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Interact CardioVasc Thorac Surg 2009;9:593-597. doi:10.1510/icvts.2009.208033
© 2009 European Association of Cardio-Thoracic Surgery

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Institutional report - Cardiac general

Age- and gender-specific values of estimated glomerular filtration rate among 6232 patients undergoing cardiac surgery

Claudius Dieza,e,*, Peter Mohrb, Daniel Kochc, Rolf-Edgar Silberd, Christof Schmida and Hans-Stefan Hofmanne

a Department of Cardiac Surgery, University Medical Centre Regensburg, Franz-Josef-Strauß-Allee 11, D-93053 Regensburg, Germany
b Department of Internal Medicine II, Martin-Luther-University Halle-Wittenberg, Ernst-Grube-Str. 40, D-06097 Halle (Saale), Germany
c Department of Internal Medicine, St. Barbara Hospital, Barbarastr. 67, 47167 Duisburg, Germany
d Department of Cardiothoracic Surgery, Martin-Luther-University Halle-Wittenberg, Ernst-Grube-Str. 40, D-06097 Halle (Saale), Germany
e Department of Thoracic Surgery, University Medical Centre Regensburg, Franz-Josef-Strauß-Allee 11, D-93053 Regensburg, Germany

Received 23 March 2009; received in revised form 11 June 2009; accepted 15 June 2009

*Corresponding author. Tel.: +49 941 944 9874; fax: +49 941 944 9802.

E-mail address: claudius.diez{at}t-online.de (C. Diez).


    Abstract
 Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
 Acknowledgements
 References
 
Impaired preoperative renal function as estimated by glomerular filtration rate (GFR) is an independent risk factor for mortality after cardiac surgery. Little is known about the actual prevalence of renal dysfunction among patients undergoing cardiac surgery in Germany. We performed a retrospective analysis of 6232 patients from 20 to 80 years. GFR was estimated with the modification of diet in renal disease (MDRD) formula. There was an age-dependent decrease in estimated glomerular filtration rates (eGFR) among both men and women. There is a stepwise age-dependent increase of chronic kidney disease (CKD) stages 3–5 (<60 ml/min/1.73 m2). The lower the eGFR the higher the risk for mortality [odds ratio 2.93 95%-confidence interval (CI) 1.92–4.53] for eGFR<30 ml/min/1.73 m2; odds ratio 1.93 (95%-CI 1.56–2.39) for eGFR 30–60 ml/min/1.73 m2 compared to patients with an eGFR>60 ml/min/1.73 m2. The actual mortality rates varied between 6.3% (307/4869) for patients with an eGFR>60 ml/min/1.73 m2, 11.3% (137/1051) for patients with an eGFR of 30–60 ml/min/1.73 m2 and 16.6% (27/163) for patients with an eGFR<30 ml/min/1.73 m2. Estimated GFR declines are age- and gender-dependent. Preoperative renal dysfunction is an important predictor of in-hospital mortality after cardiac surgery.

Key Words: Estimated GFR; Renal dysfunction; Cardiac surgery; MDRD-equation


    1. Introduction
 Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
 Acknowledgements
 References
 
Kidney dysfunction is common after cardiac surgery and predicts mortality risk and poorer long-term outcome, particularly when acute injury superimposes upon chronic kidney disease (CKD) [1]. Regardless of cause, evidence supports a role for renal impairment and accumulation of uremic toxins as direct contributors to adverse outcome. However, practice modifications can influence the likelihood of acute kidney injury. The kidney disease outcomes quality initiative (K/DOQI) has proposed to classify CKD in five stages according to the absence of albuminuria and the level of glomerular filtration rate (GFR). The guidelines propose that patients with GFR<60 ml/min/1.73 m2 are at risk and need to be evaluated and properly treated [2].

