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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Background is an emerging but under-recognized cause of bloodstream infections (BSIs) in intensive care unit (ICU) settings, where invasive procedures and immunocompromised states increase vulnerability. Despite its clinical importance, the epidemiology and risk factors associated with BSIs remain poorly understood, especially in low- and middle-income countries. Gap Most existing studies generalize Gram-negative pathogens without isolating the specific impact of in ICU populations. There is a lack of data on species, specific risk factors, infection sources, and outcome predictors. Methodology A retrospective cross-sectional study was conducted on 30 adult ICU patients admitted between January and December 2024. Clinical, procedural, and microbiological data were extracted from electronic medical records. Statistical analysis and regression modeling (Linear, Ridge, and Lasso) were applied using SPSS and Python to identify significant predictors of ICU stay and infection risk. Findings and conclusion was detected in 53.3% of patients, and 56.7% of infections are hospital-acquired. Central line use (60%), ventilator support (60%), and urinary catheterization (63.3%) were more frequent among infected individuals. Regression models identified central line placement (β=3.24), hospital-acquired infection (β=2.46), and diabetes (β=1.05) as major predictors of prolonged ICU stay. Lasso regression highlighted the device and related variables as the most robust predictors.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12381679 | PMC |
http://dx.doi.org/10.7759/cureus.91083 | DOI Listing |