Assessment of Renal Function with Social History and Body Mass Index in Elderly Patients

INTRODUCTION

Elderly people are often more susceptible to various chronic diseases due to low immunity as well as anatomic and functional changes in all the organs and systems. Along with aging, the kidneys will shrink and its filtering functions will be affected.¹ Drug elimination through the kidneys is normally impaired in the elderly, both due to reduced renal blood flow and pertur-bations in GFR.² In addition, modifiable lifestyle factors such as smoking and consumption of alcohol and BMI increase the risk, and thus association among Smoking, Heavy Drinking, and Chronic Kidney Disease.³ We have undertaken this study in elderly population to reduce the risk associated with social habits and BMI. There is no ideal way to assess renal function in the elderly. Serum creatinine level alone is often very misleading. Many geriatric patients with a “normal” serum creatinine level actually have a moderate renal impairment when GFR is estimated.⁴ So, by considering all these information and need for dosage adjustment in ge-riatric patients with respect to kidney function, we have selected this study. The Cockcroft-Gault (CG) and Modification of Diet in Renal Disease (MDRD) formulas are often used to estimate GFR. The objective was to determine the best method for estimating GFR in older adults.⁵

MATERIALS AND METHODS

The study was conducted in geriatric In-patients of Basaveshwara Medical College Hospital, Chitradurga in the department of medicine, which is a 750 bedded tertiary care hospital pro-viding health care services. The study was conducted for a period of six months. This study was approved by the “Institutional Human ethical committee” of the Basaveswara Medical College Hospital & Research Centre and S.J.M College of Pharmacy, Chitradurga (SJMCP/IEC/677A/2013-14). The inclusion criteria for the study is the patients of both gend-ers ≥ 60years, elderly patients with serum creatinine tests, patients admitted in ICU and Medicine wards and who has given informed consent for study. The exclusion criteria follows patients admitted in other Departments and elderly patient with diseases like psychiatry and cancer.

• Measurement: The eGFR was estimated using the CG equation estimate of Creatinine Clearance Rate(CCR) adjusted for Body Surface Area (CG/BSA) and the MDRD Study equation as follows:

1. CG/BSA eGFR (ml/min/1.73 m2) = 1.23 × (140 ) age) × weight/ Serum Creati-nine(SCr) × 1.73/BSA (•0.85 if female)

2. MDRD eGFR(ml/min/1.73m2)=175 × (SCr in μmol/L × 0.0113) -1.154 × (age in years) -0.203 × (0.742 [if female])

where, weight was measured in kg and Serum Creatinine in mmol L-1

• Estimated GFR was categorized as normal (90 ml min)1/1.73 m2 ), mildly decreased (60–89 ml min)1/1.73 m2 ), moderately decreased (30–59 ml min)1/1.73 m2 ) or se-verely decreased (<30 ml min)1/1.73 m2 ) according to the Kidney Disease Outcomes Quality Initiative (KDOQI) of the National Kidney Foundation guidelines.

Statistical Analysis:

• Demographic distributions were assessed by Descriptive statistics (mean, standard deviation and sum).
• The Association between eGFR Category with Age, Past medical history, Social his-tory and BMI were assessed by Chi-square test.
• Differences in CG and MDRD were tested using Paired sample t-test
• Comparison of CG and MDRD with gender were assessed by Independent Sample t-test
• Statistical Analysis was done by using Statistical Package for Service Solutions (SPSS) 19.0 version Software

RESULTS AND DISCUSSION

In our study we have enrolled 306 prescriptions, out of which 258 were non smoker, 5 were former smokers and 43 were Current smokers and 289 were with no history of alcohol consumption and 17 patients were with history of alcohol consumption. Among 306 Elder pa-tients, 118 were under weight (<22), 178 were normal weight (22-30), 10 were Overweight (>30), the results are analysed in Table 1.

Among 306 Patients (n=306), the social history was present for 53 (17.3%) patients and with no social history were 253(82.6), in which 1.6% prevalence of smokers and 0.98% prevalence of smoking and alcohol with Severely decreased eGFR i.e. <30 ml/ min/1.73m2, there was no significant association between Social History and eGFR (P>0.05). In another study Shankar et al studied the association among Smoking, Heavy Drinking, and Chronic Kidney Disease (CKD) Compared with that among never smokers, the odds ratio of developing CKD was 1.12 (95% confidence interval (CI): 0.63, 2.00) among former smokers and 1.97 (95% CI: 1.15, 3.36) among current smokers. Heavy drinking was associated with CKD, with an odds ratio of 1.99 (95% CI: 0.99, 4.01). Joint exposure to both current smoking and heavy drinking was associated with almost fivefold odds of developing CKD compared. With their absence (odds ratio ¼ 4.93, 95% CI: 2.45, 9.94). Smoking and consumption of four or more servings of alcohol per day are associated with CKD6, the results are analyzed in figure 1.

Among 306 Elder patients, in BMI categories 118 were under weight (<22 kg/m2 ), 178 were normal weight (22-30 kg/m2 ) and 10 were Overweight (>30 kg/m2 ) . In our study with severely decreased eGFR i.e. <30 ml/min/1.73m2 the 3.6% prevalance of under weight (<22 kg/m2 ), 7.8% prevalance of 22-30kg/m2 and 0.3% of >30mg/kg. There was no significant association between BMI and eGFR (P>0.05). In another study Rajeshwari Shastry et al, evaluated the performance of serum creatinine based equations to estimate GFR in Healthy South Indian Males and found that the relationships between BMI and GFR were different, depending on the equation used. While BMI positively correlated with CG- estimated GFR (r=0.471, p<0.001), it showed a negative correlation with MDRD-GFR (r=-0.268, p<0.001). Age (r=0.31, p<0.01) and serum creatinine (r=0.19, p<0.001) positively correlated with BMI7. The results are summarised in table 2, figure 2 and 3.

CONCLUSION

Among 306 Patients, the social history was present for 53%, the prevalence of smoking with alcohol have decreased eGFR. While BMI positively correlated with CG- estimated GFR. Social history with both Smoking and alcohol shown decreased kidney func-tion but BMI had no significant relation with decrease in eGFR.