Abstract
Acute kidney injury (AKI) is a common complication in burn patients linked to higher mortality, but AKI defined by KDIGO criteria in this group is understudied. This retrospective study analyzed 592 burn patients with total body surface area (TBSA) ≥10% admitted between 1 January 2010 and 1 April 2024, examining AKI prevalence, risk factors, and in-hospital mortality via electronic records and laboratory results. Patients were grouped by AKI occurrence (AKI/non-AKI) and in-hospital survival (survivor/non-survivor), with logistic regression used to identify related factors. Results showed 29.1% AKI prevalence; in-hospital mortality was over 15 times higher in AKI patients (40.7% vs. 2.6%, p < 0.001). Independent AKI risk factors included age, admission hypotension/shock, full-thickness burn area, baseline sCr, sepsis, rhabdomyolysis, and DIC. AKI stages 2 and 3 independently raised in-hospital mortality, and AKI patients had significantly higher healthcare costs (p < 0.001). In summary, 29.1% of burn patients developed AKI, which correlated with increased in-hospital mortality.
Keywords: Acute kidney injury, burn injury, risk factors, mortality
Introduction
Acute kidney injury (AKI) is defined as an abrupt decline in renal function that includes a rapid increase in serum creatinine (sCr), decrease in urine output (UO), or both. It is a syndrome comprising multiple clinical conditions with complex etiology, high morbidity, and poor prognosis including the development of chronic kidney disease, and an increased risk of short- and long-term risk of adverse outcomes [1–5]. AKI has a relatively high incidence among hospitalized patients, with the rate reaching 57.3% particularly in those admitted to the intensive care unit (ICU) [3,6–8]. According to the criteria established by the Kidney Disease: Improving Global Outcomes (KDIGO) classification, AKI is staged by serum creatinine and urine output changes: Stage 1 involves a ≥ 0.3 mg/dL sCr rise within 48 h, 1.5–1.9× baseline sCr (7 days prior), or UO <0.5 mL/kg/h for 6–12 h; Stage 2 includes 2.0–2.9× baseline sCr or UO <0.5 mL/kg/h for 12–24 h; Stage 3 is defined by ≥3.0× baseline sCr, sCr ≥4.0 mg/dL with ≥0.5 mg/dL acute rise, renal replacement therapy initiation, UO <0.5 mL/kg/h for ≥24 h, or anuria ≥12 h [1].
Patients with AKI exhibit a higher mortality rate than those without AKI, with an odds ratio (OR) of 11.3 (95% confidence interval: 7.3–17.4) [9,10]. Due to different criteria for AKI, the results of the studies varied considerably [10,11]. The incidence of AKI in burn patients ranges from 9% to 50% [12]. The pathophysiology underlying AKI in burn patients is characterized by a multifactorial interplay. Severe burn injury initiates a systemic inflammatory response syndrome SIRS, accompanied by the excessive secretion of pro-inflammatory cytokines, which precipitates microvascular dysfunction and consequent renal hypoperfusion [12]. Furthermore, hypovolemia secondary to fluid loss, myoglobinuria resulting from rhabdomyolysis, and endotoxemia associated with sepsis collectively exacerbate tubular epithelial injury and compromise glomerular filtration capacity [9–12]. Ischemic-reperfusion injury, in conjunction with oxidative stress derived from burned tissue, intensifies renal parenchymal damage, thereby synergistically contributing to the pathogenesis of AKI [12]. Some studies have shown that sepsis, higher burned total body surface area (TBSA), and the presence of multiple organ failure are high-risk factors leading to the occurrence of AKI in burn patients [9,13–15].
Compared with other diagnostic criteria, KDIGO criteria is more effective in the early diagnosis of AKI [16–18]. Few studies have reported progression of AKI, financial burden, and adverse outcomes in burn patients [10,19]. Acute renal support refers to therapeutic interventions that substitute or support impaired renal function in patients with acute kidney injury or acute exacerbation of chronic kidney disease, with the aims of maintaining fluid and electrolyte balance and remove uremic toxins. The main dialysis modalities include: intermittent hemodialysis, which involves short-term intermittent treatment (3–4 h) for toxin and fluid removal; peritoneal dialysis, which uses the peritoneum as a filter for dialysate exchange; and continuous renal replacement therapy (CRRT), which provides 24-h continuous treatment with slow removal of fluids and solutes, suitable for hemodynamically unstable patients such as those with severe burns [12]. Among these modalities, CRRT is particularly relevant in severe burn cases, and its utilization remains understudied. The purpose of the present study was to analyze the prevalence of AKI, the need for CRRT, in-hospital mortality, and risk factors associated with AKI and mortality in adult patients with TBSA ≥10%.
Materials and methods
Data source and patient population
This retrospective, cross-sectional study (Figure 1), We reviewed the electronic medical records and laboratory results of 592 burn patients at the West China Hospital of Sichuan University (Sichuan, China) from 1 January 2010 to 1 April 2024. Exclusion criteria were as follows: i) patients aged <18 years; ii) patients who arrived at the burn unit >72 h after burn injury; iii) patients with TBSA <10%; iv) Patients with length of stay (LOS) <24 h; and v) patients with incomplete data. This study was approved by the Ethics Committees of the West China Hospital of Sichuan University.
Figure 1.
Flow diagram of the study.
Data collection
The clinical data of the patients were obtained from the electronic medical record system, including age, sex, hypertension, chronic obstructive pulmonary disease (COPD), diabetes mellitus, chronic liver disease, cerebrovascular disease, malignant tumor, hypotension or shock at admission, inhalational injury, burn type, TBSA, full-thickness burn area, laboratory data, clinical event, primary and secondary outcomes, LOS in hospital, and hospitalization costs. The laboratory data were derived from the results of the first laboratory tests on admission.
Measurements and variable definitions
According to KDIGO criteria [1], the highest sCr during hospitalization, the decrease in UO (no specific urine output was recorded), or the need for CRRT was used to classify AKI. Baseline sCr was defined as the first sCr obtained at admission. if not obtained at admission, it was the lowest sCr in the first 7 days of hospitalization. Patients with a serum creatine kinase (CK) level ≥1000 U/L (at least 5x the upper limit of normal) or a record of myoglobinuria were diagnosed with rhabdomyolysis [20]. The burn depth was estimated based on clinical findings, and the burned area was estimated using the rule of nines [21].
Outcomes and follow-up
Early AKI was classified as AKI developing within 48 h of burn injury. Late AKI was defined as AKI presenting after 48 h of burn injury. The primary outcomes were the occurrence of AKI, and the severity of AKI. The secondary outcomes were in-hospital mortality, LOS in the hospital, hospitalization costs and complications.
