted to control for this issue in multiple ways. We considered and adjusted for a large number of potential confounders. Additionally, we compared outcomes in a propensity-matched subcohort of patients who had similar likelihoods of being prescribed a statin. We performed multiple sensitivity analyses to further test our results. After controlling for confounding through these multiple methods, we continued to find a strong and statistically significant protective association between statin use and the incidence of sepsis. Nonetheless, the possibility that unmeasured bias affected our results cannot be entirely excluded.

In particular, the risk of confounding by indication must be addressed because the relationship between cholesterol and mortality in dialysis patients is complex. Multiple studies have shown an inverse relationship between cholesterol and mortality for patients receiving dialysis.4244 Statin use could be a marker for higher cholesterol levels. Recently, it has been shown that the presence of inflammation or malnutrition can explain the inverse relationship between cholesterol and mortality.45 In our study, the markers of inflammation and malnutrition, namely, albumin, C-reactive protein, and interleukin 6, were similar between statin users and controls. Because the paradoxic association between cholesterol and mortality among dialysis patients can be explained by the presence of inflammation or malnutrition and because the statin and control groups in our study had similar markers of inflammation and malnutrition, it is unlikely that the protective association found among statin use and incidence of sepsis can be ascribed to higher cholesterol levels in the statin group.

Another limitation of our study is that most patient and treatment factors were assessed at baseline. For factors that may change over time, such as vascular access, medication prescriptions, and dialysis modality, this assessment timing may lead to misclassification. However, statin misclassification would have most likely led to a dilution of any true protective effect if patients in the control group were in fact treated with statins or if patients in the statin group discontinued their medication. Given that misclassification and patient crossover between statin and control groups tend to favor the null hypothesis, our findings may represent a conservative estimate of the protective effects of statins on rates of sepsis. We also attempted to control for changes in certain variables by assessing their distribution at various points. For example, we assessed whether the differences in vascular access for hemodialysis patients were statistically different between statin users and control patients at enrollment and at 6 months. We did not find any substantial differences.

Last, we relied on United States Renal Data System and Medicare data to determine our outcome. Although this method has limitations, administrative information to determine cause of hospitalization has been used widely in other observational studies.2,17ICD-9 codes have been found to have acceptable sensitivity and specificity when compared with medical record review using clinical consensus definitions of sepsis as the gold standard.2,24 However, use of ICD-9 coding information to determine the primary outcome may have resulted in underdetection of sepsis. This limitation would result in loss of statistical power.

In summary, treatment with a statin was associated with a substantial reduction in the incidence of sepsis among patients who had chronic kidney disease and received dialysis. This protective association remained strong and statistically significant after adjustment for potential confounding. To our knowledge, this is the first study to show a strong and significant effect of a medication administered long term on lower rates of sepsis among patients with chronic kidney disease. In light of the high rates of sepsis and sepsis-related mortality in such patients, these findings are important and warrant the examination of the prevention of sepsis as a potentially important benefit in a randomized trial.

Corresponding Author: Neil R. Powe, MD, MPH, MBA, Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Medical Institutions, 2024 E Monument St, Suite 2-600, Baltimore, MD 21205 (npowe@jhmi.edu).

Author Contributions: Dr Powe had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Gupta, Melamed, Powe.

Acquisition of data: Fink, Coresh, Fox, Powe.

Analysis and interpretation of data: Gupta, Plantinga, Melamed, Levin, Powe.

Drafting of the manuscript: Gupta, Plantinga.

Critical revision of the manuscript for important intellectual content: Gupta, Plantinga, Fink, Melamed, Coresh, Fox, Levin, Powe.

Statistical analysis: Gupta, Plantinga, Powe.

Obtained funding: Coresh, Powe.

Administrative, technical, or material support: Fink, Melamed, Fox, Powe.

Study supervision: Fink, Powe.

Financial Disclosures: None reported.

Funding/Support: This work was supported by grant RO1-DK 59616 from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), grant RO1-HS-08365 from the Agency for Health Care Research and Quality, and grant RO1-HL 62985 from the National Heart, Lung, and Blood Institute. Dr Powe is supported by grant K24DK02643 from NIDDK and Dr Melamed is supported by grant F32DK069017 from NIDDK.

Role of the Sponsors: None of the granting agencies listed had any role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript.

Disclaimer: Some of the data reported here have been supplied by the United States Renal Data System. The interpretation and reporting of these data are the responsibility of the authors and in no way should be seen as an official policy or interpretation of the US government.

