Evidence map›Paper›PMID 22790906›Full record

ArticleDigestive diseases and sciences2013

Liver stiffness measurements in patients with different stages of nonalcoholic fatty liver disease: diagnostic performance and clinicopathological correlation.

Ramesh Kumar, Archana Rastogi, Manoj Kumar Sharma, Vikram Bhatia, Pankaj Tyagi, Praveen Sharma, Hitendra Garg, K N Chandan Kumar, Chhagan Bihari, Shiv Kumar Sarin

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Article in Digestive diseases and sciences, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
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52citing papers in PubMed, 5 pooled it
–field-weighted citation impact
1 · What the graph read from it

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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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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

52 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Guideline
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  5. Transient elastography in clinical detection of liver cirrhosis: A systematic review and meta-analysis.Saudi journal of gastroenterology : official journal of the Saudi Gastroenterology Association
    Pooled it
  6. Article
  7. Article
  8. Evaluation of Liver Fibrosis through Noninvasive Tests in Steatotic Liver Disease.The Korean journal of gastroenterology = Taehan Sohwagi Hakhoe chi · 2024
    Review
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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Ramesh KumarDepartment of Hepatology, Institute of Liver and Biliary Sciences (ILBS), Sector D1, Vasant Kunj, New Delhi, 110070, India.
Archana Rastogi
Manoj Kumar Sharma
Vikram Bhatia
Pankaj Tyagi
Praveen Sharma
Hitendra Garg
K N Chandan Kumar
Chhagan Bihari
Shiv Kumar Sarin

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe present study evaluated performance characteristics of liver stiffness measurement (LSM) by FibroScan in patients with different stages of nonalcoholic fatty liver disease (NAFLD). PATIENTS AND

methodsA total of 307 subjects (120 NAFLD, 85 NAFLD related cirrhosis, and 102 healthy controls) were studied.

resultsIn NAFLD patients, LSM had significant correlation with fibrosis (r = 0.68, p < 0.001), and increased progressively with increasing fibrosis (p < 0.001). However, the difference between stage 1 and stage 2 fibrosis was not significant (p = 0.07). The LSM in NAFLD without fibrosis and healthy controls was similar (p = 0.37). The areas under receiver-operating characteristics (AUROC) curve of LSM for stages ≥1, ≥2, ≥3, and 4 were 0.82, 0.85, 0.94, and 0.96, respectively. The best LSM (kPa) cut-offs for fibrosis stages ≥1, ≥2, ≥3 and 4 were 6.1, 7.0, 9.0, and 11.8, respectively. The negative predictive value of LSM for excluding advanced fibrosis was 95%. For advanced fibrosis, the AUROC curve of LSM was 0.94, followed by FIB-4 (0.75), BARD score (0.68), NAFLD fibrosis score (0.66), and aspartate platelet ratio index (0.60). In multivariate analysis, LSM was the only independent predictor of advanced fibrosis (odds ratio 1.47). In patients with NAFLD cirrhosis, LSM correlated significantly with Child-Pugh score (r = 0.40, p < 0.001), serum bilirubin (r = 0.34, p = 0.02), and grades of esophageal varices (r = 0.23, p = 0.04).

conclusionLSM is a useful tool for evaluation of patients with NAFLD, and is the best among other non-invasive predictors of liver fibrosis.

Indexed as

AdultBiomarkersBiomechanical PhenomenaBiopsyElasticity Imaging TechniquesFatty LiverFemaleHumansLiverLiver CirrhosisMaleMiddle AgedNon-alcoholic Fatty Liver DiseasePredictive Value of TestsBiomarkers

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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.