GFR is an important clinical indicator of kidney function and can be used as an independent predictor of survival [3]. For many years, serum creatinine (SCr) has been used in routine clinical practice as a marker of GFR. However, it is well recognised that SCr is not an accurate marker of GFR because it is influenced by muscle mass and the relation with GFR is influenced by race, gender, age and body weight. Therefore, several formulas has been developed for the estimation of GFR and K/DOQI guidelines advocate the use of the ‘modification of diet in renal disease’ (MDRD)-formula for the calculation of GFR. This formula provides a good estimate of GFR, in particular in the GFR range <60 ml/min/1.73 m2.

However, only limited information exists on GFR estimation values in patients with cardiovascular morbidities undergoing cardiac surgery. We examined in a large cohort age- and gender specific eGFRs among 6232 adult German patients, who underwent cardiac surgery at two University Hospitals.


    2. Materials and methods
 Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
 Acknowledgements
 References
 
2.1. Patient selection

We initially included 6745 consecutive white Caucasian patients (between January 2002 and December 2007), who underwent cardiac surgery at the University Medical Centres Regensburg and Halle (Saale). We excluded 513 patients due to the following reasons: 56 patients <20 years, 90 patients with terminal renal failure and preoperative dialysis, 78 patients with missing preoperative SCr measurement and 289 patients with insufficient documentation. The final study sample comprised 6232 participants [n=3858 (Regensburg) and n=2374 (Halle)]. In addition, patients undergoing heart transplantation and ventricular assist device implantation were excluded. Informed consent was obtained from each individual and the study was approved by the Institutional Ethics Committee at both University Medical Centres.

2.2. Data collection

We retrospectively reviewed the patient's medical records and entered the data into an Excel-worksheet. The primary endpoint was the preoperative eGFR. The eGFR-associated mortality was considered as a secondary endpoint.

Preoperative risks factors, such as gender, weight, age, atrial fibrillation and diabetes were defined like in the EuroSCORE [4]. Operative data included type of operation, operation time, aortic cross-clamp time and bypass time.

2.3. GFR estimation

SCr was measured at the day of admission (either in µmol/l or mg/dl, 1 mg/dl=88.4 µmol/l).

Both hospital laboratories used the same certified enzymatic creatinine assay from the same manufacturer (Roche Diagnostics, Basel, Switzerland).

GFR was estimated with the abbreviated MDRD formula. It was expressed in ml/min/1.73 m2:



Formula 1

(1)

2.4. Statistics

Data were analysed with SPSS 16.0.2 for Windows (SPSS Inc, Chicago, USA) and Stata 10 SE for Windows (StataCorp LP, College Station, USA). Differences between normally distributed continuous data were analysed with the unpaired t-test and presented as mean differences with 95% confidence interval (CI). The Mann–Whitney U-test was used for non-normally distributed data. The CI for the difference of two medians was calculated as proposed by Bonett and Price in 2002 [5]. Overall differences between more than two groups were analysed with the analysis of variance (ANOVA) followed by Tukey's test or, where appropriate, with the Kruskal–Wallis test followed by Mann–Whitney U-test. Fisher's exact test was used for categorical variables in a 2x2 table.

Logistic regression analysis helped to examine the relationship between CKD-class and in-hospital mortality. Linear regression of eGFR on age was performed to examine the relation between eGFR decreases with age.

SigmaPlot 10.0 for Windows (www.systat.de) was used to create figures.

Data are either shown as mean and standard deviation (S.D.) or, where appropriate and indicated as median with interquartile range (IQR).


    3. Results
 Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
 Acknowledgements
 References
 
3.1. Demographic and operative data

Table 1 summarises the demographic and operative data. The majority of our study participants suffered multiple comorbidities. Almost 75% (4549/6232) of patients had long-lasting hypertension and at least 32% had diabetes. Interestingly, only 2.1% (131/6232) among our study sample were reported to have known preoperative non-dialysis dependent renal dysfunction.


