Table 3 Prediction of ARC in subgroup cohorts. 

From: Machine learning for the prediction of augmented renal clearance (ARC) in patients with sepsis in critical care units

Subgroup

AUC

Accuracy

Sensitivity

Specificity

PPV

NPV

Kappa

age > 67

0.817

0.729

0.796

0.719

0.293

0.960

0.297

age ≤ 67

0.781

0.743

0.581

0.797

0.492

0.849

0.357

SOFA > 6

0.843

0.774

0.774

0.774

0.357

0.955

0.367

SOFA ≤ 6

0.793

0.736

0.667

0.758

0.469

0.876

0.371

BMI ≥ 28

0.819

0.809

0.561

0.861

0.457

0.904

0.387

BMI < 28

0.805

0.739

0.671

0.758

0.425

0.896

0.353

CVD

0.796

0.678

0.895

0.605

0.430

0.945

0.368

non-CVD

0.826

0.764

0.752

0.767

0.415

0.934

0.394

  1. We conducted subgroup analyses based on age, SOFA, BMI and CVD. SOFA: sequential organ failure assessment; CVD: cerebrovascular disease; BMI: body mass index.
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