Comparison of methodologies to characterize haemoglobin variability in the US Medicare haemodialysis population

High hemoglobin fluctuation was a protective factor for cardiovascular-related death in peritoneal dialysis (PD) patients: A retrospective analysis of 232 patients with PD

Objectives

This study aimed to investigate the effect of hemoglobin (Hb) fluctuation after dialysis on the prognosis of cardiovascular‐related and all‐cause deaths in peritoneal dialysis (PD).

Methods

According to the Hb fluctuation, patients were divided into low fluctuation group, moderate fluctuation group, and high fluctuation group, and then, the effects of Hb fluctuation after dialysis on the prognosis of cardiovascular‐related and all‐cause death in PD were analyzed by regression analysis.

Results

A total of 232 patients were selected in this study. Compared with the low Hb fluctuation group, the moderate and high fluctuation groups had lower body mass index (BMI), estimated glomerular filtration rate (eGFR), and baseline Hb, and the moderate fluctuation group had less erythropoietin (EPO) and dialysis dose. Compared with survivors, patients with cardiovascular‐related and all‐cause deaths had lower mean Hb and Hb fluctuation (all p < 0.05). Cox regression analysis showed that before and after adjusting for confounding factors, Hb fluctuation was still independently correlated with cardiovascular prognosis, and higher Hb fluctuation was still a protective factor for cardiovascular‐related death in the Hb‐substandard group, but there was no significant correlation between Hb fluctuation and all‐cause death. Multivariate linear regression analysis revealed that Hb fluctuation was positively correlated with Kt/V and EPO dosage, but negatively correlated with the baseline Hb.

Conclusion

High Hb fluctuation was a protective factor for cardiovascular‐related death in PD with substandard Hb. Compared with Hb fluctuation, correction of anemia timely and making Hb reaches the standard level had a greater impact on reducing cardiovascular‐related death in PD.

Effects of the route of erythropoietin administration on hemoglobin variability and cardiovascular events in hemodialysis patients

Introduction

Despite of the routine use of erythropoietin in hemodialysis patients to correct anemia, its administration route's effects on hemoglobin variability and cardiovascular events remain elusive. Herein, we determined different erythropoietin administration routes' effects on hemoglobin variability in hemodialysis patients and the associated factors of hemoglobin variability and cardiovascular events.

Methods

This is a post hoc analysis of a prospective, controlled, randomized, unblinded study with 78 Korean hemodialysis patients receiving intravenous (n = 40) or subcutaneous (n = 38) erythropoietin therapy. We evaluated hemoglobin variability by calculating the frequency of hemoglobin measurements outside the target range during all visits. The high-frequency group was defined by those with hemoglobin variability over the median value (25%) while the low-frequency group was defined by those with hemoglobin variability of <25%.

Results

In this analysis, 37 patients (51.1%) were males, and the mean age was 50.6 ± 12.5 years. The frequency of the value being outside the target hemoglobin range was higher in the subcutaneous group compared to the intravenous group (p = 0.03). The low-frequency group required significantly lower erythropoietin doses compared to the high-frequency group. In the adjusted Cox analysis, the parameter high group was a significant independent risk factor for cardiovascular events (p = 0.03).

Conclusion

The risk out of the target hemoglobin range increased with subcutaneous administration compared with intravenous erythropoietin administration in hemodialysis patients. An increased frequency of the value being outside the target hemoglobin range was also associated with an increased risk of cardiovascular events.

Haemoglobin variability and all-cause mortality in haemodialysis patients: A systematic review and meta-analysis

Aim

Haemoglobin (Hb) variability has been reported to be associated with mortality in dialysis patients in some but not all studies. We aimed to establish the prognostic significance of Hb variability with all‐cause mortality in haemodialysis patients through this meta‐analysis.

Methods

The Medline, Embase, Cochrane Library and Web of Science databases were searched for studies assessing the association between Hb variability and all‐cause mortality in haemodialysis patients after adjustment for other covariates.

Results

We included three studies of five cohorts with a total of 262 641 patients. Forest plots showed that the combined hazard ratio for all‐cause mortality was 1.09 (95% CI = 1.01–1.08; P = 0.03) per 1 g/dL increase in Hb variability.

Conclusion

Based on the current evidence, our meta‐analysis found an association between Hb variability and all‐cause mortality in patients receiving haemodialysis therapy.

