Lactate, lactate clearance, and lactate-to-albumin ratio in predicting mortality in patients with critical polytrauma: A retrospective observational study

Abstract

Lactate is a product of anaerobic metabolism used to determine prognosis in critically ill trauma patients. This study investigates the mortality-predictive performance of lactate, lactate clearance, and lactate-to-albumin ratio (LAR) on admission in patients with polytrauma in a tertiary center’s intensive care unit (ICU). Polytrauma patients in the ICU between June 2019 and June 2022 were evaluated. The diagnosis of polytrauma was made according to the Berlin criteria, a widely accepted and comprehensive system for classifying the severity of multiple injuries. Patients were classified into survivor and mortality groups. The predictive performance of lactate, lactate clearance (24th hour), and LAR for 28-day mortality was compared. The study included 176 patients. The median age of the entire population was 35 (24–50) years, and 78.4% (n = 138) were male. Motor vehicle accidents were the most common cause of polytrauma in patients (48.9%, n = 86). The most common head injuries were detected in the patients (59.1%, n = 104). In the mortality group, median lactate and lactate (24th hour) levels were significantly higher (P < .001). Median albumin and LAR values were significantly lower (P < .001). Although 24-hour lactate clearance was lower in the mortality group, no significant difference was detected (36.1% vs 42.3%, P = .052). In multivariate regression analysis, LAR was an independent predictor of mortality (P < .001). In receiver operating characteristics curve analysis, the cutoff value of lactate was ≥5.4, the area under the curve (AUC) was 0.75 (95% confidence interval [CI], 0.66–0.84), the cutoff value of lactate clearance was ≤39.2, AUC was 0.60, (95% CI, 0.51–0.69), and the cutoff value of LAR was value ≥1.50, AUC 0.83 (95% CI, 0.75–0.90). In critically ill polytrauma patients, LAR on ICU admission is an independent predictor of mortality and has acceptable prognostic value. LAR is superior to lactate and 24-hour lactate clearance in predicting mortality.

1. Introduction

Trauma, the result of acute injuries from mechanical, thermal, electrical, or chemical energy exposure, is a matter of grave concern. The Berlin definition of polytrauma is having an abbreviated injury score (AIS) ≥3 for 2 or more different body parts and having at least 1 or more of 5 physiological parameters. These 5 parameters were defined as Glasgow coma scale (GCS) score ≤ 8, systolic blood pressure ≤ 90 mm Hg, partial thromboplastin time ≥ 40 seconds, international normalized ratio ≥ 1.4, and age ≥ 70 years.^[1] The abdomen, head, and thorax are the most frequently affected areas in patients with polytrauma, constituting a significant portion of the patients who require intensive care.^[2] It is important to note that trauma is the most common cause of death in young adults, with mortality rates as high as 45% reported in severe trauma cases.^[3]

Various scores have been developed to rapidly determine the severity of injury, perform triage, provide appropriate treatment, and predict prognosis in critically ill trauma patients. In critically ill trauma patients followed in the intensive care unit (ICU), GCS, acute physiology and chronic disease evaluation-II (APACHE-II), injury severity score (ISS), and revised trauma score (RTS) have been reported to predict prognosis.^[4–6] However, it is crucial to acknowledge the significant challenges in determining prognosis in polytrauma patients with high mortality rates within the first 24 hours. The metabolic response to trauma leads to hypoxia and anaerobic metabolism, and lactate is released. It has been reported that serum lactate level, an indicator of tissue hypoperfusion, is associated with poor prognosis and mortality in many clinical conditions, such as chronic obstructive pulmonary disease, sepsis, trauma, and pediatric and adult traumatic brain injury.^[6–9] However, serum lactate levels can be affected by many conditions, such as decreased hepatic lactate clearance, sepsis, chronic diseases, decreased renal excretion after decreased renal function, and thiamin deficiency. These conditions may limit the prognostic use of lactate.^[10] Since serum lactate levels can be affected by various conditions, lactate-to-albumin ratio (LAR) and lactate clearance have recently helped predict mortality in different clinical conditions.^[10,11]

This study aimed to evaluate critically ill polytrauma patients in the tertiary center’s ICU and compare the performances of lactate, 24-hour lactate clearance, and LAR in predicting 28-day mortality.

