Systemic hypertension represents a substantial global health challenge, serving as a principal contributor to cerebrovascular accidents, cardiac complications, chronic kidney disease, and increased mortality rates across diverse populations¹. The condition particularly burdens healthcare infrastructure in India, where urban prevalence has increased thirty-fold and rural prevalence ten-fold over recent decades². Contemporary epidemiological data reveals variable prevalence rates ranging from 6.2-36.4% in urban males and 2-39.4% in urban females, with rural populations showing rates of 3-36% and 5.8-37% respectively³.

Microalbuminuria, defined as urinary albumin excretion between 30-300 mg/24 hours or 20-199 µg/minute in timed collections, emerges as a critical early biomarker of hypertensive complications⁴. This subclinical manifestation precedes overt target organ dysfunction, including left ventricular hypertrophy, retinal changes, and cognitive impairment⁵. The prevalence of microalbuminuria varies considerably, affecting 10-40% of hypertensive diabetic patients and 5-7% of apparently healthy individuals⁶. As an independent cardiovascular risk predictor, microalbuminuria signifies endothelial dysfunction and warrants systematic evaluation in hypertensive management protocols⁷.

The present study aimed to evaluate hypertension severity in essential hypertensive patients, quantify microalbuminuria prevalence, assess comprehensive target organ involvement, and establish correlations between microalbuminuria levels and extent of target organ compromise

This cross-sectional study was conducted at the General Medicine Department of Sri Aurobindo Medical College and Post Graduate Institute to evaluate microalbuminuria presence in essential hypertensive patients and its association with target organ damage.

Patient Selection

Patients admitted to the General Medicine Department with essential hypertension fulfilling inclusion and exclusion criteria were recruited. Blood pressure was recorded using standard sphygmomanometer with two readings taken five minutes apart. The American College of Cardiology/American Heart Association classification was used for hypertension grading.

Inclusion Criteria:

• All adults more than 18 yrs. with BP >140/90 were included in the study

Exclusion Criteria:

• Patients with diabetes mellitus, urinary tract infections, secondary causes of hypertension and pregnant patients were excluded.

Sample Size Calculation

Sample size was calculated using the formula: N = Z₁²⁻ᴬ¹² P(1-P)/l²

• ZA = 1.96 (at 5% level of significance), P = 38%, l = Relative error (20% of P)

A total of 160 patients fulfilling inclusion criteria were included based on yearly admission feasibility of over 100 patients with newly diagnosed or existing essential hypertension.

Data Collection and Investigations

Data were collected using pre-structured proforma. Early morning mid-stream urine samples were collected for microalbuminuria assessment. The following investigations were performed: Complete Blood Count, Urea and Serum Creatinine, Electrolytes (Sodium, Potassium, Chloride), Lipid Profile, Urine Routine Microscopy, Urine for Microalbumin, Fundus Examination, Ultrasonography Whole Abdomen, Electrocardiography and Echocardiography.

Statistical Analysis

Statistical analysis was conducted using R software. Data were presented using frequency tables with mean±standard deviation for quantitative variables and frequency with percentage for qualitative variables. Chi-square test was applied for associations between qualitative variables. Pearson correlation coefficient test evaluated relationships between quantitative variables. A p-value <0.05 was considered statistically significant. One way ANOVA and Kruskal-Wallis Test was used.

Ethical Considerations

Informed consent was obtained from all patients before enrolment. The study was conducted in accordance with ethical guidelines and institutional protocols.

The study comprised 160 participants with male predominance (100 males, 62.5% vs 60 females, 37.5%). The male-to-female ratio of 1.67:1 indicates significant gender disparity warranting consideration in cardiovascular and renal outcome interpretation. Mean participant age was 51.66±15.28 years, indicating predominantly middle-aged population with established cardiovascular risk. Average hypertension duration was 9.58±5.19 years, suggesting chronic disease with potential for target organ damage. Young hypertensives with onset less than 40 yrs of age were 38.8% (62 of 160).

Table 1. Distribution of Clinical Parameters Among Study Subjects

Average systolic and diastolic blood pressures were 143.88 mmHg and 83.75 mmHg respectively, consistent with Grade 1 hypertension. Haemoglobin levels showed mild anemia (10.68 g/dL). The lipid profile demonstrated significant dyslipidaemia with markedly low HDL cholesterol (31.84 mg/dL) and elevated triglycerides (164.87 mg/dL). Proteinuria assessment revealed significant albuminuria with markedly elevated UACR (mean 1373.37 mg/g, SD 2784.01).

