Objective: To assess the clinical application value of a prediction model for red blood cell (RBC) demand in surgical procedures. Methods: Demographic data, laboratory parameters, anesthesia and transfusion records, and model prediction data were retrospectively collected from surgical patients at the First Medical Center of Chinese PLA General Hospital between 2018 and 2024. Statistical analysis was performed using the Chi-square test, t-test, and Mann-Kendall trend test. Results: From 2018 to 2024, the predictive model for RBC demand in surgical procedures was used to evaluate a total of 112 293 surgeries. During this period, the model call rate (77.49%-98.91%, P<0.05), compliance rate (56.81%-84.92%, P<0.05), and prediction accuracy rate (66.82%-94.17%, P<0.05) all showed significant upward trends. The total blood usage across the hospital (13645.4-7723.5 units, P<0.05) and the average blood usage per surgery (0.21-0.1 units, P<0.05) exhibited overall downward trends. Postoperative average hemoglobin levels in the non-compliance group (112.1-105.3 g/L in the non-compliance group vs 106.9-92.7 g/L in the compliance group, P<0.05) and the intraoperative excessive transfusion rate (5.06%-6.05% in the non-compliance group vs 0.09%-0.04% in the compliance group, P<0.05) were significantly higher in the non-compliance group compared to the compliance group. Conclusion: The predictive model for RBC demand in surgical procedures has played a positive role in conserving blood resources, optimizing blood resource allocation, and reducing intraoperative risks.

Objective: To report the antibody identification, blood management during pregnancy and the monitoring process of fetal hemolytic disease of fetus and newborn (HDFN) in a pregnant woman with a history of blood transfusion and pregnancy who developed anti-Jr . Methods: Saline tube technique and anti-human globulin technique were used for maternal blood typing, unexpected antibody screening and identification, as well as for determining antibody titer and IgG subclasses. PCR-SSP was employed for genotyping of 18 blood group systems. Next-generation sequencing (NGS) was utilized for gene sequencing of 38 blood group systems. Sanger sequencing was applied to verify rare blood group mutations detected by NGS and to investigate the corresponding rare blood group genes in family members. Blood preparation was achieved through anemia management in prenatal clinics and autologous blood collection during pregnancy. The newborn underwent the three primary tests for HDFN and plasma IgG subclass testing. Results: The pregnant woman's blood type was B, RhD positive, with a positive unexpected antibody screen, and the antibody identification pattern was consistent with a high-frequency antigen antibody. Gene sequencing revealed a homozygous ABCG2 c.376C>T mutation in the woman, resulting in the Jr(a-) phenotype, and anti-Jr antibody was present in her plasma. No compatible Jr(a-) blood was found among family members. The maternal anti-Jr IgG titer remained stable at 256 during pregnancy, with no detectable IgG1 or IgG3 subclasses against the Jr antigen. A total of 800 mL of autologous blood was collected in two stages during pregnancy. The newborn was B, RhD positive, Jr(a+), with a positive unexpected antibody screen (anti-Jr ). IgG subclass typing detected no IgG1 or IgG3. The direct antiglobulin test was positive, while the acid elution test was negative. Conclusion: The combination of serology and blood group genetic analysis provides a diagnostic basis for identifying antibodies to high-frequency antigens. Managing perinatal anemia and implementing staged autologous blood storage can secure blood supply for the perioperative period. IgG antibody subclass typing offers a reference for clinical assessment and prevention of HDFN.