2. Materials and methods

This retrospective observational study was started after receiving approval from the clinical trials review board and ethics committee of the University of Health Sciences Turkiye, Istanbul Kanuni Sultan Süleyman Training and Research Hospital (date: March 20, 2023, KAEK/2023.03.37). The study was conducted following the principles of the Declaration of Helsinki. Polytrauma patients who were followed up in Istanbul Kanuni Sultan Süleyman Training and Research Hospital ICU for 3 years between June 2019 and June 2022 were accessed through medical records. The diagnosis of polytrauma was made according to the Berlin criteria.

Inclusion criteria are as follows:

1. Age ≥ 18 years.

2. Diagnosis of polytrauma according to Berlin criteria.

3. Admitted to ICU within 24 hours after trauma.

4. Lactate level in arterial blood gas > 2.5 mmol/L.

Exclusion criteria included (1) performing cardiopulmonary resuscitation after trauma, (2) being pregnant, (3) having severe hepatorenal disease, (4) transferring from another healthcare institution, and (5) missing data.

Our analysis was comprehensive, covering a wide range of data, including demographic data, trauma sites, trauma etiology, length of stay in ICU and mechanical ventilation, other clinical characteristics, and 28-day mortality. GCS, APACHE-II, RTS, and ISS (ISS = sum of squares of AIS scores of the 3 trauma regions with the highest AIS scores) of polytrauma patients during ICU admission were analyzed according to groups. Patients were classified into the mortality and survivor groups according to their 28-day mortality. Patient data were accessed through the hospital medical record system and patient files.

2.1. Lactate, 24th hour lactate clearance, and lactate-to-albumin ratio

Serum lactate and albumin values were obtained from the blood results of all patients upon admission to the ICU. The Anesthesiology and Reanimation departments provide adult ICU services in our hospital, which has 50 beds. In patients with critical polytrauma, lactate levels are measured from arterial blood gas values at admission and the 24th hour. LAR was obtained from lactate/albumin values. Lactate clearance of the patients included in the study at the 24th hour was calculated, a practical tool for assessing patient response to treatment. Lactate clearance = (lactate at admission ‐ lactate at 24th hour)/lactate at admission × 100 was obtained from the formula.

2.2. Sample size

The G* Power 3.1 program was used to determine the sample size. Our study’s primary outcome is to compare the predictive LAR and lactate clearance values for mortality in patients with polytrauma. A total of 140 patients were calculated to be included in the study to obtain 80% power for t tests with P < .05 and an effect size of 0.5. All patients who were followed up in the ICU and diagnosed according to the Berlin criteria during the 3 years between the relevant dates were included in the study.

2.3. Statistical analysis

Statistical analysis was performed using the SPSS 26.0 (SPSS Inc., Chicago, IL) program. Before proceeding with the analyses, the data were checked, and the normality assumptions of continuous variables were examined in the following process. Shapiro–Wilks test and histogram were used to analyze the normality of continuous variables. Categorical variables are expressed as frequency and percentage, and continuous variables are expressed as median and interquartile range (Q1–Q3). Pearson Chi-square test and Fisher exact test were used to analyze categorical data between groups. An analysis of continuous data that did not show normal distribution between groups was performed using the Mann–Whitney U test. Receiver operating characteristics (ROC) curve analysis was performed to determine the mortality prediction performances of physiological scores and biomarkers (APACHE-II, GCS, LAR, ISS, RTS, albumin, and lactate) that differed significantly between groups. Youden index (sensitivity + specificity ‐ 1) was used to determine ideal cutoff values in ROC analysis. Multivariate regression analysis was used to determine whether lactate, lactate clearance, and LAR values were independent predictors of mortality. The significance level was accepted as P < .05.

3. Results

One hundred seventy-six polytrauma patients were included in the study (Fig. 1). The median age in the entire population was 35 (24–50) years, and 78.4% (n = 138) of the patients were male. Emergency surgery was performed on 39.2% (n = 69) of the patients who applied to the emergency department due to polytrauma. The mortality rate was found to be significantly higher in polytrauma patients who underwent emergency surgery (54.1% vs 35.3%, P = .037). Blunt trauma was detected in 92.6% of the patients (n = 163). The median length of stay in the ICU was 7 (4–12) days in the survivor group and 14 (5–20) days in the mortality group. Demographic data and trauma types were similar between groups (Table 1).

Figure 1.

Flow chart of the study.

Table 1.

Demographic data and some clinical characteristics of polytrauma patients.