The vast majority of patients (96.3%) presented with Grade 1 systolic hypertension, while 74.4% had normal diastolic pressure. This discordance indicates isolated systolic hypertension, characteristic of middle-aged and elderly populations due to arterial stiffening.

Fundoscopic examination revealed normal findings in 46.3% of subjects, while 53.7% demonstrated varying degrees of hypertensive retinopathy, indicating significant hypertensive retinopathy and organ damage. Left ventricular hypertrophy was present in 51.2% of subjects, with mild LVH being most common (31.9%), reflecting chronic hemodynamic burden of hypertension on cardiac structure. Diastolic dysfunction was present in 61.9% of subjects, with Grade I being most prevalent (45.0%), suggesting early cardiac involvement with impaired relaxationStructural renal changes were minimal (1.3%) despite elevated UACR levels, suggesting functional rather than structural kidney disease. No statistically

significant differences were observed between blood pressure grades for renal parameters, suggesting that kidney damage may occur early in hypertension and may not correlate linearly with current blood pressure levels.

Table 3: Correlation of Echocardiographic findings and UACR            

One-Way ANOVA (Parametric Test) to check whether the mean UACR differs significantly across the 4 echocardiographic categories was used with a p value of 0.00013. Since p < 0.05, the differences in mean UACR across echocardiographic.

Kruskal-Wallis Test (Non-Parametric Alternative) which compares the medians of UACR among the different categories was estimated to have a p-value: 0.00299. Which confirms the ANOVA result; the UACR distributions across echocardiographic groups differ significantly.

The investigation revealed demographic patterns regarding microalbuminuria prevalence across age groups. Participants exceeding 40 years demonstrated substantially higher microalbuminuria rates compared to younger cohorts⁸. This age-stratified distribution mirrors established patterns documented throughout Indian clinical populations⁹. Contemporary research has demonstrated similar findings among diabetic hypertensive patients, where individuals beyond 45 years exhibited microalbuminuria in 81.25% of cases¹⁰.

The relationship between advancing age and microalbuminuria prevalence appears particularly pronounced in hypertensive individuals with extended disease duration. Eastern Indian research has corroborated these observations, documenting microalbuminuria in 43.8% of type 2 diabetic patients with concurrent hypertension¹¹. These findings emphasize how chronological aging amplifies both renal and cardiovascular vulnerability within hypertensive populations.

The current investigation's findings regarding UACR levels across diastolic dysfunction grades revealed no statistically significant variations (p=0.958), contrasting with established literature documenting strong correlations between microalbuminuria and target organ damage¹². Previous Indian studies have demonstrated robust associations between microalbuminuria and left ventricular hypertrophy alongside hypertensive retinopathy¹³. Kerala-based research has similarly identified microalbuminuria as conferring elevated stroke risk and increased retinopathy likelihood¹⁴.

The divergent findings may reflect methodological variations, sample characteristics, or diagnostic threshold differences across studies. Research has identified strong positive correlations between UACR and both systolic and diastolic blood pressure¹⁵, suggesting that population-specific factors including comorbid conditions may modulate these relationships.

A statistically significant association emerged between proteinuria detection via dipstick methodology and elevated creatinine concentrations (p=0.016). This relationship aligns consistently with multiple Indian clinical investigations¹⁶. Research has demonstrated that protein-creatinine indices increase proportionally with hypertension severity and duration, exhibiting strong correlations with serum creatinine levels¹⁷.

The robust correlation between UACR and creatinine levels (rho=0.305, p<0.0001) identified in this investigation reinforces creatinine's reliability as an early renal damage biomarker within hypertensive populations. Contemporary research has established elevated systolic blood pressure as significant microalbuminuria predictor¹⁸.

The investigation's findings strongly support routine UACR screening implementation in hypertensive patients, particularly those exceeding 40 years or presenting with elevated creatinine levels. While UACR may not effectively stratify diastolic dysfunction severity, its association with creatinine underscores its utility in renal risk assessment protocols¹⁹. Clinical trial evidence has demonstrated that targeted antihypertensive therapy significantly reduces UACR in Indian hypertensive patients²⁰.

This comprehensive analysis provides significant insights into the intricate relationships between UACR, proteinuria, creatinine, and hypertension. The investigation established a robust positive correlation between UACR and creatinine levels (rho=0.305, p<0.0001), reinforcing UACR's effectiveness as a renal dysfunction marker in hypertensive individuals. The significant association between dipstick-detected proteinuria and elevated creatinine levels (p=0.016) suggests proteinuria's utility as an early kidney damage indicator. Furthermore, the correlation of UACR with LVH demonstrated by a p<0.0001, signifies the utility of UACR as a marker of hypertensive cardiac remodelling and end organ damage. The study findings corelate with the current literature available. 