Statistical analyses
In this study, descriptive analysis was used to summarize the demographic characteristics of burn patients. Continuous variables were expressed in terms of medians (25th and 75th percentiles). Categorical data were presented as numbers and percentages. The normality of the data distribution was tested using the Kolmogorov-Smirnov test. Mann–Whitney or t-test was used to compare continuous variables. Chi-squared analysis or Fisher’s exact test was used to compare categorical variables. Logistic regression was performed to determine the risk factors for AKI in burn patients and death-related factors.
The predictive effects of the multivariate logistic regression model were evaluated using the receiver operating characteristic (ROC) curve. Kaplan-Meier survival was used to estimate in-hospital survival in patients with AKI after burns. The log-rank test was used to test for between-group differences in survival curves.
p ≤ 0.05 was considered statistically significant. Statistical analysis was performed by the SPSS software package, version 26.0 (IBM Corp., Chicago, USA) and GraphPad Prism 8.0 software (GraphPad Software, Inc., San Diego, CA, USA).
Results
Patient characteristics and outcomes
The final study population consisted of 592 burn patients (Figure 1). Demographic and clinical characteristics of burn patients are summarized in Table 1. All patients were followed up until hospital discharge. Among the burn patients, AKI, according to the KDIGO guidelines, was diagnosed in 172 (29.1%) patients, including 72 (12.2%) with AKI stage 1, 50 (8.4%) with AKI stage 2, and 50 (8.4%) with AKI stage 3. 34 (19.8%) AKI patients were in need of CRRT. Compared to the non-AKI group, the AKI group was older, had a larger burn area, and was more likely to have a combination of hypotension and inhalation injury at admission (p < 0.05). 140 patients (81.4%) developed AKI within 2 days in all AKI patients.
Table 1.
Demographics and laboratory data of 592 burn patients.
| Variables | Total (n = 592) | Non-AKI (n = 420) | AKI (n = 172) | P value |
|---|---|---|---|---|
| Age, (year) | 42 (33,50) | 41 (32,49) | 45 (37,57) | <0.001 |
| Sex | 0.230 | |||
| Male | 463 (78.2%) | 323 (76.9%) | 140 (81.4%) | |
| Female | 129 (21.8%) | 97 (23.1%) | 32 (18.6%) | |
| Smoking | 217 (36.7%) | 144 (34.3%) | 73 (42.4%) | 0.062 |
| Drinking | 102 (17.2%) | 62 (14.8%) | 40 (23.3%) | 0.013 |
| Medical history | ||||
| Hypertension | 45 (7.6%) | 20 (4.8%) | 25 (14.5%) | <0.001 |
| COPD | 7 (1.2%) | 3 (0.7%) | 4 (2.3%) | 0.113 |
| Diabetes mellitus | 26 (4.4%) | 12 (2.9%) | 14 (8.1%) | 0.004 |
| Chronic liver disease | 30 (5.1%) | 24 (5.7%) | 6 (3.5%) | 0.262 |
| Cerebrovascular disease | 9 (1.5%) | 1 (0.2%) | 8 (4.7%) | <0.001 |
| Malignant tumor | 4 (0.7%) | 3 (0.7%) | 1 (0.6%) | 1.000 |
| Hypotension or shock at admission | 87 (14.7%) | 24 (5.7%) | 63 (36.6%) | <0.001 |
| Inhalation injury | 197 (33.3%) | 107 (25.5%) | 90 (52.3%) | <0.001 |
| Burn type | ||||
| Flame burn | 430 (72.6%) | 295 (70.2%) | 135 (78.5%) | 0.041 |
| Chemical burn | 38 (6.4%) | 29 (6.9%) | 9 (5.2%) | 0.451 |
| Electrical burn | 86 (14.5%) | 69 (16.4%) | 17 (9.9%) | 0.040 |
| Scald | 17 (2.9%) | 12 (2.9%) | 5 (2.9%) | 0.974 |
| TBSA (%) | 25 (15,50) | 20 (13,35) | 54 (32,80) | <0.001 |
| Full-thickness burn area (%) | 5 (1,18) | 4 (0,10) | 22 (10,40) | <0.001 |
| Laboratory data | ||||
| Baseline sCr (μmol/L) | 77 (65,93) | 73 (61,83) | 97 (80,125) | <0.001 |
| BUN (mmol/L) | 6.04 (4.70,7.60) | 5.64 (4.38,6.90) | 7.43 (6.10, 9.48) | <0.001 |
| Uric acid (μmol/L) | 342.6 (268.0,424.1) | 331.5 (261.0,412.0) | 372.5 (300.0,454.6) | <0.001 |
| Cystatin C (mg/L) | 0.77 (0.67,0.92) | 0.75 (0.65,0.87) | 0.86 (0.71,1.24) | <0.001 |
| ALT (U/L) | 24 (17,37) | 22 (16,35) | 28 (19,46) | <0.001 |
| AST (U/L) | 35 (25,58) | 30 (23,43) | 56 (34,112) | <0.001 |
| Creatine kinase (U/L) | 180 (107,419) | 152 (100,275) | 351 (174,1716) | <0.001 |
| Albumin (g/L) | 38 (31,42) | 40 (33,43) | 31 (25,39) | <0.001 |
| Hemoglobin (g/L) | 155 (140,170) | 154 (140,167) | 163 (141,182) | 0.001 |
| Platelets (×109/L) | 187 (132,245) | 183 (130,237) | 199 (144,271) | 0.032 |
| WBC (×109/L) | 15.2 (11.2,21.8) | 14.0 (10.5,18.5) | 21.6 (13.6,29.2) | <0.001 |
| Clinical event | ||||
| Lactic acidosis | 76 (12.8%) | 15 (3.6%) | 61 (35.5%) | <0.001 |
| Sepsis | 70 (11.8%) | 10 (2.4%) | 60 (34.9%) | <0.001 |
| Rhabdomyolysis | 119 (20.1%) | 37 (8.8%) | 82 (47.7%) | <0.001 |
| DIC | 39 (6.6%) | 1 (0.2%) | 38 (22.1%) | <0.001 |
| Primary outcome | ||||
| AKI | 87 (29.1%) | |||
| AKI stage | ||||
| stage 1 | 72 (12.2%) | 72 (41.9%) | ||
| stage 2 | 50 (8.4%) | 50 (29.1%) | ||
| stage 3 | 50 (8.4%) | 50 (29.1%) | ||
| Transient AKI | 98 (16.6%) | 98 (57.0%) | ||
| Persistent AKI | 50 (8.4%) | 50 (29.1%) | ||
| AKD | 24 (4.1%) | 24 (14.0%) | ||
| Early AKI | 140 (23.6%) | 140 (81.4%) | ||
| Late AKI | 32 (5.4%) | 32 (18.6%) | ||
| Need for CRRT | 34 (5.4%) | 34 (19.8%) | <0.001 | |
| Secondary outcome | ||||
| Mechanical ventilation | 134 (22.6%) | 48 (11.4%) | 86 (50.0%) | <0.001 |
| MODS | 66 (11.1%) | 6 (1.4%) | 60 (34.9%) | <0.001 |
| Mortality in hospital | 81 (13.7%) | 11 (2.6%) | 70 (40.7%) | <0.001 |
| LOS in hospital, days | 22 (10,51) | 21 (12,47) | 25 (6,60) | 0.830 |
| Hospitalization costs, $ | 6879 (2939, 21233) | 5240 (2747, 14253) | 15782 (4498, 36128) | <0.001 |
Continuous variables are summarized as medians (25th and 75th percentiles). Categorical variables are presented as numbers and percentages.
