Evidence map›Paper›PMID 38836118›Full record

ArticleBiomarker insights2024

Effect of Cytokeratin-18, C-peptide, MHR, and MACK-3 Biomarkers in Metabolic Dysfunction-Associated Fatty Liver Disease After Laparoscopic Sleeve Gastrectomy.

Mohamed Hany, Hala M Demerdash, Anwar Ashraf Abouelnasr, Bart Torensma

Abstract read
In one paragraph

Article in Biomarker insights, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Observational
  2. Article
  3. 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

4 authors.

Mohamed HanyDepartment of Surgery, Medical Research Institute, Alexandria University, Alexandria, Egypt.
Hala M DemerdashDepartment of Clinical Pathology, Alexandria University, Alexandria, Egypt.
Anwar Ashraf AbouelnasrDepartment of Surgery, Medical Research Institute, Alexandria University, Alexandria, Egypt.
Bart TorensmaLeiden University Medical Center (LUMC), Leiden, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Laparoscopic sleeve gastrectomy (LSG) has emerged as a valuable treatment for various metabolic disorders, including metabolic dysfunction-associated fatty liver disease (MAFLD) in patients with obesity. Consequently, there is a pressing need to develop noninvasive biomarkers for diagnosing and monitoring disease progression. Objectives: This study aimed to evaluate specific biomarkers, including Cytokeratin-18 (CK-18), C-peptide, monocyte to HDL cholesterol ratio (MHR), and MACK-3, in patients with obesity with MAFLD undergoing LSG. Design: A prospective cohort study on patients with obesity before and 6 months after the LSG procedure. Methods: 70 patients with obesity with confirmed MAFLD, determined by Transient Elastography (TE), were pre- and 6 months postoperatively tested. Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), lipid profile, ghrelin, leptin, peptide YY, GLP-1, and liver fibrosis scores, including AST/ALT ratio (AAR), Fibrosis-4 index (FIB-4), and BARD Score were tested. Results: BMI significantly decreased in all participants, with a % excess weight loss of 62.0% ± 15.4%. TE measurements revealed a significant postoperative reduction from 100% to 87.1% ( Conclusion: Serum CK-18 outperformed other selected biomarkers in predicting and monitoring MAFLD in patients with obesity, suggesting its prospective utility in clinical practice. Further studies are needed to validate the accuracy of the MACK-3 test.

Indexed as

bariatric surgeryBiomarkersCK-18C-peptideMACK-3MHRprediction

Identifiers

PMID38836118
PMCPMC11149444

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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.