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<p>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&#xa0;°C, 36–38&#xa0;°C, ≥ 38&#xa0;°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.</p>

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Early body temperature trajectories and short term prognosis in sepsis associated acute kidney injury

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月29日

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  • Zishu Song,
  • Ting Gao,
  • Liangfeng Gao,
  • Mingli Zhu,
  • Nan Feng

摘要

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.