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Filename: drivers/Session_files_driver.php
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Filename: Session/Session.php
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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Filename: models/Detail_model.php
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Filename: helpers/my_audit_helper.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Function: _error_handler
File: /var/www/html/index.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
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Function: require_once
Pressure support ventilation (PSV) should be titrated considering the pressure developed by the respiratory muscles (P) to prevent under- and over-assistance. The esophageal pressure (P) is the clinical gold standard for P assessment, but its use is limited by alleged invasiveness and complexity. The least square fitting method and the end-inspiratory occlusion method have been proposed as non-invasive alternatives for P assessment. The aims of this study were: (1) to compare the accuracy of P estimation using the end-inspiration occlusion (P) and the least square fitting (P) against the reference method based on P; (2) to test the accuracy of P and of P to detect overassistance, defined as P ≤ 1 cmHO. We studied 18 patients at three different PSV levels. At each PSV level, P, P, P were calculated on the same breaths. Differences among P, P, P were analyzed with linear mixed effects models. Bias and agreement were assessed by Bland-Altman analysis for repeated measures. The ability of P and P to detect overassistance was assessed by the area under the receiver operating characteristics curve. Positive and negative predictive values were calculated using cutoff values that maximized the sum of sensitivity and specificity. At each PSV level, P was not different from P (p = 0.96), whereas P was significantly lower than P. The bias between P and P was zero, whereas P systematically underestimated P of 6 cmHO. The limits of agreement between P and P and between P and P were ± 12 cmHO across bias. Both P ≤ 4 cmHO and P ≤ 1 cmHO had excellent negative predictive value [0.98 (95% CI 0.94-1) and 0.96 (95% CI 0.91-0.99), respectively)] to identify over-assistance. The inspiratory effort during PSV could not be accurately estimated by the least square fitting or end-inspiratory occlusion method because the limits of agreement were far above the signal size. These non-invasive approaches, however, could be used to screen patients at risk for absent or minimal respiratory muscles activation to prevent the ventilator-induced diaphragmatic dysfunction.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7330529 | PMC |
http://dx.doi.org/10.1007/s10877-020-00552-5 | DOI Listing |
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