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Table 1 Demographic data (n=6232)

 
The operative spectrum represented the typical mixture of modern cardiac surgery units. Almost two-thirds (62%) of our patients underwent coronary bypass grafting (CABG), whereas 21% received valve replacement or repair, respectively.

3.2. Age- and gender-specific eGFR values

Gender-specific values of estimated GFR (MDRD) per 5-year age groups are shown in Tables 2 and 3. Women undergoing cardiac surgery exhibited, as expected, lower eGFR values than their male counterparts (Figs. 1 and 2).


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Table 2 Estimated GFR in Caucasian males among the study sample

 

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Table 3 Estimated GFR in Caucasian females among the study sample

 

Figure 1
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Fig. 1. Estimated GFR values in Caucasian females are shown. Median (P50) values and 5th, 25th, 75th and 95th percentiles are shown according to several age groups.

 

Figure 2
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Fig. 2. Estimated GFR values in Caucasian males are presented. Median (P50) values and 5th, 25th, 75th and 95th percentiles are shown according to several age groups.

 
3.3. Stages of CKD

Since we could not acquire information on preoperative proteinuria or hematuria, our data only allowed correct classification of patients in CKD stages 3–5 (<60 ml/min/1.73 m2). Fig. 3 depicts the prevalence of CKD stages 3–5 in our study population. The prevalence increased with age, reaching 52% in women and 33% in men who are older than 80 years (P<0.001). Interestingly, younger women (<44 years and 50–54 years) significantly had more frequently CKD stage 3 and above, which places them at increased perioperative risk.


Figure 3
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Fig. 3. Prevalence of chronic kidney disease stages 3–5 (GFR<60 ml/min/1.73 m2) according to age is shown. Women >65 years have significantly more frequently CKD stages 3–5 (P<0.05) than their male counterparts.

 
A linear regression analysis helped to examine the relation between the age-dependent decreases in eGFR (Fig. 4).


Figure 4
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Fig. 4. Age-dependent decreases in eGFR among the study sample. The dotted lines represent the 95% prediction intervals, whereas the solid line is the regression line.

 
3.4. Estimated GFR and in-hospital mortality

Since it is clinically important to detect patients with preoperative renal dysfunction, we assigned them into three different eGFR groups (<30 ml/min/1.73 m2; 30–59 ml/min/1.73 m2; ≥60 ml/min/1.73 m2) and calculated the odds ratios for in-hospital mortality in a logistic regression analysis, in which the group ≥60 ml/min/1.73 m2 represented the reference group with normal eGFR. There was a 1.93-fold increase (95% CI: 1.56–2.39) in risk for mortality among the 30–59 ml/min/1.73 m2 eGFR group (P<0.001) and a 2.93-fold increase (95% CI: 1.92–4.53) for the <30 ml/min/1.73 m2 eGFR group (P<0.001) compared to the reference group.

The highest in-hospital mortality of 16.6% (27/136) was experienced among patients with an eGFR<30 ml/min/1.73 m2 followed by patients with an eGFR of 30–60 ml/min/1.73 m2 (11.5%, 137/1051). Patients with an eGFR>60 ml/min/1.73 m2 had a overall mortality of 6.3% (307/4562). The mortality and preoperative eGFR are summarised in Fig. 5.


Figure 5
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Fig. 5. Three preoperative eGFR classes and associated observed mortality are shown.

 

    4. Discussion
 Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
 Acknowledgements
 References
 
We report on the preoperative eGFR distribution and consequences on in-hospital mortality among 6232 Caucasian patients undergoing cardiac surgery in Germany at two University Hospitals.

The MDRD formula currently provides the best estimate of GFR, particularly when GFR<60 ml/min/1.73 m2 [6, 7]. Patients with an eGFR<60 ml/min/1.73 m2 are considered to be at high risk for cardiovascular morbidity, mortality and end-stage renal failure [8].

