Frequency of hyperlactatemia in craniotomy and its association with anesthesia: A prospective observational study

Abstract

Lactate plays a crucial role in neuroanesthesia, and dysregulated lactate metabolism is hypothesized to contribute to carcinogenesis. Serum lactate has been suggested as a potential biomarker for tumor malignancy and a prognostic factor in patients with brain tumors. However, the clinical significance of intraoperative hyperlactatemia in brain tumor surgery and its relationship with anesthesia technique remain unclear. The aim of this study was to investigate the incidence of hyperlactatemia in brain tumor surgeries and its association with the type of maintenance anesthesia, as well as to examine its relationship with other potential risk factors. A total of 109 brain tumor cases scheduled for elective craniotomy were analyzed. All patients received general anesthesia, and maintenance anesthesia was managed using either total intravenous anesthesia or inhalation anesthesia. The assignment of anesthesia technique was not randomized and was mainly based on intraoperative neuromonitoring needs. The patients’ lactate levels were measured after the induction of anesthesia (baseline), 1 hour after the start of surgery, and immediately after extubation. Hyperlactatemia occurred in 66 of the 109 patients (60.6%). Analysis of the intraoperative variations in lactate levels revealed a parallel increase in both the total intravenous anesthesia and inhalation groups (P = .37), and there was no statistically significant difference between them (P = .19). Patients with glial tumors had higher lactate levels than those with non-glial tumors (P = .001), and lactate levels in grade 4 brain tumors were significantly higher than those of grade 1 tumors (P = .003). This study demonstrates that hyperlactatemia is a common finding in brain tumor cases, and the preference for total intravenous or inhalation anesthesia during craniotomy does not have a significant impact on serum lactate levels. Markedly elevated lactate levels in brain tumor cases should be considered as a possible reflection of tumor aggressiveness or higher grade.

1. Introduction

Lactate plays a crucial role in neuroanesthesia. Previously, it was thought to be produced due to only anaerobic metabolism in conditions of oxygen deficiency, such as strenuous exercise, hypoxia, hypoperfusion, or shock, which is referred to as type A hyperlactatemia.^[1] However, according to current information, it can also be continuously produced in aerobic environments.

In 1923, Otto Warburg conducted pioneering research on the phenotypic characteristics of cancer cells and demonstrated that under completely aerobic conditions, glucose uptake increases, and excessive lactate production occurs. This mechanism is known as the “Warburg effect” or “type B hyperlactatemia,” which induces the proliferation and growth of tumor cells.^[1]

The role of lactate in carcinogenesis is unknown, although it is considered that dysregulated lactate metabolism contributes significantly. Many rapidly proliferating tumor cells use aerobic glycolysis, which produces lactate as the end product and thus provides them with an energy source. The acidic environment generated by lactate facilitates tumor-cell invasion and metastasis while enhancing resistance to apoptosis.^[2–6] Thus, it has been suggested that serum lactate could be a biomarker for tumor malignancy and a prognostic factor for patients with brain tumors.^[5,7–10] However, the extent to which lactate production is reflected in serum levels remains unclear.

Numerous factors can influence serum lactate levels, and there is currently no consensus about which contribute most. Research has investigated the impact of comorbidities, body mass index (BMI), tumor characteristics, corticosteroid therapy, hyperglycemia status, and the duration of surgery on lactate levels in patients with intracranial tumors.^[1,7–12] However, studies on the effect of type of anesthesia used on the development of hyperlactatemia have been limited.^[11,13]

The aim of this study was to investigate the incidence of hyperlactatemia in brain tumor surgeries and its association with the type of maintenance anesthesia. The secondary aim was to examine its relationship with other potential risk factors.

We hypothesized that lactate elevation in brain tumors is independent of anesthesia technique but may reflect tumor-related factors.

2. Materials and methods

Approval for this study was obtained from the Clinical Research Ethics Committee of the University of Health Sciences, Dişkapi Yildirim Beyazit Training and Research Hospital (October 18, 2021; decision no.: 122/14). The study prospectively examined all patients with brain tumors over the age of 18 undergoing elective craniotomy between November 1, 2021, and November 30, 2022, at a single tertiary care hospital. All patients provided written informed consent to participate in the study.