AKI: acute kidney injury; ALT: alanine aminotransferase; AST: aspartate aminotransferase; BUN: blood urea nitrogen; COPD: chronic obstructive pulmonary disease; sCr: serum creatinine; TBSA: burned total body surface area; WBC: white blood cell; AKD: acute kidney disease; CRRT: continuous renal replacement therapy; DIC: disseminated intravascular coagulation; LOS: length of stay; MODS: multiple organ dysfunction syndrome.
With regard to clinical events, patients in the AKI group had higher prevalence of mechanical ventilation (50.0% vs. 11.4%, p < 0.001), lactic acidosis (35.5% vs. 3.6%, p < 0.001), sepsis (34.9% vs. 2.4%, p < 0.001), rhabdomyolysis (47.7% vs. 8.8%, p < 0.001), and DIC (22.1% vs. 0.2%, p < 0.001) compared to patients in the non-AKI group (p < 0.001). In addition, patients in the AKI group had a higher incidence of multiple organ dysfunction syndrome (MODS, 34.9% vs. 1.4%, p < 0.001). In-hospital mortality was more than 15 times higher in patients with AKI than in the non-AKI group (40.7% vs. 2.6%, p < 0.001). The cost of treatment was more expensive in patients with AKI (p < 0.001), whereas there was no significant difference in the LOS in the hospital between the two groups (p = 0.830).
Risk factors for the development of AKI in burn patients
In the univariate logistic regression analysis (Table 2), several variables were relevant to the occurrence of AKI. In the multivariate logistic regression model (Table 2), the model showed age (OR = 1.020; p = 0.027), hypotension or shock on admission (OR = 2.476; p = 0.019), full-thickness burn area (OR = 1.090; p < 0.001), baseline sCr (OR = 1.047; p < 0.001), sepsis (OR = 21.964; p < 0.001), rhabdomyolysis (OR = 9.431; p < 0.001), and DIC (OR = 118.821; p < 0.001) were independently associated with the increased risk of the development of AKI. The multivariate logistic regression model for the occurrence of AKI after burn injury was analyzed for ROC (p < 0.001) with the area under the ROC curve (AUC) of 0.931 (0.908–0.950), which demonstrated the strong predictive power of the logistic regression model (Figure 2).
Table 2.
Univariate and multivariate logistic regression analysis for the development of AKI in burn patients.
| Variables | Crude OR (95% CI) | P value | Adjusted OR (95% CI) | P value |
|---|---|---|---|---|
| Age (year) | 1.025 (1.013–1.037) | <0.001 | 1.020 (1.002–1.039) | 0.027 |
| Drinking | 1.750 (1.122–2.730) | 0.013 | ||
| Hypertension | 3.401 (1.834–6.308) | <0.001 | 2.445 (0.979–6.106) | 0.055 |
| Diabetes mellitus | 3.013 (1.364–6.655) | 0.006 | ||
| Cerebrovascular disease | 20.439 (2.536–164.700) | 0.005 | ||
| Hypotension or shock on admission | 9.537 (5.694–15.973) | <0.001 | 2.476 (1.159–5.291) | 0.019 |
| Inhalation injury | 3.211 (2.215–4.653) | <0.001 | ||
| Flame burn | 1.546 (1.016–2.352) | 0.042 | ||
| Electrical burn | 0.042 (0.318–0.980) | 0.042 | ||
| TBSA (%) | 1.054 (1.044–1.064) | <0.001 | ||
| Full-thickness burn area (%) | 1.090 (1.072–1.108) | <0.001 | 1.090 (1.072–1.108) | <0.001 |
| Baseline sCr (μmol/L) | 1.047 (1.037–1.057) | <0.001 | 1.047 (1.037 ∼ 1.057) | <0.001 |
| BUN (mmol/L) | 1.243 (1.157–1.335) | <0.001 | ||
| Uric acid (μmol/L) | 1.001 (1.000–1.002) | 0.090 | ||
| Cystatin C (mg/L) | 1.007 (0.978–1.037) | 0.637 | ||
| ALT (U/L) | 1.009 (1.004–1.013) | <0.001 | ||
| AST (U/L) | 1.006 (1.004–1.009) | <0.001 | ||
| Creatine kinase (U/L) | 1.000 (1.000-1.000) | 0.001 | ||
| Albumin (g/L) | 0.921 (0.901–0.942) | <0.001 | ||
| Hemoglobin (g/L) | 1.009 (1.003–1.016) | 0.007 | ||
| Platelets (×109/L) | 1.003 (1.001–1.005) | 0.001 | ||
| WBC (×109/L) | 1.020 (1.006–1.034) | 0.005 | ||
| Lactic acidosis | 14.838 (8.122–27.108) | <0.001 | ||
| Sepsis | 21.964 (10.893–44.289) | <0.001 | 21.964 (10.893–44.289) | <0.001 |
| Rhabdomyolysis | 9.431 (6.008–14.806) | <0.001 | 9.431 (6.008–14.806) | <0.001 |
| DIC | 118.821 (16.160–873.674) | <0.001 | 118.821 (16.160–873.674) | <0.001 |
Bolded values represented P value < 0.05.
AKI: acute kidney injury; ALT: alanine aminotransferase; AST: aspartate aminotransferase; BUN: blood urea nitrogen; OR: odds ratio; 95% CI: 95% confidence interval; sCr: serum creatinine; TBSA: burned total body surface area; WBC: white blood cell; DIC: disseminated intravascular coagulation.
Multivariate analysis on AKI was adjusted for age, drinking, hypertension, DM, cerebrovascular disease, hypotension or shock on admission, inhalation injury, flame burn, electrical burn, TBSA, full-thickness burn area, baseline sCr, BUN, uric acid, Cystatin C, ALT, AST, creatine kinase, albumin, hemoglobin, platelets, WBC, lactic acidosis, sepsis, rhabdomyolysis, DIC. (Omnibus test: X2 =355.859, p < 0.001; Hosmer-Lemeshow test:X2=12.334, P value = 0.37).
