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
The increasing burden of multidrug-resistant bacteria affects the management of several infections. In order to prescribe adequate antibiotics, clinicians facing severe infections such as hospital-acquired pneumonia (HAP) need to promptly identify the pathogens and know their antibiotic susceptibility profiles (AST), which with conventional microbiology currently requires 24 and 48 h, respectively. Clinical metagenomics, based on whole genome sequencing of clinical samples, could improve the diagnosis of HAP, however, many obstacles remain to be overcome, namely the turn-around time, the quantification of pathogens, the choice of antibiotic resistance determinants (ARDs), the inference of the AST from metagenomic data and the linkage between ARDs and their host. Here, we propose to tackle those issues in a bottom-up, clinically driven approach.
Download full-text PDF |
Source |
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http://dx.doi.org/10.2217/fmb.15.144 | DOI Listing |
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