Evidence map›Paper›PMID 40297545›Full record

ArticleJournal of inflammation research2025

Urine Neutrophil Elastase: A Novel Predictor of ICU Admission for Patients with COVID-19 Infection.

Yu Song, Kai Zeng, Li-Kun Zhang, Jian-Nan Zhang, Kai-Li Zhang, Yu Xin, Xin-Ran Wang, Yu-Xin Zhou, Hong-Xu Li, Chang-Song Wang and 1 more

Abstract read
In one paragraph

Article in Journal of inflammation research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Yu SongKey Laboratory of Critical Care Medicine of Heilongjiang Province; Department of Critical Care Medicine, The First Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.
Kai ZengKey Laboratory of Critical Care Medicine of Heilongjiang Province; Department of Critical Care Medicine, The First Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.
Li-Kun ZhangKey Laboratory of Critical Care Medicine of Heilongjiang Province; Department of Critical Care Medicine, The First Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.
Jian-Nan ZhangKey Laboratory of Critical Care Medicine of Heilongjiang Province; Department of Critical Care Medicine, The First Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.ORCID 0000-0002-6342-8931
Kai-Li ZhangKey Laboratory of Critical Care Medicine of Heilongjiang Province; Department of Critical Care Medicine, The First Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.
Yu XinKey Laboratory of Critical Care Medicine of Heilongjiang Province; Department of Critical Care Medicine, The First Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.
Xin-Ran WangKey Laboratory of Critical Care Medicine of Heilongjiang Province; Department of Critical Care Medicine, The First Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.
Yu-Xin ZhouKey Laboratory of Critical Care Medicine of Heilongjiang Province; Department of Critical Care Medicine, The First Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.
Hong-Xu LiKey Laboratory of Critical Care Medicine of Heilongjiang Province; Department of Critical Care Medicine, The First Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.
Chang-Song WangKey Laboratory of Critical Care Medicine of Heilongjiang Province; Department of Critical Care Medicine, The First Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.
Kai-Jiang YuKey Laboratory of Critical Care Medicine of Heilongjiang Province; Department of Critical Care Medicine, The First Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: We aimed to explore the differences of neutrophil elastase (NE) levels between intensive care unit (ICU) and non-ICU patients with COVID-19 infection, as well as its predictive value for COVID-19 progression. Methods: We enrolled the patients admitted with a primary diagnosis of COVID-19. All patients in ICU were diagnosed with the critical type upon admission. Blood was taken within 24 hours, followed by examination of the blood NE level and urine NE level. Other clinical features were recorded. A logistic regression model was used to predict ICU admission. Results: A total of 83 patients were diagnosed, including 52 non-ICU cases and 31 ICU cases. The ICU group showed significantly elevated levels of Neutrophil%, Cr, D-dimer (DD), Procalcitonin (PCT), and C-reactive protein (CRP). Meanwhile, the CD3-cell, T4-cell, and Lymphocyte% levels were lower in the ICU group. Notably, the blood NE levels were similar between groups, whereas the urine NE level was highly significantly higher in the ICU group vs the non-ICU group. After dimension reduction, we constructed a logistic model (UD) using only two factors: the urine NE level and the blood DD level. The overall accuracy of was 86.1%. The urine NE has a strong efficacy in ICU prediction (AUC = 0.893), and the performance of the UD model was even better (AUC = 0.933). Conclusion: Urine NE level is a useful predictor of COVID-19 progression, particularly in patients requiring ICU care. Urine NE has a significantly positive correlation with neutrophil%, DD, and PCT, as well as a negative correlation with lymphocyte levels.

Indexed as

acute respiratory distress syndromeARDSCOVID-19intensive care unitneutrophil elastaseurine

Identifiers

PMID40297545
PMCPMC12036589

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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.