Acknowledgment: We thank the patients, staff, and medical directors of the participating clinics at Dialysis Clinic Inc and St. Raphael's Hospital who contributed to the study.

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Kinchen KS, Sadler J, Fink N.  et al.  The timing of specialist evaluation in chronic kidney disease and mortality.  Ann Intern Med. 2002;137:479-486
PubMed   |  Link to Article
Astor BC, Eustace JA, Powe NR, Klag MJ, Fink NE, Coresh J. Type of vascular access and survival among incident hemodialysis patients: the Choices for Healthy Outcomes in Caring for ESRD (CHOICE) Study.  J Am Soc Nephrol. 2005;16:1449-1455
PubMed   |  Link to Article
Plantinga LC, Fink NE, Jaar BG.  et al.  Frequency of sit-down patient care rounds, attainment of clinical performance targets, hospitalization, and mortality in hemodialysis patients.  J Am Soc Nephrol. 2004;15:3144-3153
PubMed   |  Link to Article
Miskulin DC, Meyer KB, Athienites NV.  et al.  Comorbidity and other factors associated with modality selection in incident dialysis patients: the CHOICE Study, Choices for Healthy Outcomes in Caring for End-Stage Renal Disease.  Am J Kidney Dis. 2002;39:324-336
PubMed   |  Link to Article
Athienites NV, Miskulin DC, Fernandez G.  et al.  Comorbidity assessment in hemodialysis and peritoneal dialysis using the index of coexistent disease.  Semin Dial. 2000;13:320-326
PubMed   |  Link to Article
Ollendorf DA, Fendrick AM, Massey K, Williams GR, Oster G. Is sepsis accurately coded on hospital bills?  Value Health. 2002;5:79-81
PubMed   |  Link to Article
Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects.  Biometrika1983;70:41-55. doi:10.1093/biomet/70.1.41
Rubin DB. Estimating causal effects from large data sets using propensity scores.  Ann Intern Med. 1997;127:757-763
PubMed   |  Link to Article
Parsons LS. Reducing bias in a propensity score matched-pair sample using greedy matching techniques. http://www2.sas.com/proceedings/sugi26/p214-26.pdf. Accessed July 15, 2006
Equils O, Naiki Y, Shapiro AM.  et al.  1,25-Dihydroxyvitamin D inhibits lipopolysaccharide-induced immune activation in human endothelial cells.  Clin Exp Immunol. 2006;143:58-64
PubMed   |  Link to Article
Aikawa M, Rabkin E, Sugiyama S.  et al.  An HMG-CoA reductase inhibitor, cerivastatin, suppresses growth of macrophages expressing matrix metalloproteinases and tissue factor in vivo and in vitro.  Circulation. 2001;103:276-283
PubMed   |  Link to Article
Niessner A, Steiner S, Speidl WS.  et al.  Simvastatin suppresses endotoxin-induced upregulation of toll-like receptors 4 and 2 in vivo [published online ahead of print January 26, 2006].  Atherosclerosis. 2006;189:408-413
PubMed   |  Link to Article
Kwak B, Mulhaupt F, Myit S, Mach F. Statins as a newly recognized type of immunomodulator.  Nat Med. 2000;6:1399-1402
PubMed   |  Link to Article
Weitz-Schmidt G, Welzenbach K, Brinkmann V.  et al.  Statins selectively inhibit leukocyte function antigen-1 by binding to a novel regulatory integrin site.  Nat Med. 2001;7:687-692
PubMed   |  Link to Article
del Real G, Jimenez-Baranda S, Mira E.  et al.  Statins inhibit HIV-1 infection by down-regulating Rho activity.  J Exp Med. 2004;200:541-547
PubMed   |  Link to Article
Giguère JF, Tremblay MJ. Statin compounds reduce human immunodeficiency virus type 1 replication by preventing the interaction between virion-associated host intercellular adhesion molecule 1 and its natural cell surface ligand LFA-1.  J Virol. 2004;78:12062-12065
PubMed   |  Link to Article
Catron DM, Lange Y, Borensztajn J, Sylvester MD, Jones BD, Haldar K. Salmonella enterica serovar typhimurium requires nonsterol precursors of the cholesterol biosynthetic pathway for intracellular proliferation.  Infect Immun. 2004;72:1036-1042
PubMed   |  Link to Article
Ikeura R, Murakawa S, Endo A. Growth inhibition of yeast by compactin (ML-236B) analogues.  J Antibiot (Tokyo). 1988;41:1148-1150
PubMed   |  Link to Article
Endo A. The origin of the statins.  Atheroscler Suppl. 2004;5:125-130
PubMed   |  Link to Article
Endo A. The discovery and development of HMG-CoA reductase inhibitors.  Atheroscler Suppl. 2004;5:67-80
PubMed   |  Link to Article
Baigent C, Keech A, Kearney PM.  et al. Cholesterol Treatment Trialists' (CTT) Collaborators.  Efficacy and safety of cholesterol-lowering treatment: prospective meta-analysis of data from 90,056 participants in 14 randomised trials of statins.  Lancet. 2005;366:1267-1278
PubMed   |  Link to Article
Wanner C, Krane V, Marz W.  et al.  Atorvastatin in patients with type 2 diabetes mellitus undergoing hemodialysis.  N Engl J Med. 2005;353:238-248
PubMed   |  Link to Article
Baigent C, Landry M. Study of Heart and Renal Protection (SHARP).  Kidney Int. 2003;84:S207-S210
PubMed   |  Link to Article
Lowrie EG, Lew NL. Death risk in hemodialysis patients: the predictive value of commonly measured variables and an evaluation of death rate differences between facilities.  Am J Kidney Dis. 1990;15:458-482
PubMed
Iseki K, Yamazato M, Tozawa M, Takishita S. Hypocholesterolemia is a significant predictor of death in a cohort of chronic hemodialysis patients.  Kidney Int. 2002;61:1887-1893
PubMed   |  Link to Article
Coresh J, Longenecker JC, Miller ER III, Young HJ, Klag MJ. Epidemiology of cardiovascular risk factors in chronic renal disease.  J Am Soc Nephrol. 1998;9:(suppl)  S24-S30
PubMed
Liu Y, Coresh J, Eustace JA.  et al.  Association between cholesterol level and mortality in dialysis patients: role of inflammation and malnutrition.  JAMA. 2004;291:451-459
PubMed   |  Link to Article

