败血症患者红细胞分布宽度的三种不同轨迹及其与死亡率的显著关联：一项基于组的轨迹建模研究及其验证

摘要(中文译文)

红细胞分布宽度（RDW）是脓毒症中公认的预后标志物，但其随时间动态变化及其与结局的关系尚未被探索。本研究旨在识别脓毒症早期不同的RDW轨迹，并评估其与死亡率的关系。我们开展了一项回顾性队列研究，使用MIMIC-IV数据库（n=3,813）作为推导队列，并使用昆明医科大学第一附属医院（n=467）的数据进行外部单中心验证。纳入在住院前10天内至少有7次RDW测量的脓毒症患者。采用基于组的轨迹模型（GBTM）识别RDW轨迹。基于模型拟合指标和临床可解释性，最终选择三轨迹模型：轨迹1（缓慢下降型，32.97%）、轨迹2（缓慢上升型，43.30%）和轨迹3（波动-快速下降型，23.73%）。在我们的研究中，经混杂因素调整的Cox模型显示，与轨迹1相比，轨迹3与30天死亡率（HR 1.47，95% CI 1.17-1.84）和90天死亡率（HR 1.54，95% CI 1.25-1.88）显著升高独立相关。相反，轨迹2与最有利的生存率相关。Kaplan-Meier分析一致显示轨迹3组死亡率最高。外部验证证实了模型的稳健性以及所识别轨迹一致的预后价值。本研究首次应用轨迹建模在脓毒症患者中识别出三条具有显著预后分层意义的动态RDW轨迹。其中，“波动-快速下降”轨迹是30天和90天死亡率的独立危险因素。然而，由于RDW检测频率的限制，本研究可能代表了病情更严重的人群，这可能限制结论的普遍适用性。这一发现将传统指标RDW提升为一种动态且实用的床旁风险分层工具，可能有助于临床医生早期识别高危患者。

Abstract

The red cell distribution width (RDW) is a recognized prognostic marker in sepsis, yet its dynamic changes over time and their relationship with outcomes remain unexplored. This study aimed to identify distinct RDW trajectories during the early phase of sepsis and evaluate their association with mortality. We conducted a retrospective cohort study using data from the MIMIC-IV database ( = 3,813) as the derivation cohort and from the First Affiliated Hospital of Kunming Medical University ( = 467) for external single-center validation. Sepsis patients with at least seven RDW measurements within the first 10 days of hospitalization were included. Group-based trajectory modeling (GBTM) was employed to identify RDW trajectories. A three-trajectory model was selected based on model fit indices and clinical interpretability: Trajectory 1 (Slow-Decrease, 32.97%), Trajectory 2 (Slow-Increase, 43.30%), and Trajectory 3 (Fluctuating-Rapid Decrease, 23.73%). In our study, Cox models adjusted for confounders revealed that, compared to Trajectory 1, Trajectory 3 was independently associated with significantly increased 30-day (HR 1.47, 95% CI 1.17-1.84) and 90-day mortality (HR 1.54, 95% CI 1.25-1.88). Conversely, Trajectory 2 was associated with the most favorable survival rates. Kaplan-Meier analysis consistently showed the highest mortality in the Trajectory 3 group. External validation confirmed the model's robustness and the consistent prognostic value of the identified trajectories. This study is the first to apply trajectory modeling to identify three dynamic RDW trajectories with significant prognostic stratification in sepsis patients. Among them, the "fluctuating-rapid decline" trajectory is an independent risk factor for both 30-day and 90-day mortality. However, due to the limitation of RDW testing frequency, the study may represent a group with more severe illness, which may limit the generalizability of the conclusions. This discovery elevates the conventional indicator RDW into a dynamic and practical bedside risk stratification tool, which may assist clinicians in early identification of high-risk patients.

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