Patients were excluded if they had an emergency surgery, awake craniotomy, a previous craniotomy, or conditions associated with type A hyperlactatemia (e.g., congestive heart failure, liver dysfunction, renal dysfunction, sepsis, shock, or a need for inotropic support to maintain blood pressure). Patients were prospectively followed for 3 months postoperatively to assess survival. The protocol for this clinical trial was registered at ClinicalTrials.gov (NCT05145049).

In addition to standard anesthesia monitoring, the bispectral index (BIS) was monitored for all patients (BIS, Medtronic-Covidien Products, Mansfield). After inducing general anesthesia, invasive arterial monitoring and blood gas sampling were performed. Maintenance anesthesia was managed to keep the BIS value between 40 and 60 using either total intravenous anesthesia (TIVA) or inhalation anesthesia.

The choice of anesthesia method was made in collaboration with the surgical team. It was determined based on the need for intraoperative neuromonitoring, which is now commonly used in brain tumor surgeries. Inhalation anesthesia could not be used in patients requiring neuromonitoring, as it may suppress motor-evoked potentials due to its muscle-relaxant effects.^[14] Therefore, TIVA was preferred in these cases.

TIVA was performed using propofol (5–10 mg·kg⁻¹·h⁻¹ intravenously [IV]) and remifentanil (0.05–0.4 mcg·kg⁻¹·min⁻¹ IV), while inhalation anesthesia was administered using sevoflurane (minimum alveolar concentration 1%, 0.5–3 L·min⁻¹) and remifentanil (0.05–0.4 mcg·kg⁻¹·min⁻¹ IV).

Conventional fluid therapy was applied using a balanced, lactate-free crystalloid solution administered at a rate of 3 to 5 mL·kg⁻¹·h⁻¹, with continuous monitoring of mean arterial pressure (MAP) and urine output (>0.5 mL·kg⁻¹·h⁻¹).^[15] The MAP was maintained between 60 and 65 mm Hg. If MAP dropped below 60 mm Hg, a 250 mL crystalloid bolus and 5 mg of intravenous ephedrine were administered.^[15,16] The intraoperative transfusion threshold was determined as a hemoglobin level of 8 g/dL; however, no patient required transfusion.^[16] Mannitol (0.25–0.5 g·kg⁻¹) and dexamethasone (8 mg IV) were routinely administered to all patients for brain relaxation, with mannitol infused over approximately 20 minutes at the time of skin incision.^[17] At the end of surgery, patients were extubated and transferred to the post-anesthesia care unit.

The patients’ lactate levels were measured from arterial blood gas samples (Siemens Healthineers RAPID Point 500e Blood Gas System, Siemens Healthcare Health Inc.,Tarrytown). Measurements were taken after the induction of anesthesia (baseline), 1 hour after the start of surgery, and immediately after extubation. A serum lactate level of 2 mmol·L⁻¹ or higher was considered hyperlactatemia.^[18] The recorded data comprised patients’ demographic data and clinical features, positioning during surgery, administered treatments, duration of surgery, tumor size, histopathological findings, and postoperative 3-month survival.

2.1. Statistical analysis

The distributions of variables across groups were initially tested using the Kolmogorov–Smirnov test. If the assumption of normal distribution was not met, nonparametric test methods were selected. In this context, the Student’s t test and/or the Mann–Whitney U test were applied to compare variables obtained through measurement in 2 independent groups. The chi-square and/or Fisher exact test were used to examine categorical variables. The study’s results of other demographic and group comparisons were presented as proportions for qualitative variables and mean ± standard deviation and median (25th–75th percentiles) for quantitative variables. The changes in measurements of the lactate variable at 3 different time points were examined using repeated-measures analysis of variance models for various factors. While employing this model, sphericity was analyzed using Mauchly’s test, and appropriate Huynh–Feldt statistics and related P-values were tested for main effects and interaction terms based on epsilon values. The ability to predict mortality for lactate variable measurements at all 3 time points was analyzed using receiver operating characteristic curve analysis, summarized with the area under the curve with 95% confidence intervals. Pearson and Spearman correlation coefficients were also used to examine relationships between parameters. Statistical analyses of the study were performed using IBM SPSS Statistics for Windows (version 26.0, IBM Corp., Armonk) and a P-value < .05 was considered statistically significant.