Figure 2.
ROC curve analysis on multivariate logistic regression model for AKI in burn patients.
Risk factors for in-hospital mortality in patients
In Table 3, Patients who died in the hospital were more likely to have complications of lactic acidosis, sepsis, rhabdomyolysis, AKI, MODS, DIC, and mechanical ventilation and were more likely to require CRRT (p < 0.05). Furthermore, Figure 3 revealed that the in-hospital survival of AKI stage 2, and 3 were worse than that of non-AKI patients (p < 0.001). There was no significant difference in short-term survival between patients with stage 2 and stage 3 AKI after burn injury (p < 0.001).
Table 3.
Demographic and clinical characteristics of 592 burn patients.
| Variables | Non-survivor (n = 81) | Survivor (n = 511) | P value |
|---|---|---|---|
| Age, (year) | 49 (40,67) | 41 (32,49) | <0.001 |
| Sex | |||
| Female | 20 (24.7%) | 109 (21.3%) | |
| Male | 61 (75.3%) | 402 (78.7%) | |
| Smoking | 31 (38.3%) | 186 (36.4%) | 0.745 |
| Drinking | 17 (21.0%) | 85 (16.6%) | 0.335 |
| Medical history | |||
| Hypertension | 15 (18.5%) | 30 (5.9%) | <0.001 |
| COPD | 3 (3.7%) | 4 (0.8%) | 0.057 |
| Diabetes mellitus | 3 (3.7%) | 23 (4.5%) | 1.000 |
| Chronic liver disease | 3 (3.7%) | 27 (5.3%) | 0.785 |
| Cerebrovascular disease | 6 (7.4%) | 3 (0.6%) | <0.001 |
| Malignant tumor | 0 (0.0%) | 4 (0.8%) | 1.000 |
| Hypotension or shock at admission | 40 (49.4%) | 47 (9.2%) | <0.001 |
| Inhalation injury | 52 (64.2%) | 145 (28.4%) | <0.001 |
| Burn type | |||
| Flame burn | 69 (85.2%) | 361 (70.6%) | 0.006 |
| Chemical burn | 5 (6.2%) | 32 (6.5%) | 0.923 |
| Electrical burn | 6 (6.2%) | 81 (15.9%) | 0.022 |
| Scald | 1 (1.2%) | 16 (3.1%) | 0.491 |
| TBSA (%) | 75 (45,90) | 22 (13,42) | <0.001 |
| Full-thickness burn area (%) | 30 (10,50) | 5 (1,13) | <0.001 |
| Baseline sCr (μmol/L) | 97 (82,129) | 75 (63,89) | <0.001 |
| BUN (mmol/L) | 7.91 (6.32,10.52) | 5.80 (4.54,7.06) | <0.001 |
| Uric acid (μmol/L) | 348.0 (263.5,437.8) | 341.6 (268.0,415.4) | 0.341 |
| Cystatin C (mg/L) | 1.02 (0.72,1.34) | 0.75 (0.66,0.88) | <0.001 |
| ALT (U/L) | 28 (19,50) | 23 (17,36) | 0.175 |
| AST (U/L) | 78 (45,126) | 32 (24,48) | <0.001 |
| Creatine kinase (U/L) | 678 (212,2496) | 165 (103,337) | <0.001 |
| Albumin (g/L) | 29.7 (22.2,37.3) | 38.8 (31.5,42.7) | <0.001 |
| Hemoglobin (g/L) | 151 (129,180) | 155 (141,169) | 0.829 |
| Platelets (×109/L) | 204 (102,312) | 184 (135,238) | 0.111 |
| WBC (×109/L) | 22.3 (13.4,32.9) | 14.8 (10.9,19.9) | <0.001 |
| Lactic acidosis | 53 (65.4%) | 23 (4.5%) | <0.001 |
| Sepsis | 40 (49.4%) | 30 (5.9%) | <0.001 |
| Rhabdomyolysis | 54 (66.7%) | 65 (12.7%) | <0.001 |
| DIC | 33 (40.7%) | 6 (1.2%) | <0.001 |
| Mechanical ventilation | 60 (74.1%) | 74 (14.5%) | <0.001 |
| MODS | 60 (74.1%) | 6 (1.2%) | <0.001 |
| AKI | <0.001 | ||
| Stage 0 | 11 (13.6%) | 409 (80.0%) | |
| Stage 1 | 8 (9.9%) | 64 (12.5%) | |
| Stage 2 | 25 (30.9%) | 25 (4.9%) | |
| Stage 3 | 37 (45.7%) | 13 (2.5%) | |
| Need for CRRT | 30 (37.0%) | 4 (0.8%) | <0.001 |
Continuous variables are summarized as medians (25th and 75th percentiles).
Categorical variables are presented as numbers and percentages.
AKI: acute kidney injury; ALT: alanine aminotransferase; AST: aspartate aminotransferase; BUN: blood urea nitrogen; COPD: chronic obstructive pulmonary disease; CRRT: continuous renal replacement therapy; DIC: disseminated intravascular coagulation; MODS: multiple organ dysfunction syndrome; sCr: serum creatinine; TBSA: burned total body surface area; WBC: white blood cell.
Figure 3.
Kaplan-Meier Analysis for in-hospital mortality in patients with AKI.
Log-rank test P <0.001.
The univariate logistic regression analysis suggested (Table 4), even AKI stage 1 was associated with in-hospital mortality (p < 0.001). After adjusting for relevant factors, the multivariate logistic regression model showed that AKI stage 2 (OR = 4.591; p < 0.001) and AKI stage 3 (OR = 4.534; p < 0.001) were independent risk factors for in-hospital mortality. Age (OR = 1.075; p < 0.001), TBSA (OR = 1.036; p < 0.001), lactic acidosis (OR = 6.696; p < 0.001), and MODS (OR = 43.375; p < 0.001) were also shown to be independent risk factors for in-hospital mortality.
Table 4.
