الفهرس 
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Abstract
Hypertension is one of the most common chronic diseases in the human population, affecting more than 1 billion people worldwide.
The etiology of elevated blood pressure cannot be determined in the vast majority of individuals with ’essential’ hypertension. Thus, it has proved difficult to develop precise profiles for individual patients for the purposes of identifying optimal therapies and predicting prognosis.
Key factors that contribute to the development of hypertensive nephropathy include i) inappropriately elevated sympathetic nervous activity, ii) activation of the renin–angiotensin–aldosterone system (RAAS), iii) increased arterial stiffness, iv) impaired salt and water excretion by the kidney, and v) genetic susceptibility.
Chronic kidney disease (CKD) is a worldwide public health problem with a rising incidence, poor outcomes, and high costs. The estimated glomerular filtration rate (eGFR) equations, which take into account plasma creatinine, age, sex, and race, help to identify patients with CKD formerly overlooked if the renal function had been assessed by plasma creatinine alone. The four-variable Modification of Diet in Renal Disease (MDRD) Study equation is nowadays the most commonly used formula for eGFR.
Hypertensive nephropathy is a common cause of ESRD and is associated with significant morbidity and mortality. The most effective strategy to maximally delay CKD progression must include albuminuria reduction and achievement of the BP goal of < 130/80 mmHg. This can be done by using multiple antihypertensive agents, including RAAS blockers and diuretics, together with adherence to dietary sodium restriction.
In this study, we aimed at detection of prevalence of CKD (CrCl ≤ 60 ml/min) in our essential hypertension patients and we tried to answer the question: which eGFR equation is nearest in accuracy to CrCl making it possible to avoid cumbersome 24 urine collection for measuring CrCl.
Two hundreds hypertensive patients constituted the subjects of this study. Age of those patients ranged from 33-59 years with mean 46.17 ± 7.55 years.
The patients were recruited from those attending the Internal medicine outpatient clinic and hospital inpatients of Benha University Hospital.
Inclusion criteria:
3- History of hypertension.
4- Age above 18 years.
Exclusion criteria:
9- Age below 18 years.
10- Chronic analgesic or other drug intake that might affect the kidneys.
11- Patients with history of renal disease.
12- Patients with family history of polycystic kidney disease.
13- Patients on renal replacement therapy.
14- Diabetic patients.
15- Grade III medical nephropathy on abdominal ultrasound.
All patients were subjected to thorough history taking and clinical examination with stress on the following:
5- Duration of hypertension.
6- Manifestations suggestive of secondary hypertension.
7- Antihypertensive drugs or drugs that cause hypertension.
8- Target organ complications of hypertension.
The following investigations were done to all subjects:
Fasting and 2 hours post prandial plasma glucose.
Complete blood count. (Shapiro and Greenfield, 1987)
Serum Na and K.
Serum creatinine and blood urea.
Serum uric acid.
Twice 24 hour measured creatinine clearance and taking the average of both readings.
Pelvi-abdominal ultrasound.
Estimated glomerular filtration rate using Cockcroft-Gault, MDRD, and CKD-EPI equations.
This study showed the following results:
CKD-EPI was superior to both MDRD and CGF for estimating GFR in comparison to CrCl in all patients (Accuracy 99.73, 97.77 and 95.4 respectively)
There was significant positive correlation between GFR estimated by CrCl and other three methods in all cases.
There was significant negative correlation between age and GFR estimated by four methods in all cases.
There was significant reduction in CrCl between age groups A and C and between age groups B and C as well.
There was significant reduction in GFR estimated by CKD-EPI between age groups A and C and between age groups B and C as well.
There was significant reduction in GFR estimated by MDRD between age groups A and C and between age groups B and C as well.
There was significant reduction in GFR calculated by CGF between age groups A and C and between age groups B and C as well.
In age group (A), CKD-EPI equation was superior to both MDRD and CGF for estimation of GFR in comparison to CrCl (Accuracy 99.80% vs. 98.47 and 96.67 respectively) and mean of eGFR by CKD-EPI was insignificantly lower than mean GFR by CrCl (p-value = 0.2421).
In age group (B), CKD-EPI equation was superior to both MDRD and CGF for estimation of GFR in comparison to CrCl (Accuracy 99.61% vs. 96.18 and 94.22 respectively) and mean of eGFR by CKD-EPI was insignificantly lower than mean GFR by CrCl (p-value= 0.153).
In age group (C), CKD-EPI equation was superior to both MDRD and CGF for estimation of GFR in comparison to CrCl (Accuracy 99.64% vs. 97.86 and 92.53 respectively) and mean of eGFR by CKD-EPI was significantly higher than mean GFR by CrCl (p-value= < 0.0001).
There was significant positive correlation between weight and GFR estimated by four methods in all cases.
There was significant reduction in CrCl between weight groups A and C (p-value= 0.0155).
There was significant reduction in GFR estimated by CKD-EPI between weight groups A and C (p-value= 0.0227).
There was significant reduction in GFR estimated by MDRD between weight groups A and C (p-value= 0.0263).
