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: 3122
Function: getPubMedXML
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
The intent of this study is to develop a predictive model to convert an oxygen desaturation index (ODI) to an apnea-hypopnea index (AHI). This model will then be compared to actual AHI to determine its precision. One thousand four hundred and sixty-seven subjects given polysomnograms with concurrent pulse oximetry between April 14, 2010, and February 7, 2012, were divided into model development (n = 733) and verification groups (n = 734) in order to develop a predictive model of AHI using ODI. Quadratic regression was used for model development. The coefficient of determination (r(2)) between the actual AHI and the predicted AHI (PredAHI) was 0.80 (r = 0.90), which was significant at a p < 0.001. The areas under the receiver operating characteristic curve ranged from 0.96 for AHI thresholds of ≥ 10 and ≥ 15/h to 0.97 for thresholds of ≥ 5 and ≥ 30/h. The algorithm described in this paper provides a convenient and accurate way to convert ODI to a predicted AHI. This tool makes it easier for clinicians to understand oximetry data in the context of traditional measures of sleep apnea.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1117/1.JBO.21.3.035006 | DOI Listing |
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