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
Aim: To develop and validate two aspiration prediction models in patients receiving nasogastric feeding.
Background: Aspiration is one of the most serious complications of nasogastric feeding. However, there is a lack of aspiration prediction models for nasogastric feeding.
Methods: A total of 515 patients receiving nasogastric feeding were randomly selected for this unmatched case-control study, with 103 patients in the case group and 412 patients in the control group. Logistic regression was used to develop nomogram and Classification And Regression Tree (CART) models. The performances of the models were internally validated using 1,000 bootstrapped samples.
Results: The predictive accuracy of the CART model (94.5%) was higher than that of the nomogram model (89.1%). The area under the receiver operating characteristic curve of the CART model (0.96) was slightly higher than that of the nomogram model (0.93).
Conclusions: The intubation depth, number of comorbidities, aspiration history, indwelling days, food type and the use of sedative-hypnotics may be used to identify aspiration risk.
Implications For Nursing Management: Two aspiration prediction models are provided for nurses to evaluate aspiration risk and increase the quality of nursing management.
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Source |
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http://dx.doi.org/10.1111/jonm.13093 | DOI Listing |
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