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Table 7 Diagnostic algorithms developed for autistic spectrum disorder from plasma and urinary analytes

From: Advanced glycation endproducts, dityrosine and arginine transporter dysfunction in autism - a source of biomarkers for clinical diagnosis

Algorithm no

1

2

3

4

Compartment and analyte

Plasma protein adduct residues

Plasma amino acids

Plasma protein adduct residues and amino acids

Urinary amino acids

Features

CML, 3DG-H, CMA, and DT

CML and CMA

CML, 3DG-H, CMA, and DT residues with G-H1 and GSA free adducts

GSA and pyrraline free adducts

Accuracy (%)

88.3 (85.5–91.2)

74.8 (71.7–77.9)

89.0 (87.0–91.0)

76.8 (74.6–79.0)

Sensitivity (%)

91.9 (89.1–94.6)

80.5 (75.1–86.0)

90.4 (87.7–93.1)

77.1 (73.4–80.8)

Specificity (%)

83.9 (79.3–88.4)

67.1 (58.9–75.4)

87.3 (84.1–90.5)

76.4 (72.0–80.8)

AUROC

0.94 (0.91–0.96)

0.80 (0.77–0.83)

0.95 (0.94–0.96)

0.79 (0.76–0.81)

Positive likelihood ratio

5.69 (4.49–6.89)

2.85 (2.16–3.55)

7.23 (6.09–8.38)

4.16 (2.88–5.44)

Negative likelihood ratio

0.10 (0.07–0.13)

0.28 (0.21–0.35)

0.11 (0.08–0.14)

0.30 (0.25–0.34)

Positive predictive value (%)

88.2 (85.0–91.4)

77.1 (72.9–81.4)

90.2 (87.9–92.5)

80.6 (77.6–83.5)

Negative predictive value (%)

89.1 (85.5–92.6)

75.0 (70.6–79.4)

88.0 (85.1–91.0)

73.7 (71.0–76.5)

F score

0.90 (0.87–0.92)

0.78 (0.75–0.81)

0.90 (0.88–0.92)

0.78 (0.76–0.81)

  1. Algorithm outcomes for twofold cross-validation (10 randomized repeat trials for robustness) using SVMs (95% CI given in brackets)