Effects of perioperative massive transfusion on postoperative outcomes of children undergoing brain tumor removal: a retrospective cohort study

Study design

This retrospective analysis was conducted on pediatric patients who underwent brain tumor removal at the Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, between October 2014 and March 2022. Data were obtained from retrospective review of our institution’s electronic medical record with the access period starting at July 5, 2024 and ending at July 7, 2024. Ethical approval was obtained from the Research Ethics Committee of Guangzhou Women and Children’s Medical Center (Approval No. 2024239A01, dated July 1, 2024). All procedures adhered to the principles outlined in the Declaration of Helsinki. Written informed consent was obtained from patients’ legal guardians, allowing their data to be used for future research purposes.

Patients under 18 years of age who were admitted for intracranial tumor resection and whose diagnoses were confirmed by postoperative histopathological examination were eligible for inclusion. Exclusion criteria encompassed incomplete medical records, multiple or recurrent tumors, preoperative blood transfusion history, or the absence of intraoperative transfusion.

Hematological assessment

Massive allogeneic transfusion was defined as red blood cell (RBC) transfusion equal to or exceeding the preoperative estimated blood volume within 48 h following surgery. Transfused blood volume was calculated using the formula: $\mathrm{E}\mathrm{s}\mathrm{t}\mathrm{i}\mathrm{m}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{d}\mathrm{R}\mathrm{e}\mathrm{d}\mathrm{C}\mathrm{e}\mathrm{l}\mathrm{l}\mathrm{V}\mathrm{o}\mathrm{l}\mathrm{u}\mathrm{m}\mathrm{e}\mathrm{T}\mathrm{r}\mathrm{a}\mathrm{n}\mathrm{s}\mathrm{f}\mathrm{u}\mathrm{s}\mathrm{e}\mathrm{d}(\mathrm{E}\mathrm{R}\mathrm{C}\mathrm{T})=\text{PBRC}/0.6$. Here, PBRC refers to the volume of packed red blood cells transfused, with a hematocrit of 0.6 as provided by the Guangzhou Central Blood Station. The estimated total blood volume was 80 ml/kg for infants below 2 years and 70 ml/kg for children aged 2 to 18 years.

Definitions of variables and data collection

The study examined the impact of perioperative allogeneic transfusion on clinical outcomes. Data were retrieved from the hospital’s electronic medical record system, focusing on 20 potential confounding variables. These included 13 preoperative patient-specific characteristics, such as age, sex, weight, external ventricular drainage history, American Society of Anesthesiologists (ASA) physical status, Karnofsky Performance Scale (KPS) score, anemia (defined as hemoglobin <110 g/L in the last preoperative test), and coagulopathy (platelet count <100,000/mm³, international normalized ratio >1.2, or activated partial thromboplastin time >36 s) (Talving et al., 2011).

Tumor-related variables included edema, location (supratentorial or subtentorial), number (single or multiple), brain invasion, and tumor size. Tumor characteristics were assessed using magnetic resonance imaging (MRI), with brain invasion defined as infiltration into nearby structures such as the skull base, dura mater, arachnoid, brain, or brainstem. Tumor size was measured as the largest axial diameter.

Intraoperative parameters encompassed surgical duration, blood loss, fluid infusion, and the extent of tumor resection. Resection extent was categorized using a five-point brain tumor resection score: (1) extended tumor removal; (2) complete tumor removal; (3) complete intracranial tumor removal with preservation in critical nerve functional areas; (4) incomplete tumor removal; (5) biopsy or decompression without tumor removal (Baumgarten et al., 2016). Postoperative data included Ki67 proliferation index and tumor grading based on the current World Health Organization (WHO) classification of central nervous system tumors (Louis et al., 2016).

Outcomes and follow-up

The primary outcomes of this study were 30-day mortality and 1-year survival rate. Among these, 30-day mortality was classified as a short-term outcome, while one-year survival rate represented the long-term outcomes. Children were monitored from their initial hospital admission until March 1, 2023, or the date of death, whichever occurred first.

The study also evaluated 10 secondary outcomes. Three of these focused on postoperative complications: infections (including intracranial infections, surgical site infections, pneumonia, and bloodstream infections), re-craniotomy due to bleeding or swelling, and intracranial hypertension. Additional secondary outcomes included the duration of mechanical ventilation, length of stay in the intensive care unit (ICU) and hospital, new neurological events (Table S1), and tumor recurrence or metastasis.

The diagnosis of postoperative neurological and non-neurological complications was determined using the International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10). Except for the duration of mechanical ventilation, ICU stay, hospitalization, and tumor recurrence or metastasis, all other secondary outcomes were observed within 30 days post-surgery.