A sample size calculation was performed to identify the patient group with elevated lactate levels. Previous references indicated that approximately half of the patients undergoing intracranial surgery had serum lactate levels ≥2 mmol·L⁻¹.^[19] With 95% confidence, 80% power, and an expected frequency of 50% within the target range (40%–60%), it was determined that a sample size of 96 patients would be sufficient.

3. Results

The study included a total of 142 patients. Patients were excluded because they had an awake craniotomy (n = 12) and previous craniotomy (n = 17). The correlation between hyperlactatemia and acidosis was examined to accurately identify patients with type B hyperlactatemia. Among patients with hyperlactatemia, 4 had acidosis (pH < 7.35), including 1 patient with pH < 7.25. These 4 patients who had type A hyperlactatemia were excluded from the study, and data from the remaining 109 patients were analyzed (Fig. 1).

Figure 1.

Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) flowchart.

Hyperlactatemia was present in 66 patients (60.6%), while the baseline lactate levels of 43 patients were normal (<2 mmol·L). The demographic and clinical characteristics of the patients are presented in Table 1.

Table 1.

Patients’ demographic and clinical summary.

	Median (25–75th)
Age (yr)	57 (44–64)
BMI (kg·m−2)	27 (24–30)
Surgical duration (min)	225 (180–270)
Tumor size (mm2)	35 (25–48)
Baseline lactate (mmol·L−1)	2.2 (1.5–3.2)
Intraoperative 1st hr lactate (mmol·L−1)	2.75 (1.3–3.4)
Extubation lactate (mmol·L−1)	3.2 (2.1–4.3)

	n	%
Anesthesia method
TIVA	78	71.56
Inhalation	31	28.44
Gender
Female	61	55.96
Male	48	44.04
Comorbidities
Yes	67	61.47
No	42	38.53
ASA class
1	39	35.78
2	53	48.62
3	17	15.60
Position
Supine	83	76.15
Sitting	16	14.68
Park bench	9	8.26
Prone	1	0.92
Tumor type
Glial	41	37.61
Non-glial	44	40.37
Metastasis	24	22.02
Tumor grade
1	38	34.9
2	11	10.1
3	27	24.8
4	33	30.3
Survival
Discharged	95	87.16
Exitus	14	12.84

ASA = American Society of Anesthesiologists, BMI = body mass index, TIVA = total intravenous anesthesia.

There were no significant differences between the TIVA (n = 78) and inhalation (n = 31) groups in terms of demographic or clinical variables, including age, BMI, comorbidities, American Society of Anesthesiologists (ASA) score, surgical duration, tumor size, tumor type or grade, surgical position, and survival (Tables 2 and 3).

Table 2.

Group comparisons for continuous variables.

	TIVA	Inhalation	P *
	Median (25–75th)	Median (25–75th)
Age (yr)	57 (44–63)	58 (42–69)	.62
BMI (kg·m2)	27 (24–30)	27 (24–33)	.84
Surgical duration (min)	240 (180–280)	200 (165–240)	.06
Tumor size (mm2)	35 (25–50)	32 (26–40)	.20
Baseline lactate (mmol·L−1)	2.15 (1.5–3.2)	2.3 (1.7–3.6)	.54
Intraoperative 1st hr lactate (mmol·L−1)	2.7 (1.2–3.3)	2.9 (2–4)	.23
Extubation lactate (mmol·L−1)	3.05 (2.1–4.2)	3.7 (2–5.3)	.29

BMI = body mass index, TIVA = total intravenous anesthesia.

^*Mann–Whitney U test.

Table 3.

Group comparisons for categorical data.

