From: Comparing different machine learning techniques for predicting COVID-19 severity
Variables | All cases | Non-severe cases | Severe cases | P |
---|---|---|---|---|
(n = 287) | (n = 182) | (n = 105) | ||
Fever | 88 (30.7) | 57 (31.3) | 31 (29.5) | 0.751 |
MT | 16 (5.6) | 11 (6.0) | 5 (4.8) | 0.648 |
HR, beats/min | 88 (80–99) | 87 (80–98) | 88 (84–99) | 0.122 |
SBP, mmHg | 127 (117–138) | 125 (115–136) | 131 (121–138) | 0.008 |
Laboratory findings | ||||
NLR | 3.28 (2.17–5.77) | 2.71 (1.70–4.15) | 5.73 (3.17–9.97) | < 0.001 |
HB | 127.0 (117.0–136.0) | 128.0 (119.0–136.0) | 123 (114.0–136.0) | 0.109 |
RDW-CV | 12.4 (11.9–12.9) | 12.3 (11.9–12.8) | 12.5 (11.9–13.0) | 0.032 |
LDH | 258.0 (200.0–346.5) | 231.0 (184.7–276.5) | 343.0 (261.0–452.0) | < 0.001 |
IBIL | 8.4 (6.1–11.6) | 8.9 (6.6–11.8) | 7.8 (5.6–10.80) | 0.048 |
D-Dimer | 0.7 (0.4–1.5) | 0.5 (0.3–0.9) | 1.1 (0.6–1.5) | < 0.001 |
PT | 11.3 (10.7–12.0) | 11.2 (10.6–11.7) | 11.7 (10.8–12.6) | < 0.001 |
Ca2+ | 2.10 (1.99–2.17) | 2.09 (22.0–52.25) | 2.01 (1.93–2.10) | < 0.001 |
ESR | 43.0 ( (26.0–58.0) | 40.5 (18.0–27.0) | 50.3 (35.0–65.5) | < 0.001 |
AFU | 23.0 (19.0–27.0) | 23.0 (18.0–27.0) | 23.0 (20.0–27.0) | 0.508 |
RBP | 26.4 (19.0–40.4) | 26.4 (20.6–40.5) | 26.4 (17.1–40.0) | 0.433 |
IL-6 | 8.3 (6.5–11.7) | 8.2 (6.5–10.2) | 9.2 (7.2–12.9) | 0.001 |
Hs-cTn | 3.6 (1.5–8.3) | 2.9 (1.1–5.8) | 6.2 (2.8–12.4) | < 0.001 |
AMS | 62.0 (49.0–79.5) | 62.0 (49.3–74.0) | 68.0 (49.0–97.0) | 0.078 |
CysC | 0.85 (0.75–1.03) | 0.83 (0.73–0.94) | 0.95 (0.78–1.16) | < 0.001 |
IMG | 0.01 (0.01–0.04) | 0.01 (0.00–0.03) | 0.03 (0.01–0.11) | < 0.001 |
ALP | 76.0 (59.5–94.0) | 76.0 (59.3–95.8) | 75.0 (60.0–93.0) | 0.806 |
MB | 42.4 (30.7–64.5) | 39.1 (28.0–53.0) | 50.1 (38.8–87.3) | < 0.001 |
C-CTa | < 0.001 | |||
0 | 63 (22.0%) | 63 (34.6%) | 0 (0%) | |
1 | 29 (10.1%) | 23 (12.6%) | 6 (5.7%) | |
2 | 195 (67.9%) | 96 (52.7%) | 99 (94.3%) |