29 770例患者红细胞血型意外抗体分布特征及相关因素分析

Analysis of the distribution characteristics and associated factors of unexpected red blood cell antibodies in 29,770 patients

  • 摘要:
    目的 通过对29 770例患者进行红细胞血型意外抗体筛查,分析红细胞血型意外抗体在不同患者人群及疾病中的分布特征,探讨意外抗体产生的相关影响因素,为临床输血安全提供参考依据。
    方法 选取2021年1月至2024年12月在中山大学附属第三医院急诊及住院部申请备血或输血治疗的29 770例患者作为研究对象,采用盐水法、微柱凝胶法进行抗体筛查和抗体鉴定。依据红细胞血型意外抗体检测结果,将患者分为抗体阳性组和抗体阴性组,比较两组患者的临床资料,通过χ2检验和二元Logistic回归分析筛选意外抗体产生的相关影响因素。
    结果 在29 770例申请输血的患者中,共检出意外抗体阳性521例,阳性率为1.75%。对其中228例阳性样本进行了抗体鉴定,结果显示同种抗体占55.26%(以Rh和MNS系统为主),自身抗体占44.74%。在25例混合同种抗体中,以抗-Mia(占44.00%)、抗-E、抗-cE及抗-M参与的抗体组合最为常见。χ2检验结果显示,红细胞血型意外抗体阳性组与阴性组在年龄分布、血型类型上的差异均无统计学意义(P > 0.05),而在性别构成、妊娠史、输血史和红细胞输注量比较差异均有统计学意义(P < 0.01)。二元Logistic回归分析表明,妊娠史、输血史、红细胞输注量(> 5 U)、肝硬化、贫血、消化道出血、急性白血病、系统性红斑狼疮、骨髓增生异常综合征、多发性骨髓瘤是意外抗体阳性的独立相关因素(P < 0.05)。此外,红细胞输注量越大,产生意外抗体的风险越高,呈明显的剂量-效应关系。
    结论 红细胞血型意外抗体以Rh及MNS血型系统为主,其中抗-Mia是混合同种抗体中最常见的组成成分,临床应常规开展红细胞血型意外抗体筛查与特异性鉴定,重点关注有妊娠史、输血史、红细胞输注量 > 5 U以及患有肝硬化、贫血、消化道出血、急性白血病、系统性红斑狼疮、骨髓增生异常综合征、多发性骨髓瘤等疾病的患者,并加强抗-Mia的协同检测,以降低漏检所致的输血风险,切实保障输血安全。

     

    Abstract:
    Objective To screen 29,770 patients for unexpected red blood cell (RBC) antibodies, analyze the distribution characteristics of these antibodies among different patient populations and diseases, explore relevant factors influencing unexpected antibody formation, and provide a reference for clinical transfusion safety.
    Methods A total of 29,770 patients for whom blood preparation was requested or who received transfusion therapy in the emergency department or inpatient wards of the Third Affiliated Hospital of Sun Yat-sen University from January 2021 to December 2024 were included in the study. Antibody screening and identification were performed using the saline method and microcolumn gel method. Based on the results of unexpected RBC antibody testing, the patients were divided into an antibody-positive group and an antibody-negative group. Clinical data were compared between the two groups, and the chi-square test and binary logistic regression analysis were used to identify factors associated with unexpected antibody formation.
    Results Among the 29,770 patients for whom transfusion was requested, 521 tested positive for unexpected antibodies, with a positivity rate of 1.75%. Antibody identification was performed in 228 positive samples. Alloantibodies accounted for 55.26% and predominantly belonged to the Rh and MNS blood group systems, whereas autoantibodies accounted for 44.74%. Among the 25 cases with mixed alloantibodies, the most common combinations were those involving anti-Miᵃ (44.00%), anti-E, anti-cE, and anti-M. The chi-square test showed no statistically significant differences in age distribution or blood group type between the unexpected antibody-positive and antibody-negative groups (P > 0.05), whereas statistically significant differences were observed in sex distribution, pregnancy history, transfusion history, and RBC transfusion volume (P < 0.01). Binary logistic regression analysis showed that pregnancy history, transfusion history, RBC transfusion volume ( > 5 U), liver cirrhosis, anemia, gastrointestinal bleeding, acute leukemia, systemic lupus erythematosus, myelodysplastic syndrome, and multiple myeloma were independent factors associated with unexpected antibody positivity (P < 0.05). In addition, the greater the RBC transfusion volume, the higher the risk of developing unexpected antibodies, with an evident dose-response relationship.
    Conclusions Unexpected RBC antibodies predominantly belonged to the Rh and MNS blood group systems, with anti-Miᵃ being the most common component among mixed alloantibodies. Routine screening and specificity identification of unexpected RBC antibodies should be performed in clinical practice, with particular attention to patients with a history of pregnancy or transfusion, those with an RBC transfusion volume of > 5 U, and those with liver cirrhosis, anemia, gastrointestinal bleeding, acute leukemia, systemic lupus erythematosus, myelodysplastic syndrome, or multiple myeloma. Coordinated testing for anti-Miᵃ should also be strengthened to reduce transfusion risks caused by missed detection and effectively ensure transfusion safety.

     

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