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
Purpose: This study aims to examine the predictive value of Craniocervical Flexion Test (CCFT) scores in individuals with chronic non-specific neck pain (CNNP) and to identify factors that may affect CCFT scores.
Methods: This case-control study included 73 patients with CNNP and 127 healthy controls. We assessed baseline information such as demographics, duration and frequency of CNNP onset, Neck Disability Index (NDI), and Visual Analog Scale (VAS) scores. All subjects were evaluated by the same rater for CCFT, maximal muscle strength, and endurance of the deep cervical flexors. Head and neck posture was measured using two-dimensional videography, capturing sagittal head angle (SHA), forward head angle (FHA), and protracted shoulder angle (PSA). The predictive capacity of CCFT for CNNP was evaluated using the ROC curve and area under the curve (AUC). Univariate and multivariate ordered logistic regression models were employed to analyze factors influencing CCFT scores.
Results: The final analysis included 70 participants in the CNNP group and 123 in the control group. The CNNP group demonstrated lower CCFT scores, reduced maximal muscle strength, and decreased endurance of the deep cervical muscles (<0.05). Among maximum muscle strength, endurance, and CCFT scores, the latter exhibited the highest AUC. Univariate and multivariate ordered logistic regression analyses revealed that maximal muscle strength, muscle endurance, FHA, and lower NDI scores significantly increased the likelihood of higher CCFT scores (<0.05), while SHA significantly decreased this likelihood <0.05).
Conclusion: CCFT demonstrates good predictive value for CNNP, surpassing muscle strength and endurance. Maximal muscle strength, muscle endurance, FHA, and lower NDI scores were positive influencing factors for CCFT scores, whereas SHA was a negatively influencing factor.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11583758 | PMC |
http://dx.doi.org/10.2147/JPR.S482325 | DOI Listing |
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