Applicability of Novel Urinary Biomarkers for the Assessment of Renal Injury in Selected Occupational Groups in Sri Lanka: A Comparative Study with Conventional Markers
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design and Participants
2.2. Data and Sample Collection
2.3. Sample Preparation and Analysis
2.4. Diagnostic Criteria
2.5. Statistical Analysis
2.6. Ethical Considerations
3. Results
3.1. Characteristics of the Study Participants
3.2. Novel Urinary Biomarkers
3.3. Conventional Markers
3.4. Assessment of Biomarker Performance
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Characteristics | Fisherfolk (n = 40) | Paddy Farmers (n = 40) | Sugarcane Farmers (n = 40) | Factory Workers (n = 33) | Plantation Workers (n = 35) | CKDu Patients (n = 40) |
---|---|---|---|---|---|---|
Demographic characteristics | ||||||
Age/years † | 47 (37–54) | 46 (32–55) | 50 (36–62) | 37 (29–46) | 47 (39–56) | 53 (47–65) |
Gender Male Female | 27 (67.5) 13 (32.5) | 12 (30.0) 19 (70.0) | 24 (60.0) 16 (40.0) | 21 (63.6) 12 (36.4) | 16 (45.7) 19 (54.3) | 26 (65.0) 14 (35.0) |
Clinical characteristics | ||||||
BMI/kgm−2 † | 23.7 (22.1–26.7) | 21.7 (19.4–25.6) | 20.2 (17.3–22.9) | 19.9 (18.6–22.6) | 20.8 (18.4–24.6) | 23.5 (22.0–26.0) |
Obesity ⁑ | 5 (12.5) | 5 (12.5) | 1 (2.5) | 1 (3.0) | 2 (5.7) | 1 (2.5) |
Diabetes mellitus ⁑ | 5 (12.5) * | 3 (7.5) * | 0 * | 0 * | 2 (5.7) * | 21 (52.5) |
Hypertension ⁑ | 6 (15.0) * | 3 (7.5) * | 5 (12.5) * | 0 * | 4 (11.4) * | 12 (30.0) |
Lifestyle-related characteristics | ||||||
Agrochemical Exposure ⁑ | 0 | 40 (100.0) | 32 (80.0) | 0 | 22 (62.9) | 28 (70.0) |
Drinking water quality ⁑ Low Medium High | 0 29 (72.5) 11 (27.5) | 20 (50.0) 19 (47.5) 21 (52.5) | 6 (15.0) 34 (85.0) 6 (15.0) | 2 (6.0) 22 (66.7) 11 (33.3) | 4 (11.4) 31 (88.6) 0 | 0 28 (70.0) 12 (30.0) |
Smoking ⁑ | 6 (15.0) | 2 (5.0) | 18 (45.0) | 17 (51.2) | 15 (42.9) | 1 (2.5) |
Alcohol consumption ⁑ | 19 (47.5) | 10 (25.0) | 15 (37.5) | 17 (51.5) | 22 (42.9) | 3 (2.5) |
Study Group | KIM-1 (ng/mg Cr) | NGAL (ng/mg Cr) |
---|---|---|
Fisherfolk | 0.665 (0.428–0.945) | 1.155 (0.653–1.715) |
Paddy farmers | 0.585 (0.373–0.910) | 2.515 (1.498–4.380) |
Sugarcane farmers | 0.490 (0.383–0.703) | 1.420 (0.998–1.910) |
factory workers | 1.625 (0.500–2.418) | 1.710 (0.733–5.470) |
Plantation workers | 0.67 (0.490–0.840) | 1.060 (0.690–1.600) |
CKDu patients | 5.242 (4.298–8.800) | 22.41 (4.630–154.300) |
Clinical Parameters | Fisherfolk (n = 40) | Paddy Farmers (n = 40) | Sugarcane Farmers (n = 40) | Factory Workers (n = 33) | Plantation Workers (n = 35) | CKDu Patients (n = 40) |
---|---|---|---|---|---|---|
ACR (mg/g) | 4.455 (2.885–7.645) | 3.945 (2.755–7.110) | 3.640 (2.415–18.88) | 4.600 (2.323–7.613) | 3.350 (2.430–6.350) | 1105.00 (227–2458) |
