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
Objectives: Cryptococcal meningitis (CM) and tuberculous meningitis (TBM) are common in HIV-infected adults in Africa and difficult to diagnose. Inaccurate diagnosis results in adverse outcomes. We describe patterns of meningitis in a Malawian hospital, focusing on features which differentiate CM and TBM with the aim to derive an algorithm using only clinical and basic laboratory data available in this resource-poor setting.
Methods: Consecutive patients admitted with meningitis were prospectively recruited, clinical features were recorded and cerebrospinal fluid (CSF) was examined.
Results: A total of 573 patients were recruited, and 263 (46%) had CSF consistent with meningitis. One hundred and twelve (43%) had CM and 46 (18%) had TBM. CM was associated with high CSF opening pressure and low CSF leukocyte count. Fever, neck stiffness and reduced conscious level were associated with TBM. A diagnostic index was constructed demonstrating sensitivity 83%and specificity 79% for the differentiation of CM and TBM. An algorithm was derived with 92% sensitivity for the diagnosis of CM, but only 58% specificity.
Conclusions: Although we demonstrate features associated with CM and TBM, a sufficiently sensitive and specific diagnostic algorithm could not be derived, suggesting that the diagnosis of CM and TBM in resource-limited settings still requires better access to laboratory tools.
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Source |
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http://dx.doi.org/10.1111/j.1365-3156.2010.02565.x | DOI Listing |
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