Univariate and multivariate logistic regression analysis for in-hospital mortality in burn patients.
| Variables | Crude OR (95% CI) | P value | Adjusted OR (95% CI) | P value |
|---|---|---|---|---|
| Age | 1.043 (1.027–1.058) | <0.001 | 1.075 (1.042–1.110) | <0.001 |
| Hypertension | 3.644 (1.863–7.129) | <0.001 | ||
| Cerebrovascular disease | 13.547 (3.317–55.318) | <0.001 | ||
| Hypotension or shock on admission | 9.632 (5.675–16.345) | <0.001 | ||
| Flame burn | 2.389 (1.257–4.540) | 0.008 | ||
| TBSA (%) | 1.061 (1.048–1.073) | <0.001 | 1.036 (1.014–1.058) | 0.001 |
| Full-thickness burn area (%) | 1.070 (1.055–1.085) | <0.001 | ||
| Baseline sCr (μmol/L) | 1.009 (1.005–1.014) | <0.001 | ||
| BUN (mmol/L) | 1.139 (1.069–1.214) | <0.001 | ||
| Cystatin C (mg/L) | 0.998 (0.952–1.046) | 0.942 | ||
| AST (U/L) | 1.002 (1.000–1.003) | 0.011 | ||
| Creatine kinase (U/L) | 1.000 (1.000–1.000) | 0.046 | ||
| Albumin (g/L) | 0.966 (0.941–0.991) | 0.009 | ||
| WBC (×109/L) | 1.011 (1.003–1.020) | 0.011 | ||
| Lactic acidosis | 40.161 (21.602–74.667) | <0.001 | 6.696 (2.310–19.407) | <0.001 |
| Mechanical ventilation | 16.873 (9.689–29.381) | <0.001 | ||
| Sepsis | 15.642 (8.839–27.681) | <0.001 | ||
| Rhabdomyolysis | 13.723 (8.076–23.320) | <0.001 | ||
| DIC | 57.865 (23.087–145.032) | <0.001 | ||
| MODS | 240.476 (93.380–619.282) | <0.001 | ||
| Non-AKI | Reference | 1.0 (reference) | ||
| AKI Stage 1 | 4.648 (1.801–11.994) | <0.001 | 0.673 (0.139–3.250) | 0.622 |
| AKI Stage 2 | 37.182 (16.441–84.088) | <0.001 | 4.591 (1.394–15.116) | 0.012 |
| AKI Stage 3 | 105.825 (44.309–252.746) | <0.001 | 4.534 (1.090–18.855) | 0.038 |
| Need for CRRT | 74.559 (25.262–220.051) | <0.001 | 43.375 (13.253–141.954) | <0.001 |
Continuous variables are summarized as medians (25th and 75th percentiles).
Categorical variables are presented as numbers and percentages.
AKI: acute kidney injury; AST: aspartate aminotransferase; BUN: blood urea nitrogen; CRRT: continuous renal replacement therapy; DIC: disseminated intravascular coagulation; MODS: multiple organ dysfunction syndrome; sCr: serum creatinine; TBSA: burned total body surface area; WBC: white blood cell; AKI: acute kidney injury; MODS: multiple organ dysfunction syndrome; TBSA: burned total body surface area.
Multivariate analysis on mortality was adjusted for age, hypertension, cerebrovascular disease, hypotension or shock on admission, TBSA, full-thickness burn area, lactic acidosis, mechanical ventilation, sepsis, rhabdomyolysis, DIC, MODS, AKI, and CRRT (Omnibus test: X2 =355.912, p < 0.001; Hosmer-Lemeshow test:X2=3.105, P value = 0.928).
Discussion
The main findings of the study were as follows: (i) The prevalence of AKI after burn injury was 29.1%, according to the KDIGO criteria definition. (ii) A considerable proportion (81.4%) of AKI patients developed renal dysfunction within 2 days of burn injury. (iii) 19.8% of AKI patients were in need of CRRT. (iv) The occurrence of AKI increased the cost of hospitalization.
Age, hypertension, hypotension or shock on admission, full-thickness burn area, baseline sCr, sepsis, rhabdomyolysis, and DIC were independently associated with an increased risk of AKI. Furthermore, AKI was independently associated with adverse outcomes with respect to the need for mechanical ventilation, the prevalence of MODS, and in-hospital mortality. 40.7% of AKI patients died during hospitalization, and AKI stages 2 and 3 were independent risk factors for in-hospital mortality.
In a previous study, 35.8% of burn patients were diagnosed with AKI within 3 days of admission according to KDIGO criteria [22]. A study of burn patients based on AKIN criteria reported a 33% prevalence of AKI [23]. Another study showed that there was no incidence of AKI in patients with mild burn injury, and the prevalence of AKI in patients with moderate and severe burn injury was 10% and 28.6%, respectively. The overall mortality rate in patients with AKI was 36.4% [24]. In the present retrospective analysis, the reported incidence of AKI in the burn population was 29.1%, which is consistent with previous findings reported in the literature. However, in the study by Clark et al. 601 of 1040 ICU patients eventually developed AKI during the hospital stay [16]. Furthermore, a study by Ho et al. found a 62.4% incidence of AKI within 7 days of burn injury [25]. A study by Depret et al. reported an incidence of AKI of 63.2%, with a 43% incidence of AKI within 7 days of burn injury [26]. In another study, which included 830 burn patients requiring mechanical ventilation, 48.2% of patients developed AKI of varying severity during hospitalization [27]. The prevalence of AKI was lower in this study compared to the above studies. The causes of this difference may be attributed to the different sources of the study population (community, hospital level, general ward, ICU), different inclusion criteria, and differences in the diagnostic criteria for AKI. Clark et al. included subjects from ICUs, and studies have shown that more than half of ICU patients develop AKI [3]. There are differences in baseline characteristics between ICU and general hospitalization patients. ICU patients are more critically ill on admission, and more comorbidities are likely to occur during their treatment. In addition, ICU monitoring and assessment of the condition of critically ill patients may be more likely to identify the occurrence of AKI.
Older age is a risk factor for AKI, as the elderly have a poorer foundation and are more likely to have comorbid chronic diseases such as hypertension and diabetes mellitus [10,25]. Besides hypertension is a well-known risk contributor to the development of AKI in critically ill patients [3,28,29]. In the absence of coexisting renal disease, patients with hypertension still have an increased risk of the development of AKI [30,31].
Meanwhile, hypotension or shock on admission has been independently associated with the development of AKI after burn injury. Some studies have indicated that perioperative hypotension is common and associated with poor outcomes including AKI [32,33]. Dramatic changes in hemodynamics in the early stages of severe burns and hypovolemia cause systemic hypotensive manifestations, affecting perfusion of tissues and organs, which leads to a decrease in GFR, leading to the development of AKI. With persistent ischemia, ischemic tubular injury may transform into tubular necrosis [34,35].
Additionally, the full-thickness burn area is a significant independent risk factor for the development of AKI after burn injury [11,36,37]. Areas and depths of burns, sex, age, and inhalation injury are essential characteristics of patients admitted with burns, which can reflect the severity of burns and illness. Although these factors cannot be altered, grading patients in terms of risk level as a predictor of the prognosis of burn patients is important in the treatment and management of after burn injury [11].
