Audit of red blood cell transfusion in patients with acute leukemia at a tertiary care university hospital

Analysis of hemolysis-associated acute myeloid leukemia genes obtained using weighted gene co-expression network analysis and a Mendelian randomization study

PURPOSE

We used bioinformatics methods and Mendelian randomization (MR) analysis to investigate the hub genes involved in acute myeloid leukemia (AML) and their causal relationship with hemolysis, to explore a new direction for molecular biology research of AML.

METHODS

We first differentially analyzed peripheral blood samples from 62 healthy volunteers and 65 patients with AML from the Gene Expression Omnibus database to obtain differentially expressed genes (DEGs), and intersected them with genes sourced from weighted gene co-expression network analysis (WGCNA) and the GeneCards database to obtain target genes. Target genes were screened using protein-protein interaction (PPI) network analysis and ROC curves to identify genes associated with AML. Finally, we analyzed the correlation between genes and immune cells and the relationship between toll-like receptor 4 (TLR4) and AML using MR.

RESULTS

We compared peripheral blood expression profiles using an array of 62 healthy volunteers (GSE164191) and 65 patients with AML (GSE89565) (M0:25; M1:11; M2:10; M3:1; M4:7; M4 eo t [16;16] ou inv [16]:4; M5:6; M6:1) and obtained 7,339 DEGs (3,733 upregulated and 3,606 downregulated). We intersected these DEGs with 4,724 genes from WGCNA and 1,330 genes related to hemolysis that were identified in the GeneCards database to obtain 190 target genes. After further screening these genes using the PPI network, we identified TLR4, PTPRC, FCGR3B, STAT1, and APOE, which are closely associated with hemolysis in patients with AML. Finally, we found a causal relationship between TLR4 and AML occurrence using MR analysis (p < 0.05).

CONCLUSION

We constructed a WGCNA-based co-expression network and identified hemolysis-associated AML genes.

Leading digit bias in hemoglobin thresholds for red cell transfusion

BACKGROUND

Leading digit bias is a heuristic whereby humans overemphasize the left-most digit when evaluating numbers (e.g., 9.99 vs. 10.00). The bias might affect the interpretation of hemoglobin results and influence red cell transfusion in hospitalized patients.

STUDY DESIGN AND METHODS

Adults who received a red cell transfusion while registered at the University Health Network (Toronto, Canada) between January 1, 2016 and January 1, 2022 (n = 6 years) were included. The primary analysis excluded apheresis, red cell disorders, radiology suites, and operating rooms. The primary comparison was a regression discontinuity analysis of transfusion occurrence above and below the hemoglobin threshold of 79 g/L (local units). Additional analyses tested other leading digit and control thresholds (71, 81, and 91 g/L). Secondary analyses explored temporal covariates and clinical subgroups.

RESULTS

A total of 211,872 red cell transfusions were identified over the study period (median pre-transfusion hemoglobin 76 g/L; interquartile range = 69-92 g/L), with 107,790 inpatient transfusions in the primary analysis. The 79 g/L threshold showed 815 fewer red cell units above the threshold (95% confidence interval [CI]: -1215 to -415). The 69 g/L threshold showed 2813 fewer transfused units (95% CI: -4407 to -1220), and 89 g/L showed 40 fewer units (95% CI: -408 to 328). The effect was accentuated during daytime, weekday, and May-June months, persisted in analyses including all transfusions, and was absent at control thresholds.

CONCLUSION

Leading digit bias might have a modest influence on the decision to transfuse red cells. The findings may inform practice guidelines and quasi-experimental study design in transfusion research.

The Analysis of the Effect of Blood Transfusion on Changes of Blood Platelet Parameters in Patients with Leukemia Treated with Chemotherapy

Objective

To study and analyze the effect of blood transfusion on the change of blood platelet parameters in patients with leukemia treated with chemotherapy.

Methods

Ninety-eight patients with leukemia treated with chemotherapy in the First Affiliated Hospital of Xi'an Jiaotong University from January 2021 to January 2022 were selected to observe the changes of platelet parameters before and after blood transfusion.

Results

There was significant difference between pre-transfusion and post-transfusion indexes (platelet count, mean platelet volume, and hematocrit) (P < 0.05). After binary logistic regression analysis, the use of antibiotics (OR = 2.235), blood transfusion history (OR = 3.086), abnormal white blood cell count (OR = 1.134), and frozen plasma transfusion (OR = 3.121) were the main factors of blood platelet parameters after transfusion in leukemia patients (P < 0.05).

Conclusion

Blood transfusion is beneficial to improve blood platelet parameters and prevent bleeding in patients with leukemia treated with chemotherapy. Attention should be paid to patients with risk factors for poor response to blood platelet transfusion and early intervention.

Assessing the performance of a plateletpheresis unit at a tertiary-care academic medical center in Mexico: A 6-year experience

BACKGROUND

Optimization of platelet (PLT) apheresis collection is a priority to satisfy the increasing demand of hemato-oncology patients. We assessed the performance of a plateletpheresis unit supporting hematology patients.

STUDY DESIGN AND METHODS

This descriptive retrospective study included 561 plateletpheresis collections from 2013 to 2018. For data analysis, descriptive statistics and receiver operating characteristic (ROC) curve were used. A 5-item satisfaction questionnaire was analyzed.

RESULTS

Ninety percent of the donors were males. The median plateletpheresis time was 89 minutes; its success rate was 92.5%; median donor PLT count was 232 × 10⁹ /L, women median PLT count was 247 × 10⁹ /L vs 231x10⁹ /L in men (P = .017). Seventy-seven percent donors were candidates for a double product and 24.5% were processed; 20.8% of these donors had a weight ≤75 and 79.2% >75 kg, P = .003, and 6.6% were women and 93.4% men, P = .161. Thirty-six of donors had ≥250 × 10⁹ /L and 16.8% was processed as a triple product. ROC analysis showed that with donor PLT counts ≥200 × 10⁹ /L the sensitivity for obtaining double products was 0.981 and specificity 0.714, with an area under the curve (AUC) = 0.877. The adverse effect rate was 4.3%. Of the potential donors, 6.3% were rejected. The cost of processing single or double products was 430 USD. Comfort and time spent during plateletpheresis were areas for improvement.

CONCLUSION

Platelet count and donor weight predicted PLT yield and obtaining double products. Women had higher PLT counts, but no significant difference was found between donor gender and processed products. Assessment of the apheresis unit can help to improve its performance.