There was significant reduction in GFR calculated by CGF between weight groups A and C (p-value= 0.0018).
In weight group (A), CKD-EPI equation was superior to both MDRD and CGF for estimation of GFR in comparison to CrCl (Accuracy 99.42% vs. 97.09% and 88.32% respectively) and mean of eGFR by CKD-EPI was significantly higher than mean GFR by CrCl (p-value= < 0.0092).
In weight group (B), CKD-EPI equation was superior to both MDRD and CGF for estimation of GFR in comparison to CrCl but it was insignificant (Accuracy 99.74% vs. 97.95% and 96.54% respectively).
In weight group (C), CKD-EPI equation was superior to both MDRD and CGF for estimation of GFR in comparison to CrCl but it was insignificant (Accuracy 99.74% vs. 97.24% and 92.99% respectively).
There was a statistically significant increase in mean of GFR estimated by four methods in males in comparison to females (p < 0.001).
There was significant positive correlation between GFR estimated by CrCl and other three methods in male cases.
There was significant positive correlation between GFR estimated by CrCl and other three methods in female cases.
Mean of GFR is lower in females than males (p-value 0.001) in the four methods.
In males, CKD-EPI equation was superior to both MDRD and CGF for estimation of GFR in comparison to CrCl and it was highly significant (Accuracy 99.52% vs. 93.34% and 94.49% respectively).
In females, MDRD equation was superior to both CKD-EPI and CGF for estimation of GFR in comparison to CrCl but it was insignificant (Accuracy 99.67% vs. 86.51% and 27.47% respectively).
There was non significant negative correlation between SBP and GFR estimated by four methods in all cases.
There was significant negative correlation between HTN duration and GFR estimated by four methods in all cases.
There was a statistically significant increase in mean of age, SBP and HTN duration between CKD cases and Non CKD cases.
There was a statistically significant decrease in mean of weight between CKD cases and Non CKD cases.
There was significant positive correlation between GFR estimated by CrCl and other three methods in CKD cases.
There was significant positive correlation between GFR estimated by CrCl and other three methods in non CKD cases.
In CKD patients (CrCl ≤ 60 ml/min), the accuracy of CKD-EPI is nearly equal to MDRD and both are superior to CGF for estimating GFR in comparison to CrCl method.(Accuracy 98.93% vs. 98.55% and 72.40%)
In non CKD patients (CrCl > 60 ml/min), CKD-EPI equation was superior to both MDRD and CGF for estimating GFR and it was highly significant.(Accuracy 98.28% vs. 86.65% and 90.04%)
ROC curve for serum CKD-EPI levels showed that At a cut-off value of 57 ml/min, the diagnostic sensitivity for CKD was 100% and the specificity 97.22 (95% CI, 0.982 to 1.000, P. <0.0001 ) (Fig.62). Positive predictive value (PPV) was 98.5 %, and negative predictive value (NPV) 100 %.
ROC curve for serum CGF levels showed that At a cut-off value of 57 ml/min, the diagnostic sensitivity for CKD was 88.3% and the specificity 98.6 (95% CI, 0.954 to 0.996, P. <0.0001 ) (Fig.63). Positive predictive value (PPV) was 99.1 % and negative predictive value (NPV) 82.6 %.
ROC curve for serum MDRD levels showed that At a cut-off value of 53 ml/min, the diagnostic sensitivity for CKD was 100% and the specificity 97.22 (95% CI, 0.981 to 1.000, P. <0.0001 ) (Fig.64). Positive predictive value (PPV) was 98.5 %, and negative predictive value (NPV) 100 %.
ROC curve for serum CrCl levels showed that At a cut-off value of 60 ml/min, the diagnostic sensitivity for CKD was 100% and the specificity 100% (95% CI, 0.982 to 1.000, P. =0.000) (Fig.63). Positive predictive value (PPV) was 100 % and negative predictive value (NPV) 100 %.
There was statistically significant decrease of diagnostic accuracy of CGF method in CKD in comparison to CrCl (p.= 0.0075).
There was statistically significant increase of diagnostic accuracy of CKD-EPI method in CKD in comparison to CGF (p.= 0.0075).
There was statistically significant increase of diagnostic accuracy of MDRD method in CKD in comparison to CGF (p.= 0.0087).
CONCLUSIONS:
We conclude that there is a high prevalence of CKD (CrCl ≤ 60 ml/min) in essential hypertension patients.
We also conclude that CKD-EPI equation can be used for estimating GFR in those patients with an accuracy that is insignificantly lower than CrCl making it possible to avoid the cumbersome 24 urine collection used for measuring creatinine clearance.
RECOMMALESDATIONS
We recommend that:
Essential hypertension patients should be screened for the incidence of CKD.
Awareness of CKD should be raised in essential hypertension patients through nation-wide programs.
Essential hypertension patients should be screened by CKD-EPI equation instead of measured creatinine clearance.
Limitations of eGFR equations should be known before universally applying them to different cohorts of patients and to bear in mind the influence of age, gender and weight when addressing the results of them.
A large study should be conducted comparing the different equations with measured 125I-iothalamate rather than creatinine clearance for more validation of results.