Evidence map›Paper›PMID 37481662›Full record

ArticleLipids in health and disease2023

Association between body fat composition and disease duration, clinical activity, and intravenous corticosteroid-induced response in inflammatory bowel disease.

Shubei He, Yuxia Huang, Ying Peng, Jin Chai, Kun Chen

Open access · goldAbstract read
In one paragraph

Article in Lipids in health and disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 17% 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, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  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

5 authors at 2 institutions in 1 country.

Shubei He *Department of Gastroenterology, The First Affiliated Hospital (Southwest Hospital) to Third Military Medical University (Army Medical University), Chongqing, 400038, China.
Yuxia Huang *Department of Gastroenterology, The First Affiliated Hospital (Southwest Hospital) to Third Military Medical University (Army Medical University), Chongqing, 400038, China.
Ying PengDepartment of Gastroenterology, The First Affiliated Hospital (Southwest Hospital) to Third Military Medical University (Army Medical University), Chongqing, 400038, China.
Jin ChaiDepartment of Gastroenterology, The First Affiliated Hospital (Southwest Hospital) to Third Military Medical University (Army Medical University), Chongqing, 400038, China. jin.chai@cldcsw.org.
Kun ChenDepartment of Gastroenterology, The First Affiliated Hospital (Southwest Hospital) to Third Military Medical University (Army Medical University), Chongqing, 400038, China. 13206064482@163.com.
Army Medical University · CNSouthwest Hospital · CN

Funding

Chongqing Technology Innovation and Application Development Special Rural Revitalization Project cstc2021jscx-xczxX0001National Natural Science Foundation of China 92268110
6 · The paper itself

Abstract

backgroundBody fat composition is believed to be associated with the progression, medical response, and prognosis of inflammatory bowel disease (IBD). Hence, we conducted this study to explore if fat metrics were associated with the disease activity of severe IBD and the response to intravenous corticosteroids (IVCS).

methodsWe included 69 patients with ulcerative colitis (UC) and 72 patients with Crohn's disease (CD) who had previously received IVCS during hospitalization. We quantified individual fat distribution using abdominal computed tomography slices. The correlations between fat parameters and disease activity were available with Spearman correlation analysis. The prediction model was developed using independent risk factors derived from multivariable logistic regression analysis. Model discrimination was evaluated leveraging the receiver operating characteristic curve. 1000 bootstrap resamples internally validated the model's prediction performance.

resultsNotable differences in age, nutritional status, serum cytomegalovirus replication, stool condition, and extraintestinal involvement between UC and CD patients were observed. UC subjects who responded to IVCS had higher subcutaneous adipose tissue index (SATI), visceral adipose tissue index (VATI), and mesorectal adipose tissue index (MATI) than non-responders. IVCS-responding CD individuals had lower VATI and mesenteric fat index (MFI) than non-responders. CD patients with a prolonged disease duration had a decreased SATI and an elevated MFI. VATI and MATI were reduced as UC clinically progressed, while more prominent clinical activity in CD correlated with increased VATI, MATI, and MFI. A high SATI indicated that patients with UC were more prone to be IVCS responders. For patients with CD, levels of VATI and MFI were negatively associated with effective IVCS treatment. The established models showed a discriminative accuracy of 0.834 [95% confidence interval (CI) 0.740-0.928] in the UC cohort and 0.871 (95% CI 0.793-0.949) in the CD cohort. Repeated samples supported the reliability of the developed models (AUC

conclusionHuman fat indexes represent novel imaging biomarkers for identifying IBD patients who respond to IVCS, thus building accelerated therapy regimens and avoiding the adverse effects of ineffective IVCS.

Indexed as

Colitis, UlcerativeCrohn DiseaseInflammatory Bowel DiseasesAdipose TissueAdrenal Cortex HormonesBody CompositionHumansReproducibility of ResultsAdrenal Cortex HormonesBody fat compositionComputed tomographyImaging biomarkersInflammatory bowel diseaseIntravenous corticosteroidsMedical response

Identifiers

PMID37481662
PMCPMC10363311
OpenAlexW4385073177

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.