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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Acute Compartment Syndrome (ACS) is a serious medical condition that arises from increased pressure within osteofascial compartments, leading to impaired blood flow and potential tissue damage. Early and accurate diagnosis is critical for preventing permanent damage. Current methods rely largely on qualitative assessments with limited accuracy, and those that exploit invasive pressure measurements often prove inadequate. Herein, a soft materials-based multimodal sensor probe is introduced, as well as the mechanical and thermal influences to monitor intra-compartmental pressure, tissue oxygen saturation (StO), and blood flow simultaneously at a common location within an affected compartment. The system integrates three sensors into a thin, flexible probe capable of real-time, wireless data transmission. The device allows for continuous monitoring with high reproducibility and sensitivity, to enhance diagnostic accuracy relative to current clinical practice, with the potential to early diagnosis of an acute compartment syndrome that requires fasciotomies. Large animal model studies, including short- and intermediate-term reliability assessments, highlight the key engineering features. The results reveal expected inverse relationships between pressure, StO, and flow rate under simulated compartment syndrome conditions. This multimodal approach enhances diagnostic precision, offers real-time insights, and promises to yield improved outcomes through a comprehensive, quantitative diagnosis of compartment syndrome.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12412494 | PMC |
http://dx.doi.org/10.1002/advs.202506942 | DOI Listing |