Evidence map›Paper›PMID 33488604›Full record

ArticleFrontiers in immunology2020

The Trajectory of Alterations in Immune-Cell Counts in Severe-Trauma Patients Is Related to the Later Occurrence of Sepsis and Mortality: Retrospective Study of 917 Cases.

Xijie Dong, Chuntao Wang, Xinghua Liu, Xiangjun Bai, Zhanfei Li

Open access · goldAbstract readComparative Study
In one paragraph

Article in Frontiers in immunology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

12 citing papers in PubMed, 19 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Absolute lymphocyte count trajectory predicts clinical outcome in severely injured patients.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2025
    Article
  5. Article
  6. Clinical impact of transient lymphopenia.Clinical and experimental medicine · 2024
    Article
  7. Article
  8. Observational
  9. Article
  10. Article
  11. Article
  12. Hepatocyte-derived Microparticles as Novel Biomarkers for the Diagnosis of Deep Venous Thrombosis in Trauma Patients.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
    Article
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

5 authors at 2 institutions in 1 country.

Xijie DongTrauma Center, Department of Emergency and Traumatic Surgery, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Chuntao WangTrauma Center, Department of Emergency and Traumatic Surgery, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Xinghua LiuTrauma Center, Department of Emergency and Traumatic Surgery, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Xiangjun BaiTrauma Center, Department of Emergency and Traumatic Surgery, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zhanfei LiTrauma Center, Department of Emergency and Traumatic Surgery, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Tongji Hospital · CNHuazhong University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Severe trauma is believed to disrupt the homeostasis of the immune system, and lead to dramatic changes in the circulating immune-cell count (ICC). The latter fluctuates widely over time. Knowledge about the relationship between these dramatic changes and dynamic fluctuations and the late prognosis of trauma patients is sparse. We investigated the relationship between the trajectory of alterations in the circulating ICC within 7 days in severe-trauma patients and subsequent sepsis and mortality. Methods: A retrospective analysis of 917 patients with an Injury Severity Score ≥16 was undertaken. The absolute neutrophil, lymphocyte, and monocyte counts (ANC, ALC, and AMC, respectively) on days 1, 3, and 7 (D1, D3, and D7, respectively) after trauma, and whether sepsis or death occurred within 60 days, were recorded. As the disordered circulating ICCs fluctuated widely, their time-varying slopes (D3/D1 and D7/D3) were calculated. Patients were divided into "sepsis" and "non-sepsis" groups, as well as "alive" and "death" groups. Comparative studies were conducted between every two groups. Univariate and multivariate logistic regression analyses were used to identify variables related to the risk of sepsis and mortality. Receiver operating characteristic curves were plotted to assess the predictive value of various risk factors. Results: More severe trauma caused more pronounced increases in the ANC and slower recovery of the ALC within 7 days. The ALC (D3), ANC (D7), ALC (D3/D1), and ANC (D7/D3) were independent risk factors for sepsis. The ALC (D3), ALC (D7), AMC (D7), and ALC (D3/D1) were independent risk factors for mortality. A combination of the ALC (D3) and ALC (D3/D1) exerted a good predictive value for sepsis and death. Conclusions: The trajectory of alterations in the circulating ICC in the early stage after trauma is related to subsequent sepsis and mortality.

Indexed as

AdultFemaleHumansInjury Severity ScoreLymphocyte CountLymphocytesMaleMiddle AgedMonocytesNeutrophilsPredictive Value of TestsPrognosisRetrospective StudiesRisk AssessmentRisk FactorsSepsislymphocytemonocytemortalityneutrophilsepsistrauma

Identifiers

PMID33488604
PMCPMC7820769
OpenAlexW3118560606

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.