eGFR (mL/min/1.73 m2) | 100.7 (89.1–105.3) | 106.0 (88.5–122.7) | 86.7 (59.0–118.2) | 115.1 (108.4–131.3) | 107.7 (90.3–123.5) | 20.0 (9.9–34.8) |
SCr (mg/dL) | 1.130 (1.02–1.228) | 1.010 (0.670–1.263) | 0.725 (0.590–1.243) | 0.950 (0.880–1.030) | 0.760 (0.670–0.960) | 3.990 (2.150–9.035) |
SCys-C (mg/L) | 0.810 (0.693–0.903) | 0.770 (0.578–0.855) | 1.110 (0.760–1.440) | 0.710 (0.590–0.828) | 0.830 (0.710–1.090) | 2.510 (1.715–3.443) |
BUN (mg/dL) | 21.00 (17.95–24.10) | 10.00 (8.40–12.70) | 23.70 (16.95–29.45) | 23.90 (20.48–32.15) | 26.30 (22.50–34.30) | 46.65 (26.28–73.73) |
SUA (mg/dL) | 5.385 (4.925–6.850) | 4.445 (3.185–5.288) | 5.545 (4.090–6.753) | 3.850 (3.353–4.745) | 5.060 (4.140–6.410) | 6.295 (5.258–7.593) |
ACR ≥ 30 mg/g | 3 (7.5) †,* | 2 (5.0) †,* | 9 (22.5) † | 1 (3.0) †,* | 1 (2.9) †,* | 40 (100) |
eGFR < 60 mL/min/1.73 m2 | 2 (5.0) †,* | 3 (7.5) †,* | 10 (25.0) † | 1 (3.0) †,* | 5 (14.3) † | 40 (100) |
Parameter | ROC Parameters | FF vs. PT | SW vs. PT | SF vs. PT | PF vs. PT | EW vs. PT | Overall |
---|---|---|---|---|---|---|---|
SCr (mg/dL) | AUC (95% CI) | 0.942 (0.88–1.00) | 0.977 (0.94–1.01) | 0.891 (0.82–0.97) | 0.947 (0.89–0.99) | 0.978 (0.95–1.00) | 0.944 (0.90–0.98) |
Cutoff | 1.41 | 1.30 | 1.38 | 1.65 | 1.14 | 1.21 | |
Sensitivity | 0.92 | 0.93 | 0.92 | 0.90 | 0.95 | 0.93 | |
Specificity | 0.95 | 1.00 | 0.80 | 0.93 | 0.94 | 0.81 | |
SCys-C (mg/L) | AUC (95% CI) | 0.955 (0.91–1.00) | 0.985 (0.97–1.00) | 0.807 (0.70–0.91) | 0.95 (0.90–0.99) | 0.935 (0.88–0.99) | 0.920 (0.88–0.96) |
Cutoff | 0.98 | 1.09 | 1.42 | 0.97 | 1.11 | 1.09 | |
Sensitivity | 0.95 | 0.93 | 0.88 | 0.95 | 0.92 | 0.93 | |
Specificity | 0.88 | 0.97 | 0.75 | 0.88 | 0.80 | 80.7 | |
ACR (mg/g) | AUC (95% CI) | 0.954 (0.90–1.00) | 0.963 (0.92–1.07) | 0.926 (0.87–0.98) | 0.959 (0.91–1.00) | 0.96 (0.91–1.01) | 0.949 (0.90–0.99) |
Cutoff | 8.64 | 12.71 | 28.21 | 13.28 | 10.60 | 8.55 | |
Sensitivity | 0.92 | 0.92 | 0.90 | 0.92 | 0.92 | 0.93 | |
Specificity | 0.83 | 0.88 | 0.78 | 0.93 | 0.80 | 0.77 | |
BUN (mg/dL) | AUC (95% CI) | 0.807 (0.69–0.92) | 0.757 (0.64–0.87) | 0.707 (0.59–0.83) | 0.942 (0.89–0.99) | 0.731 (0.61–0.85) | 0.789 (0.69–0.89) |
Cutoff | 20.85 | 37.25 | 37.00 | 13.55 | 38 | 24.5 | |
Sensitivity | 0.80 | 0.62 | 0.62 | 0.92 | 0.62 | 0.8 | |
Specificity | 0.48 | 0.88 | 0.83 | 0.80 | 0.91 | 0.69 | |
SUA (mg/dL) | AUC (95% CI) | 0.639 (0.52–0.76) | 0.904 (0.84–0.97) | 0.637 (0.52–0.76) | 0.851 (0.77–0.93) | 0.688 (0.57–0.81) | 0.738 (0.66–0.82) |
Cutoff | 6.94 | 5.37 | 7.00 | 5.79 | 6.41 | 4.76 | |
Sensitivity | 0.38 | 0.72 | 0.38 | 0.62 | 0.50 | 0.90 | |
Specificity | 0.78 | 0.91 | 0.78 | 0.88 | 0.80 | 0.45 | |
KIM-1 (ng/mgCr) | AUC (95% CI) | 0.998 (0.99–1.00) | 0.910 (0.84–0.98) | 0.875 (0.79–0.97) | 0.975 (0.93–1.02) | 0.999 (0.99–1.00) | 0.988 (0.98–1.00) |