Figures

Tables

Table Graphic Jump LocationTable 1. Baseline Characteristics of Patients in the CHOICE Cohort, by Statin Use
Table Graphic Jump LocationTable 2. Baseline Characteristics of Patients in the Propensity-Matched Subcohort, by Statin Use
Table Graphic Jump LocationTable 3. Ratio of the Rate of Hospitalization for Sepsis (Statin Group vs Control Group) in the Entire CHOICE Cohort and the Propensity-Matched Subcohort
Table Graphic Jump LocationTable 4. Ratio of the Rate of Hospitalization for Sepsis (Statin Group vs Control Group) in Subgroups of the Entire CHOICE Cohort: Unadjusted, Multivariate, and Propensity Score–Adjusted Analyses

References

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PubMed   |  Link to Article
Martin GS, Mannino DM, Eaton S, Moss M. The epidemiology of sepsis in the United States from 1979 through 2000.  N Engl J Med. 2003;348:1546-1554
PubMed   |  Link to Article
Brun-Buisson C, Doyon F, Carlet J.  et al.  Incidence, risk factors, and outcome of severe sepsis and septic shock in adults: a multicenter prospective study in intensive care units: French ICU Group for Severe Sepsis.  JAMA. 1995;274:968-974
PubMed   |  Link to Article
Powe NR, Jaar B, Furth SL, Hermann J, Briggs W. Septicemia in dialysis patients: incidence, risk factors, and prognosis.  Kidney Int. 1999;55:1081-1090
PubMed   |  Link to Article
Hoen B, Paul-Dauphin A, Hestin D, Kessler M. EPIBACDIAL: a multicenter prospective study of risk factors for bacteremia in chronic hemodialysis patients.  J Am Soc Nephrol. 1998;9:869-876
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Vollmer T, Key L, Durkalski V.  et al.  Oral simvastatin treatment in relapsing-remitting multiple sclerosis.  Lancet. 2004;363:1607-1608
PubMed   |  Link to Article
Sola S, Mir MQ, Lerakis S, Tandon N, Khan BV. Atorvastatin improves left ventricular systolic function and serum markers of inflammation in nonischemic heart failure.  J Am Coll Cardiol. 2006;47:332-337
PubMed   |  Link to Article
McCarey DW, McInnes IB, Madhok R.  et al.  Trial of Atorvastatin in Rheumatoid Arthritis (TARA): double-blind, randomised placebo-controlled trial.  Lancet. 2004;363:2015-2021
PubMed   |  Link to Article
Heart Protection Study Collaborative Group.  MRC/BHF Heart Protection Study of cholesterol lowering with simvastatin in 20,536 high-risk individuals: a randomised placebo-controlled trial.  Lancet. 2002;360:7-22
PubMed   |  Link to Article
Albert MA, Danielson E, Rifai N, Ridker PM. Effect of statin therapy on C-reactive protein levels: the Pravastatin Inflammation/CRP Evaluation (PRINCE): a randomized trial and cohort study.  JAMA. 2001;286:64-70
PubMed   |  Link to Article
Ridker PM, Cannon CP, Morrow D.  et al.  C-reactive protein levels and outcomes after statin therapy.  N Engl J Med. 2005;352:20-28
PubMed   |  Link to Article
Merx MW, Liehn EA, Janssens U.  et al.  HMG-CoA reductase inhibitor simvastatin profoundly improves survival in a murine model of sepsis.  Circulation. 2004;109:2560-2565
PubMed   |  Link to Article
Giusti-Paiva A, Martinez MR, Felix JV.  et al.  Simvastatin decreases nitric oxide overproduction and reverts the impaired vascular responsiveness induced by endotoxic shock in rats.  Shock. 2004;21:271-275
