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
Background: After recent debate about the best measure of anatomic injury severity, this study aimed to compare four measures based on Abbreviated Injury Scale scores derived using ICDMAP-90-the Modified Anatomic Profile (ICD/mAP), Anatomic Profile Score (ICD/APS), Injury Severity Score (ICD/ISS), and New Injury Severity Score (ICD/NISS)-with the International Classification of Diseases-based Injury Severity Score (ICISS).
Methods: Data were selected from New Zealand public hospital discharges from 1989 to 1998. There were 349,409 patients in the dataset, of whom 3,871 had died. Models were compared in terms of their discrimination and calibration using logistic regression. Age was included as a covariate.
Results: The ICISS and ICD/mAP were the best performing measures. Adding age significantly improved the discrimination and calibration of almost all the models.
Conclusion: The ICISS is a viable alternative to ICDMAP-based measures for coding anatomic injury severity on large datasets.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1097/00005373-200208000-00023 | DOI Listing |
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