Statistical analysis

All statistical analyses were conducted using SPSS 15.0 (IBM, Armonk, NY, USA), and graphical illustrations were created using GraphPad Prism 6 (GraphPad Software Inc., La Jolla, CA, USA). Descriptive statistical methods were employed, including mean ± standard deviation ( $\overline{\mathrm{x}}$ ± SD) for continuous variables or median with interquartile range (IQR, 25th–75th percentiles).

The Shapiro-Wilk test was applied to evaluate the normality of continuous variables. For normally distributed data, the T-test was used for comparisons, while the Mann-Whitney U test was employed for data that did not follow a normal distribution. Pearson’s Chi-square test was utilized to analyze categorical variables.

To account for potential confounding factors, logistic regression analysis was performed to evaluate the association between massive RBC transfusion and clinical outcomes. For each result, we first conducted a bivariate analysis. Any variable with a p-value < 0.2 is considered a candidate variable for the final model. Then gradually construct a multivariate model. For secondary outcomes, Bonferroni correction was applied to adjust the significance threshold, taking into account the impact of multiple comparisons. Long-term survival analyses were conducted using survival curves. Cox proportional hazards model was used to evaluate the impact of baseline features on survival. Statistical significance was defined as a p-value < 0.05.

Effects of massive transfusion on postoperative complications

Short-term clinical outcomes are detailed in Table 3. The MT group demonstrated significantly higher 30-day mortality (26.9% vs. 4.8%, p < 0.001), extended postoperative mechanical ventilation times (67.0 h (40.5–157.1) vs. 21.6 h (7.1–65.8), p < 0.001), prolonged ICU stays (6.0 days (3.3–11.8) vs. 2.5 days (1.0–5.0), p < 0.0010), and longer overall hospitalizations (28.0 days (20.0–36.0) vs. 20.0 days (14.0–26.0), p < 0.001) compared to the non-MT group. Additionally, postoperative intracranial hypertension occurred in significantly more patients in the MT group than in the non-MT group (35.9% vs. 8.3%, p < 0.001).

Effects of massive transfusion on primary outcomes

Logistic regression analysis revealed that perioperative massive RBC transfusion was independently associated with increased 30-day mortality after adjusting for confounding variables (OR: 0.137, 95% CI [0.036–0.528], p = 0.004; Table 4). However, no significant association was found between massive transfusion and 1-year survival rates. After adjusting confounding factors using multivariable cox regression analysis, it was found that WHO grade and massive transfusion were associated with long-term survival (Table S2). The survival analysis showed that the 1-year survival rate was 35.9% for the MT group, compared to 57.2% for the non-MT group. Correspondingly, the MT group had a lower long-term survival rate than the non-MT group (HR: 1.000, 95% CI [1.000–1.000], p = 0.029; Fig. 2).

Mortality details showed that 21 of 78 patients (26.9%) in the MT group died within 30 days, compared to 11 of 228 patients (4.8%) in the non-MT group. At 1 year, 50 of 78 patients (64.1%) in the MT group had died, compared to 98 of 228 patients (42.8%) in the non-MT group (Fig. 3). Additionally, Fig. 4 compares blood transfusion volumes between survivors and non-survivors at both the 30-day and 1-year time points. At these two time points, the blood transfusion volumes of survivors were not decreased compared to non-survivors (p > 0.05).

Effects of massive transfusion on secondary outcomes

The adjusted logistic regression model demonstrated a significant association between massive RBC transfusion and an increased risk of postoperative intracranial hypertension (OR: 4.788, 95% CI [1.547–14.824], p = 0.007; Table 5, Table S3). However, no significant associations were observed between massive transfusion and other complications, including infections, re-craniotomy, new neurologic events, tumor recurrence, or metastasis.

Patients in the MT group were significantly more likely to require prolonged mechanical ventilation (OR: 0.247, 95% CI [58.739–147.895], p < 0.001). Furthermore, logistic regression identified a significant relationship between massive transfusion and longer ICU stays (ß = 0.184, 95% CI [3.874–15.077], p = 0.001; Table S4).

Limitations

This study has several limitations. Firstly, its retrospective design inherently restricts the ability to establish causation. Secondly, the research was carried out at a single institution, which could restrict the broader applicability of its findings. Thirdly, in our case, the number of patients with certain exclusion criteria (such as preoperative blood transfusion history or recurrent tumors) was very small, and in order to reduce population heterogeneity, these patients were excluded. Therefore, our results are not applicable to these exclusion populations. Finally, the observational nature of the study precludes definitive cause-effect conclusions. To date, no large-scale randomized controlled trials have evaluated the effects of transfusion on clinical outcomes in this context. Such trials, especially those comparing varying transfusion thresholds, are urgently needed to validate these findings.

Additionally, this study used non-leukocyte-depleted RBCs, which differ from the leukocyte-depleted RBCs commonly employed in the USA and parts of Europe. This discrepancy further limits the applicability of our findings in other healthcare settings. Future studies should address these regional differences and incorporate larger, more diverse patient populations.