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
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Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
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Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
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Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
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Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
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Function: require_once
Background: Balance and gait impairments increase fall rate and injury in people with neurological disorders(PwND). The modified Dynamic Gait Index(mDGI) is a scale assessing dynamic balance during walking, however its ability in identifying Fallers and Recurrent Fallers has not been studied.
Research Question: To evaluate mDGI's ability in identifying retrospective Fallers and Recurrent Fallers establishing cut-off scores for its use in clinical practice.
Method: In this cross-sectional study, the number of retrospective falls and mDGI scores were collected. PwND were categorised as Non-Fallers or Fallers (falls≥1) and as Recurrent Fallers(falls≥2) or Non-Recurrent/Non-Fallers(falls<2) according to their number of retrospective falls over two months. Two generalised linear logistic models were developed using a machine learning method to detect Fallers (Model 1) and Recurrent Fallers (Model 2) based on mDGI scores. ROC curves were used to identify mDGI cut-off scores to distinguish between different fall categories.
Results: 58 PwND (mean ± standard deviation age: 63.4 ± 12 years) including 28 people with Multiple Sclerosis, 15 people with Parkinson's disease and 15 people with Stroke were analysed. The mDGI score(median (IQR)) for Non-Fallers, Fallers, Recurrent Fallers and Non-Recurrent/Non-Fallers was respectively 50(22), 37(22), 26.5(20.25) and 46.5(20.5)points. The cut-off to identify Fallers from Non-Fallers was 49 points(sensitivity:100 %, specificity:50 %, post-test probability with mDGI ≤ cut-off: 53.2 %, post-test probability with mDGI > cut-off: 0%, AUC:0.68), while 29 points(sensitivity:60 %, specificity:79 %, post-test probability with mDGI ≤ cut-off:52.1 %, post-test probability with mDGI > cut-off:16.1 %, AUC:0.70) was the best cut-off to identify Recurrent Fallers.
Significance: People with mDGI score>49 points have low or minimal fall risk, while people with mDGI score≤49 points should be further investigated with other scales before starting a balance-focused rehabilitation intervention. People scoring ≤29 points on the mDGI scale may need a fall prevention intervention, regardless of the results of other balance clinical measures.
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Source |
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http://dx.doi.org/10.1016/j.gaitpost.2021.09.201 | DOI Listing |
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