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 Table of Contents  
ORIGINAL ARTICLE
Year : 2019  |  Volume : 6  |  Issue : 2  |  Page : 9-12

Kidney disease screening in a group of female health personnel: Who are often missing?


1 Department of Nephrology, Chattagram Maa-O-Shishu Hospital Medical College, Chittagong, Bangladesh
2 Department of Medicine, Chattagram Maa-O-Shishu Hospital Medical College, Chittagong, Bangladesh
3 Department of Pediatric Nephrology, Chattagram Maa-O-Shishu Hospital Medical College, Chittagong, Bangladesh

Date of Submission30-Dec-2018
Date of Decision15-Aug-2019
Date of Acceptance18-Oct-2019
Date of Web Publication26-Feb-2021

Correspondence Address:
Dr. Rajat Sanker Roy Biswas
Department of Medicine, Chattagram Maa-O-Shishu Hospital Medical College, Chittagong
Bangladesh
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jina.jina_20_18

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  Abstract 


Background and Objective: Data on early-stage of chronic kidney disease (CKD) and the prevalence of CKD are very limited, especially more scanty in our female population. Hence, data from a kidney screening program organized at the Chattagram Maa-O-Shishu Hospital premises in connection with the observance of World Kidney Day 2018 were looked at for renal function among a group of female health personnel. Methods: This was a cross-sectional study among a group of female health personnel working at the hospital. Age, body weight, height, Body mass index (BMI), and blood pressure were documented, and serum creatinine was measured at a single sitting. The kidney function was estimated by calculating the glomerular filtration rate (GFR) using the Modified Diet in Renal Disease formula. Kidney function was classified according to estimated GFR (eGFR) and Kidney Disease Outcomes Quality Initiative (K/DOQI) guidelines. Results: A total of 101 female health personnel were studied – physicians - 23; nurses - 45, and health assistants - 33. Majority participants (51%) were in the age group of 20–29 years; 5% were <20-year-old; and 9.9% were more than 40-year-old. The distribution of eGFR was symmetrical, with the majority (82%) of individuals in the 60–89 mL/min category; 11.88% had 30–59 mL/min category and only 5.9% of the study population had eGFR >90 mL/min category. An inverse relation between the age and eGFR and a direct relation between the BMI and eGFR were observed in the study. Conclusion: The results indicate that low GFR levels and consequently a high burden of likely CKD are prevailing in our female population. It is not clear whether such observations are the result of the transportability problems associated with the GFR prediction equations or with the suitability of K/DOQI guidelines for the classification of CKD in our population or both. Well-planned, larger, and community- and hospital-based studies are warranted to clarify these issues, especially for our female population.

Keywords: Estimated glomerular filtration rate, female health personnel, modified diet in renal disease formula, serum creatinine


How to cite this article:
Kashem M A, Biswas RS, Jewel KH. Kidney disease screening in a group of female health personnel: Who are often missing?. J Integr Nephrol Androl 2019;6:9-12

How to cite this URL:
Kashem M A, Biswas RS, Jewel KH. Kidney disease screening in a group of female health personnel: Who are often missing?. J Integr Nephrol Androl [serial online] 2019 [cited 2021 Jul 24];6:9-12. Available from: http://www.journal-ina.com/text.asp?2019/6/2/9/310195




  Introduction Top


The incidence of chronic kidney disease (CKD) is growing at an alarming rate, and the majority of individuals with early stages of CKD go undetected as they are mostly remained asymptomatic.[1] Kidney disease usually progresses silently, often destroying most of the kidney functions before causing any symptoms. The early detection of failing kidney function and its complications may delay or prevent the development of the end-stage renal disease.[2] The previous study showed that most of the CKD patients who report to the tertiary care hospitals were already in the state of end stages when renal replacement therapy is the only answer which is largely unaffordable and unavailable in our country.[3] Early identification and appropriate nephrological management of patients with mild renal disease have been increasingly recognized as an important opportunity to delay the progression of renal disease.[4] In view of this, renal status in a group of female health personnel was assessed by measuring serum creatinine and estimating glomerular filtration rate (GFR) in a kidney screening program, organized to coincide with the observance of “World Kidney Day 2018” at the campus of Chattagram Maa-O-Shishu Hospital (CMOSH), Agrabad, Chittagong, Bangladesh, who have limited access to health-care screening.


