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
Objectives: To evaluate the effectiveness of a three-dimensional (3D) printed transparent kidney model as a surgical navigator for robot-assisted partial nephrectomy (RPN) in patients with complex renal tumours, defined by a R.E.N.A.L. (Radius, Exophytic/Endophytic, Nearness, Anterior/Posterior, Location) nephrometry score of ≥7.
Patients And Methods: A total of 80 patients who underwent RPN were included in the present prospective case-matched study (case group [n = 40, application of 3D-printed transparent kidney model during RPN] vs matching group [n = 40, routine protocol]). The RPNs were performed by a single experienced surgeon. The RPN procedure consisted of six steps: (i) preparation of the renal hilar vessel for clamping, (ii) tumour detection and dissection, (iii) robotic ultrasonography, (iv) tumour resection, (v) calyx repair and haemostasis, and (vi) renorrhaphy. The time for each step, console time, and warm ischaemia time were compared between the two groups as a surrogate marker for surgical effectiveness.
Results: Both groups were well-balanced for all baseline characteristics. The use of the model reduced the console time by ~20% compared to the matched group (64.6 vs 78.5 min, P = 0.001). On multivariate logistic regression analysis, tumour radius (P < 0.001) and application of the model (P = 0.009) were identified as significant predictors of a console time of ≤70 min.
Conclusion: We established the usefulness of a personalised 3D-printed transparent kidney model for more effective RPNs. Use of the 3D-printed transparent kidney model reduced the operative time even for complex renal tumours and would be expected to broaden the indications for PN.
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Source |
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http://dx.doi.org/10.1111/bju.15275 | DOI Listing |
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