	Overall	Group survivor	Group mortality	P
	(n = 176)	(n = 139)	(n = 37)
Age (years)	35 (24–50)	33 (23–50)	40 (27–53)	.425
Sex, n (%)				.649
Female	38 (21.6)	29 (20.9)	9 (24.3)
Male	138 (78.4)	110 (79.1)	28 (75.7)
Trauma type, n (%)				1.000
Blunt	163 (92.6)	128 (92.1)	35 (94.6)
Penetrating	13 (7.4)	11 (7.9)	2 (5.4)
Duration of ICU (days)	7 (5–14)	7 (4–12)	14 (5–20)	.007
Duration of Mv (days)	2 (0–7)	0 (0–3)	8 (5–25)	<.001
Accepted unit, n (%)				.037
Emergency room	107 (60.8)	90 (64.7)	17 (45.9)
Operating theater	69 (39.2)	49 (35.3)	20 (54.1)
GCS	9 (5–12)	10 (7–13)	3 (3–5)	<.001
APACHE-II	16 (10–22)	14 (9–19)	27 (22–30)	<.001
RTS	2 (2–3)	2 (2–3)	2 (1–2)	<.001
ISS	25 (18–27)	18 (18–27)	41 (25–41)	<.001
Lactate (mmol/L)	3.8 (2.9–5.6)	3.6 (2.8–4.8)	5.9 (3.7–9.6)	<.001
Lactate (24 hours) (mmol/L)	2.4 (1.5–3.6)	1.9 (1.4–3.1)	3.2 (2.4–4.8)	<.001
Lactate clearance (24 h)	38.4 (27–55.9)	42.3 (27.9–57.6)	36.1 (22.1–47.1)	.052
Albumin (g/dL)	3.6 (3.1–4.1)	3.8 (3.3–4.2)	3.0 (2.0–3.7)	<.001
LAR	1.0 (0.8–1.7)	0.9 (0.7–1.4)	2.0 (1.1–3.5)	<.001

Data are expressed as number of patients, percentage and median (interquartile range = Q1–Q3).

APACHE-II = acute physiology and chronic health assessment-II, GCS = Glasgow coma scale, ICU = intensive care unit, ISS = injury severity score, LAR = Laktat-to- albumin ratio, Mv = mechanical ventilation, RTS = revised trauma score.

In the mortality group, median GCS and RTS scores were significantly lower, and APACHE-II and ISS scores were significantly higher (P < .001 for all). Median lactate values at the time of admission to ICU were significantly higher in the mortality group than in the survivor group [(5.9 (3.7–9.6) vs 3.6 (2.8–4.8), P < .001)]. Lactate levels at the 24th hour were also significantly higher in the mortality group (P < .001). Median lactate clearance at 24 hours was lower in the mortality group but did not differ significantly (36.1% vs 42.3%, P = .052). Median albumin levels in the mortality group were significantly lower than in the survivor group (3.0 vs 3.8 g/dL, P < .001). Median LAR values were significantly higher in the mortality group [2.0 (1.1–3.5) vs 0.9 (0.7–1.4), P < .001)] (Table 1).

The most common causes of polytrauma in the entire population are motor vehicle accidents (48.9%, n = 86), falls (36.4%, n = 64), and assaults (5.1%, n = 9) (Table 2).

Table 2.

Trauma etiologies of patients with polytrauma.

	Overall	Group survivor	Group mortality
	(n = 176)	(n = 139)	(n = 37)
Motor vehicle crash	86 (48.9)	66 (47.5)	20 (54.1)
Fall	64 (36.4)	49 (35.3)	15 (40.5)
Fight/battering	9 (5.1)	9 (6.5)	0
Work accidents, crush	4 (2.3)	4 (2.9)	0
Gunshot wounds/explosions	10 (5.7)	8 (5.8)	2 (5.4)
Stab wounds	4 (2.3)	4 (2.9)	0

Values are expressed as the number of patients and percentage.

In patients with polytrauma, the most common (59.1%, n = 104) head injuries (epidural, subdural, subarachnoid, intraparenchymal hemorrhages, cerebral contusion, linear fractures) and (36.9%, n = 65) extremity injuries were detected (Table 3).

Table 3.

Injury patterns of polytrauma patients.

	Polytrauma patients
	(n = 176)
	n	%
Head injuries	104	59.1
Extremity injuries	65	36.9
Maxillofacial injuries	58	32.9
Pneumothorax, hemopneumothorax, contusion	51	28.9
Pelvic injuries	32	18.2
Rib fracture	24	13.6
Spine injury	22	12.5
Hepatic, splenic, renal injuries	18	10.2
Gastrointestinal injuries	15	8.5
Clavicle, scapula, sternum fractures	14	7.9

Values are expressed as the number of patients and percentage.

