Conflicts between external responsibilities and current models of working

respectively while CGLBW underestimated in 67% of the patients

Table 11; frequency of overestimation and underestimation by each equation in the patients

N=57

CGABW

n (%)

MDRD n (%)

CGLBW

n (43)

overestimation 40 (70) 19 (33) 49 (86)

underestimation 17 (30) 38 (67) 8 (14)

CHAPTER SIX DISCUSSION

The result of this study demonstrated the peculiar problems of CKD in Nigeria and sub-saharan Africa as more than half of the patients were in the middle age group. This age group is the most active productive years economically and this reflects a huge loss to the individual, family and the nation. It also places huge demand on the fragile health system by the age group that should contribute most significantly to the economy.⁹³ This is similar to results found by Chijioke et al

94in Ilorin Nigeria and Ulasi et al ⁹⁵, in Enugu, South East Nigeria where the peak prevalence of CKD was between the third and the fifth decades. However results of studies from developed countries showed a peak age between 65 and 75years.¹⁸This may be due to early detection and treatment with better access to healthcare facilities in developed countries as against the socioeconomic and technological constraints in developing countries particularly sub Saharan Africa.⁹⁶

The commonest aetiology of chronic kidney disease among the study population was chronic glomerulonephritis (CGN) closely followed by hypertension both being jointly responsible for CKD in more than 52% of the patients. Diabetes mellitus solely accounted for 15.7%. This is consistent with earlier report on the aetiology of CKD in Nigeria.⁹⁷Studies from Sudan by El sharrif et al⁹⁸ found CGN as the leading cause among patients less than 40 years old and hypertension the leading cause in patients between the ages of 40years and 60years. Abboud et al⁹⁹also from Sudan found 38 patients with CGN out of the 120 patients with established chronic renal failure. The other causes include renal calculi and diabetic nephropathy. A review of the South African Dialysis and transplant registry 2012 reported 32.4 % of CKD was due to

hypertension, 12.4% diabetic nephropathy and 9.5% glomerulonephritis¹⁰⁰ In a study by Arogundade et al ¹⁰¹ hypertension was the leading cause of CKD closely followed by CGN with both jointly accounting for almost 60% of the CKD patients. Diabetes and hypertension are the leading causes of chronic kidney disease in all developed and many developing countries.^{103, 105,}

106

The utility of an estimated GFR is a function of its precision and accuracy, and a valid estimated GFR should be close to the true value or acceptable standard. All the equations correlated positively with the standard of 24 hour creatinine clearance. The GFR generated using the lean body weight in the CGLBW correlated best with the creatinine clearance (r=0.724) followed by the CGABW equations (r=0.687) and the MDRD (r=0.674). The highest agreement was observed when comparing CGLBW and creatinine clearance and it also had the least bias and best precision.

Rostoker et al⁵⁷ had similar findings in his study with an equally small bias.

For the controls correlation between measured creatinine clearance and estimated GFR by all the 3 equations was poor (r = 0.18 for abbreviated MDRD equation) and negative; r = -0.18 for CGLBW and r= -0.64 for CGABW) All the equations equally had poor precision in the controls.

For the patients reviewed the CGLBW had 79% and 54% accuracy within 30% (P30) and 20%

(P20) of the standard, CGABW had 56 % and 44% and MDRD 56% AND 30% respectively.

Levey et al¹⁰⁷ found a better precision and accuracy in which both CGABW and MDRD had estimates within 30% of measured GFR of 91% and 90% respectively. However the serum creatinine used in the study by Levey was standardised to IDMS. In the study by Teruel Briones et al⁶⁶, the MDRD equation (P30; 85%) was more accurate than the CGABW (P30; 70%). The CGLBW was not reviewed in the study. Gaspari et al³⁶ had a similar result with P20 for MDRD

almost 80% and CGABW 60%. CGLBW was also not considered in this study. The review by Pöge et al¹⁰⁸ equally showed the estimates by CGABW was particularly poor with a P30 less than 40%.

MDRD and CGABW tended to overestimate the creatinine clearance in most of the patients (Table 10) while the CGLBW tended to underestimate.

