Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Aims: Gastroesophageal varices (GOV) is a common complication in patients with portal hypertension. We conducted a meta-analysis in attempt to evaluate the diagnostic accuracy of computed tomography (CT) as a noninvasive imaging tool for identifying GOV in reference to esophagogastroduodenoscopy (EGD).
Methods: A systemic literature search of multiple databases were conducted to identify articles that investigated the diagnostic performance of CT for GOV, while employing EGD as reference standard. A 2×2 table was conducted according to the available published data for both esophageal varices (EV) and gastric varices (GV) as individual subgroups. The following indices were calculated: pooled sensitivity and specificity, positive and negative likelihood ratio, diagnostic odds ratio, and area under receiver operating characteristics. All statistical analyses were conducted via STATA13.0 and RevMan5.3.
Results: A total of 11 studies were included in this meta-analysis, 10 articles evaluated the diagnostic accuracy of CT for EV (807 subjects) and 7 articles for GV (583 subjects). The pooled sensitivity and specificity for identifying EV were 0.896 (95% CI, 0.841-0.934) and 0.723 (95% CI, 0.644-0.791), respectively, with an AUROC of 0.86. The pooled sensitivity and specificity for identifying GV were 0.955 (95% CI, 0.903-0.980) and 0.658 (95% CI, 0.433-0.829), respectively, with an AUROC of 0.95. A subgroup analysis suggested varying CT technology could serve as a potential source of heterogeneity between included studies. A Deek's funnel plot indicated a low probability for publication bias.
Conclusion: Computed tomography could potentially replace EGD as a primary screening tool for diagnosing GOV, however results should be interpreted with caution given its suboptimal specificity.
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http://dx.doi.org/10.1016/j.dld.2016.02.007 | DOI Listing |