Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background & Aims: In autoimmune hepatitis (AIH), inflammation is closely related to fibrosis. Although transaminase levels are commonly used to assess hepatic inflammation, they may not relate directly to the histology. We developed a noninvasive diagnostic score as an alternative to liver biopsy to help optimize treatment for AIH and monitor disease progress.
Methods: Eighty-two participants with type 1 AIH who had undergone liver biopsy were included (44 in training and 38 in validation sets). Liver histology was assessed according to the histologic activity index (HAI; score 0-18) and Ishak's histologic fibrosis index (HFI; score 0-6). High inflammation was defined as HAI>4, and advanced fibrosis was defined as HFI>2. Routine laboratory test findings and stepwise linear regression were used to develop the best models predicting HAI and HFI. The best cut-off value to predict high inflammation and advanced fibrosis for these formulas was then calculated based on receiver-operating characteristic analysis.
Results: The cut-off value for a model predicting high inflammation was ≥3.57 (AUROC = 0.93; 95% CI: 0.86-1.00), with 100% sensitivity and 85% specificity. High inflammation was confirmed with an 81% positive predictive value and excluded with a 100% negative predictive value. In the validation set, the sensitivity, specificity, positive predictive value and negative predictive values were 100, 56, 88 and 100% respectively. The diagnostic yield of the fibrosis score was unsatisfactory.
Conclusions: The noninvasive inflammatory score based on four routine laboratory parameters discriminated patients with and without significant hepatic inflammation and may facilitate follow-up of type 1 AIH patients.
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Source |
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http://dx.doi.org/10.1111/liv.12198 | DOI Listing |
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