Yang Penglei, Yuan Jun, He Jie, Yu Lina, Gu Xue, Ding Xizhen, Chen Qihong
Department of Critical Care Medicine, Jiangdu People's Hospital Affiliated to Yangzhou University, Yangzhou, China.
Department of Emergency Medicine, Yangzhou Jiangdu Traditional Chinese Medicine Hospital, Yangzhou, China.
Front Pharmacol. 2025 Aug 28;16:1615618. doi: 10.3389/fphar.2025.1615618. eCollection 2025.
This study utilized the causal forest algorithm to explore the heterogeneity of treatment effects of low-dose red blood cell (RBC) transfusion on the 90-day survival rate of sepsis patients with hemoglobin (Hb) levels of 7-9 g/dL to develop personalized transfusion strategies.
The data of patients the met the Sepsis-3 criteria with a minimum Hb level of 7-9 g/dL were obtained from the MIMIC-IV and MIMIC-III databases and divided into RBC transfusion and non-transfusion groups. Patients in both groups were paired using a propensity score matching analysis (PSM) after which a causal forest model was constructed using MIMIC-IV data. The model's accuracy was analyzed using out-of-bag data. Individual treatment effects (ITE) of MIMIC-III patients were predicted and categorized into four subgroups: Quantile1 to Quantile4, based on the effect size. Kaplan-Meier survival curves were established for each Quantile to determine the survival rates.
The MIMIC-IV and MIMIC-III database comprised 1,652 and 868 patients, with 826 (50%) and 434 (50%) in the RBC transfusion group, respectively, after PSM. The mean prediction coefficient estimated by the causal forest was 1.00 with a standard error of 0.57, while the differential forest prediction coefficient was 1.64 with a standard error of 0.48, demonstrating the model's ability to effectively identify differences in the impact of transfusion on survival rates among individuals. There was significant heterogeneity in the ITE among patients in the MIMIC-III validation cohort. Moreover, the ITE values were divided into Quantile1: -5.4% (-8.0%, -3.9%), Quantile2: -2.1% (-2.6%, -1.7%), Quantile3: -0.5% (-0.1%, +0.1%), and Quantile 4: +3.6% (+2.0%, +6.6%). The Kaplan-Meier curves and the log-rank test demonstrated that the RBC transfusion decreased the survival of patients in Quantile1 (p < 0.001) and Quantile2 (p = 0.011) but increased the survival of patients in Quantile4 (p < 0.001).
RBC transfusions among sepsis patients with Hb levels of 7-9 g/dL exhibit heterogenous treatment effects, which reduces the mortality of patients with high ITE. Although the causal forest model can guide personalized transfusion in these cases, randomized controlled trials are needed to validate these findings.
本研究利用因果森林算法探讨低剂量红细胞（RBC）输注对血红蛋白（Hb）水平为7 - 9 g/dL的脓毒症患者90天生存率的治疗效果异质性，以制定个性化输血策略。
从MIMIC-IV和MIMIC-III数据库中获取符合Sepsis-3标准且最低Hb水平为7 - 9 g/dL的患者数据，并分为RBC输血组和非输血组。两组患者采用倾向评分匹配分析（PSM）进行配对，之后使用MIMIC-IV数据构建因果森林模型。利用袋外数据分析模型的准确性。预测MIMIC-III患者的个体治疗效果（ITE），并根据效应大小分为四个亚组：分位数1至分位数4。为每个分位数建立Kaplan-Meier生存曲线以确定生存率。
MIMIC-IV和MIMIC-III数据库分别包含1652例和868例患者，PSM后RBC输血组分别有826例（50%）和434例（50%）。因果森林估计的平均预测系数为1.00，标准误差为0.57，而差异森林预测系数为1.64，标准误差为0.48，表明该模型能够有效识别输血对个体生存率影响的差异。MIMIC-III验证队列患者的ITE存在显著异质性。此外，ITE值分为分位数1：-5.4%（-8.0%，-3.9%），分位数2：-2.1%（-2.6%，-1.7%），分位数3：-0.5%（-0.1%，+0.1%），分位数4：+3.6%（+2.0%，+6.6%）。Kaplan-Meier曲线和对数秩检验表明，RBC输血降低了分位数1患者的生存率（p < 0.001）和分位数2患者的生存率（p = 0.011），但提高了分位数4患者的生存率（p < 0.