	TIVA (n, %)	Inhalation (n, %)	P *
Gender
Female	41 (52.56)	20 (64.52)	.25
Male	37 (47.44)	11 (35.48)
Comorbidities
Yes	51 (65.38)	16 (51.61)	.18
No	27 (34.62)	15 (48.39)
ASA
1	28 (35.9)	11 (35.48)	.99
2	38 (48.72)	15 (48.39)
3	12 (15.38)	5 (16.13)
Position
Supine	57 (73.08)	26 (83.87)	.07†
Sitting	12 (15.38)	4 (12.9)
Park bench	9 (11.54)	0 (0)
Prone	0 (0)	1 (3.23)
Tumor type
Glial	29 (37.18)	12 (38.71)	.31
Non-glial	29 (37.18)	15 (48.39)
Metastasis	20 (25.64)	4 (12.9)
Tumor grade
1	26 (33.3)	12 (38.7)	.29
2	8 (10.3)	3 (9.7)
3	23 (29.5)	4 (12.9)
4	21 (26.9)	12 (38.7)
Survival
Discharged	69 (88.46)	26 (83.87)	.53†
Exitus	9 (11.54)	5 (16.13)

ASA = American Society of Anesthesiologists, TIVA = total intravenous anesthesia.

^*Chi-square test.

^†Fisher exact test.

We examined the variations in lactate levels during surgery in the TIVA and inhalation groups, which indicated that lactate levels increased in parallel in both groups (P = .37). There was no significant difference between the 2 groups (P = .19). However, the variation in lactate over time was significant in both groups (P < .001). The baseline lactate value was significantly different from both the value at the first hour intraoperatively and the value measured upon extubation. The first hour intraoperative lactate value was also substantially different from the value at extubation (Fig. 2).

Figure 2.

Comparison of lactate variation between the TIVA and inhalation groups. No significant difference was observed between groups (P₁). The variation in lactate levels over time was significant within both groups (P₂) and the increase occurred in parallel in both groups (P₃). ANOVA = analysis of variance, SD = standard deviation.

Regarding tumor type, patients with glial tumors had higher lactate levels than those with non-glial tumors (P = .001). The variation in lactate levels over time was significant across all tumor types (P < .001), although the variations were parallel to each other (P = .95; Fig. 3).

Figure 3.

Comparison of lactate variation between glial and non-glial tumors at baseline, 1st hour, and extubation. Lactate levels were significantly higher in patients with glial tumors compared with those with non-glial tumors (P₁ = .001). A significant variation in lactate levels was observed over time in both groups (P₂ < .001), with no significant group–time interaction (P₃ = .950), indicating a parallel variation across groups. ANOVA = analysis of variance, SD = standard deviation.

Specifically, lactate levels in grade 4 brain tumors were significantly higher than those of grade 1 tumors (P = .003). The variation in lactate levels over time was significantly different across all groups (P < .001) but remained parallel (P = .84; Fig. 4).

Figure 4.

Comparison of lactate variation across tumor grades at baseline, 1st hour, and extubation. Lactate levels were significantly higher in patients with grade 4 tumors compared with those with grade 1 tumors (P₁ = .003). A significant increase in lactate levels was observed over time in all grades (P₂ < .001), and no significant interaction was found between time and tumor grade (P₃ = .849), indicating a parallel trend across groups. ANOVA = analysis of variance, SD = standard deviation.

Patients were compared according to gender, ASA score, patient position, and survival. No statistically significant differences were observed between the groups in these comparisons (P > .05), but the variation in lactate levels over time was considerable (P < .001). The increase in lactate was parallel across all groups (P = .05). No correlation was identified between lactate variation and age, BMI, duration of surgery, or tumor size (P > .05).

Receiver operating characteristic analysis indicated that lactate measurements were not predictive of mortality at any time point (P > .05, Fig. 5). Malignancy, high tumor grade, and advanced age negatively impacted 3-month survival (P = .004, P = .002, and P = .02, respectively).

Figure 5.

Lactate’s predictive value for mortality was assessed using receiver operating characteristic (ROC) analysis. Lactate measurements at baseline, at the intraoperative 1st hour, and immediately after extubation were not found to have significant predictive power for mortality.

4. Discussion

This study demonstrates that hyperlactatemia is common in cases of intracranial tumors. Although lactate levels showed a clear association with tumor type and grade, they were not influenced by the anesthetic method (TIVA or inhalation anesthesia), age, gender, BMI, ASA score, duration of surgery, tumor size, or patient position.