PubMed   |  Link to Article
Ando H, Takamura T, Ota T, Nagai Y, Kobayashi K. Cerivastatin improves survival of mice with lipopolysaccharide-induced sepsis.  J Pharmacol Exp Ther. 2000;294:1043-1046
PubMed
Liappis AP, Kan VL, Rochester CG, Simon GL. The effect of statins on mortality in patients with bacteremia.  Clin Infect Dis. 2001;33:1352-1357
PubMed   |  Link to Article
Almog Y, Shefer A, Novack V.  et al.  Prior statin therapy is associated with a decreased rate of severe sepsis.  Circulation. 2004;110:880-885
PubMed   |  Link to Article
Hackam DG, Mamdani M, Li P, Redelmeier DA. Statins and sepsis in patients with cardiovascular disease: a population-based cohort analysis.  Lancet. 2006;367:413-418
PubMed   |  Link to Article
Fox CS, Longenecker JC, Powe NR.  et al.  Undertreatment of hyperlipidemia in a cohort of United States kidney dialysis patients.  Clin Nephrol. 2004;61:299-307
PubMed
Kinchen KS, Sadler J, Fink N.  et al.  The timing of specialist evaluation in chronic kidney disease and mortality.  Ann Intern Med. 2002;137:479-486
PubMed   |  Link to Article
Astor BC, Eustace JA, Powe NR, Klag MJ, Fink NE, Coresh J. Type of vascular access and survival among incident hemodialysis patients: the Choices for Healthy Outcomes in Caring for ESRD (CHOICE) Study.  J Am Soc Nephrol. 2005;16:1449-1455
PubMed   |  Link to Article
Plantinga LC, Fink NE, Jaar BG.  et al.  Frequency of sit-down patient care rounds, attainment of clinical performance targets, hospitalization, and mortality in hemodialysis patients.  J Am Soc Nephrol. 2004;15:3144-3153
PubMed   |  Link to Article
Miskulin DC, Meyer KB, Athienites NV.  et al.  Comorbidity and other factors associated with modality selection in incident dialysis patients: the CHOICE Study, Choices for Healthy Outcomes in Caring for End-Stage Renal Disease.  Am J Kidney Dis. 2002;39:324-336
PubMed   |  Link to Article
Athienites NV, Miskulin DC, Fernandez G.  et al.  Comorbidity assessment in hemodialysis and peritoneal dialysis using the index of coexistent disease.  Semin Dial. 2000;13:320-326
PubMed   |  Link to Article
Ollendorf DA, Fendrick AM, Massey K, Williams GR, Oster G. Is sepsis accurately coded on hospital bills?  Value Health. 2002;5:79-81
PubMed   |  Link to Article
Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects.  Biometrika1983;70:41-55. doi:10.1093/biomet/70.1.41
Rubin DB. Estimating causal effects from large data sets using propensity scores.  Ann Intern Med. 1997;127:757-763
PubMed   |  Link to Article
Parsons LS. Reducing bias in a propensity score matched-pair sample using greedy matching techniques. http://www2.sas.com/proceedings/sugi26/p214-26.pdf. Accessed July 15, 2006
Equils O, Naiki Y, Shapiro AM.  et al.  1,25-Dihydroxyvitamin D inhibits lipopolysaccharide-induced immune activation in human endothelial cells.  Clin Exp Immunol. 2006;143:58-64
PubMed   |  Link to Article
Aikawa M, Rabkin E, Sugiyama S.  et al.  An HMG-CoA reductase inhibitor, cerivastatin, suppresses growth of macrophages expressing matrix metalloproteinases and tissue factor in vivo and in vitro.  Circulation. 2001;103:276-283
