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
Outcome prediction after spinal cord injury (SCI) is essential for early counseling and orientation of the rehabilitative intervention. Moreover, prognostication of outcome is crucial to achieving meaningful stratification when conceiving clinical trials. Neurophysiological examinations are commonly employed for prognostication after SCI, but whether neurophysiology could improve the functional prognosis based on clinical predictors remains an open question. Data of 224 patients included in the European Multicenter Study about Spinal Cord Injury were analyzed with bootstrapping analysis and multivariate logistical regression to derive prediction models of complete functional recovery in the chronic stage after traumatic cervical SCI. Within 40 days after SCI, we evaluated age, gender, the motor and sensory cumulative scores of the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI), and neurophysiological variables (motor evoked potentials, sensory evoked potentials, nerve conduction study) as possible predictors. Positive outcome was defined by a Spinal Cord Independence Measure total score of 100. Analyzing clinical variables, we derived a prediction model based on the ISNCSCI total motor score and age: the area under the receiver operating curve (AUC) was 0.936 (95% confidence interval [CI]: 0.904-0.968). Adding neurophysiological variables to the model, the AUC increased significantly: 0.956 (95% CI: 0.930-0.982; p = 0.019). More patients could be correctly classified by adding the electrophysiological data. Our study demonstrates that neurophysiological assessment improves the prediction of functional prognosis after traumatic cervical SCI, and suggests the use of neurophysiology to optimize patient information, rehabilitation, and discharge planning and the design of future clinical trials.
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http://dx.doi.org/10.1089/neu.2017.5576 | DOI Listing |
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