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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Objectives: Pressure injuries (PIs) are a global health concern, particularly in the context of an ageing population. They impose significant economic and social burdens, serve as key indicators of nursing quality, and are associated with increased mortality and morbidity.
Methods: We conducted a multi-center prospective descriptive study involving 3867 critically ill adults admitted to ICUs across 28 hospitals in Gansu Province, China, from April 1, 2021, to July 31, 2023. Data were collected using the "Long Hu Hui" PI risk management platform, which covers 98 indicators.
Results: The incidence of hospital-acquired PIs was 5.20 %. Univariate analysis identified 15 significant indicators associated with PIs, including body temperature, blood oxygen saturation, and central venous pressure. Logistic regression analysis revealed body temperature, diastolic blood pressure, blood oxygen saturation, haemoglobin, central venous pressure, and blood urea nitrogen as independent risk factors for PIs. A clinical prediction model was developed, demonstrating superior predictive performance compared to existing scales.
Conclusions: This study identified key physiological and biochemical markers associated with developing PIs in critically ill adults. The developed prediction model offers a more accurate tool for clinical risk assessment and may guide preventive strategies.
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http://dx.doi.org/10.1016/j.jtv.2025.100912 | DOI Listing |