  Methods Top


On March 8, 2018, at the campus of CMOSH, Agrabad, Chittagong, Bangladesh, the Department of Nephrology organized a free kidney screening program among a group of female health personnel with prior permission from the institutional ethical committee. A total of 101 individuals who were apparently healthy included in the study on first come and first serve basis. Individuals having the history of systemic diseases such as diabetes mellitus, hypertension, or previously diagnosed CKD were excluded from the study. Age, body weight, height, and blood pressure (BP) were documented on the spot, and body mass index (BMI) was calculated for all individuals, participated in the study. Five-milliliter venous blood was collected for the measurement of serum creatinine, which was done by an enzymatic method on auto-analyzer (DADE Behring Limited, USA) in the college laboratory.

The GFR, calculated using the simplified modified diet in renal disease (MDRD) formula, detects CKD more accurately than does the serum creatinine level alone and is used for renal function staging.[5] Using these estimated GFRs (eGFRs) and the Kidney Disease Outcomes Quality Initiative, kidney function was classified for each participant. According to the K/DOQI guidelines to define CKD, we should have at least 3 months' history of renal function decrement. Since we conducted a single screening program and tested only once, we used the term “likely CKD” instead of definitive CKD in this study.

The participants were divided into four groups according to their BMI based on the WHO international classification as follows: <18.5 kg/m2 (underweight), 18.5–24.99 kg/m2 (normal), 25–29.99 kg/m2 (overweight), and 󖾒 kg/m2 (obese).

Statistical analysis

Data were analyzed using? SPSS version 20 (IBM, Armonk, NY, USA). Results are presented as numbers, percentages, mean, standard deviation (SD), median, and range. Student's t-test and Chi-square test were used for comparison of means and proportions where were appropriate. The crude (unadjusted) relationship between the exposure variables (age, BP, BMI) and eGFR was examined by univariate logistic regression analysis.


  Results Top


[Table 1] shows different demographic data of the individuals where mean age was 30.01 ± 7.87 years; mean BMI was 25.08 ± 4.58 kg/m2; mean systolic and diastolic pressure were 115.95 ± 10.85 mmHg and 74.45 ± 10.85 mmHg; and mean serum creatinine and eGFR (MDRD) were 0.8436±0.1014 (mg/dL) and 72.68 ± 11.23 (mL/min), respectively.
Table 1: Demographic data of the studied participants

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Values expressed as number and percentages and eGFR calculated by MDRD formula. The mean age (± SD) of the population was 30.01 ± 07.87 years (range 16–65 years); 5% were younger than 20 years, 51% were 20–29 years, 35% were 30–39 years, and 10% were more than 40-year-old. Mean systolic and diastolic BPs were 115.95 ± 16.93 mmHg and 74.45 ± 10.85 mmHg, respectively.

The agewise distribution of eGFR is shown in [Table 2]. Only 6 (5.94%) participants had eGFR >90 mL/min, majority individuals 83 (82.17%) had eGFR 60–89 mL/min; and 12 (11.88%) had eGFR 30–59 range [Table 3]. [Figure 1] shows the relationship between age and eGFR, where there was an inverse relation between the two. eGFR showed a positive correlation with the BMI, as shown in [Figure 2].
Table 2: Age-wise distribution of estimated glomerular filtration rate calculated by modified diet in renal disease formula

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Table 3: Stratification of the participants according to the estimated glomerular filtration rate (n=101)

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Figure 1: The relationship between age and estimated glomerular filtration rate

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Figure 2: The relationship between the BMI and estimated glomerular filtration rate