Furthermore, CGABW and MDRD4 overestimated the creatinine clearance in 32.5% and 23.2% of the 43 patients assigned to CKD stage 3 by creatinine clearance. In contrast, the CGLBW

underestimated in 25.9% of the same group of participants and underestimated in 2.3%. The same pattern was noticed among the participants in CKD stage 4 where CGABW and MDRD4

overestimated the measured creatinine clearance and there was underestimation by CGLBW. Out of the 3 estimating equations, the CGABW was most likely to generate higher recommended drug doses, and CGLBW equation was most likely to generate lowest recommended drug doses.

Estimates using CGABW retained within the same stage almost two-third of the participants classified CKD stage 3 by creatinine clearance while one-third of the remaining subjects who were originally in CKD stage 3 had their were reclassified into CKD stage 2. None of the patients had a less favourable classification with the CGABW. A sub-analysis of this group of 15 patients who had their CKD stage reviewed to less severe CKD stages showed that their mean body mass index and their mean body surface area were significantly greater than the whole group. However, the BMI and the BSA of the patients classified into the CKD stage 4 by CGABW

was not significantly different from that of the whole group. Possible reasons for differential accuracy include reduced creatinine generation attributable to loss of muscle mass or decreased protein intake, in chronic illness, in this case CKD stage 4; greater measurement error and biological variation in GFR at different GFR levels, and limitations of generalizing equations developed in populations with CKD.

The estimates from CGLBW invite caution in drug dosing and a more aggressive CKD management approach in patients to reduce rapid progression to end stage renal disease (ESRD).⁷⁸ In the same vein, the CGLBW estimates could lead to systematic and continuous underdosing particularly of antibiotics in healthy subjects with the possible emergence drug resistance over a long time. Poggio et al⁶⁷ found a similar trend of overestimation of GFR by MDRD. A similar result was obtained in study by Stoves et al¹⁰⁹as well as Rule et al¹¹⁰. In all these studies, only the CGABW was reviewed with the MDRD; the CGLBW was not reviewed.

Rigalleau et al⁶⁹ also found that the CGABW overestimated GFR in a study of 200 diabetics. They also found that replacing the actual body weight with the calculated ideal body weight improved the classification of the patients without a significant change in correlation. The overestimation of creatinine clearance by CGABW has been found to be worse in obesity.¹¹¹

Only 50% of the participants were well classified by CGABW and MDRD4 into the appropriate CKD stage in the study by Levey et al.⁸ Froissart et al⁷⁷ suggested that the concordance in classification depends on the proportion of patients who happen to be near the boundaries of the subgroups. In their own study CKD classification showed that only 70.8% of subjects were classified in the proper category when using the MDRD formula and 67.6% when using the CG one, which clearly highlights the limitations of both formulas. When the CG and the MDRD formulas were used in their study, 28.8 and 16.7% of stage 4 CKD patients were misclassified as stage 3 CKD patients, respectively. This could introduce undue delays in the preparation for renal replacement therapy. In contrast, about 20% of subjects with measured GFR ≥60 ml/min per 1.73 m² were classified as having stage 3 CKD with both formulas, which could lead to unnecessary assessment of CKD-related complications.

The findings were similar to the findings of Lim et al⁵⁴ and Rostoker et al⁵⁸ in their studies.

Friedman et al¹¹² also found that the CGABW formula grossly overestimates eGFR and should not be used in obese individuals. For the controls, MDRD overestimated the creatinine clearance in most of the participants while both the CGLBW and CGABW underestimated the creatinine clearance. This was more significant with the CGLBW because of the lower multiplicative effect of the lean body mass in the equation. Possible explanations for the greater errors at higher eGFR, as well as relatively poorer performance of the MDRD equation include unresolved differences in the calibration of serum creatinine, error in measurement of GFR, short-term biologic variation in creatinine clearance, and variation among populations in clinical characteristics that are not incorporated into the MDRD Study equation and affect the association of serum creatinine with creatinine clearance (e.g muscle mass, diet).