Three studies of five cohorts with a total of 262 641 patients showed a combined hazard ratio for all‐cause mortality in HD patients to be 1.09 (95% CI = 1.01–1.08; P = 0.03) per 1 g/dL increase in the haemoglobin level. A significant heterogeneity exists between the studies.

The role of hemoglobin variability as a prognostic indicator in peritoneal dialysis patients: a retrospective descriptive study

PURPOSE

To investigate the effect of hemoglobin fluctuations on cardiovascular prognosis of patients on peritoneal dialysis (PD).

METHODS

Retrospective descriptive study, with sample composed of 333 patients treated with PD at the Renal Unit. Two indicators were adopted to indicate hemoglobin fluctuations of PD patients: absolute value of hemoglobin variability (HV) and HV trend. Moreover, the new cardiovascular events and recurrent rate of cardiovascular events within 3 months after PD were recorded and were compared in groups of PD patients classified by hemoglobin fluctuation indicators.

RESULTS

Patients whose HV value is less than 10 g/l have an increased risk of new cardiovascular events than patients with HV value > 10 g/l (27.2 vs. 12.2%, p < 0.05) during 3 months after PD. Patients who kept high hemoglobin values (≥ 110 g/l) 3 months after PD are prone to develop recurrent cardiovascular events than patients with relatively low hemoglobin values (< 110 g/l; p < 0.05).

CONCLUSIONS

Hemoglobin fluctuations were associated with the cardiovascular prognosis in patients on PD. A limitation of our study is its retrospective design. However, the results in this research indicated anemia in PD patients without cardiovascular events history should be timely treated. Instead, hemoglobin should be kept within a relatively low level in patients with history of cardiovascular events. Additional clinical researches are needed to verify and improve our findings.

Effect of dialysis dose and membrane flux on hemoglobin cycling in hemodialysis patients

Many studies found that hemoglobin (Hb) fluctuation was closely related to the prognosis of the maintenance hemodialysis patients. We investigated the association of factors relating dialysis dose and dialyzer membrane with Hb levels. We undertook a randomized clinical trial in 140 patients undergoing thrice-weekly dialysis and assigned patients randomly to a standard or high dose of dialysis; Hb level was measured every month for 12 months. In the standard-dose group, the mean (±SD) urea reduction ratio was 65.1% ± 7.3%, the single-pool Kt/V was 1.26 ± 0.11, and the equilibrated Kt/V was 1.05 ± 0.09; in the high-dose group, the values were 73.5% ± 8.7%, 1.68 ± 0.15, and 1.47 ± 0.11, respectively. The standard deviation (SD) and residual SD (liner regression of Hb) values of Hb were significantly higher in the standard-dose group and low-flux group. The percentage achievement of target Hb in the high-dose dialysis group and high-flux dialyzer group was significantly higher than the standard-dose group and low-flux group, respectively. Patients undergoing hemodialysis thrice weekly appear to have benefit from a higher dialysis dose than that recommended by current KDQQI (Kidney Disease Qutcome Quality Initiative) guidelines or from the use of a high-flux membrane, which is in favor of maintaining stable Hb levels.

Does erythropoietin cause hemoglobin variability--is it 'normal'?

Hemoglobin variability (Hb-var) in patients with chronic kidney disease has been stipulated to be a result of exogenous treatment with erythropoiesis stimulating agents (ESA) and has been related to mortality in dialysis patients. We hypothesized the existence of Hb-var independent of ESA administration and compared it to that in healthy adults using data from the Scripps-Kaiser and NHANES III databases. We studied the Hb-var in 1571 peritoneal dialysis patients which included 116 patients not requiring treatment with erythropoietin. We systematically studied the differences between the groups that needed ESA therapy and those who did not. White race and male sex were significant predictors of need for erythropoietin therapy. We found peritoneal dialysis patients to exhibit significantly increased Hb-var independent of treatment with exogenous erythropoietin (0.99 gm/dL vs. 1.17 gm/dL, p-value<0.001). We found age to be a significant determinant of Hb-var in the ESA treated group. Hb-var in younger patients (<30 years) was increased by 50% compared to young healthy adults. The Hb-var in elderly (>60 years) peritoneal dialysis patients was similar to that seen in healthy elders, suggesting similarity with anemia of aging. We conclude that exogenous ESA administration does not explain Hb-var entirely but may enhance it. Intrinsic factors affecting erythropoiesis including age may be the major determinants of Hb-var.

