Noninvasive clinical model for the diagnosis of nonalcoholic steatohepatitis in overweight and morbidly obese patients undergoing bariatric surgery
Liver biopsy, an invasive method, is the gold standard for differentiate nonalcoholic steatohepatitis (NASH) from other stages of fatty liver disease. A noninvasive test to diagnose NASH and disease severity before surgery and also for monitoring disease status after bariatric surgery (BS) will be a...
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Veröffentlicht in: | Chirurgia (Bucharest, Romania : 1990) Romania : 1990), 2012-11, Vol.107 (6), p.772-779 |
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creator | Pirvulescu, I Gheorghe, L Csiki, I Becheanu, G Dumbravă, M Fica, S Martin, S Sarbu, A Gheorghe, C Diculescu, M Copăescu, C |
description | Liver biopsy, an invasive method, is the gold standard for differentiate nonalcoholic steatohepatitis (NASH) from other stages of fatty liver disease. A noninvasive test to diagnose NASH and disease severity before surgery and also for monitoring disease status after bariatric surgery (BS) will be an important medical challenge.
To create a noninvasive biomarkers model for the diagnosis of NASH in overweight, obese and morbidly obese patients (MOP).
Sixty patients (mean BMI= 47.81kg/m2) were admitted after exclusion of other causes of liver disease. Liver biopsies were obtained at the time of the bariatric surgery or by percutaneous liver biopsy and graded using Kleiner score. Continuous variables were compared using Wilcoxon rank sum test and for prediction of NASH we used logistic regression.
Logistic regression analysis showed that BMI, ALT, AST, alkaline phosphatase (ALP), HOMA-R, hs-CRP, M30, M65, leptine and adiponectine levels remained independent predictors for NASH (p less than 0.02). Using AUC analysis, we established the following cutoff levels being indicative of NASH: BMI ė 47 kg/m2, ALT ė 32 IU/mL, AST ė 25 IU/mL, ALP ė 85 IU/mL, HOMA-IR ė 4, M65 ė 389 U/L. Adiponectine less than 13.5 mg/L. A NASH-score, calculated as the sum of these 7 parameters, at a cutoff level of 4 points, can accurately predict NASH (sensitivity of 90%, specificity of 93.94% and AUC of 0.9576).
We propose a noninvasive model for NASH diagnosis in MOP that should be validated prospectively. Using this noninvasive score, NASH would be predicted without the risks of liver biopsy. |
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To create a noninvasive biomarkers model for the diagnosis of NASH in overweight, obese and morbidly obese patients (MOP).
Sixty patients (mean BMI= 47.81kg/m2) were admitted after exclusion of other causes of liver disease. Liver biopsies were obtained at the time of the bariatric surgery or by percutaneous liver biopsy and graded using Kleiner score. Continuous variables were compared using Wilcoxon rank sum test and for prediction of NASH we used logistic regression.
Logistic regression analysis showed that BMI, ALT, AST, alkaline phosphatase (ALP), HOMA-R, hs-CRP, M30, M65, leptine and adiponectine levels remained independent predictors for NASH (p less than 0.02). Using AUC analysis, we established the following cutoff levels being indicative of NASH: BMI ė 47 kg/m2, ALT ė 32 IU/mL, AST ė 25 IU/mL, ALP ė 85 IU/mL, HOMA-IR ė 4, M65 ė 389 U/L. Adiponectine less than 13.5 mg/L. A NASH-score, calculated as the sum of these 7 parameters, at a cutoff level of 4 points, can accurately predict NASH (sensitivity of 90%, specificity of 93.94% and AUC of 0.9576).
