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脓毒症患者体温与全因死亡率之间的关联:MIMIC-IV数据库分析

Association between body temperature and all-cause mortality in patients with sepsis: analysis of the MIMIC-IV database.

作者信息

Zhao Yunuo, Zhang Bo

机构信息

Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China.

Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China.

出版信息

Eur J Med Res. 2024 Dec 26;29(1):630. doi: 10.1186/s40001-024-02219-2.

DOI:10.1186/s40001-024-02219-2
PMID:39726025
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11673708/
Abstract

BACKGROUND

Abnormal body temperature (fever or hypothermia) is a critical symptom in sepsis and is strongly associated with clinical prognosis and disease progression. Given the duality and variability of body temperature fluctuations throughout the disease course, further research is essential to refine clinical strategies for temperature management in sepsis patients.

METHODS

We extracted clinical data of sepsis patients from the MIMIC-IV database. A restricted cubic spline (RCS) curve was employed to describe the non-linear relationship between body temperature and clinical outcomes. Based on peak temperature within the first 24 h after admission, patients were categorized into three groups: < 36 °C, 36-38 °C, and > 38 °C. We subsequently matched patients one-to-one into three cohorts using a pairwise propensity score matching (PSM) approach. Alongside clinical data, we conducted log-rank and McNemar tests, and established multiple models, including multiple Cox regression, overlap-weighted (OW) adjusted Cox regression, multiple logistic regression, and OW-adjusted multiple logistic regression, to investigate the impact of temperature on clinical outcomes.

RESULTS

A total of 35,499 sepsis patients were included in my study: 311 with a temperature below 36 °C, 27,538 with a temperature between 36 and 38 °C, and 7650 with a temperature above 38 °C. The RCS analysis revealed a non-linear, U-shaped relationship between body temperature and 28-day, ICU, and in-hospital mortality. Patients with hypothermia had significantly higher 28-day mortality (54.34% vs. 19.28%), ICU mortality (44.37% vs. 12.89%), and in-hospital mortality (49.20% vs. 17.46%) compared to those with hyperthermia. Among patients younger than 65 years, hyperthermia was a protective factor against 28-day mortality relative to normal body temperature, while the opposite was observed in patients aged 65 and older. This trend was consistent in the analysis of ICU and in-hospital mortality.

CONCLUSIONS

Among sepsis patients admitted to the ICU, a peak temperature below 36 °C within the first 24 h of admission was associated with higher 28-day mortality. However, no significant difference in clinical prognosis was observed between normothermic and hyperthermic patients.

摘要

背景

体温异常(发热或体温过低)是脓毒症的关键症状,与临床预后和疾病进展密切相关。鉴于疾病过程中体温波动的二元性和变异性,进一步研究对于完善脓毒症患者体温管理的临床策略至关重要。

方法

我们从MIMIC-IV数据库中提取了脓毒症患者的临床数据。采用受限立方样条(RCS)曲线来描述体温与临床结局之间的非线性关系。根据入院后24小时内的最高体温,将患者分为三组:<36°C、36-38°C和>38°C。随后,我们使用成对倾向评分匹配(PSM)方法将患者一对一匹配为三个队列。除临床数据外,我们进行了对数秩检验和McNemar检验,并建立了多个模型,包括多元Cox回归、重叠加权(OW)调整的Cox回归、多元逻辑回归和OW调整的多元逻辑回归,以研究体温对临床结局的影响。

结果

我的研究共纳入35499例脓毒症患者:311例体温低于36°C,27538例体温在36至38°C之间,7650例体温高于38°C。RCS分析显示体温与28天、ICU和住院死亡率之间存在非线性U形关系。与体温过高的患者相比,体温过低的患者28天死亡率(54.34%对19.28%)、ICU死亡率(44.37%对12.89%)和住院死亡率(49.20%对17.46%)显著更高。在65岁以下的患者中,相对于正常体温,体温过高是28天死亡率的保护因素,而在65岁及以上的患者中则观察到相反的情况。这一趋势在ICU和住院死亡率分析中是一致的。

结论

在入住ICU的脓毒症患者中,入院后24小时内最高体温低于36°C与28天死亡率较高相关。然而,体温正常和体温过高的患者在临床预后方面未观察到显著差异。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3e2/11673708/eb51be7e7ba3/40001_2024_2219_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3e2/11673708/ac3c3dc85b88/40001_2024_2219_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3e2/11673708/16ae7d49dc89/40001_2024_2219_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3e2/11673708/e55d932c2234/40001_2024_2219_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3e2/11673708/ed7d57c6901c/40001_2024_2219_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3e2/11673708/eb51be7e7ba3/40001_2024_2219_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3e2/11673708/ac3c3dc85b88/40001_2024_2219_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3e2/11673708/16ae7d49dc89/40001_2024_2219_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3e2/11673708/e55d932c2234/40001_2024_2219_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3e2/11673708/ed7d57c6901c/40001_2024_2219_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3e2/11673708/eb51be7e7ba3/40001_2024_2219_Fig5_HTML.jpg

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