Beyond linear methods of data analysis: time series analysis and its applications in renal research

Analysis of temporal trends in medicine is needed to understand normal physiology and to study the evolution of disease processes. It is also useful for monitoring response to drugs and interventions, and for accountability and tracking of health care resources. In this review, we discuss what makes time series analysis unique for the purposes of renal research and its limitations. We also introduce nonlinear time series analysis methods and provide examples where these have advantages over linear methods. We review areas where these computational methods have found applications in nephrology ranging from basic physiology to health services research. Some examples include noninvasive assessment of autonomic function in patients with chronic kidney disease, dialysis-dependent renal failure and renal transplantation. Time series models and analysis methods have been utilized in the characterization of mechanisms of renal autoregulation and to identify the interaction between different rhythms of nephron pressure flow regulation. They have also been used in the study of trends in health care delivery. Time series are everywhere in nephrology and analyzing them can lead to valuable knowledge discovery. The study of time trends of vital signs, laboratory parameters and the health status of patients is inherent to our everyday clinical practice, yet formal models and methods for time series analysis are not fully utilized. With this review, we hope to familiarize the reader with these techniques in order to assist in their proper use where appropriate.

Greater variability in kidney function is associated with an increased risk of death

Intra-individual variability in kidney function is a common phenomenon; however, predictors of kidney function variability and its prognostic significance are not known. To examine this question, we assembled a cohort of 51,304 US veterans with an estimated glomerular filtration rate (eGFR) <60 ml/min at the end of the study period and who had at least two eGFR measurements during the previous 3 years. Variability in kidney function was defined for each patient as the coefficient of variation of the regression line fitted to all outpatient measures of eGFR during this time frame. In adjusted analyses, blacks, women, and those with Current Procedural Terminology and ICD-9-CM diagnostic codes for hypertension, diabetes, cardiovascular disease, peripheral artery disease, chronic lung disease, hepatitis C, dementia, acute kidney injury, and those with a greater number of hospitalizations had greater variability in eGFR. After a median follow-up of 4.9 years, there were 23.66%, 25.68%, and 31.23% deaths among patients in the lowest, intermediate, and highest tertiles of eGFR variability, respectively. Compared with the referent (those in the lowest tertile), patients in the highest tertile had a significantly increased risk of death with a hazard ratio of 1.34 (1.28-1.40), an association consistently present in all sensitivity analyses. Thus, our results demonstrate that greater variability in kidney function is independently associated with increased risk of death.

Facility-level interpatient hemoglobin variability in hemodialysis centers participating in the Dialysis Outcomes and Practice Patterns Study (DOPPS): Associations with mortality, patient characteristics, and facility practices

BACKGROUND

Hemodialysis patients with larger hemoglobin level fluctuations have higher mortality rates. We describe facility-level interpatient hemoglobin variability, its relation to patient mortality, and factors associated with facility-level hemoglobin variability or achieving hemoglobin levels of 10.5-12.0 g/dL. Facility-level hemoglobin variability may reflect within-patient hemoglobin variability and facility-level anemia-control practices.

STUDY DESIGN

Prospective cohort study.

SETTING & PARTICIPANTS

Data from the Dialysis Outcomes and Practice Patterns Study (DOPPS; 26,510 hemodialysis patients, 930 facilities, 12 countries, 1996-2008) and from the Centers for Medicare & Medicaid Services (CMS; 193,291 hemodialysis patients, 3,741 US facilities, 2002).

PREDICTORS

Standard deviation (SD) in single-measurement hemoglobin levels in hemodialysis patients in facility cross-sections (facility-level hemoglobin SD); patient characteristics; facility practices.

OUTCOMES

Patient-level mortality; additionally, facility practices correlated with facility-level hemoglobin SD or patient hemoglobin levels of 10.5-12.0 g/dL.

RESULTS

Facility-level hemoglobin SD varied more than 5-fold across DOPPS facilities (range, 0.5-2.7 g/dL; mean, 1.3 g/dL) and by country (range, 1.1 in Japan-DOPPS [2005/2006] to 1.7 g/dL in Spain-DOPPS [1998/1999]), with substantial decreases seen in many countries from 1998 to 2007. Facility-level hemoglobin SD was related inversely to patient age, but was associated minimally with more than 30 other patient characteristics and facility mean hemoglobin levels. Several anemia management practices were associated strongly with facility-level hemoglobin SD and having a hemoglobin level of 10.5-12.0 g/dL. When examined in CMS data, facility-level hemoglobin SD was positively associated with within-patient hemoglobin SD during the prior 6 months. Patient mortality rates were higher with greater facility-level hemoglobin SD (DOPPS: HR, 1.08 per 0.5-g/dL greater facility-level hemoglobin SD [95% CI, 1.02-1.15; P = 0.006]; CMS: HR, 1.16 per 0.5-g/dL greater facility-level hemoglobin SD [95% CI, 1.11-1.21; P < 0. 001]).

