Predictive value of arterial blood lactate to serum albumin ratio for in-hospital mortality of patients with community-acquired pneumonia admitted to the Intensive Care Unit.

IF 2.6 4区 医学 Q1 MEDICINE, GENERAL & INTERNAL Postgraduate Medicine Pub Date : 2023-04-01 DOI:10.1080/00325481.2022.2110769
Chaoqun Xu, Haoran Liu, Hao Zhang, Jun Zeng, Quan Li, Yang Yi, Nan Li, Ruxin Cheng, Qi Li, Xiangdong Zhou, Chuanzhu Lv
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引用次数: 2

Abstract

Objective: To investigate the predictive value of the arterial blood lactate to serum albumin ratio (LAR) on in-hospital mortality of patients with community-acquired pneumonia (CAP) admitted to the Intensive Care Unit (ICU).

Methods: Clinical datasets of 1720 CAP patients admitted to ICU from MIMIC-IV database were retrospectively analyzed. Patients were randomly assigned to the training cohort (n=1204) and the validation cohort (n=516) in a ratio of 7:3. X-tile software was used to find the optimal cut-off value for LAR. The receiver operating curve (ROC) analysis was conducted to compare the performance between LAR and other indicators. Univariate and multivariate Cox regression analyses were applied to select prognostic factors associated with in-hospital mortality. Based on the observed prognostic factors, a nomogram model was created in training cohort, and the validation cohort was utilized to further validate the nomogram.

Results: The optimal cut-off value for LAR in CAP patients admitted to ICU was 1.6 (the units of lactate and albumin were, respectively, 'mmol/L' and 'g/dL'). The ROC analysis showed that the discrimination abilities of LAR were superior to other indicators except Sequential Organ Failure Assessment score and Simplified acute physiology score (SAPSII), which had the same abilities. Age, mean arterial pressure, SpO2, heart rate, SAPSII score, neutrophil-to-lymphocyte ratio, and LAR were found to be independent predictors of poor overall survival in the training cohort by multivariate Cox regression analysis and were incorporated into the nomogram for in-hospital mortality as independent factors. The nomogram model, exhibiting medium discrimination, had a C-index of 0.746 (95% CI = 0.715-0.777) in the training cohort and 0.716 (95% CI = 0.667-0.765) in the validation cohort.

Conclusion: LAR could predict in-hospital mortality of patients with CAP admitted to ICU independently as a readily accessible biomarker. The nomogram that included LAR with other independent factors performed well in predicting in-hospital mortality.

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动脉血乳酸/血清白蛋白比值对社区获得性肺炎住院患者死亡率的预测价值
目的:探讨动脉血乳酸/血清白蛋白比(LAR)对重症监护病房(ICU)社区获得性肺炎(CAP)患者住院死亡率的预测价值。方法:回顾性分析MIMIC-IV数据库中1720例ICU住院CAP患者的临床资料。患者按7:3的比例随机分配到训练组(n=1204)和验证组(n=516)。利用X-tile软件寻找LAR的最佳截止值。采用受试者工作曲线(ROC)分析比较LAR与其他指标的表现。采用单因素和多因素Cox回归分析选择与住院死亡率相关的预后因素。根据观察到的预后因素,在训练队列中建立nomogram模型,并利用验证队列进一步验证nomogram。结果:ICU住院CAP患者LAR的最佳临界值为1.6(乳酸和白蛋白单位分别为“mmol/L”和“g/dL”)。ROC分析显示,除序期器官衰竭评分和简化急性生理评分(SAPSII)外,LAR的识别能力优于其他指标,两者的识别能力相同。通过多变量Cox回归分析发现,年龄、平均动脉压、SpO2、心率、SAPSII评分、中性粒细胞与淋巴细胞比率和LAR是训练队列中总生存率差的独立预测因子,并作为独立因素纳入住院死亡率的nomogram。训练组和验证组的c指数分别为0.746 (95% CI = 0.715-0.777)和0.716 (95% CI = 0.667-0.765)。结论:LAR作为一种易于获取的生物标志物,可预测独立入住ICU的CAP患者的住院死亡率。包括LAR与其他独立因素的nomogram在预测院内死亡率方面表现良好。
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来源期刊
Postgraduate Medicine
Postgraduate Medicine 医学-医学:内科
CiteScore
6.10
自引率
2.40%
发文量
110
审稿时长
6-12 weeks
期刊介绍: Postgraduate Medicine is a rapid peer-reviewed medical journal published for physicians. Tracing its roots back to 1916,  Postgraduate Medicine  was established by Charles Mayo, MD, as a peer-to-peer method of communicating the latest research to aid physicians when making treatment decisions, and it maintains that aim to this day. In addition to its core subscriber base, Postgraduate Medicine is distributed to hundreds of US-based physicians within internal medicine and family practice.
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