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
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Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
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Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
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Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
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Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
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Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
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Function: require_once
Importance: Growing consensus suggests that frailty-associated risks should inform shared surgical decision making. However, it is not clear how best to screen for frailty in preoperative surgical populations.
Objective: To develop and validate the Risk Analysis Index (RAI), a 14-item instrument used to measure surgical frailty. It can be calculated prospectively (RAI-C), using a clinical questionnaire, or retrospectively (RAI-A), using variables from the surgical quality improvement databases (Veterans Affairs or American College of Surgeons National Surgical Quality Improvement Projects).
Design, Setting, And Participants: Single-site, prospective cohort from July 2011 to September 2015 at the Veterans Affairs Nebraska-Western Iowa Heath Care System, a Level 1b Veterans Affairs Medical Center. The study included all patients presenting to the medical center for elective surgery.
Exposures: We assessed the RAI-C for all patients scheduled for surgery, linking these scores to administrative and quality improvement data to calculate the RAI-A and the modified Frailty Index.
Main Outcomes And Measures: Receiver operator characteristics and C statistics for each measure predicting postoperative mortality and morbidity.
Results: Of the participants, the mean (SD) age was 60.7 (13.9) years and 249 participants (3.6%) were women. We assessed the RAI-C 10 698 times, from which we linked 6856 unique patients to mortality data. The C statistic predicting 180-day mortality for the RAI-C was 0.772. Of these 6856 unique patients, we linked 2785 to local Veterans Affairs Surgeons National Surgical Quality Improvement Projects data and calculated the C statistic for both the RAI-A (0.823) and RAI-C (0.824), along with the correlation between the 2 scores (r = 0.478; P < .001). Of these 2785 patients, there were sufficient data to calculate the modified Frailty Index for 1021, in which the C statistics were 0.865 (RAI-A), 0.797 (RAI-C), and 0.811 (modified Frailty Index). The correlation between the RAI-A and RAI-C was 0.547, and the correlations of the modified Frailty Index to the RAI-A and RAI-C were 0.301 and 0.269, respectively (all P < .001). A cutoff of RAI-C of at least 21 classified 18.3% patients as "frail" with a sensitivity of 0.50 and specificity of 0.82, whereas the RAI-A was less sensitive (0.25) and more specific (0.97), classifying only 3.7% as "frail."
Conclusions And Relevance: The RAI-C and RAI-A represent effective tools for measuring frailty in surgical populations with predictive ability on par with other frailty tools. Moderate correlation between the measures suggests convergent validity. The RAI-C offers the advantage of prospective, preoperative assessment that is proved feasible for large-scale screening in clinical practice. However, further efforts should be directed at determining the optimal components of preoperative frailty assessment.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7140150 | PMC |
http://dx.doi.org/10.1001/jamasurg.2016.4202 | DOI Listing |
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