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NDT Advance Access originally published online on December 19, 2005
Nephrology Dialysis Transplantation 2006 21(6):1736-1738; doi:10.1093/ndt/gfi324
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© The Author [2005]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org


Letter

Estimation of glomerular filtration rate in patients with normal serum creatinine undergoing primary PCI: is it really normal?

Email: jolmal{at}poczta.onet.pl

Sir,

Kidney disease and cardiovascular disease seem to be lethally synergistic and both approach a level of epidemy, particularly in the elderly. The 2002 DOQI (Dialysis Outcomes Quality Initiative) states that individuals with a reduced glomerular filtration rate (GFR) are at greater risk for cardiovascular disease (CVD) and cardiac deaths [1]. The ability to identify chronic renal insufficiency may allow early implementation of treatments that could arrest or delay the progression of renal damage, enable effective treatment of its complications and reduce the risk of drug-induced nephrotoxicity. Contrast nephropathy is a potentially serious complication of diagnostic angiography and percutanous coronary intervention (PCI) [2]. Unfortunately, the cardiovascular risk increases in a concentration range of serum creatinine where this parameter is very insensitive to changes in GFR. The current Kidney Disease Outcomes Quality Initiative (K/DOQI) guidelines advocate creatinine-based equations for estimating the GFR to identify patients with potential kidney disease and to classify them into different stages on the basis of these values [1].

The aim of our study was to establish the prevalence of kidney dysfunction in patients with normal serum creatinine using estimated GFR according to the simplified MDRD [1] and Cockroft–Gault [3] formulae in a cohort of 1413 consecutive patients undergoing primary PCI due to ischaemic heart disease (988 males, 425 females). Normal serum creatinine (<1.5 mg/dl in males and <1.2 mg/dl in females) was observed in 1337 (95%) patients (943 males, 394 females). The mean GFR was 73.02±21.96 ml/min (Cockcroft–Gault formula) and 90.37±25.11 ml/min (MDRD). According to the Cockcroft–Gault formula, stage 2 chronic kidney disease (CKD), i.e. GFR 60–89 ml/min, was found in 627 patients (49.29%) and stage 3 CKD, i.e. GFR 30–59 ml/min, in 391 (30.74%) patients with normal serum creatinine. According to the MDRD formula, stage 2 CKD was found in 639 patients (50.78%) and stage 3 in 94 (4.79%) patients with normal serum creatinine. Patients with hypertension (n = 749), hyperlipidaemia (n = 417), smokers (n = 207) and those with a positive family history of ischaemic heart disease (n = 219) tended to have lower GFR, but not elevated serum creatinine. Patients with diabetes (n = 299) have a lower GFR measured using the Cockcroft–Gault formula (64.05±23.68 vs 69.99±22.93 ml/min, P<0.05), but not with the MDRD (82.76±28.66 vs 85.65±24.92, P = 0.20) despite comparable values of serum creatinine (1.07±0.45 vs 1.06±0.35 mg/dl, P = 0.66). Normal serum creatinine was found in 394 females (92.7%). According to the Cockcroft–Gault formula, stage 2 CKD was found in 165 (40.74%) and stage 3 in 195 (48.15%) females with normal serum creatinine. According to the MDRD formula, stage 2 CKD was found in 249 (63.20%) and stage 3 in 65 (16.50%) females with normal serum creatinine. Normal serum creatinine was found in 943 males (95.45%). According to the Cockcroft–Gault formula, stage 2 CKD was found in 661 (49.73%) and stage 3 in 196 (20.96%) males with normal serum creatinine. According to the MDRD formula, stage 2 CKD was found in 431 (42.63%) and stage 3 CKD was found in 29 (3.08%) males with normal serum creatinine. Females were significantly older (63.84±11.08 vs 57.39±11.47 years, P<0.01) with significantly lower GFR estimated using the Cockcroft–Gault formula (60.59±17.27 vs 78.21±21.63 ml/min, P<0.001), MDRD (78.29±19.91 vs 95.36±25.35 ml/min, P<0.001), lower serum creatinine (0.85±0.14 vs 1.03±0.19 mg/dl, P<0.01) despite similar body mass index (28.08±4.75 vs 28.29±4.07 kg/m2).