Recently, one study provided both reference values of MDRD-eGFR for non-diseased (n=3732) and diseased (n=2365) white Caucasians [9]. There was an age-dependent decrease in eGFR. How eGFR is distributed among patients undergoing cardiac surgery has not been published yet, although these patients comprise a heterogeneous population, suffer multiple comorbidities, such as hypertension and diabetes mellitus and experience severe operative stress. The presence of CKD is one of the most potent risk factors for cardiovascular disease such that patients with CKD have a 10–20-fold risk of cardiac death compared to sex- and age-matched controls [8, 10]. In patients undergoing CABG, chronic renal failure, defined as SCr >200 µmol/l (2.26 mg/dl) and end-stage renal dysfunction are recognised risk factors for increased perioperative mortality and are accounted for in the commonly used cardiac risk stratification systems [4].

Our data for in-hospital mortality are in line with three recently published studies, where it was shown that even mild renal preoperative dysfunction predicts in-hospital mortality and post-discharge survival [11–13]. Therefore, surgeons should be aware of subtle changes in eGFR for risk stratification in patients undergoing cardiac surgery. However, our data on mortality and preoperative eGFR should be carefully interpreted and weighed against a large heterogeneous population with various surgical procedures and comorbidities. Thus, the mere median EuroSCORE value might not appear to reflect the actual mortality in our study with respect to impaired eGFR. The EuroSCORE only considers creatinine values >200 µmol/l as renal dysfunction, but several studies have shown that this arbitrary threshold proved not to be useful in the evaluation of renal dysfunction.

As expected, our data also demonstrated an age- and gender-dependent increase in CKD stage 3 and above. In particular, women <45 years undergoing cardiac surgery experience a more than two-fold higher prevalence of CKD stage 3 and above indicating a more severe disease status.

Our data also indicate that the 60 ml/min/1.73 m2 threshold independent of age appears difficult to define a diseased population. As illustrated in our study, MDRD-eGFR decreases with age. In the reference study, an eGFR of 60 ml/min/1.73 m2 was within the normal reference range (P5–P95) for men >60 years and women >50 years. Even with the most optimistic view, this threshold with respect to age was not included in our eGFR range for all age groups and independent of gender. Closer inspection of our data showed that in particular the P5 and P25 values were much lower compared to a reference sample.

Although there is still much debate on the use of the formulae for estimating GFR and newer formulae, such as the Mayo Clinic formula were introduced, a recent study showed that using the MDRD equation results in nearly unbiased estimates of GFR [14].

4.1. Implications

Cardiovascular surgeons should be very aware of subtle changes in preoperative GFR as an independent risk factor for patients undergoing cardiac surgery. The association between renal dysfunction and increased incidence of postoperative mortality requires improved resource planning by those responsible for health care provision. A better understanding of mechanisms underlying progressive renal dysfunction and improved renal protection strategies during the operative period may ameliorate both in-hospital and late survival following cardiovascular surgery.

4.2. Strengths and limitations

This is the largest contemporary German analysis of preoperative renal dysfunction in patients undergoing cardiac surgery. Data provided were directly collected from medical records and the database is 98.5% complete for all analysed fields. It was re-validated by another co-author before analysis. These procedures should have reduced errors, but did not eliminate them completely.

This study has limitations. Firstly, conclusions from a retrospective observational study are necessarily limited in their application and do not allow statements on causality. Secondly, we cannot provide long-term survival data because of difficult postoperative survival data retrieval in Germany. Thirdly, observational bias, particularly for outcomes defined by clinical interventions, which are dependent upon various treatment thresholds used by different clinicians, are a common error found in database derived studies. We finally remark that our study is purely exploratory, especially by using automatic selection procedures which are known to generally overestimate the influences of prognostic factors [15]. As such, we would like to see replications of our analyses in independent samples.


    Acknowledgements
 Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
 Acknowledgements
 References
 
We would like to thank the secretaries of the Department of Cardiothoracic Surgery and the members of the Medical Record Archive at the University Halle-Wittenberg. Additionally, we would like to thank Mr S. Festner from the Department of Cardiothoracic Surgery at the University Medical Centre Regensburg for database management.


