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
Objective: This study was undertaken to evaluate a modified form of Estimation of Physiologic Ability and Surgical Stress (E-PASS) for surgical audit comparing with other existing models.
Background: Although several scoring systems have been devised for surgical audit, no nation-wide survey has been performed yet.
Methods: We modified our previous E-PASS surgical audit system by computing the weights of 41 procedures, using data from 4925 patients who underwent elective digestive surgery, designated it as mE-PASS. Subsequently, a prospective cohort study was conducted in 43 national hospitals in Japan from April 1, 2005, to April 8, 2007. Variables for the E-PASS and American Society of Anesthesiologists (ASA) status-based model were collected for 5272 surgically treated patients. Of the 5272 patients, we also collected data for the Portsmouth modification of Physiologic and Operative Severity Score for the enUmeration of Mortality and morbidity (P-POSSUM) in 3128 patients. The area under the receiver operative characteristic curve (AUC) was used to evaluate discrimination performance to detect in-hospital mortality. The ratio of observed to estimated in-hospital mortality rates (OE ratio) was defined as a measure of quality.
Results: The numbers of variables required were 10 for E-PASS, 7 for mE-PASS, 20 for P-POSSUM, and 4 for the ASA status-based model. The AUC (95% confidence interval) values were 0.86 (0.79-0.93) for E-PASS, 0.86 (0.79-0.92) for mE-PASS, 0.81 (0.75-0.88) for P-POSSUM, and 0.73 (0.63-0.83) for the ASA status-based model. The OE ratios for mE-PASS among large-volume hospitals significantly correlated with those for E-PASS (R = 0.93, N = 9, P = 0.00026), P-POSSUM (R = 0.96, N = 6, P = 0.0021), and ASA status-based model (R = 0.83, N = 9, P = 0.0051).
Conclusion: Because of its features of easy use, accuracy, and generalizability, mE-PASS is a candidate for a nation-wide survey.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1097/SLA.0b013e3181f66199 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!