Infection is the second most common cause of death (after cardiovascular disease) among hemodialysis patients (1,2 3 4 1,3–7
Observational studies have suggested that a higher dialysis dose and use of a high-flux membrane may each decrease the likelihood of infectious events (1,8 9
The present report (1 2 3
Materials and Methods
Study Design
The design and methods of the HEMO Study have been reported previously (9
Baseline
The subjects were enrolled in the baseline phase between March 1995 and October 2000 and randomized between May 1995 and February 2001. Eligibility requirements for baseline enrollment included age between 18 to 80 yr, receiving in-center hemodialysis thrice weekly, and on hemodialysis > 3 mo. Demographic and clinical information was collected at baseline. Patients were excluded during baseline if (1 ) their residual urea clearance in a 24 to 46-hr urine collection was > 1.5 ml/min per 35 L of urea volume, (2 ) their serum albumin (nephelometry) was < 2.6 g/dl, (3 ) they failed to achieve the high target dialysis dose in ≤ 4.5 h on two of three consecutive monitored dialysis sessions, (4 ) they had serious comorbid medical conditions, including active malignancy or infection, unstable angina, or end-stage cardiac, pulmonary, or hepatic disease, or (5 ) they were scheduled for a living donor kidney transplant.
Interventions
Patients meeting the inclusion and exclusion criteria were randomized to the study interventions in a 2 × 2 factorial design with equal allocation. Each patient was randomized to receive either a standard (eKt/V 1.45) or high (eKt/V 1.05) dialysis dose, and to dialyze with either a low-flux (32 β2 -microglobulin clearance < 10 ml/min) or high-flux (32 β2 -microglobulin clearance > 20 ml/min) membrane. Unmodified cellulose dialyzers were excluded. The target dialysis dose was achieved by manipulating dialyzer clearance, dialysis blood flow, and treatment time (minimum ≥ 2.5 h). Adherence to dose intervention was monitored by monthly urea kinetic modeling. β2 -microglobulin clearance was measured every 2 mo for high-flux dialyzers and every 6 mo for low-flux membranes. Dialyzer reuse was permitted, but the number of reuses was limited in the high-flux arm to meet the target β2 M clearance. The mean achieved equilibrated Kt/V (eKt/V) was 1.53 ± 0.09 in the high-dose group and 1.16 ± 0.08 in the standard-dose group; the single pool Kt/V (spKt/V) was 1.71 ± 0.11 and 1.32 ± 0.09, respectively. The mean achieved β2 -microglobulin clearances were 3.4 ± 7.2 ml/min and 33.8 ± 11.4 ml/min in the low-flux and high-flux groups, respectively. Other than the study interventions, the dialysis and medical management of the patients conformed to current standards of care. Data collection ended in December 2001. The mean patient followup for mortality was 2.84 yr.
Definition of Clinical Outcomes
The primary study outcome was all-cause mortality. Three main secondary outcomes were evaluated: first cardiac hospitalization or all-cause death, first infection-related hospitalization or all-cause death, and first declining albumin event (> 15% decrease from baseline) or all-cause death. A fourth main secondary outcome was the rate of non–access-related hospitalizations. Other outcomes included cause-specific mortality and composites of death and first hospitalizations for cardiac disease or infection.
Determination of Clinical Outcomes
Each hospitalization of a study subject was reported by the clinical center, following review of the discharge summary, pertinent medical records, and diagnostic tests. For each death, the clinical center provided the death certificate, USRDS death notification form, and a brief narrative summary prepared by the local principal investigator. All infection-related hospitalizations or deaths were subclassified as “bacteremia or sepsis,” “deep tissue infection,” or a combination of both. In addition, each infectious outcome was categorized as being access-related or non–access-related. Finally, the clinical center assigned specific medical diagnosis codes from a predefined list for each hospitalization (up to four diagnoses were permitted).
An Outcome Review Committee, comprising investigators blinded to the patient’s randomization group, performed independent audits of all clinical center reports of deaths and first cardiac or infection-related hospitalization. All mortality reviews required independent audits of the clinical center’s death report by two members of the committee. Agreement on the category of the primary cause of death was required. When the reviewers disagreed, the cause of death was adjudicated during a conference call of the Outcome Review Committee.
