Evidence mapPaperPMID 40410700Full record

ArticleBMC gastroenterology2025

Aggregate index of systemic inflammation tied to increased fatty liver disease risk: insights from NHANES data.

Meng Zhang, Yuan Yuan, Chenglong Wang, You Huang, Mingli Fan, Xiangling Li, Zujie Qin

Abstract read
In one paragraph

Article in BMC gastroenterology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. 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

7 authors.

Meng Zhang *Guangxi International Zhuang Medicine Hospital (Affiliated International Zhuang Medicine Hospital, Guangxi University of Chinese Medicine), Nanning, 530200, China.
Yuan Yuan *School of Public Health and Management, Guangxi University of Chinese Medicine, Nanning, 530200, China.
Chenglong WangGuangxi International Zhuang Medicine Hospital (Affiliated International Zhuang Medicine Hospital, Guangxi University of Chinese Medicine), Nanning, 530200, China.
You HuangInstitute of Chinese Medicine, Zhuang and Yao Medicine, Guangxi University of Chinese Medicine, Nanning, 530200, China.
Mingli FanInstitute of Chinese Medicine, Zhuang and Yao Medicine, Guangxi University of Chinese Medicine, Nanning, 530200, China.
Xiangling LiInstitute of Chinese Medicine, Zhuang and Yao Medicine, Guangxi University of Chinese Medicine, Nanning, 530200, China. haoyunlinglong@163.com.
Zujie QinGuangxi International Zhuang Medicine Hospital (Affiliated International Zhuang Medicine Hospital, Guangxi University of Chinese Medicine), Nanning, 530200, China. 109741754@qq.com.

Funding

the Guangxi Key Discipline of TCM (Zhuang medicine) GZXK-Z-20-60the Guangxi Natural Science Foundation 2023GXNSFBA026188the NATCM's Project for High-level Construction of Key TCM Disciplines in Minority Pharmacy (Zhuang Pharmacy) zyyzdxk-2023165
6 · The paper itself

Abstract

backgroundFatty liver disease (FLD), characterized by hepatic lipid accumulation, impairs quality of life and can progress to cirrhosis and hepatocellular carcinoma, imposing a healthcare burden. This study investigates the association between the aggregate index of systemic inflammation (AISI) and FLD prevalence, evaluating AISI's potential as an early biomarker for risk assessment.

methodsData were obtained from the National Health and Nutrition Examination Survey (NHANES) database, which encompasses the years 2017 through 2020. Participants were chosen based on the availability of controlled attenuation parameter (CAP) scores derived from transient elastography (TE), a technique utilized for assessing liver steatosis. The formula employed to compute the AISI is as follows: AISI = N × P × M / L, where N, P, M, and L refer to neutrophils, platelets, monocytes, and lymphocytes, respectively. Additionally, demographic, socioeconomic, dietary, and health-related information was gathered. Logistic regression models were utilized to pinpoint risk factors associated with FLD, and a nomogram was created to forecast FLD risk.

resultsOf the 3,961 participants, 2,377 (60.0%) were diagnosed with FLD based on a CAP score ≥ 248 dB/m. Elevated AISI was significantly associated with FLD (P = 0.021). Other significant risk factors included sex, age, BMI, race, marital status, hypertension, and diabetes. The nomogram demonstrated excellent discriminatory performance with an AUC of 0.814 (95% CI: 0.800, 0.827) and good calibration.

conclusionThis study reveals a significant, independent association between elevated AISI and increased FLD risk in the U.S. population, even after adjusting for confounders. AISI demonstrated good discriminative performance for FLD, but its effect size suggests it should supplement, not replace, existing clinical risk assessment tools. AISI, a cost-effective biomarker, holds potential for enhancing FLD screening, particularly in resource-limited settings.

Indexed as

Fatty LiverInflammationAdultAgedBiomarkersElasticity Imaging TechniquesFemaleHumansMaleMiddle AgedNomogramsNutrition SurveysPrevalenceRisk AssessmentRisk FactorsUnited StatesBiomarkersAggregate index of systemic inflammationComplete blood cell count-derived inflammatory indicatorFatty liver diseaseInflammationNHANES

Identifiers

PMID40410700
PMCPMC12101034

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.