Mean sCr, estimated glomerular filtration rate, or the closest SCr measured at outpatient follow-up or within one week to one year before the onset of the disease is the best reflection of baseline renal function. In this study, burn injury is a sudden event, and the above baseline sCr may be difficult to obtain. If the above data were not available, the baseline sCr was defined as the first sCr value measured within 48 h after admission to the hospital. Baseline sCr is also a biomarker for predicting AKI [38–40]. Higher baseline sCr values can predict chronic kidney disease after acute kidney injury [41]. A prospective cohort study revealed that sCr >1.1 mg/dl within 48 h of admission was independently associated with the occurrence of AKI [38]. It is noteworthy that the limitations in the definition of baseline sCr in acute burn patients may exert a non-negligible impact on the assessment of AKI. The currently commonly used standard definitions, namely the first sCr measured upon admission and the lowest sCr within 7 days prior to admission, both have biases in acute burn patients due to the dilution effect of fluid resuscitation. The first sCr measured upon admission may overestimate the baseline level due to hemoconcentration or muscle breakdown before resuscitation, which may further overestimate the incidence of AKI or erroneously upgrade its staging, such as misclassifying actually AKI Stage 1 as Stage 2. In contrast, the lowest sCr within 7 days prior to admission may underestimate the baseline level due to fluid dilution, thereby possibly underestimating the incidence of AKI or erroneously downgrading its staging, for example, misclassifying actually Stage 2 AKI as Stage 1. Both situations carry the risk of misclassification: the former may misclassify the transient creatinine fluctuations related to resuscitation as AKI, while the latter may mask the true extent of early renal injury, which in turn may lead to deviations in the results of correlation analysis between AKI and clinical variables. Due to the inherent difficulties in obtaining baseline data of acute burn patients, most of them lack creatinine records during the stable period before injury, and there is currently no better alternative. This issue is not unique to this study but a common methodological challenge in the field of burn nephropathy. Future studies can explore alternative approaches such as combining pre-injury estimated glomerular filtration rate and dynamically monitoring the trend of creatinine changes to optimize the assessment, so as to more accurately evaluate AKI in acute burn patients.
One study demonstrated that for every 10-fold increase in peak CK after burn injury, the incidence of AKI would increase by 70% and the mortality rate by nearly 50% [42]. In previous study that included 128 patients admitted to the ICU for burn injury, rhabdomyolysis was independently associated with the development of early AKI [36]. In another retrospective analysis that included burn patients for almost 10 years, rhabdomyolysis occurred in almost half of the patients with electrocution injuries and was strongly associated with the need for RRT [43]. Therefore, the timely diagnosis and treatment of rhabdomyolysis after a burn injury may be a key point in preventing the occurrence of AKI.
In patients with burn TBSA >20%, the incidence of sepsis ranges from 3% to 30% [44]. Several studies have shown that the presence of sepsis as well as septic shock is closely associated with the development of AKI [10,45]. Sepsis is a major trigger for the development of AKI in critically ill patients. Sepsis-associated AKI is a prevalent clinical syndrome in ICU, contributing to about half of the incidence of AKI from all causes [46]. DIC occurrence remained strongly associated with severe acute kidney injury in patients with septic shock [47]. Our study also indicated an independent associated between DIC and burn-related AKI.
Consistent with studies in other burn injury populations [9,48], in-hospital mortality was much higher in patients with AKI (40.7%) than in patients without AKI (2.6%) in the present study. Mosier et al. found that AKI occurred within 24 h of burn injury predicted further deterioration of renal function and higher mortality in the future, and that the mortality rate was higher in patients with early AKI compared to patients with non-AKI (36% vs. 13%) [49]. In the study by Kuo et al. the mortality rate of patients with AKI after burn injury was 50.9%, which was about seven times higher than that of patients with non-AKI, and the occurrence of AKI was predictive of death in the burned population [22]. Postoperative AKI also constituted a substantial risk factor for major adverse kidney events occurring within 30 days after burn surgery, encompassing death, the initiation of new renal replacement therapy, and the persistence of prolonged renal dysfunction [50]. In addition, patients with AKI had a significantly higher 90-day mortality rate than patients with non-AKI [51]. In conclusion, patients with AKI after burn injury have a high mortality rate and a poor prognosis.
Study limitations
Although the KDIGO criteria are useful for the diagnosis of AKI after burns, the use of UO and sCr criteria in burn patients is limited [14], the prevalence of AKI may still be underestimated. Changes in sCr levels can be delayed from the reality of renal dysfunction and recovery, and sCr levels may not rise rapidly despite the fact that renal injury has already occurred. UO is not sensitive in the diagnosis of AKI [52]. In patients with severe burn injury, UO can be relatively normal due to varying degrees of fluid resuscitation, especially in the early stages of kidney injury. Furthermore, UO may not be taken seriously clinically. As this is a retrospective study, specific urine output was not collected, making it impossible to accurately count the number of AKI cases diagnosed solely based on urine output criteria (particularly Stage 1). In subsequent studies, we will improve the data collection process by systematically recording hourly urine output to more strictly adhere to the KDIGO criteria.The diagnosis of AKI is not easy. Considering the lack of obvious signs and symptoms in the development of early AKI and the limitations of UO and sCr in the diagnosis of early AKI, it is crucial to explore novel biomarkers for the assessment of AKI. In addition, the relationship between AKI and long-term outcomes of patients was not analyzed in this study due to the change and absence of patient contact information, and long-term follow-up data of patients were not obtained.
Conclusion
AKI occurred in 29.1% of burn patients. AKI was associated with increased mortality and health care costs. Age, hypotension or shock on admission, full-thickness burn area, baseline sCr, sepsis, rhabdomyolysis, and DIC can lead to an increased risk of AKI. AKI stage 2 and 3 are independently associated with in-hospital mortality.
Acknowledgments
Each author contributed to the article and approved the submitted version.
Funding Statement
This study was supported by the Science and Technology Planning Project of Sichuan Province [grant numbers 2023YFH0031].
Disclosure statement
No potential conflict of interest was reported by the author(s).
Ethical approval
This project was authorized by the Biomedical Ethics Committee of West China Hospital of Sichuan University (Approved No. 1000, 2022).
Informed consent
Individual informed consent was waived given that the study was retrospective.
Data availability statement
The datasets are available from the corresponding author on reasonable request.
