Evidence map›Paper›PMID 37726414›Full record

ArticleScientific reports2023

Predictive value of ELWI combined with sRAGE/esRAGE levels in the prognosis of critically ill patients with acute respiratory distress syndrome.

Chengliang Zhang, Dekun Yin, Xi Zhu, Wenshuo Zhou, Zhihua Xu, Liuping Wu, Weili Gu

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Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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7 authors.

Chengliang Zhang *Department of Intensive Care Medicine, The Second Affiliated Hospital of Nantong University, 6# North Road, Child Lane, Chongchuan District, Nantong, 226001, Jiangsu, China.
Dekun Yin *Department of Anesthesiology, Funing People's Hospital of Jiangsu, Yancheng, 224400, Jiangsu Province, China.
Xi ZhuGrade 21, Clinical Medicine, Nantong University Medical School, Nantong, 226001, Jiangsu, China.
Wenshuo ZhouDepartment of Intensive Care Medicine, The Second Affiliated Hospital of Nantong University, 6# North Road, Child Lane, Chongchuan District, Nantong, 226001, Jiangsu, China.
Zhihua XuDepartment of Intensive Care Medicine, The Second Affiliated Hospital of Nantong University, 6# North Road, Child Lane, Chongchuan District, Nantong, 226001, Jiangsu, China.
Liuping WuDepartment of Anesthesiology, Affiliated Hospital of Nantong University, Nantong, 226001, China. wuliuping_ntu@163.com.
Weili GuDepartment of Intensive Care Medicine, The Second Affiliated Hospital of Nantong University, 6# North Road, Child Lane, Chongchuan District, Nantong, 226001, Jiangsu, China. guweili1980@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute respiratory distress syndrome (ARDS) is a life-threatening condition. Accurate judgement of the disease progression is essential for controlling the condition in ARDS patients. We investigated whether changes in the level of serum sRAGE/esRAGE could predict the 28-day mortality of ICU patients with ARDS. A total of 83 ARDS patients in the ICU of the Second Affiliated Hospital of Nantong University from January 2021 to June 2022 were consecutively enrolled in this study. Demographic data, primary diagnosis and comorbidities were obtained. Multiple scoring systems, real-time monitoring systems, and biological indicators were determined within 6 h of admission. The clinical parameters for survival status of the ARDS patients were identified by multivariate logistic regression. Receiver operating characteristic (ROC) curve analysis was employed to verify the accuracy of the prognosis of the related parameters. The admission level of sRAGE was significantly higher in the nonsurvival group than in the survival group (p < 0.05), whereas the serum esRAGE level showed the opposite trend. Multivariate logistic regression analysis showed that sRAGE (AUC 0.673, p < 0.05), esRAGE (AUC 0.704, p < 0.05), and ELWI (extravascular lung water index) (AUC 0.717, p < 0.05) were independent risk factors for the prognosis of ARDS. Model B (ELWI + esRAGE) could not be built as a valid linear regression model (ELWI, p = 0.079 > 0.05). Model C (esRAGE + sRAGE) was proven to have no significance because it had a predictive value similar to that of the serum levels of esRAGE (Z = 0.993, p = 0.351) or sRAGE (Z = 1.116, p = 0.265) alone. Subsequently, Model D (sRAGE + esRAGE + ELWI) showed the best 28-day mortality predictive value with a cut-off value of 0.426 (AUC 0.841; p < 0.001), and Model A (sRAGE + ELWI) had a cut-off value of 0.401 (AUC 0.820; p < 0.001), followed by sRAGE (AUC 0.704, p = 0.004), esRAGE (AUC 0.717, p = 0.002), and ELWI (AUC 0.637, p = 0.028). In addition, there was no statistically significant difference between Model A and Model D (Z = 0.966, p = 0.334). The admission level of sRAGE was higher in the nonsurvival group, while the serum esRAGE level showed the opposite trend. Model A and Model D could be used as reliable combined prediction models for predicting the 28-day mortality of ARDS patients.

Indexed as

Critical IllnessRespiratory Distress SyndromeComputer SystemsDisease ProgressionHumansPrognosis

Identifiers

PMID37726414
PMCPMC10509270

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.