Evidence map›Paper›PMID 36687421›Full record

ArticleFrontiers in medicine2022

Monocyte subtype expression patterns in septic patients with diabetes are distinct from patterns observed in obese patients.

Dan Ning, Kunal Garg, Benjamin Mayer, Benedikt Schick, Hendrik Bracht, Eberhard Barth, Manfred Weiss, Chen Li, Julian Schneider, E Marion Schneider

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 26% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. The Modulation of Septic Shock: A Proteomic Approach.International journal of molecular sciences · 2024
    Article
  4. 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

10 authors at 2 institutions in 1 country.

Dan NingClinic for Anaesthesiology and Intensive Care Medicine, Ulm University Hospital, Ulm, Germany.
Kunal GargClinic for Anaesthesiology and Intensive Care Medicine, Ulm University Hospital, Ulm, Germany.
Benjamin MayerFaculty of Medicine, Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany.
Benedikt SchickClinic for Anaesthesiology and Intensive Care Medicine, Ulm University Hospital, Ulm, Germany.
Hendrik BrachtClinic for Anaesthesiology and Intensive Care Medicine, Ulm University Hospital, Ulm, Germany.
Eberhard BarthClinic for Anaesthesiology and Intensive Care Medicine, Ulm University Hospital, Ulm, Germany.
Manfred WeissClinic for Anaesthesiology and Intensive Care Medicine, Ulm University Hospital, Ulm, Germany.
Chen LiClinic for Anaesthesiology and Intensive Care Medicine, Ulm University Hospital, Ulm, Germany.
Julian SchneiderClinic for Anaesthesiology and Intensive Care Medicine, Ulm University Hospital, Ulm, Germany.
E Marion SchneiderClinic for Anaesthesiology and Intensive Care Medicine, Ulm University Hospital, Ulm, Germany.
University Hospital Ulm · DEUniversität Ulm · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sepsis causes a high rate of mortality and long-term morbidity, associated with an imbalance of innate immunity against infections and inflammation. Obesity and diabetes increase the risk for disease severity. Monocyte dysfunction plays a major role and justify further investigations. Objective: To investigate the distribution and inflammatory phenotypes in circulating monocyte subsets in patients manifesting with sepsis including septic shock with and without obesity and diabetes. Methods: A total of 235 blood samples were tested from critically ill adult patients registered at the intensive care unit (ICU). The cohorts were divided into non-diabetic groups with or without obesity and diabetic groups with or without obesity, suffering from sepsis or septic shock. We determined frequencies of total monocytes and of monocyte subsets in the circulation and density expression levels of functional markers, including CD14, CD16, HLA-DR, CD33, CD163, CD206, and arginase-1 by flow cytometric analysis. Results: When progressing to septic shock in non-diabetic and diabetic patients, the percentages of total monocytes among the leukocyte population and of CD33+ and CD14+ monocytes among the monocyte population were consistently down-regulated compared to non-sepsis in non-diabetic and diabetic patients, respectively. Non-diabetic sepsis patients further presented with decreased CD33 and up-regulated CD163 expression density, which was absent in diabetic patients. We subsequently addressed obesity-related changes of monocytes in non-diabetic and diabetic septic patients. Obese septic patients with diabetes were unique in displaying increased monocytic CD16 and CD163 expression. However, obese septic patients without diabetes solely presented with lower amounts of non-classical monocytes. Body mass index (BMI) dependent changes were restricted to diabetic septic patients, with a significantly higher diminution of the classical monocyte subset and concomitantly increased CD16 expression densities. Conclusion: Distribution and phenotypes of monocyte subsets were differentially modulated in critically ill patients with and without metabolic disease when progressing to sepsis or septic shock. Only diabetic septic patients displayed decline of classical monocytes and increase of CD16 expression densities. Therefore, diabetes but not obesity appears to promote the inflammatory phenotype of circulating monocytes in critically ill patients.

Indexed as

CD14CD16CD163monocyte subsetsobesitysepsistype 2 diabetes

Identifiers

PMID36687421
PMCPMC9849690
OpenAlexW4313570737

What OpenQuestion holds

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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.