References
- 1.Section 2: AKI Definition. Kidney Int Suppl. 2011;2(1):19–36. doi: 10.1038/kisup.2011.32. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Ronco C, Bellomo R, Kellum JA.. Acute kidney injury. Lancet. 2019;394(10212):1949–1964. doi: 10.1016/S0140-6736(19)32563-2. [DOI] [PubMed] [Google Scholar]
- 3.Hoste EA, Bagshaw SM, Bellomo R, et al. Epidemiology of acute kidney injury in critically ill patients: the multinational AKI-EPI study. Intensive Care Med. 2015;41(8):1411–1423. doi: 10.1007/s00134-015-3934-7. [DOI] [PubMed] [Google Scholar]
- 4.See EJ, Jayasinghe K, Glassford N, et al. Long-term risk of adverse outcomes after acute kidney injury: a systematic review and meta-analysis of cohort studies using consensus definitions of exposure. Kidney Int. 2019;95(1):160–172. doi: 10.1016/j.kint.2018.08.036. [DOI] [PubMed] [Google Scholar]
- 5.Lewington AJ, Cerdá J, Mehta RL.. Raising awareness of acute kidney injury: a global perspective of a silent killer. Kidney Int. 2013;84(3):457–467. doi: 10.1038/ki.2013.153. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Lameire NH, Bagga A, Cruz D, et al. Acute kidney injury: an increasing global concern. Lancet. 2013;382(9887):170–179. doi: 10.1016/S0140-6736(13)60647-9. [DOI] [PubMed] [Google Scholar]
- 7.Al-Jaghbeer M, Dealmeida D, Bilderback A, et al. Clinical decision support for in-hospital AKI. J Am Soc Nephrol. 2018;29(2):654–660. doi: 10.1016/S0140-6736(13)60647-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Mehta RL, Cerdá J, Burdmann EA, et al. International society of nephrology’s 0by25 initiative for acute kidney injury (zero preventable deaths by 2025): a human rights case for nephrology. Lancet. 2015;385(9987):2616–2643. doi: 10.1016/S0140-6736(15)60126-X. [DOI] [PubMed] [Google Scholar]
- 9.Brusselaers N, Monstrey S, Colpaert K, et al. Outcome of acute kidney injury in severe burns: a systematic review and meta-analysis. Intensive Care Med. 2010;36(6):915–925. doi: 10.1007/s00134-010-1861-1. [DOI] [PubMed] [Google Scholar]
- 10.Folkestad T, Brurberg KG, Nordhuus KM, et al. Acute kidney injury in burn patients admitted to the intensive care unit: a systematic review and meta-analysis. Crit Care. 2020;24(1):2. doi: 10.1186/s13054-019-2710-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Wu G, Xiao Y, Wang C, et al. Risk factors for acute kidney injury in patients with burn injury: a meta-analysis and systematic review. J Burn Care Res. 2017;38(5):271–282. doi: 10.1097/BCR.0000000000000438. [DOI] [PubMed] [Google Scholar]
- 12.Legrand M, Clark AT, Neyra JA, et al. Acute kidney injury in patients with burns. Nat Rev Nephrol. 2024;20(3):188–200. doi: 10.1038/s41581-023-00769-y. [DOI] [PubMed] [Google Scholar]
- 13.Uchino S, Kellum JA, Bellomo R, et al. Acute renal failure in critically ill patients: a multinational, multicenter study. JAMA. 2005;294(7):813–818. doi: 10.1001/jama.294.7.813. [DOI] [PubMed] [Google Scholar]
- 14.Clark A, Neyra JA, Madni T, et al. Acute kidney injury after burn. Burns. 2017;43(5):898–908. doi: 10.1016/j.burns.2017.01.023. [DOI] [PubMed] [Google Scholar]
- 15.Colpaert K, Hoste EA.. Acute kidney injury in burns: a story of volume and inflammation. Crit Care. 2008;12(6):192. doi: 10.1186/cc7106. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Clark AT, Li X, Kulangara R, et al. Acute kidney injury after burn: a cohort study from the parkland burn intensive care unit. J Burn Care Res. 2019;40(1):72–78. doi: 10.1093/jbcr/iry046. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Rodrigues FB, Bruetto RG, Torres US, et al. Incidence and mortality of acute kidney injury after myocardial infarction: a comparison between KDIGO and RIFLE criteria. PLoS One. 2013;8(7):e69998. doi: 10.1371/journal.pone.0069998. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Luo X, Jiang L, Du B, et al. A comparison of different diagnostic criteria of acute kidney injury in critically ill patients. Crit Care. 2014;18(4):R144. doi: 10.1186/cc13977. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Forni LG, Darmon M, Ostermann M, et al. Renal recovery after acute kidney injury. Intensive Care Med. 2017;43(6):855–866. doi: 10.1007/s00134-017-4809-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Stahl K, Rastelli E, Schoser B.. A systematic review on the definition of rhabdomyolysis. J Neurol. 2020;267(4):877–882. doi: 10.1007/s00415-019-09185-4. [DOI] [PubMed] [Google Scholar]
- 21.Yoshino Y, Ohtsuka M, Kawaguchi M, et al. The wound/burn guidelines - 6: guidelines for the management of burns. J Dermatol. 2016;43(9):989–1010. doi: 10.1111/1346-8138.13288. [DOI] [PubMed] [Google Scholar]
- 22.Kuo G, Yang SY, Chuang SS, et al. Using acute kidney injury severity and scoring systems to predict outcome in patients with burn injury. J Formos Med Assoc. 2016;115(12):1046–1052. doi: 10.1016/j.jfma.2016.10.012. [DOI] [PubMed] [Google Scholar]
- 23.Chung KK, Stewart IJ, Gisler C, et al. The Acute Kidney Injury Network (AKIN) criteria applied in burns. J Burn Care Res. 2012;33(4):483–490. doi: 10.1097/BCR.0b013e31825aea8d. [DOI] [PubMed] [Google Scholar]
- 24.Ren H, Zhou X, Dai D, et al. Assessment of urinary kidney injury molecule-1 and interleukin-18 in the early post-burn period to predict acute kidney injury for various degrees of burn injury. BMC Nephrol. 2015;16(1):142. doi: 10.1186/s12882-015-0140-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Ho G, Camacho F, Rogers A, et al. Early acute kidney injury following major burns. J Burn Care Res. 2021;42(2):126–134. doi: 10.1093/jbcr/iraa215. [DOI] [PubMed] [Google Scholar]
- 26.Dépret F, Boutin L, Jarkovský J, et al. Prediction of major adverse kidney events in critically ill burn patients. Burns. 2018;44(8):1887–1894. doi: 10.1016/j.burns.2018.08.007. [DOI] [PubMed] [Google Scholar]
- 27.Clemens MS, Stewart IJ, Sosnov JA, et al. Reciprocal risk of acute kidney injury and acute respiratory distress syndrome in critically ill burn patients. Crit Care Med. 2016;44(10):e915-22–e922. doi: 10.1097/CCM.0000000000001812. [DOI] [PubMed] [Google Scholar]
- 28.Levey AS, James MT.. Acute kidney injury. Ann Intern Med. 2017;167(9):ITC66–ITC80. Erratum in: Ann Intern Med. 2018 Jan 2;168(1:84. doi:10.7326/L17-0682. doi: 10.7326/AITC201711070. [DOI] [PubMed] [Google Scholar]