All first infection-related or cardiac hospitalization reports were audited by one member of the Outcome Review Committee. This review process required agreement between the Clinical Center’s principal investigator and the Outcome Review Committee member as to the classification of the cause of hospitalization. When agreement could not be reached between the Outcome Review Committee member and the Clinical Center investigator, the case was adjudicated by the Outcome Review Committee. To evaluate the accuracy of the review process, the level of agreement between the diagnosis reported by the Clinical Center and the Outcome Committee was examined. When the clinical center determined that a hospitalization was due to infection, the Outcome Committee agreed 96% of the time. The Outcome Committee also concurred with the clinical center classification of the first hospitalization as “bacteremia or sepsis,” “deep tissue infection,” and “access-related hospitalization” in 92%, 95%, and 88% of cases. When the clinical center did not report an infectious etiology for the hospitalization, the Outcome Committee disagreed in only 4% of the time.
Subsequent infection-related and cardiac hospitalizations were not routinely audited by the Outcome Committee. To further assess the validity of the classification in those instances, a random subset of subsequent hospitalizations was adjudicated by the Outcome Committee. The sensitivity and specificity of the clinical center’s diagnosis of infectious hospitalization was 92% and 99%, respectively, when the Outcome Committee’s diagnosis was taken as the gold standard. On this basis, we concluded that the Clinical Center classification could be accepted with a high degree of confidence in those instances that were not audited by the Outcome Committee.
Each month, the clinical center completed a form for each study patient specifying what type of vascular access (fistula, graft, or catheter) was being used for dialysis. For the purpose of this analysis, we assumed that the type of access specified in the form preceding a death or hospitalization was the one in use at the time of the infectious event.
Statistical Analyses
The effects of the dose and flux interventions were investigated for two classes of infectious outcomes. The first class consisted of outcomes defined by a single event for each patient. These included (1 ) all-cause mortality, (2 ) the main secondary composite outcome including the first infection-related hospitalization or death from any cause, (3 ) infection-related death, (4 ) the first infection-related hospitalization, and (5
The effects of the randomized interventions on each of these outcomes was evaluated using Cox regression (10 11,12
The second class of outcomes included multiple events for patients having more than one occurrence of the designated infection-related hospitalization. These outcomes were (1 ) all infection-related hospitalizations, (2 ) all infection-related hospitalizations that were access-related, (3 ) all infection-related hospitalizations that were non–access-related, (4 ) all infection-related hospitalizations presenting as deep-tissue infections, and (5 ) all infection-related hospitalizations presenting as bacteremia or sepsis. The effects of the randomized treatment interventions on each of these outcomes were evaluated using overdispersed Poisson regression analysis (13
Event rates for both classes of outcomes defined above were defined as the ratio of the total number of events to the total patient years of follow-up for that outcome, using the same rules for censoring as in the Cox and Poisson regressions described above.
The relationships of access type with infection-related death and with the composite outcome including the infection-related hospitalization or infection-related death were evaluated by Cox regressions relating the indicated outcomes to the access type designated on the monthly kinetic modeling form as a time-dependent covariate. These Cox regression models included the seven pre-specified baseline factors and randomized treatment group as covariates.
The relationship of the conditional probability that a patient’s infection-related hospitalization resulted in death to the randomized treatment groups and the seven pre-specified baseline factors was investigated using multiple logistic regression. Deaths occurring within 3 d of discharge were attributed to the infection-related hospitalization in this analysis.
All analyses of the effects of the interventions were intent-to-treat. Kaplan-Meier survival curves (14 P -values are two-sided, without adjustment for multiple comparisons.
Results
The HEMO Study randomized 1846 chronic hemodialysis patients, and they had a mean follow-up for mortality of 2.84 yr. A summary of the demographic and clinical characteristics of the study cohort is presented in Table 1 . The study population tended to be younger than the US hemodialysis population. The proportion of black patients was higher, reflecting the demographics of the participating dialysis units.
