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: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
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
Objective: To better adjust the risk for preeclampsia, multifactorial models in first trimester of pregnancy have found the way in clinical practice. This study compares the available test algorithms.
Study Design: In a cross-sectional study between November 2013 and April 2016 we compared the tests results of three first trimester testing algorithms for preeclampsia in 413 women. Risk for preterm preeclampsia was calculated with three different algorithms: Preeclampsia Predictor™ Software by PerkinElmer (PERK), ViewPoint® Software by GE Healthcare (VP) and the online calculator of the Fetal Medicine Foundation (FMF).We analyzed the data descriptively and determined Cohen's Kappa to assess the agreement among the algorithms.
Results: VP classified 89(21.5%) women, PERK 43(10.4%) women and FMF 90 (21.8%) women as having high risk for preterm preeclampsia (<34 weeks of gestation for VP and PERK and <37 weeks of gestation for FMF). Agreement between tests ranged from moderate to substantial (PERK/VP: κ = 0.56, PERK/ FMF: κ = 0.50, and VP/ FMF: κ = 0.72).
Conclusion: The three algorithms are similar but not equal. This may depend on chosen cut off, but also on test properties. This study cannot decide which algorithm is the best, but differences in results and cut offs should be taken into account.
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Source |
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http://dx.doi.org/10.1016/j.ejogrb.2018.11.006 | DOI Listing |
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