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
Background Mortality risk and outcome in critically ill patients can be predicted by scoring systems, such as APACHE and SAPS. The identification of prognostic biomarkers, simple to measure upon admission to an intensive care unit (ICU) is an open issue. The aim of this observational study was to assess the prognostic value of plasma mid-regional pro-adrenomedullin (MR-proADM) at ICU admission in non-selected patients in comparison to Acute Physiology and Chronic Health Evaluation II (APACHEII) and Simplified Acute Physiology Score II (SAPSII) scores. Methods APACHEII and SAPSII scores were calculated after 24 h from ICU admission. Plasma MR-proADM levels were measured by TRACE-Kryptor on admission (T0) and after 24 h (T24). The primary endpoint was intra-hospital mortality; secondary endpoint was length of stay (LOS). Results One hundred and twenty-six consecutive non-selected patients admitted to an ICU were enrolled. Plasma MR-proADM levels were correlated with LOS (r=0.28; p=0.0014 at T0; r=0.26; p=0.005 at T24). Multivariate analysis showed that T0 MR-proADM was a significant predictor of mortality (odds ratio [OR]: 1.27; 95% confidence interval [95%CI]: 1.03-1.55; p=0.022). Receiver operating characteristic curves analysis revealed that MR-proADM on ICU admission identified non-survivors with high accuracy, not inferior to the one of APACHEII and SAPSII scores (area under the curve [AUC]: 0.71; 95%CI: 0.62-0.78; p=0.0002 for MR-proADM; AUC: 0.71; 95%CI: 0.62-0.79; p<0.0001 for APACHEII; AUC: 0.8; 95%CI: 0.71-0.87; p<0.0001 for SAPSII). Conclusions Our findings point out a role of MR-proADM as a prognostic tool in non-selected patients in ICUs being a reliable predictor of mortality and LOS and support its use on admission to an ICU to help the management of critically ill patients.
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http://dx.doi.org/10.1515/cclm-2018-0645 | DOI Listing |
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