Objective: To investigate the damaging effects of red blood cell supernatant (RBC-S) stored for different durations (7 d, 14 d, and 28 d) on vascular endothelial cells, and to explore the underlying mechanisms using bioinformatics analysis, so as to provide references for optimizing red blood cell transfusion strategies. Methods: Human umbilical vein endothelial cells (HUVECs) were co-cultured with RBC-S stored for 7, 14 and 28 days, designated as the 7 d group, 14 d group and 28 d group respectively, which were collectively defined as the experimental groups. Cell damage was evaluated by cell proliferation assay (Cell Counting Kit8, CCK8), lactate dehydrogenase (LDH) release assay, 4′, 6diamidino2phenylindole (DAPI) staining, and flow cytometry for apoptosis and reactive oxygen species (ROS) levels. The damage degree of RBC-S on vascular endothelial cells was assessed by statistical analysis of damage data among different groups. Since the damage effect reached a plateau at all time points, the 28 d storage group was selected as the representative for further mechanistic studies. Transcriptomic analysis was performed to explore the role of frizzled class receptor 1 (FZD1) and Wnt signaling pathway in red blood cell storagerelated endothelial dysfunction. Results: Compared with the control group, the storage groups treated with 7 d, 14 d, and 28 d RBC-S showed significantly decreased cell proliferation rates [control group 100%, 7 d group (69.51±2.30)%, 14 d group (74.54±2.89)%, 28 d group (73.59±2.36)%, P<0.05], significantly reduced numbers of DAPI-stained cell nuclei [control group (213±12.5) per field, 7 d group (140.33±17.04) per field, 14 d group (152.00±23.72) per field, 28 d group (144.33±19.09) per field, P<0.05] and significantly increased LDH release [control group (1), 7 d group (8.33±1.41), 14 d group (9.23±0.83), 28 d group (9.16±0.60), P<0.05]. There was no significant difference in the degree of damage caused by RBC-S among different storage groups (P>0.05). With the prolongation of storage time, free hemoglobin (FHb) gradually increased [control group (not detected), 7 d (16.57±6.38) mg/L, 14 d (76.80±22.83) mg/L, 28 d (286.97±29.02) mg/L, P<0.05]. The apoptotic rate (20.53±2.94)% and ROS relative intensity (5.13±0.91) in the 28 d storage group were significantly higher than those in the control group (P<0.05). Transcriptomic analysis showed that FZD1 played a key role in vascular endothelial dysfunction induced by red blood cell storage and was closely related to the Wnt signaling regulatory network. Conclusion: RBC-S stored for 7 d, 14 d, or 28 d can all significantly damage vascular endothelial cells, and the damaging effect reaches a plateau at 7 d of storage. Mechanistic investigation of the 28 d group indicated that the downregulation of the FZD1/Wnt signaling pathway may play a critical role in vascular endothelial dysfunction induced by red blood cell storage, providing a theoretical basis for further optimizing red blood cell storage and transfusion strategies.

Objective: To explore the influencing factors of blood transfusion volume in obstetric patients based on the national health development strategy, and to provide evidence for clinical transfusion management and maternal and infant safety. Methods: A total of 1 203 obstetric patients who received blood transfusion in a tertiary hospital in Beijing from 2013 to 2023 were enrolled retrospectively. Seventeen indicators including age, body mass index (BMI), hemoglobin and prothrombin time were selected as research variables. Descriptive analysis was conducted firstly. Scatter plot matrix was used to analyze the correlation between continuous variables and transfusion volume, and box plots were used to analyze the relationship between categorical variables and transfusion volume. Linear regression, logistic regression and random forest models were established for empirical analysis, and ROC curves and AUC values were compared to evaluate model performance. Results: Descriptive analysis showed that the distribution of obstetric blood transfusion volume was right-skewed, and multiple indicators were significantly correlated with transfusion volume. Linear regression indicated that 9 variables such as age, BMI and hemoglobin had linear correlation with transfusion volume. Logistic regression confirmed that 7 variables including BMI and hemoglobin were statistically correlated with the probability of massive blood transfusion. Random forest model screened the core influencing factors, which were ranked by importance: hemoglobin, prothrombin time, hematocrit, BMI, activated partial thromboplastin time, platelet count and age. The AUC values of logistic regression and random forest were 0.78 and 0.81 respectively, and the latter had better predictive performance. Conclusion: Prenatal anemia, coagulation disorders, advanced age, obesity, gestational hypertension, placental abnormalities and organ damage can increase the risk of massive blood transfusion in obstetric patients. The random forest model has better analytical and predictive ability in this study. The results can provide reference for accurate blood transfusion and risk prediction in obstetrics.

Objective: To analyze the distribution characteristics of unexpected antibodies among voluntary blood donors at a hospital in Beijing, with a focus on the seasonal distribution patterns of natural antibodies represented by the MNS and Lewis systems, as well as their correlation with concurrent local epidemic trends of the influenza virus, so as to provide a scientific basis for clinical transfusion safety early-warning and management strategies. Methods: A total of 82 780 voluntary blood donors from March 2023 to February 2026 at our hospital were enrolled. Positive screening for unexpected antibodies was identified through ABO blood group re-evaluations and minor crossmatch incompatibilities. Based on climatological seasonal definitions—spring (March to May), summer (June to August), autumn (September to November), and winter (December to February of the following year) —differences in the detection rates of various antibody classifications across different seasons were compared. Local influenza surveillance data from the same period were collected, and their correlation with the positive rate of influenza virus was analyzed. Results: A total of 98 cases (0.12%) positive for unexpected antibodies were identified among the 82 780 blood donors, including 87 cases with specific antibodies. The MNS system antibodies (anti-M) accounted for the highest proportion (54 cases, 55.10%). The detection rate of unexpected antibodies was significantly different in different seasons (P<0.05), and the detection rate in winter was significantly higher than that in spring, summer, and autumn (P<0.05). Correlation analysis showed that the monthly detection rate of total unexpected antibodies was positively correlated with the positive rate of influenza virus (r=0.423, P=0.010); The correlation between the monthly detection rate of unexpected antibodies and the positive rate of influenza virus in Lewis system (r=0.398, P=0.016) and MNS system (r=0.389, P=0.019) was statistically significant; However, no correlation was found for other antibodies such as those of the Rh system (P>0.05). Conclusion: The detection of unexpected antibodies in voluntary blood donors showed significant aggregation in winter, and was ecologically correlated with the positive rate of influenza virus in the region at the population level, which was more obvious in MNS and Lewis blood group system antibodies. These results suggest that influenza virus infection may have a potential impact on the expression of natural antibodies. Enhancing unexpected antibody identification and early warning for clinical crossmatch risks during winter is of great significance for ensuring the safety of clinical blood transfusion.

