A noninvasive clinical scoring model predicts risk of nonalcoholic steatohepatitis in morbidly obese patients

Alex Ulitsky, Ashwin N. Ananthakrishnan, Richard Komorowski, James Wallace, Sri Naveen Surapaneni, Jose Franco, Kia Saeian, Samer Gawrieh

Research output: Contribution to journalArticle

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Abstract

Background: A simple model to predict nonalcoholic steatohepatitis (NASH) in patients with nonalcoholic fatty liver disease is desirable to optimize the selection of patients for liver biopsy. We investigated a large group of morbidly obese patients to derive a scoring system based on simple clinical and laboratory variables. Methods: Consecutive subjects undergoing bariatric surgery and without evidence of other liver disease or significant alcohol use underwent intraoperative liver biopsy. Demographic, clinical, and biochemical variables were collected. A scoring model was derived using variables found to be independent predictors of NASH. The scores were divided into four risk categories (low, intermediate, high, and very high). Positive and negative predictive values (PPV/NPV) were derived for each category and the area under the receiver operator curve (AUROC) was calculated. Results: A total of 253 subjects were included: 52 (20.6%) had NASH, 116 (45.8%) had simple steatosis, and 85 (33.6%) had normal liver histology. Only ten subjects (19% of NASH group) had significant (≥ stage 2) fibrosis. Multivariate analysis identified diabetes, abnormal ALT, and hypertriglyceridemia as independent predictors of NASH. Sleep apnea showed a strong trend toward significance and was also included in the model. This model showed a NPV of 89.7% in the low risk category and a PPV of 75% in the very high risk category, with AUROC of 0.76. Conclusions: A simple scoring system performs well in predicting NASH and can be used in the clinic to optimize the selection of morbidly obese patients for liver biopsy.

Original languageEnglish (US)
Pages (from-to)685-691
Number of pages7
JournalObesity Surgery
Volume20
Issue number6
DOIs
StatePublished - Jun 2010
Externally publishedYes

Fingerprint

Liver
Biopsy
Bariatric Surgery
Hypertriglyceridemia
Sleep Apnea Syndromes
Non-alcoholic Fatty Liver Disease
Patient Selection
Liver Diseases
Histology
Fibrosis
Multivariate Analysis
Alcohols
Demography

Keywords

  • Hepatosteatosis
  • Liver biopsy
  • Morbid obesity
  • NAFLD
  • NASH
  • Predictive model

ASJC Scopus subject areas

  • Surgery
  • Endocrinology, Diabetes and Metabolism
  • Nutrition and Dietetics

Cite this

Ulitsky, A., Ananthakrishnan, A. N., Komorowski, R., Wallace, J., Surapaneni, S. N., Franco, J., ... Gawrieh, S. (2010). A noninvasive clinical scoring model predicts risk of nonalcoholic steatohepatitis in morbidly obese patients. Obesity Surgery, 20(6), 685-691. https://doi.org/10.1007/s11695-010-0118-y

A noninvasive clinical scoring model predicts risk of nonalcoholic steatohepatitis in morbidly obese patients. / Ulitsky, Alex; Ananthakrishnan, Ashwin N.; Komorowski, Richard; Wallace, James; Surapaneni, Sri Naveen; Franco, Jose; Saeian, Kia; Gawrieh, Samer.

In: Obesity Surgery, Vol. 20, No. 6, 06.2010, p. 685-691.

Research output: Contribution to journalArticle

Ulitsky, A, Ananthakrishnan, AN, Komorowski, R, Wallace, J, Surapaneni, SN, Franco, J, Saeian, K & Gawrieh, S 2010, 'A noninvasive clinical scoring model predicts risk of nonalcoholic steatohepatitis in morbidly obese patients', Obesity Surgery, vol. 20, no. 6, pp. 685-691. https://doi.org/10.1007/s11695-010-0118-y
Ulitsky A, Ananthakrishnan AN, Komorowski R, Wallace J, Surapaneni SN, Franco J et al. A noninvasive clinical scoring model predicts risk of nonalcoholic steatohepatitis in morbidly obese patients. Obesity Surgery. 2010 Jun;20(6):685-691. https://doi.org/10.1007/s11695-010-0118-y
Ulitsky, Alex ; Ananthakrishnan, Ashwin N. ; Komorowski, Richard ; Wallace, James ; Surapaneni, Sri Naveen ; Franco, Jose ; Saeian, Kia ; Gawrieh, Samer. / A noninvasive clinical scoring model predicts risk of nonalcoholic steatohepatitis in morbidly obese patients. In: Obesity Surgery. 2010 ; Vol. 20, No. 6. pp. 685-691.
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abstract = "Background: A simple model to predict nonalcoholic steatohepatitis (NASH) in patients with nonalcoholic fatty liver disease is desirable to optimize the selection of patients for liver biopsy. We investigated a large group of morbidly obese patients to derive a scoring system based on simple clinical and laboratory variables. Methods: Consecutive subjects undergoing bariatric surgery and without evidence of other liver disease or significant alcohol use underwent intraoperative liver biopsy. Demographic, clinical, and biochemical variables were collected. A scoring model was derived using variables found to be independent predictors of NASH. The scores were divided into four risk categories (low, intermediate, high, and very high). Positive and negative predictive values (PPV/NPV) were derived for each category and the area under the receiver operator curve (AUROC) was calculated. Results: A total of 253 subjects were included: 52 (20.6{\%}) had NASH, 116 (45.8{\%}) had simple steatosis, and 85 (33.6{\%}) had normal liver histology. Only ten subjects (19{\%} of NASH group) had significant (≥ stage 2) fibrosis. Multivariate analysis identified diabetes, abnormal ALT, and hypertriglyceridemia as independent predictors of NASH. Sleep apnea showed a strong trend toward significance and was also included in the model. This model showed a NPV of 89.7{\%} in the low risk category and a PPV of 75{\%} in the very high risk category, with AUROC of 0.76. Conclusions: A simple scoring system performs well in predicting NASH and can be used in the clinic to optimize the selection of morbidly obese patients for liver biopsy.",
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AU - Surapaneni, Sri Naveen

AU - Franco, Jose

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AB - Background: A simple model to predict nonalcoholic steatohepatitis (NASH) in patients with nonalcoholic fatty liver disease is desirable to optimize the selection of patients for liver biopsy. We investigated a large group of morbidly obese patients to derive a scoring system based on simple clinical and laboratory variables. Methods: Consecutive subjects undergoing bariatric surgery and without evidence of other liver disease or significant alcohol use underwent intraoperative liver biopsy. Demographic, clinical, and biochemical variables were collected. A scoring model was derived using variables found to be independent predictors of NASH. The scores were divided into four risk categories (low, intermediate, high, and very high). Positive and negative predictive values (PPV/NPV) were derived for each category and the area under the receiver operator curve (AUROC) was calculated. Results: A total of 253 subjects were included: 52 (20.6%) had NASH, 116 (45.8%) had simple steatosis, and 85 (33.6%) had normal liver histology. Only ten subjects (19% of NASH group) had significant (≥ stage 2) fibrosis. Multivariate analysis identified diabetes, abnormal ALT, and hypertriglyceridemia as independent predictors of NASH. Sleep apnea showed a strong trend toward significance and was also included in the model. This model showed a NPV of 89.7% in the low risk category and a PPV of 75% in the very high risk category, with AUROC of 0.76. Conclusions: A simple scoring system performs well in predicting NASH and can be used in the clinic to optimize the selection of morbidly obese patients for liver biopsy.

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