1 Baker Medical Research Institute, Melbourne, Victoria, 2 Endocrinology Unit and Department of Medicine, University of Melbourne, Heidelberg, Victoria, 3 Diabetes Centre, Royal Prince Alfred Hospital and Discipline of Medicine, University of Sydney, NSW and 4 Sydney Diabetes, Department of Diabetes, Endocrinology and Metabolism, Royal North Shore Hospital, Sydney, Australia
Correspondence and offprint requests to: Dr Merlin C. Thomas, Baker Medical Research Institute, PO Box 6492, Melbourne, VIC 8008, Australia. Email: mthomas{at}baker.edu.au
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Abstract |
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Methods. A full blood count was obtained in addition to routine testing in a cross-sectional survey of all patients with type 2 diabetes in long-term follow-up at the Austin Medical Centre, Melbourne (n = 670) and the Royal Prince Alfred Hospital (n = 915) and the Royal North Shore Hospital (n = 540), Sydney, Australia. The prevalence and correlates of anaemia (haemoglobin < 130 g/l in men and < 120 g/l in women) were identified using multivariate logistic regression.
Results. Roughly, one in five patients in each centre had anaemia. Patients at greatest risk could be readily identified by the presence of renal disease, manifested as impaired renal function and/or albuminuria in > 75% of patients with anaemia. Patients with diabetes and mild renal impairment [creatinine clearance (CCr) 6090 ml/min/1.73 m2] were twice as likely to have anaemia as those with normal renal function (CCr > 90 ml/min/1.73 m2). Diabetics with moderate renal impairment (CCr < 60 ml/min/1.73 m2) were also twice as likely to have anaemia as those with mild renal impairment. Patients with anaemia were also more likely to have macrovascular disease, reflecting the high prevalence of nephropathy in these patients.
Conclusions. Anaemia is a prevalent finding in patients with type 2 diabetes and represents a significant unrecognized burden. Patients at greatest risk can be identified by the presence of renal disease, either in the form of renal impairment and/or albuminuria.
Keywords: albuminuria; cardiovascular disease; diabetic nephropathy; erythropoietin; renal impairment; type 2 diabetes
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Introduction |
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In the diabetes clinic, the prevalence of unrecognized anaemia might be significantly higher than in the general population. In a recent cross-sectional survey of patients with diabetes in a single clinic, we found that nearly a quarter of all outpatients had anaemia [5]. It is in precisely these patients that the additional burden of anaemia may be significant in determining the outcome of comorbid vascular disease. Certainly, reduced haemoglobin (Hb) levels, even to a limited degree, identify patients at increased risk of hospitalization and mortality [6,7]. As a follow-up to our initial study [5], we present a much larger composite survey from three clinical centres in order to estimate the burden of anaemia in outpatients with type 2 diabetes. In addition, we specifically examine the impact of anaemia in patients over 65 years of age, which represents the fastest growing diabetic subgroup [8] associated with the greatest level of vascular disease.
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Subjects and methods |
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Patient data were obtained from three Australian centres: the Austin Medical Centre (AMC), Melbourne (n = 670) and the Royal Prince Alfred (RPA) Hospital (n = 915) and the Royal North Shore (RNS) Hospital, Sydney (n = 540). The majority of patients were referred to these clinics by general practitioners requiring assistance with surveillance and management of the long-term complications of diabetes. Approximately 20% of the patients were referred from other sources, including specialty units within each hospital. At the time of this audit none of these clinics shared patient care with nephrology services. Data collected as part of these cross-sectional surveys were obtained with the approval of respective hospital ethics committees and meet National Health and Medical Research Council (NHMRC) ethics guidelines.
Determination of variables
Standard indices were collected from the most recent routine clinical visit, including creatinine, urea, fasting lipid profile and HbA1c determined by high-performance liquid chromatography. Urinary creatinine, urea and albumin excretion were estimated from a 24 h urine collection. Clinical data, including anthropometric measurements, age, gender, body mass index, duration of diabetes, length of follow-up and the presence or absence of macrovascular disease, were obtained from patient records on all patients. In addition, Hb concentration was obtained for all patients. Results obtained outside the outpatient setting (e.g. patients in an emergency situation or hospitalized) were excluded. Hb was primarily handled both as a continuous variable and recoded as a binary outcome for estimating the prevalence of anaemia. The presence of anaemia was defined by a Hb < 130 g/l in men and < 120 g/l in women; a gender-specific definition established by the World Health Organization (WHO) [9].
