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. 2023 Oct 17;13:17686. doi: 10.1038/s41598-023-45034-1

Table 2.

Logistic regression analyses for predicting CKD risks.

Univariate analysis Multivariate analysis
OR 95% CI P value OR 95% CI P value
Gender
 Male (vs. female) 5.20 2.90–9.31  < 0.001 4.01 2.09–7.70  < 0.001
Age
 Continuous 1.05 1.03–1.07  < 0.001 1.04 1.01–1.06 0.002
Stone composition
 Non-uric acid (ref) (ref)
 Mixed-uric acid 4.53 2.48–8.26  < 0.001 2.73 1.43–5.21 0.002
 Pure-uric acid 9.72 5.46–17.29  < 0.001 5.92 3.18–11.02  < 0.001
NLR
 High (> 2.8 vs. ≤ 2.8) 1.99 1.29–3.09 0.002 1.72 1.03–2.88 0.039
Overweight
 Yes (BMI > 25 vs. ≤ 25) 1.20 0.77–1.86 0.426
DM
 Yes vs. No 1.55 0.97–2.45 0.065
HTN
 Yes vs. No 1.65 1.07–2.55 0.024
Gout
 Yes vs. No 3.09 1.57–6.06 0.001 1.37 0.81–2.30 0.242
CVD
 Yes vs. No 1.30 0.59–6.90 0.517
Hyperuricemia
 Yes (> 7 vs. ≤ 7 mg/dL) 2.26 1.12–4.57 0.023
Dyslipidemia
 Yes vs. No 0.80 0.40–1.60 0.524
Acidic urine
 Yes (pH < 6 vs. ≥ 6) 1.55 0.99–2.42 0.056

Parameters used for multivariate regression analysis: gender, age, stone composition, NLR, HTN. OR odds ratio, CI confidence interval, DM type 2 diabetes mellitus, HTN hyper-tension, CVD cardiovascular diseases, NLR neutrophil/lymphocyte ratio.