Objective: To investigate the molecular mechanism of ABO blood type gene c. 899G>A leading to the occurrence of subtype A. Methods: Serological methods were used to identify ABO blood types. Genotyping was performed using polymerase chain reaction sequence specific (PCR-SSP) kits, and Sanger sequencing was used to analyze the ABO gene exons 1-7. PacBio third-generation sequencing was employed for ABO gene full-length haplotype analysis. AlphaFold3 was used to predict protein structure, and ChimeraX software was used to analyze the impact of amino acid changes caused by base mutations on protein structure. Results: The patient exhibited group O of forward typing and group A of reverse typing. Weak A. antigen was detected by absorption-elution test. Molecular biology detection revealed three mutation sites, c. 261delG, c. 297A>G, and c. 899G>A. Third-generation sequencing showed that one haplotype was recombinant ABO O.01.01 and the other haplotype was recombinant ABO B.01-O.01.01, with c. 297A>G and c. 899G>A located on this recombinant haplotype. Protein structure prediction indicated that c. 899G>A resulted in premature termination codons and translation interruption of ABO blood group genes, leading to a 55 amino acid deletion at the C-terminus. Conclusion: The c. 899G>A mutation in the ABO gene of the patient resulted in reduced A antigen expression and an A subtype phenotype.

[Objective] To evaluate the risk of bacterial contamination of platelets apheresis and improve the clinical diagnosis rate of transfusion-transmitted bacterial infections. [Methods] A retrospective analysis was conducted on 11 cases involving bacterial contamination detected in apheresis platelets during quality inspections at our center from 2021 to 2023, as well as cases of transfusion-transmitted bacterial infection (TTBI) caused by platelet transfusion. The return of positive platelet bacteria test results and clinical transfusion adverse reactions were statistically analyzed. [Results] There were 9 donors with bacteria-contaminated platelets, of which 3 were reported as clinical transfusion reaction, 4 were detected by quality sampling, and 2 were identified by appearance detection before transfusion. The bacterial contamination rate of platelets was about 0.08% (9/10 762). The contaminated platelets were involved in 11 cases of TTBI, with an incidence of TTBI of approximately 0.05% (11/21 916). Only 3 cases of transfusion reactions were clinically reported, while the rest were case tracking with positive results of platelet bacterial test from quality sampling. The clinical return rate of TTBI was 27.27% (3/11), with an average reporting time of 8.12 hours after the occurrence of transfusion reactions. The majority of the contaminated platelets were detected at the end stage of storage, with 55.56% (5/9) of platelets collected on the 4th day after collection. Partial contaminated platelets were identified through quality sampling, with a positive rate of 2.78% (4/144). [Conclusion] The platelet bacterial contamination rate is high, but with low clinical return rate. It is recommended to conduct routine platelet bacterial monitoring and improve clinical diagnostic level.