Table 1: a
In the course of the study, 871 patients died, providing an annual death rate of 16.6%. An infectious etiology was responsible for 201 deaths, or 23.1% of all deaths in the study (Table 2 ). The annual rate of infection-related death was 3.8%. There were 1698 infection-related hospitalizations, giving an annual rate of 35.0%. Of these, 55% were classified as deep tissue infections only, and 45% as having bacteremia or sepsis. In addition, 23% of all infection-related hospitalizations were considered access-related, and 77% non–access-related.
Table 2:
The most common disease categories responsible for infection-related death, first infection-related hospitalization, and all infection-related hospitalizations included respiratory disease (20.4 to 23.5%), vascular access infections (16.9 to 25.0%), and infection of unknown source (30.3 to 34.6%) (Table 3 ). Among patients with an infection-related hospitalization due to cardiac disease, 25.0% had coexisting vascular access infection. Conversely, 3.1% of infection-related hospitalizations that were access-related had a coexisting cardiac infection. The overall probability of death during an infection-related hospitalization was 15%, but it varied greatly according to the disease category (Table 4 ): 30% for cardiac infections, 17% for respiratory infections, and only 7% for vascular access-related infections.
Table 3:
Table 4: a by any cause
The overall likelihood of death was not significantly different among patients randomized to the high dose versus standard dose, nor did it differ between patients randomized to the high-flux versus low-flux dialysis (Figure 1 ). Similarly, infection-related deaths, first infection-related hospitalizations, composite infectious outcomes, and rate of all infection-related hospitalizations or major classes of infection were not significantly reduced by a high dose or by high-flux membranes (Figure 1 ). Finally, infection-free survival was similar between patients randomized to a high or standard Kt/V and similar between patients with high-flux and low-flux membranes (Figure 2 ).
Figure 1. :
95% confidence limits for the effects of the treatment Interventions. Relative risks compare the high-dose with the standard-dose group and the high-flux with the low-flux group. Shown are the primary outcome (mortality), infection-related deaths, infection-related hospitalizations, and selected additional secondary outcomes. Analyses are stratified by clinical center, and adjusted for baseline age, gender, race, duration of dialysis, diabetes, ICED score, excluding diabetes, and serum albumin.
Figure 2. :
Survival curves for infection-free survival by randomized treatment group. After adjustment for the baseline factors, the high-dose group had a 3% lower rate for the composite of first infection-related hospitalization or all-cause death (95% CI, −9% to +14%; P = 0.60) than the standard-dose group, and the high-flux group had an 9% lower rate (95% CI, −3% to +19%; P = 0.14) than the low-flux group.
In a multivariable analysis, including the two randomization variables (dialysis dose and flux), as well as seven predefined baseline clinical variables, only diabetes, hypoalbuminemia, and high co-morbidity score (ICED) predicted a higher rate of infection-related hospitalization (Table 5 ). A similar analysis identified patient age, baseline serum albumin, ICED code, and number of years on dialysis as significant predictors of infectious deaths (Table 5 ). Finally, among the seven prespecified clinical variables, the RR of death during an infection-related hospitalization was affected significantly only by patient age (RR, 1.44 [1.21 to 1.72] per 10 yr; P < 0.001) and baseline serum albumin (RR, 0.46 [0.25 to 0.84] per g/dl; P = 0.01).
Table 5:
Only about one fifth of all first infection-related hospitalizations were considered to be access-related (Table 2 ). Among the subset of first infection-related hospitalizations that were access-related, the class of infection differed according to the type of vascular access. When the patient was dialyzing with a catheter, the infection was classified as “bacteremia or sepsis” 90% of time; in contrast, when the patient was dialyzing with a fistula or graft, this class of infection was observed 54 and 55% of the time, respectively (Figure 3 ).
Figure 3. :
First infection-related hospitalization that was access-related, classified by type of vascular access and type of infection (gray bars, bacteremia or sepsis; white bars, deep tissue infection only). The number of patients is listed inside the bars. Access classification was missing for 12 hospitalizations. The class of infection differed significantly between patients dialyzing with catheters and those dialyzing with a fistula or graft (P < 0.001). The numbers of affected patients are indicated in the bars.