We propose a noninvasive model for NASH diagnosis in MOP that should be validated prospectively. Using this noninvasive score, NASH would be predicted without the risks of liver biopsy.</description><identifier>ISSN: 1221-9118</identifier><identifier>PMID: 23294957</identifier><language>eng</language><publisher>Romania</publisher><subject>Adiponectin - blood ; Adult ; Alanine Transaminase - blood ; Alkaline Phosphatase - blood ; Aspartate Aminotransferases - blood ; Bariatric Surgery ; Biomarkers - blood ; Biopsy - methods ; Biopsy, Needle ; Body Mass Index ; C-Reactive Protein - metabolism ; Diagnosis, Differential ; Fatty Liver - blood ; Fatty Liver - diagnosis ; Fatty Liver - etiology ; Female ; Glucose Tolerance Test ; Humans ; Hydroxyquinolines - blood ; Insulin - blood ; Insulin Resistance ; Keratin-18 - blood ; Leptin - blood ; Logistic Models ; Male ; Middle Aged ; Non-alcoholic Fatty Liver Disease ; Obesity, Morbid - blood ; Obesity, Morbid - complications ; Obesity, Morbid - diagnosis ; Obesity, Morbid - surgery ; Overweight - diagnosis ; Overweight - surgery ; Peptide Fragments - blood ; Predictive Value of Tests ; Sensitivity and Specificity ; Severity of Illness Index ; Statistics, Nonparametric ; Treatment Outcome</subject><ispartof>Chirurgia (Bucharest, Romania : 1990), 2012-11, Vol.107 (6), p.772-779</ispartof><rights>Celsius.</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23294957$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Pirvulescu, I</creatorcontrib><creatorcontrib>Gheorghe, L</creatorcontrib><creatorcontrib>Csiki, I</creatorcontrib><creatorcontrib>Becheanu, G</creatorcontrib><creatorcontrib>Dumbravă, M</creatorcontrib><creatorcontrib>Fica, S</creatorcontrib><creatorcontrib>Martin, S</creatorcontrib><creatorcontrib>Sarbu, A</creatorcontrib><creatorcontrib>Gheorghe, C</creatorcontrib><creatorcontrib>Diculescu, M</creatorcontrib><creatorcontrib>Copăescu, C</creatorcontrib><title>Noninvasive clinical model for the diagnosis of nonalcoholic steatohepatitis in overweight and morbidly obese patients undergoing bariatric surgery</title><title>Chirurgia (Bucharest, Romania : 1990)</title><addtitle>Chirurgia (Bucur)</addtitle><description>Liver biopsy, an invasive method, is the gold standard for differentiate nonalcoholic steatohepatitis (NASH) from other stages of fatty liver disease. A noninvasive test to diagnose NASH and disease severity before surgery and also for monitoring disease status after bariatric surgery (BS) will be an important medical challenge.
To create a noninvasive biomarkers model for the diagnosis of NASH in overweight, obese and morbidly obese patients (MOP).
Sixty patients (mean BMI= 47.81kg/m2) were admitted after exclusion of other causes of liver disease. Liver biopsies were obtained at the time of the bariatric surgery or by percutaneous liver biopsy and graded using Kleiner score. Continuous variables were compared using Wilcoxon rank sum test and for prediction of NASH we used logistic regression.
Logistic regression analysis showed that BMI, ALT, AST, alkaline phosphatase (ALP), HOMA-R, hs-CRP, M30, M65, leptine and adiponectine levels remained independent predictors for NASH (p less than 0.02). Using AUC analysis, we established the following cutoff levels being indicative of NASH: BMI ė 47 kg/m2, ALT ė 32 IU/mL, AST ė 25 IU/mL, ALP ė 85 IU/mL, HOMA-IR ė 4, M65 ė 389 U/L. Adiponectine less than 13.5 mg/L. A NASH-score, calculated as the sum of these 7 parameters, at a cutoff level of 4 points, can accurately predict NASH (sensitivity of 90%, specificity of 93.94% and AUC of 0.9576).