The reported incidence of hyperlactatemia in brain tumor surgeries is 32% to 68%.^[5,11,20] Many rapidly proliferating tumor cells use aerobic glycolysis for energy, with lactate as the end product. Hyperlactatemia observed in cancer cells is known to induce tumor-cell growth and division,^[1] but the causes and effects of hyperlactatemia in patients remain unclear. This study prospectively examined all intracranial tumor surgeries conducted within 1 year (78.9% supratentorial, 21.1% infratentorial), and the results showed that preoperative lactate levels exceeded the normal range (≥2 mmol) in 60% of the 109 patients. This incidence of hyperlactatemia was consistent with the literature and was similar to the rate of malignant tumors in our cohort.

A close relationship between serum lactate levels and both tumor type and grade has been well documented.^{[1,5,8,9,19,21]} High-grade gliomas are characterized by enhanced aerobic glycolysis and increased lactate production, reflecting an elevated glycolytic flux that is closely associated with tumor aggressiveness. Under physiological conditions, cells rely on highly efficient oxidative phosphorylation for energy production; however, in malignant tumors such as glioblastoma multiforme, cancer cells preferentially shift toward glycolysis even in the presence of sufficient oxygen. Although glycolysis is less efficient in ATP yield, its high rate enables rapid ATP production, thereby meeting the increased energy demands of rapidly proliferating and invasive tumor cells. In parallel, lactate regulates the tumor microenvironment and supports the preferential use of glucose for cell proliferation and metastasis.^[2,22] While some studies have reported conflicting results,^[7,12,23] our findings indicate that perioperative hyperlactatemia is associated with tumor type and grade. Monitoring serum lactate levels in patients with brain tumors may provide valuable information regarding tumor malignancy. Therefore, aggressive tumors may require more careful consideration of perioperative hemodynamic management and perfusion targets.

There is limited research on the effect of anesthesia methods on serum lactate levels. In a retrospective analysis of 496 patients, de Smalen et al^[11] reported that hyperlactatemia developed less frequently in patients who received TIVA after intracranial tumor surgery. The researchers suggested that propofol may have a protective effect against hyperlactatemia, which is supported by cellular studies showing that propofol inhibits lactate dehydrogenase release, thereby reducing lactate accumulation.^[24,25] Most evidence highlighting the benefits of TIVA comes from in vitro studies.^[26,27] Clinical studies supporting this perspective also exist; however, they have been conducted in different surgical contexts. For example, 1 study examined lactate variations during spinal surgeries lasting more than 8 hours,^[28] while another assessed lactate levels in 44 endarterectomy cases.^[29]

Furthermore, in the study by de Smalen et al,^[11] hyperlactatemia was retrospectively assessed, and the results were based exclusively on its incidence. Since lactate levels were measured only in the postoperative period, with no preoperative or intraoperative monitoring, intraoperative factors could not be evaluated; therefore, postoperative hyperlactatemia could not be definitively attributed to TIVA or inhalation anesthesia. In this prospective study, we investigated lactate level variations under TIVA and inhalation anesthesia. Our findings showed that the choice of anesthesia method has no substantial influence on lactate levels and does not support the presumed superiority of TIVA over inhalation anesthesia.

There are conflicting research results regarding factors that may cause hyperlactatemia in patients with intracranial tumors. There is no consistent evidence regarding the association of age and gender with hyperlactatemia.^[5,7,10] Another frequently examined factor in the literature is BMI. Ioannoni et al^[10] and Garavaglia et al^[30] suggested that high BMI may increase serum lactate levels. This can be explained by increased lactate release due to muscle ischemia and tissue breakdown in individuals with high BMI. Prolonged surgery duration and immobility may increase the risk of hyperlactatemia.^[11,12,31] Rhabdomyolysis has been reported in neurosurgical patients undergoing surgery in a lateral position lasting more than 5 hours.^[32] However, some researchers argue that surgery duration and BMI do not affect lactate levels.^[5,11,30,33] There is also no consensus on the relationship between tumor size and lactate levels.^[5,7] In the present study, no significant relationship was observed between BMI, surgery duration, surgical position, tumor size, and lactate levels. The relative homogeneity of perioperative conditions – such as predominantly supine positioning, relatively short procedures, and comparable tumor sizes – may also have contributed to the absence of statistical differences among these variables.

