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
Longitudinal physical activity monitoring is a novel and promising objective outcome measure for patients with degenerative spine disorder (DSD) that currently lacks established standards for data collection and interpretation. Here, we monitored 100 patients with DSD with the Apple Watch to establish the optimal duration and pattern of step count monitoring needed to estimate their weekly physical activity before their elective surgery. Participants were predominantly female (65.3%), had an average age of 61.5 years, and showed consistent step counts between preoperative days, as well as across weekends and weekdays. Intraclass correlations (ICC) analysis showed that a step count average over 2 days achieved an ICC of 0.92 when compared to a 7-day average before surgery, while 4 days were required for a similar agreement of 0.93 with a 14-day average. Sequential linear regression demonstrated that incorporating additional preoperative days improved the model's ability to predict 7- and 14-days step count averages. We conclude that, while daily preoperative step counts remain relatively stable, longer activity monitoring is necessary to account for the variance in step count over an increasing time frame, and the full extent of data fluctuation may only become apparent with long-term trend analysis.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11358281 | PMC |
http://dx.doi.org/10.1038/s41598-024-70912-7 | DOI Listing |
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