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
Background: Cardiopulmonary exercise testing is an increasingly common test and is considered the accepted standard for assessing exercise capacity. Quantifying variability is important to assess the instrument for quality control purposes. Though guidelines recommend biologic control testing, there are minimal data on how to do it. We sought to describe variability for oxygen consumption (V̇ ), carbon dioxide production (V̇ ), and minute ventilation (V̇) at various work rates under steady-state conditions in multiple subjects over a 1-y period to provide a practical approach to assess and perform biologic control testing.
Methods: We performed a single-center, prospective study with 4 healthy subjects, 2 men and 2 women. Subjects performed constant work rate exercise tests for 6 min each at 25-100 W intervals on a computer-controlled cycle ergometer. Data were averaged over the last 120 s at each work rate to reflect stepwise steady-state conditions. Descriptive statistics, including the mean, median, range, SD, and coefficient of variation (CoV) are reported for each individual across the 4 work rates and all repetitions. As these data were normative, z-scores were utilized, and a value greater than ± 1.96 z-scores was used to define significant test variability.
Results: Subjects performed 16-39 biocontrol studies over 1-y. The mean CoV for all subjects in V̇ was 6.59%, V̇ was 6.41%, and V̇ was 6.32%. The ± 1.96 z-scores corresponded to a 9.4-18.1% change in V̇ , a 9.6-18.1% change in V̇ , and a 9-21.5% change in V̇ across the 4 workloads.
Conclusions: We report long-term variability for steady-state measurement of V̇ , V̇ , and V̇ obtained during biocontrol testing. Utilizing ± 1.96 z-scores allows one to determine if a result exceeds expected variability, which may warrant investigation of the instrument.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9993516 | PMC |
http://dx.doi.org/10.4187/respcare.10022 | DOI Listing |
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