Cutoff | 2.608 | 3.352 | 2.984 | 2.928 | 2.291 | 2.76 | |
Sensitivity | 1.00 | 0.92 | 1.00 | 1.00 | 1.00 | 1.00 | |
Specificity | 0.98 | 0.76 | 0.78 | 0.95 | 0.97 | 0.96 | |
NGAL (ng/mgCr) | AUC (95% CI) | 0.936 (0.87–1.00) | 0.777 (0.67–0.88) | 0.923 (0.86–0.99) | 0.819 (0.72–0.92) | 0.863 (0.78–0.95) | 0.893 (0.82–0.96) |
Cutoff | 1.54 | 10.88 | 1.59 | 7.58 | 7.36 | 3.12 | |
Sensitivity | 0.95 | 0.12 | 0.90 | 0.68 | 0.70 | 0.88 | |
Specificity | 0.75 | 0.88 | 0.75 | 0.93 | 0.86 | 0.82 |
Predictor Variable | KIM-1 | NGAL | ACR | eGFR | ||||
---|---|---|---|---|---|---|---|---|
β | p | β | p | β | p | β | p | |
Age | −0.048 | 0.354 | −0.094 | 0.174 | −0.069 | 0.255 | −0.163 | 0.002 |
Gender | 0.06 | 0.264 | −0.003 | 0.967 | −0.32 | 0.612 | −0.04 | 0.491 |
BMI | 0.032 | 0.535 | −0.05 | 0.462 | 0.041 | 0.494 | 0.012 | 0.829 |
Occupation | 0.415 | <0.0001 | 0.207 | 0.002 | 0.292 | <0.0001 | −2.08 | <0.0001 |
Hypertension | 0.259 | <0.0001 | 0.093 | 0.272 | 0.368 | <0.0001 | −0.487 | <0.0001 |
Diabetes mellitus | 0.182 | 0.001 | 0.233 | <0.0001 | 0.085 | 0.226 | 0.014 | 0.827 |
Quality of Drinking water | −0.05 | 0.385 | −0.029 | 0.707 | 0.008 | 0.905 | 0.039 | 0.535 |
Agrochemical exposure | −0.09 | 0.881 | −0.078 | 0.339 | 0.007 | 0.922 | 0.079 | 0.224 |
Smoking | −0.073 | 0.163 | −0.06 | 0.392 | −0.137 | 0.015 | 0.045 | 0.43 |
Alcohol consumption | 0.157 | 0.001 | 0.091 | 0.216 | −0.064 | 0.324 | 0.097 | 0.099 |
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Ekanayake, E.M.D.V.; Gunasekara, T.D.K.S.C.; De Silva, P.M.C.S.; Jayasinghe, S.; Chandana, E.P.S.; Jayasundara, N. Applicability of Novel Urinary Biomarkers for the Assessment of Renal Injury in Selected Occupational Groups in Sri Lanka: A Comparative Study with Conventional Markers. Int. J. Environ. Res. Public Health 2022, 19, 5264. https://doi.org/10.3390/ijerph19095264
Ekanayake EMDV, Gunasekara TDKSC, De Silva PMCS, Jayasinghe S, Chandana EPS, Jayasundara N. Applicability of Novel Urinary Biomarkers for the Assessment of Renal Injury in Selected Occupational Groups in Sri Lanka: A Comparative Study with Conventional Markers. International Journal of Environmental Research and Public Health. 2022; 19(9):5264. https://doi.org/10.3390/ijerph19095264
Chicago/Turabian StyleEkanayake, E. M. D. V., T. D. K. S. C. Gunasekara, P. Mangala C. S. De Silva, Sudheera Jayasinghe, E. P. S. Chandana, and Nishad Jayasundara. 2022. "Applicability of Novel Urinary Biomarkers for the Assessment of Renal Injury in Selected Occupational Groups in Sri Lanka: A Comparative Study with Conventional Markers" International Journal of Environmental Research and Public Health 19, no. 9: 5264. https://doi.org/10.3390/ijerph19095264