Although catheters represented just 7.6% of the vascular accesses in the study, catheters were used in 32% of the access-related infections. A time-dependent Cox regression analysis, adjusted for clinical center and the seven predefined clinical variables, found a significantly higher likelihood of infection-related death among patients dialyzing with catheters compared with those dialyzing with fistulas (RR, 2.30 [95% CI, 1.45 to 3.64]; P < 0.001]. Similarly, the likelihood of first infection-related hospitalization or infection-related death was significantly higher for patients dialyzing with catheters compared with those dialyzing with fistulas (RR, 1.85 [95% CI, 1.47, 2.33]; P < 0.001).
Discussion
The HEMO Study confirms the high frequency of infections among chronic hemodialysis patients. Serious infections accounted for almost one fourth of all deaths. This proportion is about twice as high as the 12% of deaths estimated previously on the basis of retrospective analysis of the HCFA Death Notification Form (1,8 2
Previous studies suggesting a beneficial effect of higher flux or higher Kt/V on infectious outcomes have been hampered by being nonrandomized, retrospective, or small sample size. In a large observational study of USRDS patients, Bloembergen et al. (1 versus 1.32) on infectious outcomes (Figures 1 and 2 ). The present study does not preclude the possibility of patients with a Kt/V approximately 1.3 having fewer infectious events than those with an even lower Kt/V. However, it does not support the utility of exceeding current K/DOQI guidelines for hemodialysis adequacy (Kt/V ≥ 1.20) (15
In vitro studies suggest a defect in polymorphonuclear cell function in uremic patients (16,17 18 8 5 2 M clearances, 33.8 ± 11.4 ml/min versus 3.4 ± 7.2 ml/min, respectively) on infectious outcomes (Figures 1 and 2 ). Bioincompatible, unsubstituted cellulose dialyzers were excluded; it is therefore not possible to draw conclusions from the current study about their effect on infections.
The HEMO Study excluded patients with advanced age, those with severe comorbidity, and those with severe access problems that precluded achievement of the high-dose dialysis target. The possibility that a higher dose of dialysis or the use of high-flux membranes may benefit these patient subsets cannot be excluded.
The HEMO Study confirms previous reports showing an increased risk of serious infectious events among diabetic patients, older patients, individuals with serious co-morbidity, patients with hypoalbuminemia, and those using catheters for access (1,3–7 19–21
Catheters were an important predictor of infection-related hospitalizations in the HEMO study. In agreement, Hoen et al. (5 6 22–24
In conclusion, neither increasing the dialysis dose above current DOQI guidelines nor switching to high-flux dialyzers is likely to reduce infection-related deaths or hospitalizations in hemodialysis patients. Although only about 20% of all infection-related hospitalizations are access-related, they may represent the subgroup that is most preventable by changing practice patterns. The other risk factors, including age, diabetes, co-morbidity, dialysis vintage, and hypoalbuminemia, are not readily modifiable. A concerted effort to reduce the proportion of dialysis patients dialyzing with catheters could substantially reduce the frequency of infection-related hospitalizations, particularly those classified as bacteremia or sepsis.
This study was supported by the National Institute of Diabetes and Digestive and Kidney Diseases. Additional support was provided by Baxter Healthcare, Fresenius Medical Care, R&D Laboratories, and Ross Laboratories. Portions of this manuscript have been presented in abstract form at the American Society of Nephrology meeting in Philadelphia, PA, October 30–November 4, 2002.
