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: To improve the performance of simplified sleep studies, it is essential to properly estimate the sleep time.
Objectives: Our aim is to estimate sleep efficiency on the basis of flow breathing signal characteristics.
Methods: Twenty subjects with sleep apnea-hypopnea syndrome diagnosed by polysomnography were studied. A characteristic pattern of flow signal defined our criteria for wakefulness and sleep. Sleep was analyzed in 2 different runs: (1) in the usual manner (neurological and respiratory variables), and (2) only the nasal cannula flow signal was displayed on the computer screen and the sleep and wakefulness periods were scored according to our criteria. At the end of the scoring process, all the signals were displayed on the screen to analyze the concordance.
Results: Three thousand and sixty-nine screens were analyzed. The polysomnography sleep efficiency measured was 80.8%. The estimated sleep efficiency measured by nasal prongs was 78.9%. The detection and concordance of wakefulness had a sensitivity of 58.7%, a specificity of 96.4%, a positive predictive value of 81.3% and a negative predictive value of 89.6%.
Conclusions: Our criteria for sleep and wakefulness based on airflow waveform morphology are a helpful parameter for estimating sleep efficiency in a simplified sleep study.
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Source |
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http://dx.doi.org/10.1159/000264656 | DOI Listing |
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