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Autor(en) / Beteiligte
Titel
A Histologic Scoring System for Prognosis of Patients With Alcoholic Hepatitis
Ist Teil von
  • Gastroenterology (New York, N.Y. 1943), 2014-05, Vol.146 (5), p.1231-1239.e6
Ort / Verlag
United States: Elsevier Inc
Erscheinungsjahr
2014
Quelle
MEDLINE
Beschreibungen/Notizen
  • Background & Aims There is no histologic classification system to determine prognoses of patients with alcoholic hepatitis (AH). We identified histologic features associated with disease severity and created a histologic scoring system to predict short-term (90-day) mortality. Methods We analyzed data from 121 patients admitted to the Liver Unit (Hospital Clinic, Barcelona, Spain) from January 2000 to January 2008 with features of AH and developed a histologic scoring system to determine the risk of death using logistic regression. The system was tested and updated in a test set of 96 patients from 5 academic centers in the United States and Europe, and a semiquantitative scoring system called the Alcoholic Hepatitis Histologic Score (AHHS) was developed. The system was validated in an independent set of 109 patients. Interobserver agreement was evaluated by weighted κ statistical analysis. Results The degree of fibrosis, degree of neutrophil infiltration, type of bilirubinostasis, and presence of megamitochondria were independently associated with 90-day mortality. We used these 4 parameters to develop the AHHS to identify patients with a low (0–3 points), moderate (4–5 points), or high (6–9 points) risk of death within 90 days (3%, 19%, and 51%, respectively; P < .0001). The AHHS estimated 90-day mortality in the training and test sets with an area under the receiver operating characteristic value of 0.77 (95% confidence interval, 0.71–0.83). Interrater agreement values were 0.65 for fibrosis, 0.86 for bilirubinostasis, 0.60 for neutrophil infiltration, and 0.46 for megamitochondria. Interestingly, the type of bilirubinostasis predicted the development of bacterial infections. Conclusions We identified histologic features associated with the severity of AH and developed a patient classification system that might be used in clinical decision making.

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