Evidence map›Paper›PMID 34408466›Full record

ArticleJournal of inflammation research2021

Early Elevation of Thioredoxin-1 Serum Levels Predicts 28-Day Mortality in Patients with Sepsis.

Xing Li, Hua Shen, Tinghong Zhou, Xiaoyu Cao, Ying Chen, Yan Liang, Ting Lu, JiaFen He, ZhouLin Dou, ChuaiKai Liu and 2 more

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Journal of inflammation research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.4field-weighted citation impact, top 42% of its field
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

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Frontiers in immunology · 2026
    Article
  4. Review
  5. The Importance of Thioredoxin-1 in Health and Disease.Antioxidants (Basel, Switzerland) · 2023
    Review
  6. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 1 institution in 1 country.

Xing Li *Department of Critical Care, Changsha of Traditional Chinese Medicine Hospital, Changsha, 410010, Hunan Province, People's Republic of China.
Hua Shen *Department of Critical Care, Changsha of Traditional Chinese Medicine Hospital, Changsha, 410010, Hunan Province, People's Republic of China.
Tinghong ZhouDepartment of Critical Care, Changsha of Traditional Chinese Medicine Hospital, Changsha, 410010, Hunan Province, People's Republic of China.
Xiaoyu CaoDepartment of Critical Care, Changsha of Traditional Chinese Medicine Hospital, Changsha, 410010, Hunan Province, People's Republic of China.
Ying ChenDepartment of Critical Care, Changsha of Traditional Chinese Medicine Hospital, Changsha, 410010, Hunan Province, People's Republic of China.
Yan LiangDepartment of Critical Care, Changsha of Traditional Chinese Medicine Hospital, Changsha, 410010, Hunan Province, People's Republic of China.
Ting LuDepartment of Critical Care, Changsha of Traditional Chinese Medicine Hospital, Changsha, 410010, Hunan Province, People's Republic of China.
JiaFen HeDepartment of Critical Care, Changsha of Traditional Chinese Medicine Hospital, Changsha, 410010, Hunan Province, People's Republic of China.
ZhouLin DouDepartment of Critical Care, Changsha of Traditional Chinese Medicine Hospital, Changsha, 410010, Hunan Province, People's Republic of China.
ChuaiKai LiuDepartment of Critical Care, Changsha of Traditional Chinese Medicine Hospital, Changsha, 410010, Hunan Province, People's Republic of China.
Yong TangDepartment of Critical Care, Changsha of Traditional Chinese Medicine Hospital, Changsha, 410010, Hunan Province, People's Republic of China.
Zeixang ZhuDepartment of Critical Care, Changsha of Traditional Chinese Medicine Hospital, Changsha, 410010, Hunan Province, People's Republic of China.
Hunan Academy of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSepsis is the leading cause of death in critically ill patients, and the prevention of which requires precise outcome prediction and early intervention. We evaluated the prognostic prediction value of serum thioredoxin-1 (Trx-1) as an anti-inflammatory factor in patients with sepsis.

methodsAs a prospective study, patients with sepsis admitted to the intensive care unit (ICU) of our hospital during 2020 were recruited. Medical history collection, sequential organ failure assessment (ΔSOFA), and laboratory tests were performed within 24 h of admission. Serum levels of Trx-1 and other inflammatory biomarkers were detected with samples dynamically collected before, during, and after septic shock. Patients were categorized as survivors and non-survivors according to survival status on day 28. Correlation between Trx-1 and other sepsis-associated parameters as well as the correlation of Trx-1 and other sepsis-associated parameters with 28-day mortality were evaluated. Prognostic factors were identified by Cox regression analyses.

resultsA total of 187 patients were recruited. Serum Trx-1 level was positively correlated with inflammatory factors (interleukin-6, C-reactive protein, procalcitonin) and index of sepsis severity (ΔSOFA score, partial pressure of oxygen/fraction of inspired oxygen), all of which were significantly higher in non-survivors than survivors. While Trx-1 level at different timepoints and its evolution over time significantly differed between survivors and non-survivors, the initial Trx-1 level outperformed the other parameters in predicting 28-day survival. With 38.27 ng/mL as the cutoff value, serum Trx-1 predicted 28-day survival with optimal sensitivity and specificity.

conclusionEarly increases in serum levels of Trx-1 can predict 28-day mortality in sepsis patients in the ICU.

Indexed as

mortalityprognosissepsisthioredoxin-1

Identifiers

PMID34408466
PMCPMC8364846
OpenAlexW3192299773

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.