    References
 Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
 Acknowledgements
 References
 

  1. Stafford-Smith M, Patel UD, Phillips-Bute BG, Shaw AD, Swaminathan M. Acute kidney injury and chronic kidney disease after cardiac surgery. Adv Chronic Kidney Dis 2008;15:257–277.[CrossRef][Medline]
  2. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis 2002;39:S1–S266.[CrossRef][Medline]
  3. Jin R, Grunkemeier GL, Brown JR, Furnary AP. Estimated glomerular filtration rate and renal function. Ann Thorac Surg 2008;86:1–3.[Abstract/Free Full Text]
  4. Nashef SA, Roques F, Michel P, Gauducheau E, Lemeshow S, Salamon R. European system for cardiac operative risk evaluation (EuroSCORE). Eur J Cardiothorac Surg 1999;16:9–13.[Abstract/Free Full Text]
  5. Bonett DG, Price RM. Statistical inference for a linear function of medians: confidence intervals, hypothesis testing, and sample size requirements. Psychol Methods 2002;7:370–383.[CrossRef][Medline]
  6. 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]
  7. Poggio ED, Wang X, Greene T, Van Lente F, Hall PM. Performance of the modification of diet in renal disease and Cockcroft-Gault equations in the estimation of GFR in health and in chronic kidney disease. J Am Soc Nephrol 2005;16:459–466.[Abstract/Free Full Text]
  8. Cirillo M, Laurenzi M, Mancini M, Zanchetti A, Lombardi C, De Santo NG. Low glomerular filtration in the population: prevalence, associated disorders, and awareness. Kidney Int 2006;70:800–806.[CrossRef][Medline]
  9. Wetzels JF, Kiemeney LA, Swinkels DW, Willems HL, den Heijer M. Age- and gender-specific reference values of estimated GFR in Caucasians: the Nijmegen Biomedical Study. Kidney Int 2007;72:632–637.[CrossRef][Medline]
  10. Foley RN, Wang C, Collins AJ. Cardiovascular risk factor profiles and kidney function stage in the US general population: the NHANES III study. Mayo Clin Proc 2005;80:1270–1277.[Abstract/Free Full Text]
  11. Brown JR, Cochran RP, MacKenzie TA, Furnary AP, Kunzelman KS, Ross CS, Langner CW, Charlesworth DC, Leavitt BJ, Dacey LJ, Helm RE, Braxton JH, Clough RA, Dunton RF, O'Connor GT. Long-term survival after cardiac surgery is predicted by estimated glomerular filtration rate. Ann Thorac Surg 2008;86:4–11.[Abstract/Free Full Text]
  12. Filsoufi F, Rahmanian PB, Castillo JG, Chikwe J, Carpentier A, Adams DH. Early and late outcomes of cardiac surgery in patients with moderate to severe preoperative renal dysfunction without dialysis. Interact CardioVasc Thorac Surg 2008;7:90–95.[Abstract/Free Full Text]
  13. Howell NJ, Keogh BE, Bonser RS, Graham TR, Mascaro J, Rooney SJ, Wilson IC, Pagano D. Mild renal dysfunction predicts in-hospital mortality and post-discharge survival following cardiac surgery. Eur J Cardiothorac Surg 2008;34:390–395; discussion 395.[Abstract/Free Full Text]
  14. Hallan S, Astor B, Lydersen S. Estimating glomerular filtration rate in the general population: the second Health Survey of Nord-Trondelag (HUNT II). Nephrol Dial Transplant 2006;21:1525–1533.[Abstract/Free Full Text]
  15. Babyak MA. What you see may not be what you get: a brief, nontechnical introduction to overfitting in regression-type models. Psychosom Med 2004;66:411–421.[Abstract/Free Full Text]




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