World Journal of Emergency Medicine ›› 2026, Vol. 17 ›› Issue (1): 57-64.doi: 10.5847/wjem.j.1920-8642.2026.023
• Original Articles • Previous Articles Next Articles
Xin Lu1, Mubing Qin1, Zengrui Song1, Ying Chen2, Huadong Zhu1, Yanxia Gao3(
), Yi Li1(
)
Received:2025-09-01
Accepted:2025-12-20
Online:2026-01-29
Published:2026-01-01
Contact:
Yanxia Gao, Email: gaoyanxiazzu@163.comXin Lu, Mubing Qin, Zengrui Song, Ying Chen, Huadong Zhu, Yanxia Gao, Yi Li. Normal initial lactate level in sepsis patients: is lactate still useful for prognosis prediction?[J]. World Journal of Emergency Medicine, 2026, 17(1): 57-64.
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URL: http://wjem.com.cn/EN/10.5847/wjem.j.1920-8642.2026.023
Table 1.
Clinical characteristics and outcomes comparison among the lactate-based clinical phenotypes of sepsis patients
| Variables | Total (n=6,926) | Normal-normal (n=1,691) | Normal-elevated (n=266) | Elevated-normal (n=2,523) | Elevated-elevated (n=2,446) | P-value |
|---|---|---|---|---|---|---|
| Database, n (%) | <0.001 | |||||
| MIMIC-IV | 5,216 (75.3) | 1,401 (82.9) | 201 (75.6) | 1,838 (72.8) | 1,776 (72.6) | |
| eICU | 1,710 (24.7) | 290 (17.1) | 65 (24.4) | 685 (27.2) | 670 (27.4) | |
| Age, years, median (IQR) | 65.4 (54.0, 75.8) | 65.8 (54.4, 75.8) | 65.9 (56.2, 77.8) | 66 (54, 76) | 64.9 (53.4, 75.3) | 0.078 |
| Gender, male (%) | 3,911 (56.5) | 897 (53.0) | 154 (57.9) | 1,448 (57.4) | 1,412 (57.7) | 0.013 |
| SOFA score, median (IQR) | 5 (3, 7) | 4 (2, 6) | 4 (3, 6) | 5 (3, 7) | 6 (4, 9) | <0.001 |
| Lactate parameters, median (IQR) | ||||||
| Lactate change rate | 0.6 (0.4, 0.9) | 0.8 (0.7, 1.1) | 1.8 (1.4, 2.4) | 0.4 (0.3, 0.5) | 0.7 (0.5, 1.0) | <0.001 |
| Lactate difference | -1.1 (-2.6, -0.2) | -0.2 (-0.5, 0.1) | 1.1 (0.7, 1.9) | -2.1 (-3.6, -1.3) | -1.2 (-3.3, 0) | <0.001 |
| Vasopressor, n (%) | 4,253 (61.4) | 852 (50.4) | 132 (49.6) | 1,528 (60.6) | 1,741 (71.2) | <0.001 |
| Sepsis origins, n (%) | ||||||
| Pulmonary infection | 3,405 (49.2) | 953 (56.4) | 133 (50.0) | 1,137 (45.1) | 1,182 (48.3) | <0.001 |
| Urinary tract infection | 1,688 (24.4) | 439 (26.0) | 61 (22.9) | 578 (22.9) | 610 (24.9) | 0.113 |
| Intra-abdominal infection | 1,009 (14.6) | 198 (11.7) | 32 (12.0) | 324 (12.8) | 455 (18.6) | <0.001 |
| Skin soft tissue infection | 696 (10.0) | 194 (11.5) | 24 (9.0) | 256 (10.1) | 222 (9.1) | 0.082 |
| Bacteremia | 676 (9.8) | 135 (8.0) | 19 (7.1) | 211 (8.4) | 311 (12.7) | <0.001 |
| Outcomes | ||||||
| Mechanical ventilation, n (%) | 5,613 (81.0) | 1,414 (83.6) | 212 (79.7) | 1,995 (79.1) | 1,992 (81.4) | 0.003 |
| Renal replacement therapy, n (%) | 1,113 (16.1) | 205 (12.1) | 48 (18.0) | 269 (10.7) | 591 (24.2) | <0.001 |
| ICU LOS, d, median (IQR) | 5.4 (3.1, 10.1) | 5.9 (3.4, 10.4) | 5.5 (3.1, 10.1) | 4.9 (3, 8.7) | 5.8 (3, 11.3) | <0.001 |
| Hospital LOS, d, median (IQR) | 11.8 (6.9, 19.9) | 12.5 (7.8, 20.5) | 10.9 (6.6, 18.1) | 11.7 (7.0, 18.8) | 11.3 (5.0, 20.8) | <0.001 |
| In-hospital mortality, n (%) | 1,837 (26.5) | 316 (18.7) | 90 (33.8) | 403 (16.0) | 1,028 (42.0) | <0.001 |
Figure 1.
Workflow of the study and phenotype distribution. A: absolute counts of sepsis patients by lactate-based phenotypes in the MIMIC-IV and eICU databases; B: prevalence of lactate-based phenotypes in sepsis patients (MIMIC-IV); C: prevalence of lactate-based phenotypes in sepsis patients (eICU).
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