Evidence map›Paper›PMID 36909342›Full record

ArticleFrontiers in endocrinology2023

Identifying advanced MAFLD in a cohort of T2DM and clinical features.

Ana Maria Sanchez-Bao, Alfonso Soto-Gonzalez, Manuel Delgado-Blanco, Vanesa Balboa-Barreiro, Diego Bellido

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Article in Frontiers in endocrinology, 2023. 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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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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.

Ana Maria Sanchez-BaoDivision of Endocrinology and Nutrition, Ferrol University Clinical Hospital, Ferrol, Spain.
Alfonso Soto-GonzalezDivision of Endocrinology and Nutrition, A Coruña University Clinical Hospital, A Coruña, Spain.
Manuel Delgado-BlancoDivision of Gastroenterology and Hepatology, A Coruña University Clinical Hospital, A Coruña, Spain.
Vanesa Balboa-BarreiroEpidemiology Department, A Coruña University Clinical Hospital, A Coruña, Spain.
Diego BellidoDivision of Endocrinology and Nutrition, Ferrol University Clinical Hospital, Ferrol, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: MAFLD is the most common cause of chronic liver disease, affecting 25% of the global population. Patients with T2DM have an increased risk of developing MAFLD. In addition, patients with T2DM have a higher risk of advanced forms of steatohepatitis and fibrosis. Identifying those patients is critical in order to refer them to specialist and appropriate management of their disease. Aims and Objectives: To estimate advanced fibrosis prevalence in a cohort of patients with T2DM and to identify possible predictors. Methods: subjects with T2DM during regular health check-up were enrolled. Demographic and general characteristics were measured, including metabolic parameters and homeostasis model assessment of insulin resistance (HOMA2-IR). Four non-invasive fibrosis scores (NAFLD fibrosis scores, FIB-4, APRI, Hepamet fibrosis score) were measure and compared with transient elastography (TE). Results: 96 patients (21%) presented risk of significant fibrosis (≥F2) measured by TE and 45 patients (10%) presented with risk of advanced fibrosis F3-F4. Liver fibrosis was related to BMI, AC, HOMA2-IR. The results of the non-invasive fibrosis scores have been validated with the results obtained in the TE. It is observed that the index with the greatest area under the curve (AUC) is APRI (AUC=0.729), with a sensitivity of 62.2% and a specificity of 76.1%. However, the test with better positive likelihood ratio (LR+) in our study is NAFLD fibrosis score. Conclusions: Our results show that in a general T2DM follow up, 10% of patients were at risk of advanced fibrosis. We found a positive correlation between liver fibrosis and BMI, AC and HOMA2-IR. Non-invasive fibrosis markers can be useful for screening, showing NAFLD Fibrosis score a better LHR+ compared to TE. Further studies are needed to validate these results and elucidate the best screening approach to identify those patients at risk of advanced MAFLD.

Indexed as

Diabetes Mellitus, Type 2Elasticity Imaging TechniquesNon-alcoholic Fatty Liver DiseaseFibrosisHumansLiver Cirrhosisliver fibrosisMAFLDmetabolic syndromeNAFLDNASHobesityT2DM

Identifiers

PMID36909342
PMCPMC9992874

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