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Table 4 Characterization of subgroups after AKI detection

From: Algorithm-based detection of acute kidney injury according to full KDIGO criteria including urine output following cardiac surgery: a descriptive analysis

 

Total cohort

Disease group

AKI stages

Characteristic

N = 21045

Median (IQR) / n (%)

AKI

N = 13755

Median (IQR) / n (%)

No AKI

N = 7290

Median (IQR) / n (%)

p-valuea

AKI 1

N = 3707

Median (IQR) / n (%)

AKI 2

N = 6423

Median (IQR) / n (%)

AKI 3

N = 3625

Median (IQR) / n (%)

Age at admission

71 (62, 78)

72 (63, 78)

70 (61, 78)

< 0.001

72 (63, 78)

72 (63, 78)

72 (64, 78)

Male

15,048 (72%)

10,010 (73%)

5038 (69%)

< 0.001

2724 (73%)

4667 (73%)

2619 (72%)

Length ICU stay (day)

7.8 (5.8, 11.8)

8.8 (6.1, 12.5)

6.6 (4.9, 9.4)

< 0.001

7.6 (5.9, 11.1)

8.8 (6.2, 12.1)

10.1 (6.9, 13.5)

Number of drugs administered

18 (13, 24)

21 (16, 27)

13 (3, 18)

< 0.001

18 (14, 22)

21 (17, 27)

24 (18, 34)

Number of patients receiving nephrotoxic drugs

1374 (6.5%)

1097 (8.0%)

277 (3.8%)

< 0.001

200 (5.4%)

489 (7.6%)

408 (11%)

Number of different AKI comorbidities/ risk factors

2 (0, 3)

2 (1, 4)

0 (0, 2)

< 0.001

2 (1, 3)

3 (1, 4)

3 (1, 4)

  1. Percentages are computed with N of each subgroup. Distinction is made between general patient info (age, sex), length of ICU stay, medication and comorbidities.
  2. aWilcoxon rank sum test; Pearson’s Chi-squared test