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: 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: Cardiac syncope represents clinical situation with serious prognosis. The aim of the present study was to develop the diagnostic scoring system based on the clinical history allowing to distinguish between cardiac and noncardiac syncope.
Methods: Clinical history was obtained in the form of the structured questionnaire in 60 patients with cardiac syncope (mean age 70 ± 10 years, 33 men) an in 140 patients with noncardiac syncope (mean age 45 ± 20 years, 44 men). Multivariate regression analysis identified seven variables that were included in the final regression model.
Results: The age above 55 years, presence of structural heart disease, syncope in supine position, absence of prodromal symptoms, and chest pain before syncope were predictive of cardiac syncope. Predictors of noncardiac syncope were recovery duration of more than 1 minute and syncope occurring immediately after standing up. A diagnostic point score was derived from the regression coefficients. The sum of the points identified patients with cardiac syncope if the diagnostic point score was ≤2. Diagnostic performance of the score was assessed on the validation group of 67 patients with syncope (21 patients with cardiac syncope and 46 patients with noncardiac syncope). Sensitivity was 81%, specificity 84.8%, positive predictive value 70.8%, and negative predictive value 90.7%.
Conclusion: Predictive model based on parameters form clinical history of the patients may help to distinguish between cardiac and other causes of syncope.
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Source |
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http://dx.doi.org/10.1111/j.1540-8159.2011.03167.x | DOI Listing |
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