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  Discussion Top


We observed an average eGFR level of 72.68 ± 11.23 mL/min (49–96 mL/min) in the studied participants, which is on the lower side of the generally accepted values for normal GFR estimates of 100–110 mL/min[6]). Eighty-two percent of our individuals had eGFR 60–89 mL/min category, i.e., at CKD stage II and 11.88% individuals had eGFR 30–59 mL/min category, i.e., at CKD stage III which is an alarming signal for the nation. Previous studies also showed a prevalence of poor or low GFR in the normal population.[7],[8] As we do not know the exact average GFR level in our female population; hence, it is difficult to draw any conclusions on this small data. In general, the risk of developing CKD is higher in women than in men. Hence, early health screening is very vital to avoid the kidney diseases in the later life. Recently, there has been increasing emphasis on appropriate treatment and timely referral of individuals with early renal disease.[4]

Moreover, GFR was on average 4 mL/min lower in females than in males. However, this needs to be confirmed or contradicted by way of more community-based studies. In any case, there is a need to define the GFR profiles in normal controls in our population.

As per the K/DOQI definition of CKD, we observed a very high proportion (11.9%) of likely CKD in the stage 3; 82% in the stage 2; and only 5.6% in the stage 1 in our study population. In addition, it also raises the question of whether or not the cutoffs recommended by the K/DOQI guidelines for the various stages of CKD are applicable for all populations worldwide. Ideally, any international recommendations should be based on international data. However, a number of investigators believe that the use of prediction equations in population-based studies suggest a surprisingly high prevalence of CKD.[9],[10],[11] This leads to raise the question of doubt in the utility of these equations for the epidemiologic research. The transportability problem,[12] i.e., validity of these formulas to other populations with different characteristics, needs to be addressed before commenting on this. Another contributing factor may be related to the issue of measurement methodology and calibration of serum creatinine.[13] On the whole, the burden of CKD in this small group of population is shown much higher compared to the available prevalence/incidence data on the Indian population.[9],[14] The difference may be partly due to the fact that the earlier studies did not depend on GFR/eGFR but on serum creatinine/clinical judgment.

The apparently lower level of eGFR results in problems of staging due to fixed cutoffs in the K/DOQI classification of CKD stages. Actually, it is not known if the classification can be applied to our population. Whether the lower level of GFR in the population indicates a greater susceptibility to developing CKD or proportionately lower cutoff values at each stage are required is not known.

The age-wise distribution of GFR indicated that the peak was in the age group of 30–39 years. We observed a linear negative correlation between age and GFR, as shown in [Figure 1]. This is in agreement with other reports based on cross-sectional data,[15] but slightly more than the decline based on longitudinal data.[16] Our data also showed that increased BMI consistently associated with the reduced eGFR [Figure 2], as shown in the previous study.[17]

The correspondence between eGFR and serum creatinine values among the various stages of CKD led to the interesting observation that serum creatinine levels were not elevated even in CKD stage III, though the GFR indicated derangement or presence of disease. Only in CKD stages IV and V could elevated levels of serum creatinine be seen. Thus, if we depend on serum creatinine alone, there is a possibility of missing the diagnosis of the disease when it is in its earlier stages. Similar views have also been reported previously.[18],[19] Our results are based on only 101 females, who were likely to be different from the general population of the community by virtue of gender. The results, therefore, need to be interpreted with this in mind. Only one-time measurements of serum creatinine and a lack of calibration of the measurement of serum creatinine are some of the limitations of the study.


  Conclusion Top


There is a high prevalence of reduced GFR in our adult female population. GFR estimates using serum creatinine and MDRD study equations are better predictors of reduced GFR than serum creatinine alone. The advantage of this cross-sectional study is that it recruited predominantly hospital staff who can be followed up in the future to see the effect of aging on GFR. We also recommend more studies in our population with a larger sample size in both genders to clarify the above issues.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Jafar TH, Schmid CH, Levey AS. Serum creatinine as marker of kidney function in South Asians: A study of reduced GFR in adults in Pakistan. J Am Soc Nephrol 2005;16:1413-9.  Back to cited text no. 1
    
2.
McClellan WM, Ramirez SP, Jurkovitz C. Screening for chronic kidney disease: Unresolved issues. J Am Soc Nephrol 2003;14:S81-7.  Back to cited text no. 2
    
