ABSTRACT
BACKGROUND: Semiquantitative dipstick tests are utilized for albuminuria screening. METHODS: In a prospective cross-sectional survey, we analyzed the diagnostic test validity of the semiquantitative colorimetric indicator-dye-based Combur9-Test® and the albumin-specific immunochromatographic assay Micral-Test® for the detection of albuminuria, the distribution of the semiquantitative measurements within the albuminuria stages according to KDIGO, and the utility for albuminuria screening compared with an albumin-to-creatinine ratio (ACR) in a walk-in population. RESULTS: In 970 subjects, albuminuria (≥30 mg/g) was detected in 12.7% (95% CI 85.6-96.3%) with the ACR. Sensitivity was 82.9% (95% CI 75.1-89.1%) and 91.9% (95% CI 88.7-96.9%) and specificity 71.5% (95% CI 68.4-74.6%) and 17.5% (95% CI 15.0-20.2%) for the Combur9-Test® and Micral-Test®, respectively. Correct classification to KDIGO albuminuria stages A2/A3 with the Combur9-Test® was 15.4%, 51.4%, and 87.9% at cut-offs of 30, 100, and ≥300 mg/dL, and with the Micral-Test® it was 1.8%, 10.5%, and 53.6% at cut-offs of 2, 5, and 10 mg/dL, respectively. Overall, disagreement to KDIGO albuminuria was seen in 27% and 73% with the Combur9-Test® and Micral-Test®, respectively. From the total population, 62.5% and 15.3% were correctly ruled out and 2.2% and 1% were missed as false-negatives by the Combur9-Test® and Micral-Test®, respectively. CONCLUSION: Compared to the Combur9-Test®, the utility of the Micral-Test® is limited, because the fraction of correctly ruled out patients is small and a large proportion with a positive Micral-Test® require a subsequent ACR conformation test.
ABSTRACT
In sub-Saharan Africa (SSA), epidemiological data for chronic kidney disease (CKD) are scarce. We conducted a prospective cross-sectional study including 952 patients in an outpatient clinic in Tanzania to explore CKD prevalence estimates and the association with cardiovascular and infectious disorders. According to KDIGO, we measured albumin-to-creatinine ratio and calculated eGFR using CKD-EPI formula. Factors associated with CKD were calculated by logistic regression. Venn diagrams were modelled to visualize interaction between associated factors and CKD. Overall, the estimated CKD prevalence was 13.6% (95% CI 11-16%). Ninety-eight patients (11.2%) (95% CI 9-14%) were categorized as moderate, 12 (1.4%) (95% CI 0-4%) as high, and 9 (1%) (95% CI 0-3%) as very high risk according to KDIGO. History of tuberculosis (OR 3.75, 95% CI 1.66-8.18; p = 0.001) and schistosomiasis (OR 2.49, 95% CI 1.13-5.18; p = 0.02) were associated with CKD. A trend was seen for increasing systolic blood pressure (OR 1.02 per 1 mmHg, 95% CI 1.00-1.03; p = 0.01). Increasing BMI (OR 0.92 per 1kg/m2, 95% CI 0.88-0.96; p = <0.001) and haemoglobin (OR 0.82 per 1g/dL, 95% CI 0.72-0.94; p = 0.004) were associated with risk reduction. Diabetes was associated with albuminuria (OR 2.81, 95% CI 1.26-6.00; p = 0.009). In 85% of all CKD cases at least one of the four most common factors (hypertension, diabetes, anaemia, and history of tuberculosis or schistosomiasis) was associated with CKD. A singular associated factor was found in 61%, two in 14%, and ≥3 in 10% of all CKD cases. We observed a high prevalence estimate for CKD and found that both classical cardiovascular and neglected infectious diseases might be associated with CKD in a semi-rural population of SSA. Our finding provides further evidence for the hypothesis that the "double burden" of non-communicable and endemic infectious diseases might affect kidney health in SSA.
