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
To individually prescribe rehabilitation contents, it is of importance to know and quantify factors for rehabilitation success and the risk for a future healthcare use. The objective of our multivariable prediction model was to determine factors of rehabilitation success and the risk for a future healthcare use in patients with high-grade, chronic low back pain. We included members of the German pension fund who participated from 2012 to 2019 in multimodal medical rehabilitation with physical and psychological treatment strategies because of low back pain (ICD10:M54.5). Candidate prognostic factors for rehabilitation success and for a future healthcare use were identified using Gradient Boosting Machines and Random Forest algorithms in the R-package caret on a 70% training and a 30% test set. We analysed data from 154,167 patients; 8015 with a second medical rehabilitation measure and 5161 who retired because of low back pain within the study period. The root-mean-square errors ranged between 494 (recurrent rehabilitation) and 523 (retirement) days ( R2 = 0.183-0.229), whereas the prediction accuracy ranged between 81.9% for the prediction of the rehabilitation outcome, and 94.8% for the future healthcare use prediction model. Many modifiable prognostic factors (such as duration of the rehabilitation [inverted u-shaped], type of the rehabilitation, and aftercare measure), nonmodifiable prognostic factors (such as sex and age), and disease-specific factors (such as sick leave days before the rehabilitation [linear positive] together with the pain grades) for rehabilitation success were identified. Inpatient medical rehabilitation programmes (3 weeks) may be more effective in preventing a second rehabilitation measure and/or early retirement because of low back pain compared with outpatient rehabilitation programs. Subsequent implementation of additional exercise programmes, cognitive behavioural aftercare treatment, and following scheduled aftercare are likely to be beneficial.
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Source |
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http://dx.doi.org/10.1097/j.pain.0000000000003087 | DOI Listing |
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