However, the absence of significant UACR differences across diastolic dysfunction grades and hypertension severity indicates that UACR alone may be insufficient for assessing disease progression. The study underscores regular renal function monitoring importance, particularly through UACR and proteinuria measurements, for early kidney dysfunction detection in hypertensive patients.

Key limitations include the cross-sectional study design preventing causal relationship establishment, single-center scope limiting generalizability, and limited biomarker assessment excluding other important indicators. Future investigations should adopt longitudinal approaches, incorporate multiple centers, and expand biomarker assessment for comprehensive understanding of hypertension pathophysiology.

World Health Organization. Hypertension. WHO Fact Sheet 2021. Available at: https://www.who.int/news-room/fact-sheets/detail/hypertension

2. Gupta R, Gaur K, Ram CVS. Emerging trends in hypertension epidemiology in India. J Hum Hypertens. 2019;33(8):575-587.
3. Anchala R, Kannuri NK, Pant H, et al. Hypertension in India: a systematic review and meta-analysis of prevalence, awareness, and control of hypertension. J Hypertens. 2014;32(6):1170-1177.
4. American Diabetes Association. Standards of medical care in diabetes-2021. Diabetes Care. 2021;44(Suppl 1):S1-S232.
5. Gerstein HC, Mann JF, Yi Q, et al. Albuminuria and risk of cardiovascular events, death, and heart failure in diabetic and nondiabetic individuals. JAMA. 2001;286(4):421-426.
6. Mogensen CE. Microalbuminuria predicts clinical proteinuria and early mortality in maturity-onset diabetes. N Engl J Med. 1984;310(6):356-360.
7. Hillege HL, Fidler V, Diercks GF, et al. Urinary albumin excretion predicts cardiovascular and noncardiovascular mortality in general population. Circulation. 2002;106(14):1777-1782.
8. Parving HH, Lewis JB, Ravid M, et al. Prevalence and risk factors for microalbuminuria in a referred cohort of type II diabetic patients: a global perspective. Kidney Int. 2006;69(11):2057-2063.

9. Sharma SK, Ghimire A, Radhakrishnan J, et al. Prevalence of hypertension, obesity, diabetes, and metabolic syndrome in Nepal. Int J Hypertens. 2011;2011:821971.
10. Saboo B, Joshi S, Brahmbhatt A. Comparing various screening methods for detecting microalbuminuria in diabetic patients. Int J Diabetes Dev Ctries. 2006;26(4):153-157.
11. Das S, Pal S, Mitra M. Prevalence of microalbuminuria among type 2 diabetic patients and its association with diabetes control: a hospital-based cross-sectional study. Int J Med Sci Public Health. 2013;2(3):685-689.
12. Wachtell K, Ibsen H, Olsen MH, et al. Albuminuria and cardiovascular risk in hypertensive patients with left ventricular hypertrophy: the LIFE study. Ann Intern Med. 2003;139(11):901-906.
13. Rema M, Premkumar S, Anitha B, et al. Prevalence of diabetic retinopathy in urban India: the Chennai Urban Rural Epidemiology Study (CURES) eye study, I. Invest Ophthalmol Vis Sci. 2005;46(7):2328-2333.
14. Jose MD, Otahal P, Kirkland G, et al. Chronic kidney disease in Tasmania. Nephrology. 2009;14(8):743-749.
15. Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl. 2013;3(1):1-150.
16. Manjunath G, Tighiouart H, Ibrahim H, et al. Level of kidney function as a risk factor for atherosclerotic cardiovascular outcomes in the community. J Am Coll Cardiol. 2003;41(1):47-55.
17. Kshirsagar AV, Bang H, Bomback AS, et al. A simple algorithm to predict incident kidney disease. Arch Intern Med. 2008;168(22):2466-2473.
18. Bakris GL, Williams M, Dworkin L, et al. Preserving renal function in adults with hypertension and diabetes: a consensus approach. Am J Kidney Dis. 2000;36(3):646-661.
19. Brenner BM, Cooper ME, de Zeeuw D, et al. Effects of losartan on renal and cardiovascular outcomes in patients with type 2 diabetes and nephropathy. N Engl J Med. 2001;345(12):861-869.
20. Patel A, MacMahon S, Chalmers J, et al. Effects of a fixed combination of perindopril and indapamide on macrovascular and microvascular outcomes in patients with type 2 diabetes mellitus (the ADVANCE trial): a randomised controlled trial. Lancet. 2007;370(9590):829-840.