In the ROC curve analysis of physiological scores and biomarkers that showed significant differences between groups, a cutoff value of APACHE-II ≥ 20.5 and area under the curve (AUC) = 0.92 (95% confidence interval [CI], 0.88–0.96), a cutoff value of GCS ≤ 5.5 and AUC = 0.85 (95% CI, 0.78–0.92), a cutoff value of ISS ≥ 33, and AUC = 0.80 (95% CI, 0.70–0.88), the cutoff value of RTS was ≤2.5 and AUC = 0.78 (95% CI, 0.69–0.86).

Cutoff value of LAR ≥ 1.50 and AUC = 0.83 (95% CI, 0.75–0.90), cutoff value of albumin ≤ 3.15 and AUC = 0.77 (95% CI, 0.69–0.86), cutoff value of lactate ≥ 5.4 mmoL and AUC = 0.75 (95% CI, 0.66–0.84), and the cutoff value of LC was ≥ 39.2 and AUC = 0.60 (95% CI, 0.51–0.69) (Table 4).

Table 4.

Prognostic performances of scores and biomarkers in predicting mortality.

	Cutoff	Sensitivity	Specificity	AUC (95% CI)	P
Scores
APACHE-II	20.5	0.87	0.83	0.92 (0.88–0.96)	<.001
GCS	5.5	0.86	0.78	0.85 (0.78–0.92)	<.001
ISS	33	0.62	0.91	0.80 (0.70–0.88)	<.001
RTS	2.5	0.92	0.48	0.78 (0.69–0.86)	<.001
Biomarkers
LAR	1.50	0.68	0.81	0.83 (0.75–0.90)	<.001
Albumin (g/dL)	3.15	0.60	0.81	0.77 (0.69–0.86)	<.001
Lactate (mmol/L)	5.4	0.62	0.82	0.75 (0.66–0.84)	.001
Lactate clearance	39.2	0.70	0.53	0.60 (0.51–0.69)	.052

APACHE-II = acute physiology and chronic health assessment-II, AUC = area under curve, GCS = Glasgow coma scale, ISS = injury severity score, LAR = Lakat-to-albumin ratio, RTS = revised trauma score.

In the multivariate regression analysis of biomarkers helpful in predicting mortality, LAR during ICU admission in patients with polytrauma was found to be an independent predictor of mortality (P < .001) (Table 5).

Table 5.

Multivariate logistic regression analysis in predicting mortality.

Variables	OR	95% CI (min–max)	P
Lactate	1.128	0.803–1.585	.194
Lactate clearance	1.015	0.994–1.035	.100
LAR	0.176	0.074–0.419	<.001
Constant	20.378		<.001

CI = confidence interval (minimum–maximum), LAR = Laktat-to-albumin ratio, OR = odds ratio.

4. Discussion

In this study evaluating patients with polytrauma, it was determined that the LAR value obtained from blood samples on admission was an independent predictor of mortality and had an acceptable prognostic value. LAR was superior to lactate and lactate clearance in predicting mortality in this patient group. In addition, it was determined that LAR values had a prognostic value similar to APACHE-II, GCS, ISS, and RTS scores, which are used to determine prognosis in trauma patients in the ICU.

Due to the increase in high-energy traumas worldwide, the number of patients with polytrauma has increased. Understanding the most common etiological causes of polytrauma, such as traffic accidents, falls, and gunshot wounds.^[12] It has been reported that polytrauma is more common in young men, the head area is most frequently affected, and the majority of traumas are blunt trauma.^[12,13] In our study, the most common causes of polytrauma were motor vehicle accidents (48.9%) and falls (36.4%). Polytraumas were primarily detected in young (median age 35 years) men (78.4%). The most common trauma site was the head region (59.1%), and the majority of traumas were blunt trauma (92.6%). Freitas et al^[13] reported that age and gender did not affect mortality in patients with polytrauma. The current study found similar results, suggesting that the causes of polytrauma may vary depending on the development level of the countries and the characteristics of the trauma patients accepted by the health institutions.

Various scoring systems are used in critically ill patients in the ICU. Scoring systems help determine prognosis and prevent mortality by allowing aggressive treatment planning. The literature reports that GCS and APACHE-II can predict prognosis in both trauma and non-trauma critical patients, and RTS and ISS can predict prognosis in critical trauma patients.^{[5,6,13–15]} It has been reported that GCS and RTS scores were significantly lower, and APACHE-II scores were higher in trauma patients with mortality.^[5] Lee et al^[15] stated that median ISS scores were significantly higher in TBI patients with mortality. In our study, GCS and RTS scores were significantly lower in the mortality group, and APACHE-II and ISS scores were significantly higher.