We propose a noninvasive model for NASH diagnosis in MOP that should be validated prospectively. Using this noninvasive score, NASH would be predicted without the risks of liver biopsy.</description><subject>Adiponectin - blood</subject><subject>Adult</subject><subject>Alanine Transaminase - blood</subject><subject>Alkaline Phosphatase - blood</subject><subject>Aspartate Aminotransferases - blood</subject><subject>Bariatric Surgery</subject><subject>Biomarkers - blood</subject><subject>Biopsy - methods</subject><subject>Biopsy, Needle</subject><subject>Body Mass Index</subject><subject>C-Reactive Protein - metabolism</subject><subject>Diagnosis, Differential</subject><subject>Fatty Liver - blood</subject><subject>Fatty Liver - diagnosis</subject><subject>Fatty Liver - etiology</subject><subject>Female</subject><subject>Glucose Tolerance Test</subject><subject>Humans</subject><subject>Hydroxyquinolines - blood</subject><subject>Insulin - blood</subject><subject>Insulin Resistance</subject><subject>Keratin-18 - blood</subject><subject>Leptin - blood</subject><subject>Logistic Models</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Non-alcoholic Fatty Liver Disease</subject><subject>Obesity, Morbid - blood</subject><subject>Obesity, Morbid - complications</subject><subject>Obesity, Morbid - diagnosis</subject><subject>Obesity, Morbid - surgery</subject><subject>Overweight - diagnosis</subject><subject>Overweight - surgery</subject><subject>Peptide Fragments - blood</subject><subject>Predictive Value of Tests</subject><subject>Sensitivity and Specificity</subject><subject>Severity of Illness Index</subject><subject>Statistics, Nonparametric</subject><subject>Treatment Outcome</subject><issn>1221-9118</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNo1kL1OwzAUhTOAaFX6CsgjSyRfO3WSEVX8SQgWmCPHvkmMHDvYTlGfgxcmFeUsZzifvuFcZGtgDPIaoFpl2xg_6RJBGaX8Klsxzuqi3pXr7OfVO-MOMpoDEmWNM0paMnqNlnQ-kDQg0Ub2zkcTie-I805a5QdvjSIxoUx-wEkmk5bdOOIPGL7R9EMi0unFFFqj7ZH4FiOSE4guRTI7jaH3xvWklcHIFE66OfQYjtfZZSdtxO25N9nHw_37_il_eXt83t-95BOURcoZMKFZV-sCOiqrlukdY4WgGhQIAbxGgVxXElSnS8V3FWDBAFsseFkIJfkmu_3zTsF_zRhTM5qo0Frp0M-xAVZyTksBYkFvzujcjqibKZhRhmPzfyT_BWwhcw8</recordid><startdate>201211</startdate><enddate>201211</enddate><creator>Pirvulescu, I</creator><creator>Gheorghe, L</creator><creator>Csiki, I</creator><creator>Becheanu, G</creator><creator>Dumbravă, M</creator><creator>Fica, S</creator><creator>Martin, S</creator><creator>Sarbu, A</creator><creator>Gheorghe, C</creator><creator>Diculescu, M</creator><creator>Copăescu, C</creator><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>7X8</scope></search><sort><creationdate>201211</creationdate><title>Noninvasive clinical model for the diagnosis of nonalcoholic steatohepatitis in overweight and morbidly obese patients undergoing bariatric surgery</title><author>Pirvulescu, I ; Gheorghe, L ; Csiki, I ; Becheanu, G ; Dumbravă, M ; Fica, S ; Martin, S ; Sarbu, A ; Gheorghe, C ; Diculescu, M ; Copăescu, C</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p174t-2126d2f9d41f0a8b2d522460d1c166139e6e3d8a1cfd7c3581e421ebe43746ca3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Adiponectin - blood</topic><topic>Adult</topic><topic>Alanine Transaminase - blood</topic><topic>Alkaline Phosphatase - blood</topic><topic>Aspartate Aminotransferases - blood</topic><topic>Bariatric Surgery</topic><topic>Biomarkers - blood</topic><topic>Biopsy - methods</topic><topic>Biopsy, Needle</topic><topic>Body Mass Index</topic><topic>C-Reactive Protein - metabolism</topic><topic>Diagnosis, Differential</topic><topic>Fatty Liver - blood</topic><topic>Fatty Liver - diagnosis</topic><topic>Fatty Liver - etiology</topic><topic>Female</topic><topic>Glucose Tolerance Test</topic><topic>Humans</topic><topic>Hydroxyquinolines - blood</topic><topic>Insulin - blood</topic><topic>Insulin Resistance</topic><topic>Keratin-18 - blood</topic><topic>Leptin - blood</topic><topic>Logistic Models</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Non-alcoholic Fatty Liver Disease</topic><topic>Obesity, Morbid - blood</topic><topic>Obesity, Morbid - complications</topic><topic>Obesity, Morbid - diagnosis</topic><topic>Obesity, Morbid - surgery</topic><topic>Overweight - diagnosis</topic><topic>Overweight - surgery</topic><topic>Peptide Fragments - blood</topic><topic>Predictive Value of Tests</topic><topic>Sensitivity and Specificity</topic><topic>Severity of Illness Index</topic><topic>Statistics, Nonparametric</topic><topic>Treatment Outcome</topic><toplevel>online_resources</toplevel><creatorcontrib>Pirvulescu, I</creatorcontrib><creatorcontrib>Gheorghe, L</creatorcontrib><creatorcontrib>Csiki, I</creatorcontrib><creatorcontrib>Becheanu, G</creatorcontrib><creatorcontrib>Dumbravă, M</creatorcontrib><creatorcontrib>Fica, S</creatorcontrib><creatorcontrib>Martin, S</creatorcontrib><creatorcontrib>Sarbu, A</creatorcontrib><creatorcontrib>Gheorghe, C</creatorcontrib><creatorcontrib>Diculescu, M</creatorcontrib><creatorcontrib>Copăescu, C</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>MEDLINE - Academic</collection><jtitle>Chirurgia (Bucharest, Romania : 1990)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pirvulescu, I</au><au>Gheorghe, L</au><au>Csiki, I</au><au>Becheanu, G</au><au>Dumbravă, M</au><au>Fica, S</au><au>Martin, S</au><au>Sarbu, A</au><au>Gheorghe, C</au><au>Diculescu, M</au><au>Copăescu, C</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Noninvasive clinical model for the diagnosis of nonalcoholic steatohepatitis in overweight and morbidly obese patients undergoing bariatric surgery</atitle><jtitle>Chirurgia (Bucharest, Romania : 1990)</jtitle><addtitle>Chirurgia (Bucur)</addtitle><date>2012-11</date><risdate>2012</risdate><volume>107</volume><issue>6</issue><spage>772</spage><epage>779</epage><pages>772-779</pages><issn>1221-9118</issn><abstract>Liver biopsy, an invasive method, is the gold standard for differentiate nonalcoholic steatohepatitis (NASH) from other stages of fatty liver disease. A noninvasive test to diagnose NASH and disease severity before surgery and also for monitoring disease status after bariatric surgery (BS) will be an important medical challenge.
To create a noninvasive biomarkers model for the diagnosis of NASH in overweight, obese and morbidly obese patients (MOP).
Sixty patients (mean BMI= 47.81kg/m2) were admitted after exclusion of other causes of liver disease. Liver biopsies were obtained at the time of the bariatric surgery or by percutaneous liver biopsy and graded using Kleiner score. Continuous variables were compared using Wilcoxon rank sum test and for prediction of NASH we used logistic regression.
Logistic regression analysis showed that BMI, ALT, AST, alkaline phosphatase (ALP), HOMA-R, hs-CRP, M30, M65, leptine and adiponectine levels remained independent predictors for NASH (p less than 0.02). Using AUC analysis, we established the following cutoff levels being indicative of NASH: BMI ė 47 kg/m2, ALT ė 32 IU/mL, AST ė 25 IU/mL, ALP ė 85 IU/mL, HOMA-IR ė 4, M65 ė 389 U/L. Adiponectine less than 13.5 mg/L. A NASH-score, calculated as the sum of these 7 parameters, at a cutoff level of 4 points, can accurately predict NASH (sensitivity of 90%, specificity of 93.94% and AUC of 0.9576).
We propose a noninvasive model for NASH diagnosis in MOP that should be validated prospectively. Using this noninvasive score, NASH would be predicted without the risks of liver biopsy.</abstract><cop>Romania</cop><pmid>23294957</pmid><tpages>8</tpages></addata></record> |
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subjects | Adiponectin - blood Adult Alanine Transaminase - blood Alkaline Phosphatase - blood Aspartate Aminotransferases - blood Bariatric Surgery Biomarkers - blood Biopsy - methods Biopsy, Needle Body Mass Index C-Reactive Protein - metabolism Diagnosis, Differential Fatty Liver - blood Fatty Liver - diagnosis Fatty Liver - etiology Female Glucose Tolerance Test Humans Hydroxyquinolines - blood Insulin - blood Insulin Resistance Keratin-18 - blood Leptin - blood Logistic Models Male Middle Aged Non-alcoholic Fatty Liver Disease Obesity, Morbid - blood Obesity, Morbid - complications Obesity, Morbid - diagnosis Obesity, Morbid - surgery Overweight - diagnosis Overweight - surgery Peptide Fragments - blood Predictive Value of Tests Sensitivity and Specificity Severity of Illness Index Statistics, Nonparametric Treatment Outcome |
title | Noninvasive clinical model for the diagnosis of nonalcoholic steatohepatitis in overweight and morbidly obese patients undergoing bariatric surgery |
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