LIMITATIONS

Residual confounding.

CONCLUSIONS

Facility-level hemoglobin SD was associated strongly and positively with patient mortality, not tightly linked to numerous patient characteristics, but related strongly to facility anemia management practices. Facility-level hemoglobin variability may be modifiable and its optimization may improve hemodialysis patient survival.

Development of an erythropoietin prescription simulator to improve abilities for the prescription of erythropoietin stimulating agents: is it feasible?

BACKGROUND

The increasing use of erythropoietins with long half-lives and the tendency to lengthen the administration interval to monthly injections call for raising awareness on the pharmacokinetics and risks of new erythropoietin stimulating agents (ESA). Their pharmacodynamic complexity and individual variability limit the possibility of attaining comprehensive clinical experience. In order to help physicians acquiring prescription abilities, we have built a prescription computer model to be used both as a simulator and education tool.

METHODS

The pharmacokinetic computer model was developed using Visual Basic on Excel and tested with 3 different ESA half-lives (24, 48 and 138 hours) and 2 administration intervals (weekly vs. monthly). Two groups of 25 nephrologists were exposed to the six randomised combinations of half-life and administration interval. They were asked to achieve and maintain, as precisely as possible, the haemoglobin target of 11-12 g/dL in a simulated naïve patient. Each simulation was repeated twice, with or without randomly generated bleeding episodes.

RESULTS

The simulation using an ESA with a half-life of 138 hours, administered monthly, compared to the other combinations of half-lives and administration intervals, showed an overshooting tendency (percentages of Hb values > 13 g/dL 15.8 ± 18.3 vs. 6.9 ± 12.2; P < 0.01), which was quickly corrected with experience. The prescription ability appeared to be optimal with a 24 hour half-life and weekly administration (ability score indexing values in the target 1.52 ± 0.70 vs. 1.24 ± 0.37; P < 0.05). The monthly prescription interval, as suggested in the literature, was accompanied by less therapeutic adjustments (4.9 ± 2.2 vs. 8.2 ± 4.9; P < 0.001); a direct correlation between haemoglobin variability and number of therapy modifications was found (P < 0.01).

CONCLUSIONS

Computer-based simulations can be a useful tool for improving ESA prescription abilities among nephrologists by raising awareness about the pharmacokinetic characteristics of the various ESAs and recognizing the factors that influence haemoglobin variability.

Hemoglobin variability does not predict mortality in European hemodialysis patients

Patients with CKD exhibit significant within-patient hemoglobin (Hb) level variability, especially with the use of erythropoiesis stimulating agents (ESAs) and iron. Analyses of dialysis cohorts in the United States produced conflicting results regarding the association of Hb variability with patient outcomes. Here, we determined Hb variability in 5037 European hemodialysis (HD) patients treated over 2 years to identify predictors of high variability and to evaluate its association with all-cause and cardiovascular disease (CVD) mortality. We assessed Hb variability with various methods using SD, residual SD, time-in-target (11.0 to 12.5 g/dl), fluctuation across thresholds, and area under the curve (AUC). Hb variability was significantly greater among incident patients than prevalent patients. Compared with previously described cohorts in the United States, residual SD was similar but fluctuations above target were less frequent. Using logistic regression, age, body mass index, CVD history, dialysis vintage, serum albumin, Hb, angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) use, ESA use, dialysis access type, dialysis access change, and hospitalizations were significant predictors of high variability. Multivariable adjusted Cox regression showed that SD, residual SD, time-in-target, and AUC did not predict all-cause or CVD mortality during a median follow-up of 12.4 months (IQR: 7.7 to 17.4). However, patients with consistently low levels of Hb (<11 g/dl) and those who fluctuated between the target range and <11 g/dl had increased risks for death (RR 2.34; 95% CI: 1.24 to 4.41 and RR 1.74; 95% CI: 1.00 to 3.04, respectively). In conclusion, although Hb variability is common in European HD patients, it does not independently predict mortality.