The level of albuminuria was defined categorically from the most recent urinalysis according to standard guidelines. Albumin excretion rate (AER), derived from 24 h urinary albumin measurement, was categorically defined from the three most recent AER measurements. Macroalbuminuria was defined as two of three AER measurements > 200 µg/min. Microalbuminuria was defined as two of three AER measurements between 20 and 200 µg/min. Normoalbuminuria was defined by two of three AER measurements < 20 µg/min. The term elevated albuminuria was used to denote patients with either micro- or macroalbuminuria (AER > 20 µg/min). Creatinine clearance (CCr) was determined using the CockcroftGault formula expressed per 1.73 m2 of body surface area. For categorical analysis, moderate renal impairment was defined by a CCr of < 60 ml/min/1.73 m2, mild renal impairment by a CCr of between 60 and 90 ml/min/1.73 m2 and normal renal function by a CCr > 90 ml/min/1.73 m2.
Statistical methods
As clinical data were obtained separately, observations pertaining to each population are provided separately in addition to pooled results. Continuous data are expressed as means±SEM. Differences in continuous variables were compared using Student's t-tests (two groups) or one-way analysis of variance (three or more groups, with subgroups compared using Fisher's partial least-squares difference post hoc test). Differences in categorical variables were compared using chi-square analysis. Pearson correlation was used to analyse univariate associations between continuous variables. Logistic regression was used to analyse associations between independent predictors.
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Results |
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Prevalence of anaemia
The overall distribution of Hb levels was remarkably similar in all three centres (Figure 1). Hb levels in each population were normally distributed, with only a small degree of skewness seen at the lower end of the Hb range. Roughly one in five patients in all three centres had anaemia according to WHO guidelines (men: < 130 g/l; women: < 120 g/l). The current Australian guidelines provide a government subsidy for the use of synthetic erythropoietin analogues for patients with moderate renal impairment and a Hb of < 100 g/l [http://www1.health.gov.au/pbs]. Using this criterion, 3% of clinic patients warranted intervention.
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Most patients with anaemia could be identified by the presence of either moderate renal impairment or elevated albuminuria. Over three-quarters of anaemic patients had one or other of these risk factors. Approximately 70% of the remaining patients with anaemia and neither albuminuria nor renal impairment had a prolonged duration of diabetes (> 10 years).
The effect of age
Anaemia was more common with advancing age in patients with diabetes in all three centres. Approximately 70% of patients with diabetes and anaemia in each centre were over the age of 65 years (compared with approximately half of patients without anaemia). Although the so-called anaemia of ageing may contribute to this phenomenon [10], this observation was confounded by the increased prevalence of renal disease (both in terms of low CCr and elevated albuminuria) in elderly patients. Although correlated with age, after adjusting for these additional variables, there was no independent association between age and Hb, either in pooled analysis or in any of the three populations individually.
The effect of gender
Figure 1 demonstrates that gender is an important determinant of raw Hb level, represented by divergent reference ranges documented in the general population. This gender difference is incorporated into the WHO guidelines for the diagnosis of anaemia [9], meaning that gender was eliminated as an independent predictor of anaemia in each of the three centres. The validity of this correction, which incorporates the disparate gender reference ranges, has been questioned recently in the BMJ [11]. However, the use of a single cut-off level of Hb to define anaemia would then include twice as many women represented as men.
Interaction with macrovascular disease
Patients with type 2 diabetes in each of the tertiary referral centres have high rates of macrovascular disease, consistent with their advanced age and the high prevalence of hypertension and nephropathy. Patients with macrovascular disease were nearly twice as likely to have anaemia compared with those free of macrovascular disease (Figure 3A). In addition, patients with anaemia were significantly more likely to have any comorbid macrovascular disease (Figure 3B). After correcting for glomerular filtration rate (GFR) and albuminuria in patients with macrovascular disease using logistic regression analysis, this association was eliminated. However, patients with anaemia were significantly more likely to have a history of cerebrovascular disease and peripheral vascular disease, even after correcting for GFR and albuminuria.
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Discussion |
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Although this survey has not attempted to define the cause of anaemia in any patient, those at greatest risk could be identified by the presence of renal disease, manifested as impaired renal function and/or elevated albuminuria in > 75% of patients with anaemia. This suggests that the predominant cause of anaemia may be renal in origin. This finding has implications for the often extensive investigations that are undertaken to define the cause of anaemia in such patients. In addition, the finding of anaemia in a patient with diabetes should direct the treating physician to investigate the possibility of renal involvement.