PubMed   |  Link to Article
Niessner A, Steiner S, Speidl WS.  et al.  Simvastatin suppresses endotoxin-induced upregulation of toll-like receptors 4 and 2 in vivo [published online ahead of print January 26, 2006].  Atherosclerosis. 2006;189:408-413
PubMed   |  Link to Article
Kwak B, Mulhaupt F, Myit S, Mach F. Statins as a newly recognized type of immunomodulator.  Nat Med. 2000;6:1399-1402
PubMed   |  Link to Article
Weitz-Schmidt G, Welzenbach K, Brinkmann V.  et al.  Statins selectively inhibit leukocyte function antigen-1 by binding to a novel regulatory integrin site.  Nat Med. 2001;7:687-692
PubMed   |  Link to Article
del Real G, Jimenez-Baranda S, Mira E.  et al.  Statins inhibit HIV-1 infection by down-regulating Rho activity.  J Exp Med. 2004;200:541-547
PubMed   |  Link to Article
Giguère JF, Tremblay MJ. Statin compounds reduce human immunodeficiency virus type 1 replication by preventing the interaction between virion-associated host intercellular adhesion molecule 1 and its natural cell surface ligand LFA-1.  J Virol. 2004;78:12062-12065
PubMed   |  Link to Article
Catron DM, Lange Y, Borensztajn J, Sylvester MD, Jones BD, Haldar K. Salmonella enterica serovar typhimurium requires nonsterol precursors of the cholesterol biosynthetic pathway for intracellular proliferation.  Infect Immun. 2004;72:1036-1042
PubMed   |  Link to Article
Ikeura R, Murakawa S, Endo A. Growth inhibition of yeast by compactin (ML-236B) analogues.  J Antibiot (Tokyo). 1988;41:1148-1150
PubMed   |  Link to Article
Endo A. The origin of the statins.  Atheroscler Suppl. 2004;5:125-130
PubMed   |  Link to Article
Endo A. The discovery and development of HMG-CoA reductase inhibitors.  Atheroscler Suppl. 2004;5:67-80
PubMed   |  Link to Article
Baigent C, Keech A, Kearney PM.  et al. Cholesterol Treatment Trialists' (CTT) Collaborators.  Efficacy and safety of cholesterol-lowering treatment: prospective meta-analysis of data from 90,056 participants in 14 randomised trials of statins.  Lancet. 2005;366:1267-1278
PubMed   |  Link to Article
Wanner C, Krane V, Marz W.  et al.  Atorvastatin in patients with type 2 diabetes mellitus undergoing hemodialysis.  N Engl J Med. 2005;353:238-248
PubMed   |  Link to Article
Baigent C, Landry M. Study of Heart and Renal Protection (SHARP).  Kidney Int. 2003;84:S207-S210
PubMed   |  Link to Article
Lowrie EG, Lew NL. Death risk in hemodialysis patients: the predictive value of commonly measured variables and an evaluation of death rate differences between facilities.  Am J Kidney Dis. 1990;15:458-482
PubMed
Iseki K, Yamazato M, Tozawa M, Takishita S. Hypocholesterolemia is a significant predictor of death in a cohort of chronic hemodialysis patients.  Kidney Int. 2002;61:1887-1893
PubMed   |  Link to Article
Coresh J, Longenecker JC, Miller ER III, Young HJ, Klag MJ. Epidemiology of cardiovascular risk factors in chronic renal disease.  J Am Soc Nephrol. 1998;9:(suppl)  S24-S30
PubMed
Liu Y, Coresh J, Eustace JA.  et al.  Association between cholesterol level and mortality in dialysis patients: role of inflammation and malnutrition.  JAMA. 2004;291:451-459
PubMed   |  Link to Article

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