Literature DB >> 30248233

Reducing NAFLD-screening time: A comparative study of eight diagnostic methods offering an alternative to ultrasound scans.

Filippo Procino1, Giovanni Misciagna2, Nicola Veronese3,4, Maria G Caruso3,4, Marisa Chiloiro5, Anna M Cisternino3, Maria Notarnicola4, Caterina Bonfiglio1, Irene Bruno1, Claudia Buongiorno1, Angelo Campanella1, Valentina Deflorio1, Isabella Franco1, Rocco Guerra1, Carla M Leone1, Antonella Mirizzi1, Alessandro Nitti1, Alberto R Osella1.   

Abstract

BACKGROUND & AIMS: The use of ultrasound scan (US) in non-alcoholic fatty liver disease (NAFLD) screening overloads US waiting lists. We hypothesized and tested a hybrid two-step method, consisting of applying a formula, to exclude subjects at low risk, before US.
METHODS: The sample included 2970 males and females (937 with NAFLD) diagnosed by US. We selected eight formulas: Fatty Liver Index (FLI), Hepatic Steatosis Index (HIS), body mass index (BMI), waist circumference (WC), Abdominal Volume Index (AVI), waist-to-height ratio (WHtR), waist/height0.5 (WHT.5R) and Body Roundness Index (BRI), and calculated their performance in the two-step method evaluating percentage reduction of the number of liver US (US reduction percentage), percentage of false negative and percentage of NAFLD identified.
RESULTS: The US reductions percentage were 52.2% (WHtR), 52.1% (HIS), 51.8% (FLI), 50.8% (BRI), 50.7% (BMI and WHt_5R), 46.5% (WC) and 45.2% (AVI). The false negative percentage were 8.5% (WHtR), 7.9% (BRI), 7.3% (WHt_5R), 7.2% (BMI), 6.7% (HIS), 6.6% (FLI), 5.6% (WC) and 5.2% (AVI). The best percentage of NALFD identified was obtained using AVI (83.6%) before US, then WC (82.2%), FLI (79%), HIS (78.9%), BMI (77.3%), WHt_5R (76.9%), BRI (74.8%) and WHtR (73%).
CONCLUSION: The best formula to use in two-step diagnostic NAFLD screening was AVI, which showed a low false negative rate and a higher percentage of identified NAFLD. Other studies evaluating the economic advantages of this screening method are warranted.
© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  NAFLD screening; abdominal volume index; fatty liver index; hepatic steatosis index

Year:  2018        PMID: 30248233     DOI: 10.1111/liv.13970

Source DB:  PubMed          Journal:  Liver Int        ISSN: 1478-3223            Impact factor:   5.828


  8 in total

1.  Development and validation of a neural network for NAFLD diagnosis.

Authors:  Paolo Sorino; Angelo Campanella; Caterina Bonfiglio; Antonella Mirizzi; Isabella Franco; Antonella Bianco; Maria Gabriella Caruso; Giovanni Misciagna; Laura R Aballay; Claudia Buongiorno; Rosalba Liuzzi; Anna Maria Cisternino; Maria Notarnicola; Marisa Chiloiro; Francesca Fallucchi; Giovanni Pascoschi; Alberto Rubén Osella
Journal:  Sci Rep       Date:  2021-10-12       Impact factor: 4.379

2.  Non-Alcoholic Fatty Liver Disease is Associated with Higher Metabolic Expenditure in Overweight and Obese Subjects: A Case-Control Study.

Authors:  Rosa Reddavide; Anna Maria Cisternino; Rosa Inguaggiato; Ornella Rotolo; Iris Zinzi; Nicola Veronese; Vito Guerra; Fabio Fucilli; Giuseppe Di Giovanni; Gioacchino Leandro; Sara Giannico; Maria Gabriella Caruso
Journal:  Nutrients       Date:  2019-08-07       Impact factor: 5.717

3.  Selecting the best machine learning algorithm to support the diagnosis of Non-Alcoholic Fatty Liver Disease: A meta learner study.

Authors:  Paolo Sorino; Maria Gabriella Caruso; Giovanni Misciagna; Caterina Bonfiglio; Angelo Campanella; Antonella Mirizzi; Isabella Franco; Antonella Bianco; Claudia Buongiorno; Rosalba Liuzzi; Anna Maria Cisternino; Maria Notarnicola; Marisa Chiloiro; Giovanni Pascoschi; Alberto Rubén Osella
Journal:  PLoS One       Date:  2020-10-20       Impact factor: 3.240

4.  Performance of Fatty Liver Index in Identifying Non-Alcoholic Fatty Liver Disease in Population Studies. A Meta-Analysis.

Authors:  Marco Castellana; Rossella Donghia; Vito Guerra; Filippo Procino; Luisa Lampignano; Fabio Castellana; Roberta Zupo; Rodolfo Sardone; Giovanni De Pergola; Francesco Romanelli; Pierpaolo Trimboli; Gianluigi Giannelli
Journal:  J Clin Med       Date:  2021-04-26       Impact factor: 4.241

5.  Waist-to-height ratio, an optimal anthropometric indicator for metabolic dysfunction associated fatty liver disease in the Western Chinese male population.

Authors:  Jinwei Cai; Cuiting Lin; Shuiqing Lai; Yingshan Liu; Min Liang; Yingfen Qin; Xinghuan Liang; Aihua Tan; Yong Gao; Zheng Lu; Chunlei Wu; Shengzhu Huang; Xiaobo Yang; Haiying Zhang; Jian Kuang; Zengnan Mo
Journal:  Lipids Health Dis       Date:  2021-10-27       Impact factor: 3.876

6.  The usefulness of obesity and lipid-related indices to predict the presence of Non-alcoholic fatty liver disease.

Authors:  Guotai Sheng; Song Lu; Qiyang Xie; Nan Peng; Maobin Kuang; Yang Zou
Journal:  Lipids Health Dis       Date:  2021-10-10       Impact factor: 3.876

7.  Machine-Learning Algorithm for Predicting Fatty Liver Disease in a Taiwanese Population.

Authors:  Yang-Yuan Chen; Chun-Yu Lin; Hsu-Heng Yen; Pei-Yuan Su; Ya-Huei Zeng; Siou-Ping Huang; I-Ling Liu
Journal:  J Pers Med       Date:  2022-06-23

8.  Relationship between triglyceride glucose index and the incidence of non-alcoholic fatty liver disease in the elderly: a retrospective cohort study in China.

Authors:  Chen Huanan; Li Sangsang; Adwoa Nyantakyiwaa Amoah; Bo Yacong; Chen Xuejiao; Shi Zhan; Wan Guodong; Huang Jian; Shi Songhe; Lyu Quanjun
Journal:  BMJ Open       Date:  2020-11-27       Impact factor: 2.692

  8 in total

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