[Objective] To compare the efficacy and safety of deglycerolized red blood cells (DRBC) and suspended red blood cells (SRBC) based on the propensity score matching (PSM) method, so as to provide evidence for the rational use of DRBC resources in clinical practice. [Methods] A total of 89 patients who received DRBC transfusion and 2 916 patients who received SRBC transfusion in our hospital from January 2023 to September 2024 were included. A 1∶1 nearest neighbor PSM was used to balance covariates such as gender, age, and body mass index (BMI). The changes of hemoglobin (Hb), red blood cell (RBC) count, hematocrit (HCT), and inflammatory markers such as white blood cell (WBC) count, neutrophil (NE) count, C-reactive protein (CRP), and Interleukin-6(IL-6) in the last 72 hours after transfusion were analyzed by SPSS 26.0 and R software to evaluate clinical efficacy and transfusion safety. [Results] The baseline of the two groups was balanced after PSM (P>0.05). There was no significant difference in the total effective rate between the DRBC group (80.9%) and the SRBC group (86.5%) (P>0.05). In the SRBC group, WBC (×10 /L) increased from 9.634±6.742 to 10.147±6.835, CRP (mg/dL) increased from 5.468±4.647 to 6.174±6.114, and IL-6(pg/mL) decreased from 213.733±587.191 to 157.255±552.626. In the DRBC group, WBC (×10 /L) decreased from 11.123±7.880 to 11.011±8.549, CRP (mg/dL) decreased from 5.729±4.761 to 5.326±4.466, and IL-6(pg/mL) decreased from 238.806±639.060 to 152.255±266.558. Compared with the before treatment, the differences between the SRBC group and DRBC group were not statistically significant (P>0.05). Among all patients included in the statistics, the overall incidence of transfusion adverse reactions was 0.205% (6/2 916) in the SRBC group, and no adverse reactions occurred in the DRBC group. The incidence in the SRBC group was higher than that in the DRBC group. [Conclusion] Based on PSM analysis, there was no significant difference in the efficacy and safety of DRBC transfusion compared with SRBC transfusion, which can provide evidence-based support for routine application.

[Abstract] [Objective] To compare and analyze the efficacy of platelet transfusion in patients with different doses, and to analyze the risk factors for platelet transfusion refractoriness. [Methods] A total of 5 827 patients who received platelet transfusion in the PLA General Hospital from May 2023 to May 2024 were selected as the research subjects, among which 4 780 patients were transfused with 1 therapeutic dose of platelets, and 1 047 patients were transfused with 0.5 therapeutic dose of platelets, and the efficacy of platelet transfusion was compared between the two groups. The effects of gender, disease type, white blood cell count before transfusion, fever, number of platelet transfusions, and platelet antibodies on platelet transfusion refractoriness were analyzed using univariate analysis, and the independent risk factors affecting platelet transfusion refractoriness were further analyzed by multivariate logistic regression. [Results] Among 4 780 patients, 3553 (74.3%) were effective and 1 227 (25.7%) were ineffective. Among 1 047 patients, 0.5 platelet infusion was effective in 755 cases (72.1%) and ineffective in 292 cases (27.9%). There was no significant difference in the effective rate of platelet transfusion between the two groups (P>0.05). Univariate analysis showed that the therapeutic effect of platelet transfusion was related to age, the number of platelet transfusion, disease type, platelet antibodies and white blood cell count before transfusion (P<0.05), while age, gender, fever and blood type were not related to the therapeutic effect of platelet transfusion (P>0.05). The results of multi-factor analysis showed that age, white blood cell count >50×10⁹/L, platelet transfusion times, disease type and platelet antibody were independent risk factors for ineffective transfusion (P<0.05). [Conclusion] There is no significant difference in the efficacy of platelet infusion with 0.5 therapeutic dose or 1 therapeutic dose. In addition, age, white blood cell count >50×10⁹/L, the number of platelet transfusion, disease type and platelet antibodies were the factors affecting the ineffective platelet transfusion in group 2.

[Abstract] [Objective] To analyze the detection ability of one imported and three domestic microcolumn agglutination anti-human globulin cards in unexpected antibody screening test. [Methods] A total of 104 positive samples from antibody screening test conducted at our hospital from July to September 2022 were selected. Microcolumn agglutination antiglobulin tests were performed in parallel with antibody screening tests using one imported card (A Card) and three domestic cards (B, C and D Cards ) to analyze the differences in the sensitivity, specificity and agglutination intensity scores. [Results] The sensitivity of the four anti-human globulin cards was as follows: D card 88.51% (131/148) > C card 83.22% (124/149) > B card 81.63% (120/147) > A card 80.54% (120/149); the specificity was A card 97.79% (133/136) > B card 95.65% (132/138) > D card 95.62% (131/137) > C card 93.38% (127/136); and the average agglutination intensity score (points) was D card 214.57 > C card 191.90 > A Card 179.69 > B Card 175.83, and the H value of Kruskal-Wallis test was 7.221, with no statistically significant difference (P > 0.05). Among them, C card was prone to false positives, accounting for 3.16% (9/285), and A card was prone to false negatives, accounting for 10.18% (29/285). [Conclusion] There were differences in the detection ability of anti-human globulin cards of different manufacturers, and some domestic cards have higher detection performance than imported cards. It is recommended to use anti-human globulin cards of two manufacturers routinely in clinical practice, that is, to use cards with high detection sensitivity for antibody screening tests to avoid antibody missed detection as much as possible, and to use cards with high specificity for cross-matching blood tests to avoid delays in transfusion due to false positives, which could hinder transfusion treatment.