Resuscitation in trauma and critically ill patients is a complex task. In the care of patients with polytrauma, it is crucial to recognize and treat bleeding early, limit the consequences of hypovolemic shock, and diagnose traumatic injuries. Lactate, a product of anaerobic metabolism, plays a pivotal role in evaluating the effectiveness of treatment in these patients. The serum lactate level is a crucial indicator of microcirculatory dysfunction.^[16] Lactate levels have been reported to be associated with injury severity, length of hospital stay, and mortality in both pediatric and adult trauma patients.^[6,17,18] Lactate clearance, the level of lactate cleared from the serum within a certain period, is also necessary to demonstrate the quality of resuscitation measures in both trauma and non-trauma-critical patients.^[19,20] However, there are also studies indicating that lactate or lactate clearance during hospital admission is not associated with mortality in patients with polytrauma.^[13] Wang et al^[21] reported that serum lactate levels helped predict mortality in patients with moderate to severe TBI. In our study, lactate levels at ICU admission and the 24th hour were significantly higher in the mortality group. Although lactate clearance at the 24th hour was low in the mortality group, no significant difference was found (P = .052). We believe that conditions such as trauma etiologies, liver and kidney dysfunction, and the use of vasopressor drugs such as epinephrine will affect the ability of lactate clearance to predict mortality.

Albumin, a negative acute phase protein, is known to be a biomarker for prognosis in septic patients. Inflammation plays a vital role in traumatic brain injury. The inflammatory response, cell activation, migration and recruitment of neutrophils, and release of inflammatory mediators can lead to secondary damage.^[22] Increased vascular permeability and blood–brain barrier dysfunction after secondary injury in patients with TBI induces albumin and fluid leakage and migration of immune cells. This albumin leak disrupts the basement membrane, further increasing blood–brain barrier permeability and causing vasogenic edema.^[23] Wang et al^[21] reported that median albumin levels in the mortality group of patients with TBI were significantly lower than those in the survivor group. In another study, it was stated that serum albumin levels were found to be significantly low in geriatric trauma patients with in-hospital mortality.^[24] In our study, a significant portion of the patients with polytrauma were patients with TBI. Consistent with the literature, the mortality group’s median albumin levels on admission were significantly lower. Albumin levels are affected by nutritional imbalances and liver and kidney disease. Since various factors can affect lactate and albumin levels, the lactate-to-albumin ratio has been reported to be a reliable prognostic marker in non-trauma critically ill patients and patients with TBI.^[8,17,21] Wang et al^[21] reported in the same study that the LAR rate in the mortality group was significantly higher than in the survivor group. Although lactate clearance was low in the mortality group in our study, there was no significant difference. Consistent with the literature, median LAR values were significantly higher in the mortality group. In addition to being an independent predictor of mortality, LAR values were determined to have an acceptable prognostic value in predicting mortality (AUC = 0.81, P < .001). At the same time, it was determined that the LAR value was superior to lactate and lactate clearance in predicting 28-day mortality in patients with polytrauma. These findings underscore the reliability of the LAR as a prognostic marker, providing clinicians with a confident tool for patient prognosis.

Our study has some limitations. First, it is retrospective and single-center. Secondly, lactate clearance measurements are lactate clearance at the 24th hour. Early lactate clearances (6 and 12 hours) could not be calculated because blood gases were not studied from every patient in the study. Thirdly, although patients were admitted to the ICU within the first 24 hours after trauma, the post-traumatic period could not be determined. Fourth, patients with severe hepatorenal disease were excluded from the study, whereas polytrauma patients with hepatorenal trauma were included. Hepatorenal trauma may have affected biomarkers, especially LAR.

5. Conclusion

In conclusion, it is essential for survival to identify patients with poor prognosis in critically ill polytrauma patients, where high mortality rates can be observed. LAR is an independent predictor of mortality in patients with polytrauma, and its acceptable prognostic value is a reliable indicator. The prognostic value of LAR is superior to serum lactate level and lactate clearance.

Author contributions

Conceptualization: Kadir Arslan, Ayca Sultan Sahin.

Data curation: Kadir Arslan.

Formal analysis: Kadir Arslan.

Investigation: Kadir Arslan.

Methodology: Kadir Arslan, Ayca Sultan Sahin.

Supervision: Kadir Arslan, Ayca Sultan Sahin.

Visualization: Kadir Arslan.

Writing – original draft: Kadir Arslan.