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: 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
Objective: The motorcyclist demographic is shifting to a larger proportion of riders over the age of 40. We sought to identify differences in orthopedic injury distribution and severity between 3 age cohorts and identify independent factors that contribute to fractures following a motorcycle collision (MCC).
Methods: A trauma registry at a level 1 trauma center was queried for motorcycle-related orthopedic injuries between January 1, 2008, and December 31, 2014. Subjects were stratified into 3 age groups: Young (<40 years), middle-aged (40-59 years), and elderly (≥60 years). Age groups were compared with respect to gender, weight, mechanism of collision, helmet use, Glascow Coma Scale (GCS), fracture type and location, Injury Severity Score (ISS), and hospital length of stay (LOS). A logistic regression model was constructed to identify independent factors that contribute to fractures following MCCs.
Results: Five hundred sixty-seven patients received care for motorcycle-related injuries (219 young, 264 middle-aged, and 84 elderly). Patients were predominantly male (88.7%), were wearing a helmet at the time of collision (58.0%), and sustained a mean of 1.48 fractures per patient. The primary mechanism of collision was noncollision transport accidents (41.4%). Elderly riders weighed significantly more than middle-aged and young riders (P < .0001). There was a significant difference in mean GCS between age groups (P = .02), with elderly patients demonstrating the highest mean GCS (14.0 ± 3.3). Young patients sustained no fractures most frequently when compared with middle-aged and elderly riders (P = .002). There was a significant difference in the percentage of patients sustaining right-sided, lower body fractures between age groups (P = .02) for elderly, middle-aged, and young patients, respectively. There was also a significant difference between age groups in the percentage of riders sustaining fractures other than those of the extremities, pelvis, or spine (P = .0005). Only age was identified as an independent predictor of sustaining a fracture (P = .008).
Conclusions: Elderly patients sustained fractures more frequently. There was no difference between age groups with respect to injury severity. Mechanism of collision may have more influence than age with respect to fracture type and location. Further research is warranted to develop a more widely generalizable characterization of motorcycle collision injury patterns, risk factors, and patient characteristics.
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http://dx.doi.org/10.1080/15389588.2018.1494384 | DOI Listing |
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