3.
Kashem A, Dutta PK, Huda MN, Das S, Yunus EB, Chowdhury D. Clinical profiles of chronic kidney disease patients at the time of maiden presentation: An experience at the nephrology ward, Chittagong medical college hospital. J Chittagong Med Coll Teach Assoc 2010;21:7-10.  Back to cited text no. 3
    
4.
Jungers P. Screening for renal insufficiency: Is it worth while? Is it feasible? Nephrol Dial Transplant 1999;14:2082-4.  Back to cited text no. 4
    
5.
Levey AS, Greene T, Kusek JW, Beck GJ. Simplified equation to predict glomerular filtration rate from serum creatinine. J Am Soc Nephrol 2000;11:828.  Back to cited text no. 5
    
6.
Delanaye P, Schaeffner E, Ebert N, Cavalier E, Mariat C, Krzesinski JM, et al. Normal reference values for glomerular filtration rate: What do we really know? Nephrol Dial Transplant 2012;27:2664-72.  Back to cited text no. 6
    
7.
Duncan L, Heathcote J, Djurdjev O, Levin A. Screening for renal disease using serum creatinine: Who are we missing? Nephrol Dial Transplant 2001;16:1042-6.  Back to cited text no. 7
    
8.
Wesson LG. Renal hemodynamics in physiolocal states. In: Wesson LG, editor. Physiology of the Human Kidney. New York: Grune and Stratton; 1969. p. 96-108.  Back to cited text no. 8
    
9.
Singh NP, Ingle GK, Saini VK, Jami A, Beniwal P, Lal M, et al. Prevalence of low glomerular filtration rate, proteinuria and associated risk factors in North India using cockcroft-gault and modification of diet in renal disease equation: An observational, cross-sectional study. BMC Nephrol 2009;10:4.  Back to cited text no. 9
    
10.
Clase CM, Garg AX, Kiberd BA. Prevalence of low glomerular filtration rate in nondiabetic Americans: Third national health and nutrition examination survey (NHANES III). J Am Soc Nephrol 2002;13:1338-49.  Back to cited text no. 10
    
11.
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;41:1-2.  Back to cited text no. 11
    
12.
Chadban SJ, Briganti EM, Kerr PG, Dunstan DW, Welborn TA, Zimmet PZ, et al. Prevalence of kidney damage in Australian adults: The ausDiab kidney study. J Am Soc Nephrol 2003;14:S131-8.  Back to cited text no. 12
    
13.
Justice AC, Covinsky KE, Berlin JA. Assessing the generalizability of prognostic information. Ann Intern Med 1999;130:515-24.  Back to cited text no. 13
    
14.
Coresh J, Toto RD, Kirk KA, Whelton PK, Massry S, Jones C, et al. Creatinine clearance as a measure of GFR in screenees for the African-American study of kidney disease and hypertension pilot study. Am J Kidney Dis 1998;32:32-42.  Back to cited text no. 14
    
15.
Coresh J, Wei GL, McQuillan G, Brancati FL, Levey AS, Jones C, et al. Prevalence of high blood pressure and elevated serum creatinine level in the United States: Findings from the third national health and nutrition examination survey (1988-1994). Arch Intern Med 2001;161:1207-16.  Back to cited text no. 15
    
16.
Lindeman RD, Tobin JD, Shock NW. Association between blood pressure and the rate of decline in renal function with age. Kidney Int 1984;26:861-8.  Back to cited text no. 16
    
17.
Kawamoto R, Kohara K, Tabara Y, Miki T, Ohtsuka N, Kusunoki T, et al. An association between body mass index and estimated glomerular filtration rate. Hypertens Res 2008;31:1559-64.  Back to cited text no. 17
    
18.
Lindeman RD, Tobin J, Shock NW. Longitudinal studies on the rate of decline in renal function with age. J Am Geriatr Soc 1985;33:278-85.  Back to cited text no. 18
    
19.
Walser M, Drew HH, LaFrance ND. Creatinine measurements often yielded false estimates of progression in chronic renal failure. Kidney Int 1988;34:412-8.  Back to cited text no. 19
    


    Figures

  [Figure 1], [Figure 2]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]


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[Pubmed] | [DOI]



 

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