- 29.Søvik S, Isachsen MS, Nordhuus KM, et al. Acute kidney injury in trauma patients admitted to the ICU: a systematic review and meta-analysis. Intensive Care Med. 2019;45(4):407–419. doi: 10.1007/s00134-019-05535-y. [DOI] [PubMed] [Google Scholar]
- 30.James MT, Grams ME, Woodward M, et al. A meta-analysis of the association of estimated gfr, albuminuria, diabetes mellitus, and hypertension with acute kidney injury. Am J Kidney Dis. 2015;66(4):602–612. doi: 10.1053/j.ajkd.2015.02.338. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Mahmoodi BK, Matsushita K, Woodward M, et al. Associations of kidney disease measures with mortality and end-stage renal disease in individuals with and without hypertension: a meta-analysis. Lancet. 2012;380(9854):1649–1661. doi: 10.1016/S0140-6736(12)61272-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Lankadeva YR, May CN, Bellomo R, et al. Role of perioperative hypotension in postoperative acute kidney injury: a narrative review. Br J Anaesth. 2022;128(6):931–948. doi: 10.1016/j.bja.2022.03.002. [DOI] [PubMed] [Google Scholar]
- 33.Maheshwari K, Turan A, Mao G, et al. The association of hypotension during non-cardiac surgery, before and after skin incision, with postoperative acute kidney injury: a retrospective cohort analysis. Anaesthesia. 2018;73(10):1223–1228. doi: 10.1111/anae.14416. [DOI] [PubMed] [Google Scholar]
- 34.Eriksson M, Brattström O, Mårtensson J, et al. Acute kidney injury following severe trauma: risk factors and long-term outcome. J Trauma Acute Care Surg. 2015;79(3):407–412. doi: 10.1097/TA.0000000000000727. [DOI] [PubMed] [Google Scholar]
- 35.Kellum JA, Romagnani P, Ashuntantang G, et al. Acute kidney injury. Nat Rev Dis Primers. 2021;7(1):52. doi: 10.1038/s41572-021-00284-z. [DOI] [PubMed] [Google Scholar]
- 36.Chen B, Zhao J, Zhang Z, et al. Clinical characteristics and risk factors for severe burns complicated by early acute kidney injury. Burns. 2020;46(5):1100–1106. doi: 10.1016/j.burns.2019.11.018. [DOI] [PubMed] [Google Scholar]
- 37.Hong DY, Lee JH, Park SO, et al. Plasma neutrophil gelatinase-associated lipocalin as early biomarker for acute kidney injury in burn patients. J Burn Care Res. 2013;34(6):e326-32–e332. doi: 10.1097/BCR.0b013e31827d1f36. [DOI] [PubMed] [Google Scholar]
- 38.Yang HT, Yim H, Cho YS, et al. Assessment of biochemical markers in the early post-burn period for predicting acute kidney injury and mortality in patients with major burn injury: comparison of serum creatinine, serum cystatin-C, plasma and urine neutrophil gelatinase-associated lipocalin. Crit Care. 2014;18(4):R151. doi: 10.1186/cc13989. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Kym D, Cho YS, Yoon J, et al. Evaluation of diagnostic biomarkers for acute kidney injury in major burn patients. Ann Surg Treat Res. 2015;88(5):281–288. doi: 10.4174/astr.2015.88.5.281. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Rakkolainen I, Vuola J.. Plasma NGAL predicts early acute kidney injury no earlier than s-creatinine or cystatin C in severely burned patients. Burns. 2016;42(2):322–328. doi: 10.1016/j.burns.2015.11.006. [DOI] [PubMed] [Google Scholar]
- 41.James MT, Pannu N, Hemmelgarn BR, et al. Derivation and External Validation of Prediction Models for Advanced Chronic Kidney Disease Following Acute Kidney Injury. JAMA. 2017;318(18):1787–1797. doi: 10.1001/jama.2017.16326. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Stewart IJ, Cotant CL, Tilley MA, et al. Association of rhabdomyolysis with renal outcomes and mortality in burn patients. J Burn Care Res. 2013;34(3):318–325. doi: 10.1097/BCR.0b013e31825addbd. [DOI] [PubMed] [Google Scholar]
- 43.Rakkolainen I, Lindbohm JV, Vuola J.. Factors associated with acute kidney injury in the Helsinki Burn Centre in 2006-2015. Scand J Trauma Resusc Emerg Med. 2018;26(1):105. doi: 10.1186/s13049-018-0573-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Dvorak JE, Ladhani HA, Claridge JA.. Review of sepsis in Burn Patients in 2020. Surg Infect (Larchmt). 2021;22(1):37–43. doi: 10.1089/sur.2020.367. [DOI] [PubMed] [Google Scholar]
- 45.Palmieri T, Lavrentieva A, Greenhalgh D.. An assessment of acute kidney injury with modified RIFLE criteria in pediatric patients with severe burns. Intensive Care Med. 2009;35(12):2125–2129. doi: 10.1007/s00134-009-1638-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Bellomo R, Kellum JA, Ronco C, et al. Acute kidney injury in sepsis. Intensive Care Med. 2017;43(6):816–828. doi: 10.1007/s00134-017-4755-7. [DOI] [PubMed] [Google Scholar]
- 47.Helms J, Merdji H, Loewert S, et al. Disseminated intravascular coagulation is strongly associated with severe acute kidney injury in patients with septic shock. Ann Intensive Care. 2023;13(1):119. doi: 10.1186/s13613-023-01216-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Martins J, Nin N, Muriel A, et al. Early acute kidney injury is associated with in-hospital adverse outcomes in critically ill burn patients: an observational study. Nephrol Dial Transplant. 2023;38(9):2002–2008. doi: 10.1093/ndt/gfac339. [DOI] [PubMed] [Google Scholar]
- 49.Mosier MJ, Pham TN, Klein MB, et al. Early acute kidney injury predicts progressive renal dysfunction and higher mortality in severely burned adults. J Burn Care Res. 2010;31(1):83–92. doi: 10.1097/BCR.0b013e3181cb8c87. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Yu J, Seo YJ, Lee SK, et al. Postoperative acute kidney injury and risk factors for major adverse kidney events within 30 days of burn surgery. Burns. 2025;51(6):107533. doi: 10.1016/j.burns.2025.107533. [DOI] [PubMed] [Google Scholar]
- 51.Kim HY, Kong YG, Park JH, et al. Acute kidney injury after burn surgery: preoperative neutrophil/lymphocyte ratio as a predictive factor. Acta Anaesthesiol Scand. 2019;63(2):240–247. doi: 10.1111/aas.13255. [DOI] [PubMed] [Google Scholar]
- 52.Haase M, Kellum JA, Ronco C.. Subclinical AKI–an emerging syndrome with important consequences. Nat Rev Nephrol. 2012;8(12):735–739. doi: 10.1038/nrneph.2012.19. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets are available from the corresponding author on reasonable request.