Song Zishu, Gao Ting, Gao Liangfeng, Zhu Mingli, Feng Nan
Emergency Department, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China.
Department of Critical Care Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China.
Sci Rep. 2025 Aug 29;15(1):31820. doi: 10.1038/s41598-025-17170-3.
To explore the associations between temperature trajectories and in-hospital mortality and renal replacement therapy in patients with sepsis-associated acute kidney injury (SA-AKI). By using data from the Medical Information Mart for Intensive Care (MIMIC)-IV, participants were divided into three groups (≤ 36 °C, 36-38 °C, ≥ 38 °C). We identified body temperature trajectories by a latent class mixed model and explored the associations of these trajectories with in-hospital mortality using Cox hazard proportional regression models, further exploring the associations with renal replacement therapy using logistic regression models. Total 1,831 in-hospital deaths during 9,760 person-years of follow-up were documented. In the hypothermia group, five different temperature trajectory classes were identified: L1, L2, L3, L4, and L5. Similarly, four trajectory classes (M1, M2, M3, and M4) emerged in the normal temperature group, whereas the hyperthermia group presented four distinct trajectory classes (H1, H2, H3, and H4). Compared with patients with the M3 trajectory, those with the L1 (hazard ratio [HR]: 2.41, 95% confidence interval [CI]: 1.58-3.66), L2 (HR: 1.48, 95% CI 1.11-1.97), L3 (HR: 1.27, 95% CI 1.01-1.59), L4 (HR: 1.29, 95% CI 1.08-1.54), and M1 (HR: 1.29, 95% CI 1.06-1.57) trajectories were at greater risk of in-hospital mortality. For patients with different baseline temperatures, the L1 (HR: 1.95, 95% CI 1.19-3.18), M1 (HR: 1.28, 95% CI 1.05-1.56), and H4 (HR: 2.37, 95% CI 1.05-5.36) trajectories were related to an elevated risk of in-hospital mortality. The study suggests that early body temperature trajectories are linked to increased in-hospital mortality risk in patients with SA-AKI.
探讨脓毒症相关性急性肾损伤（SA-AKI）患者体温轨迹与院内死亡率及肾脏替代治疗之间的关联。利用重症监护医学信息数据库（MIMIC）-IV中的数据，将参与者分为三组（≤36°C、36 - 38°C、≥38°C）。我们通过潜在类别混合模型确定体温轨迹，并使用Cox风险比例回归模型探讨这些轨迹与院内死亡率的关联，进一步使用逻辑回归模型探讨与肾脏替代治疗的关联。在9760人年的随访期间共记录了1831例院内死亡病例。在体温过低组中，识别出五种不同的体温轨迹类别：L1、L2、L3、L4和L5。同样，正常体温组出现了四种轨迹类别（M1、M2、M3和M4），而体温过高组呈现出四种不同的轨迹类别（H1、H2、H3和H4）。与具有M3轨迹的患者相比，具有L1（风险比[HR]：2.41，95%置信区间[CI]：1.58 - 3.66）、L2（HR：1.48，95%CI 1.11 - 1.97）、L3（HR：1.27，95%CI 1.01 - 1.59）、L4（HR：1.29，95%CI 1.08 - 1.54）和M1（HR：1.29，95%CI 1.06 - 1.57）轨迹的患者院内死亡风险更高。对于具有不同基线体温的患者，L1（HR：1.95，95%CI 1.19 - 3.18）、M1（HR：1.28，95%CI 1.05 - 1.56）和H4（HR：2.37，95%CI 1.05 - 5.36）轨迹与院内死亡风险升高相关。该研究表明，早期体温轨迹与SA-AKI患者院内死亡风险增加有关。