Interventional cardiologists are being asked to perform PCI on increasing numbers of patients with significant co-morbidities such as CKD. Patients with CKD have an enhanced mortality after an acute coronary syndrome and after PCI with or without stenting [4]. Since a marked reduction in GFR can be present before it is reflected as elevated serum creatinine, it is recommended that the chemical laboratory reports not only the serum creatinine concentration, but also the estimated GFR [5]. Surprisingly, in our study, we found a high prevalence of CKD, on the basis of estimated GFR, in patients with coronary artery disease and normal serum creatinine undergoing primary PCI. CKD is an under-recognized co-morbidity in patients with coronary artery disease and is associated with higher mortality risk. A recent study by Reddan et al. [6] published in the October issue of this journal prompted us to estimate GRF using two formulae: the simplified MDRD formula and the Cockcroft–Gault formula in a cohort of 1413 patients undergoing primary PCI. We found that in 1337 patients, creatinine was normal. In the SYMPHONY and 2nd SYMPHONY trials, patients with creatinine were also excluded [6]. We found a slightly higher percentage of patients with a creatine clearance <90 ml/min according to the modified MDRD formula—55.57 vs 50.10% in the study of Reddan et al. [6]. In addition, when the Cockcroft–Gault formula was used, the percentage of CKD in studied patients reached 80.03%. We found this prevalence of CKD enormously high.

The K/DOQI guidelines recommend estimating GFR in patients who are at risk for kidney disease using the MDRD study formulae. Within the 5th and 95th percentile for age, both formulae provide similar measurements, which were consistent with age-specific historic inulin clearance values [5]. The Cockcroft–Gault equation provided higher estimates at younger ages, and lower estimates at older ages (e.g. >70 years) than those obtained with the simplified MDRD formula [5]. It may at least partly explain our results. However, the accuracy of the MDRD formula in patient populations outside of the USA is also unclear [7]; therefore, we used both methods to estimate the GFR in our patients. On the basis of our results, we should stress that the prevalence of CKD and the impact of CKD on mortality and morbidity in patients with coronary artery disease undergoing primary percutaneous transluminal coronary angioplasty is probably underappreciated. It is reported that this population is not treated aggressively or with evidence-based therapies as frequently as those with normal GFR [6]. Renal dysfunction is thus a novel risk factor which must be incorporated into currently used algorithms to assess risk factor profiles. We also have to bear in mind that the risk of contrast nephropathy with worse outcomes is enhanced in these patients. A lower GRF in women, due to older age and lower body weight, explains why females are more prone to contrast nephropathy. Formulaic estimates of clearances can provide better information than serum creatinine alone.

Conflict of interest statement. None declared.

Hanna Bachorzewska-Gajewska1, Jolanta Malyszko2, Jacek S. Malyszko2, Slawomir Dobrzycki1, Bozena Sobkowicz3 and Wlodzimierz Musial3

1 Department of Invasive Cardiology2 Department of Nephrology3 Department of Cardiology Medical University Bialystok Poland

References

  1. National Kidney Foundation K/DOQI: clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis 2002; 39: S1–S266[CrossRef][ISI][Medline]
  2. Marenzi G, Lauri G, Assanelli E et al. Contrast-induced nephropathy in patients undergoing primary angioplasty for acute myocardial infarction. J Am Coll Cardiol 2004; 44: 1780–1785[Abstract/Free Full Text]
  3. Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron 1976; 16: 31–41[ISI][Medline]
  4. Naidu SS, Selzer F, Jacobs A et al. Renal insufficiency is an independent predictor of mortality after percutaneous coronary intervention. Am J Cardiol 2003; 92: 1160–1164[CrossRef][ISI][Medline]
  5. Coresh J, Astor BC, Greene T, Eknoyan G, Levey AS. Prevalence of chronic kidney disease and decreased kidney function in the adult US population: Third National Health and Nutrition Examination Survey. Am J Kidney Dis 2003; 41: 1–12[ISI][Medline]
  6. Reddan DN, Szczech L, Bhapkar MV et al. Renal function, concomitant medication use and outcomes following acute coronary syndromes. Nephrol Dial Transplant 2005; 20: 2105–2112[Abstract/Free Full Text]
  7. Froissart M, Rossert J, Jacquot C, Paillard M, Houillier P. Predictive performance of the modification of diet in renal disease and Cockcroft–Gault equations for estimating renal function. J Am Soc Nephrol 2005; 16: 763–773[Abstract/Free Full Text]

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