1. Bloembergen WE, Stannard DC, Port FK, Wolfe RA, Pugh JA, Jones CA, Greer JW, Golper TA, Held PJ: Relationship of dose of hemodialysis and cause-specific mortality. Kidney Int 50: 557–565, 1996
2. US Renal Data System: USRDS 2000 Annual Data Report: Atlas of End-Stage Renal Disease in the United States. Bethesda, MD, National Institute of Health, National Institute of Diabetes and Digestive and Kidney Diseases, 2000
3. Powe NR, Jaar B, Furth SL, Hermann J, Briggs W: Septicemia in dialysis patients: Incidence, risk factors, and prognosis. Kidney Int 55: 1081–1090, 1999
4. Sarnak MJ, Jaber BL: Mortality caused by sepsis in patients with end-stage renal disease compared with the general population. Kidney Int 58: 1758–1764, 2000
5. 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 9: 869–876, 1998
6. Pastan S, Soucie M, McClellan WM: Vascular access and increased risk of death among hemodialysis patients. Kidney Int 62: 620–626, 2002
7. Tokars JI, Light P, Anderson J, Miller ER, Parrish J, Armistead N, Jarvis WR, Gehr T: A prospective study of vascular access infections at seven outpatient hemodialysis centers. Am J Kidney Dis 37: 1232–1240, 2001
8. Bloembergen WE, Hakim RM, Stannard DC, Held PJ, Wolfe RA, Agodoa LYC, Port FK: Relationship of dialysis membrane and cause-specific mortality. Am J Kidney Dis 33: 1–10, 1999
9. Eknoyan G, Beck GJ, Cheung AK, Daugirdas JT, Greene T, Kusek JW, Allon M, Bailey J, Delmez JA, Depner TA, Dwyer JT, Levey AS, Levin NW, Milford E, Ornt DB, Rocco MV, Schulman G, Schwab SJ, Teehan BP, Toto R: Effect of dialysis dose and membrane flux on mortality and morbidity in maintenance hemodialysis patients: Primary results of the HEMO Study. N Engl J Med 347: 2010–2019, 2002
10. Cox DR: Regression models and life tables (with discussion). J Royal Stat Soc Series B 34: 187–220, 1972
11. Miskulin DC, Athienites N, Yan G, Martin AA, Ornt DB, Kusek JW, Meyer KB, Levey AS: Comorbidity assessment using the Index of Coexistent Diseases in a multicenter clinical trial. Kidney Int 60: 1498–1510, 2000
12. Athienites NV, Miskulin DC, Fernandez G, Bunnapradist S, Simon G, Landa M, Schmid CH, Greenfield S, Levey AS, Meyer KB: Comorbidity assessment in hemodialysis and peritoneal dialysis using the index of coexistent disease. Semin Dial 13: 320–326, 2000
13. McCullagh P, Nelder JA: Generalized Linear Models. New York, Chapman & Hall, 1989
14. Kaplan EL, Meier P: Nonparametric estimation from incomplete observations. J Am Soc Stat Assoc 53: 457–481, 1958
15. NKF-K/DOQI clinical practice guidelines: Update 2000: Am J Kidney Dis 37 [suppl 1]: S5–S6, 2001
16. Horl WH, Haag-Weber M, Georgopoulos A, Block LH: Physicochemical characterization of a polypeptide present in uremic serum that inhibits the biologic activity of polymorphonuclear cells. Proc Natl Acad Sci USA 87: 6353–6357, 1990
17. Cohen G, Rudnicki M, Horl WH: Isolation of modified ubiquitin as a neutrophil chemotaxis inhibitor from uremic patients. J Am Soc Nephrol 9: 451–456, 1998
18. Vanholder R, Ringoir S, Dhondt A, Hakim R: Phagocytosis in uremic and hemodialysis patients: A prospective and cross sectional study. Kidney Int 39: 320–327, 1991
19. Kaysen GA: Biologic basis of hypoalbuminemia in ESRD. J Am Soc Nephrol 9: 2368–2376, 1998
20. Kaysen GA, Dubin JA, Muller HG, Rosales LM, Levin NW, Group HS: The acute-phase response varies with time and predicts serum albumin levels in hemodialysis patients. Kidney Int 58: 346–352, 2000
21. Owen WF, Lowrie EG: C-reactive protein as an outcome predictor for maintenance hemodialysis patients. Kidney Int 54: 627–636, 1998
22. Schwab SJ, Beathard GA: The hemodialysis catheter conundrum: Hate living with them, but can’t live without them. Kidney Int 56: 1–17, 1999
23. Tokars JI, Miller ER, Alter MJ, Arduino MJ: National surveillance of dialysis-associated diseases in the United States, 2000. Semin Dial 15: 162–171, 2002
24. Reddan D, Klassen P, Frankenfield DL, Szczech L, Schwab S, Coladonato J, Rocco M, Lowrie EG, Owen WF: National profile of practice patterns for hemodialysis vascular access in the United States. J Am Soc Nephrol 13: 2117–2124, 2002