The underestimation by CGLBW and overestimation by the MDRD in the patients is similar to findings in the Ashanti study.¹⁵ However few studies have equally noticed underestimation of the creatinine clearance by MDRD-4 equation in some populations and also that gender, age and BMI can affect the accuracy of predictive equations.¹¹¹ The use of lean mass in the estimation may also explain the lower estimates obtained by CGLBW and the reduced tendency to overestimation. This is similar to observations by Lim et al ⁵⁴ and Verhave et al.¹¹³These findings were confirmed in studies by Willems et al¹¹⁴. The contrast was further demonstrated in a study by Melloni et al¹¹⁵in which the CG underestimated the standard GFR particularly in females, elderly and significantly in elderly females. Similarly, CGABW overestimated the GFR in obese and overweight individuals and its use in creatinine based equations is cautiously approached¹¹⁶. This is due to the disparity between muscle mass and body weight ratio.

Highlighting the impact of weight on Cockcroft gault equation and to reduce the significant bias

across the various weight categories, Winter et al¹¹⁷ introduced non-uniform multiplicative factors for underweight, normal weight, overweight and obese individuals. This is cumbersome.

Similar results were obtained in the study by Nguyen et al.¹¹⁸They found a systematic proportional bias with the use of actual body weight which was eliminated significantly with incorporation of the lean body weight.

From findings in this study, a cautious application of CGLBW estimates in epidemiological studies is advisable. Such studies may involve patients with chronic kidney disease as well as healthy cohorts. The tendency to underestimate by CGLBW may be misleading due to overdiagnosis. Non –uniformity in patient characteristics also preclude the free application across board. The Ashanti study classified significantly more patients into CKD 3-5 using CGABW.15A similar finding was recorded in the south Asian study involving the general population.¹⁷ However in the study by Matsha et al¹⁶ in South Africa, significantly more patients were found in the same CKD groups by the MDRD equations.

The observed and expected differences in performance by range of GFR suggest that we may not be able to optimize the performance of any equation for all clinical populations across a wide range of GFRs. If the goal is to select a single estimating equation for routine use by clinical laboratories, estimating equations need to be further improved and standardized. The accuracy and worldwide generalizability of GFR estimating equations might be improved by using such alternative filtration markers as cystatin C, which is less dependent on muscle mass. However, all filtration markers have non-GFR determinants, so it is unlikely that imprecision will be eliminated by any single marker.

The observation of a total misclassification rate less than 30%, with CGLBW suggest that it may reasonably substitute the creatinine clearance in our patient population. This result contradicts those that suggest the CG equation is an inefficient method to estimate GFR in advanced CKD¹¹⁹

CHAPTER SEVEN CONCLUSION

The study Cockcroft-Gault equation using the lean body weight performed better than the other Cockcroft Gault equations and the MDRD in estimating GFR of patients in advanced stage of CKD. However due to the tendency to under estimate the creatinine clearance in this group of patients it encourages caution in drug dosing and a more aggressive care in advanced CKD .We conclude that using the lean body and adjusting for body surface area improves accuracy of the original Cockcroft-Gault equation and may be more appropriate in patients with advanced chronic kidney disease. Further studies are needed to validate these findings.

RECOMMENDATIONS From this study, I will like to suggest the following

1. That the lean body weight and body surface area of each patient be calculated and used in the estimation of the GFR using Cockcroft Gault

2. That there is still a need to generate equations that are uniformly reliable across the various CKD stages and ethnicity.

3. That there is a need to make the IDMS assay available and affordable for uniformity.

4. Preventive programme including health education must be put in place to reduce the percentage of patient presenting with advanced CKD

LIMITATIONS OF THE STUDY

1. The use of IDMS traceable assay serum creatinine recommended by the NKDEP laboratory working group could not be used in this study on account of unavailability and cost.

2. The gold standard of Inulin clearance is not available for the purpose of this study to measure the standard GFR. The non availability is due to the difficulty in getting it, the cost as well as the cumbersomeness of measuring Inulin clearance which has limited use in research and clinical practice

3. The collection of urine and blood samples could not be done at once for all participants. Collecting at once could have limited errors of laboratory analysis.

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