We have previously shown that reduced renal function is the most important determinant of Hb levels in patients with diabetes [5]. As renal function fell, the prevalence of anaemia increased exponentially in all three centres surveyed. However, the effect of renal impairment is not confined to patients with elevated serum creatinine levels. Even in patients with a normal serum creatinine, CCr was associated with the prevalence of anaemia (P<0.01 in all centres). This finding underlines the importance of an estimated CCr in the management of patients with diabetes, particularly in the elderly, where reduced muscle mass can lead to pseudonormalization of serum creatinine levels.
This survey also demonstrates the independent association between albuminuria and anaemia. Proteinuria itself does not appear to be the causal factor, as proteinuria of non-diabetic aetiology is not associated with an increased risk of renal anaemia [2]. It appears more likely that proteinuria is a marker of tubulointerstitial injury in diabetes, perhaps more so than in other, primarily glomerular, conditions associated with proteinuria. Although the synthesis of erythropoietin in response to renal anaemia appears to be reduced in diabetes beyond that seen in other renal diseases [13], patients with diabetes are still able to mount an appropriate response to acute hypoxia [14], suggesting that the peritubular cells that produce erythropoietin are not simply lost. It seems likely that the anaemia-sensing (rather than secretory) mechanisms are dysfunctional in the anaemia of diabetes. This is phenomenologically similar to impaired glucose sensing in diabetic islets, which may respond normally to acute stimulation with arginine but inappropriately to glucose stimulus [15]. It is also conceivable that both of these findings may be linked to changes in blood flow mediated though up-regulation of the local reninangiotensin system [16].
It has been suggested that the widespread use of angiotensin-converting enzyme (ACE) inhibitors in diabetes, particularly in patients with elevated albuminuria or renal impairment, may contribute to a reduction in Hb [2]. However, recent evidence fails to support any significant link between ACE inhibitor use and Hb levels [17]. In addition, after correcting for differences in CCr in the AMC cohort, we have shown previously that there is no association between ACE inhibitor use and anaemia. It has also been suggested that autonomic degeneration as a result of diabetes may diminish erythropoietin release [13]. As autonomic neuropathy is closely correlated with renal injury, it is difficult to assess its independent influence. However, denervated kidneys used for transplantation appear to release erythropoietin normally [18].
It remains to be established what role anaemia may have in the development or progression of diabetic complications. Certainly, detection of anaemia identifies patients at increased risk for progressive renal disease [7], hospitalization and premature death [19]. Among middle-aged, community-based persons, the combination of nephropathy and anaemia is independently associated with an increased risk of stroke [20]. Although anaemia appears to be strongly associated with macrovascular disease and progression of nephropathy in patients with type 2 diabetes, this effect may be attributable to associated confounders, including renal impairment and albuminuria. However, the opposite might also be true, as some of the effects of renal impairment may be mediated through anaemia. In addition, patients with anaemia were more likely to have a symptomatic history of peripheral or cerebrovascular disease than those without anaemia, even after adjusting for GFR and albuminuria.
It is yet to be established that correction of anaemia in patients with diabetes will have any benefit. Tiredness, a common complaint in patients with diabetes [12], may significantly impact upon quality of life. Certainly, exercise tolerance, perhaps the most important risk factor in patients with type 2 diabetes, may be improved following treatment with erythropoietin analogues [21]. Correction of anaemia might also play a significant role in maintaining patients in a community setting. Treatment with erythropoietin in patients with heart failure might also have beneficial effects on end-organ function [22]. For patients with diabetes with ischaemic complications (representing 3050% of outpatients), correction of anaemia might also be beneficial. However, such benefits must be carefully balanced against the significant financial cost involved in treating these patients, as well as the potential for deleterious effects of erythropoietin, including raised blood pressure and pure red-cell aplasia. Correcting anaemia by other means, such as transfusion, also carries associated risks, including human lymphocyte antigen sensitization. It is hoped that upcoming randomized, double-blind controlled studies will clarify the role of correction of anaemia in patients with diabetes. In the meanwhile, this survey should encourage heightened awareness of the potential burden of anaemia in patients with type 2 diabetes and the high prevalence of kidney disease in those with anaemia.
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Acknowledgments |
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Conflict of interest statement. None declared.
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References |
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