Nevertheless, the intraoperative rise in lactate levels in both anesthesia groups suggests the involvement of additional physiological mechanisms beyond anesthesia type or procedural factors. The adrenergic response to surgical stress may have transiently accelerated glycolysis, while a temporary reduction in hepatic blood flow during general anesthesia could have decreased lactate clearance.

The impact of hyperlactatemia on clinical outcomes in brain tumors remains unclear. Parameters such as the length of hospital stay, neurological complications, and survival duration are essential. The general consensus is that hyperlactatemia is not associated with survival or poor neurological outcomes but is linked to prolonged hospitalization.^{[11,20,23,33,34]} However, a systematic review and meta-analysis by Sharapi et al^[31] indicated that perioperative hyperlactatemia was not associated with significant postoperative outcomes such as the development of new neurological deficits, 30-day mortality, 6-month survival, or prolonged hospitalization. In the current study, hyperlactatemia was not associated with 3-month survival, and serum lactate levels could not be used to predict mortality. The association of mortality with advanced age, malignancy, and high-grade tumors was expected.

Although the current data are controversial, it has been suggested that lactate may have neuroprotective properties and could be a potential therapeutic alternative for patients with moderate brain injury.^[35–37] Additionally, it has been mentioned that blocking lactate flow with monocarboxylate transporter inhibitors may suppress tumor invasion.^[3,38,39] Such studies highlight the relationship between brain tumors and lactate and could offer hope for future tumor therapies.

A distinction of our study from others lies in its prospective design and the evaluation of outcomes based on changes in lactate levels rather than the incidence of hyperlactatemia. The observational nature of this study allowed us to examine multiple potential risk factors simultaneously. However, this approach also introduced some limitations. First, due to the observational design of the study and the widespread use of intraoperative neuromonitoring, the anesthesia technique was not randomized, and TIVA was more frequently used as the maintenance anesthesia method. This resulted in an imbalance between the study groups, which may have influenced the comparative analyses. In addition, the interaction of certain perioperative risk factors may have affected the results. Given the differing outcomes reported in the literature, there is also a need for more comprehensive and prospective studies on this topic. Finally, the lack of systematic assessment of postoperative neurological deficits and the absence of regular postoperative lactate monitoring further limited the scope of our research. These limitations should be considered when interpreting the study’s results.

5. Conclusion

This study suggests that hyperlactatemia is a common finding in brain tumor cases rather than an unexpected complication, and that the preference for total intravenous or inhalation anesthesia during craniotomy does not have a significant impact on serum lactate levels. Markedly elevated lactate levels in brain tumor cases should be considered a possible reflection of tumor aggressiveness or higher grade. Increasing awareness of this association may help clinicians interpret intraoperative lactate changes more accurately and guide future research in this area.

Acknowledgments

The authors thank Prof Dr Mustafa Kemal Bayar from the Department of Anesthesiology and Reanimation, Faculty of Medicine, Ankara University, Ankara, Türkiye for his valuable contributions, and Assoc. Prof Dr Can Ateş from the Department of Biostatistics and Medical Informatics, Faculty of Medicine, Aksaray University, Aksaray, Türkiye for his professional expertise in biostatistics.

Author contributions

Conceptualization: Fatma Ozkan Sipahioglu, Asli Donmez.

Data curation: Fatma Ozkan Sipahioglu, Funda Atar.

Investigation: Fatma Ozkan Sipahioglu, Funda Atar, Ceyda Ozhan Caparlar.

Project administration: Fatma Ozkan Sipahioglu, Ceyda Ozhan Caparlar, Asli Donmez.

Validation: Funda Atar.

Visualization: Funda Atar.

Methodology: Ceyda Ozhan Caparlar.

Writing – original draft: Fatma Ozkan Sipahioglu.

Writing – review & editing: Ceyda Ozhan Caparlar, Asli Donmez.