ASO Author Reflections: Trimming the Fat: Improving Access to Immediate Breast Reconstructive Surgery by Streamlining Operating Room Resources

2019 ◽  
Vol 26 (S3) ◽  
pp. 729-730
Author(s):  
Esta S. Bovill ◽  
Elaine C. McKevitt
2019 ◽  
Vol 74 (1) ◽  
pp. 13-28 ◽  
Author(s):  
N.D. Thimmappa ◽  
J.V. Vasile ◽  
C.Y. Ahn ◽  
J.L. Levine ◽  
M.R. Prince

2012 ◽  
Vol 48 ◽  
pp. S177 ◽  
Author(s):  
M. Kiechle ◽  
E. Klein ◽  
D. Paepke ◽  
H. Bronger ◽  
J. Ettl ◽  
...  

2020 ◽  
Vol 2 (11) ◽  
pp. 1753-1756
Author(s):  
Paulina R. Skaff ◽  
Bridget S. Phillips ◽  
John H. Lobban ◽  
Christopher M. Bianco

1991 ◽  
Vol 87 (4) ◽  
pp. 785-787
Author(s):  
Franco Marconi ◽  
Mario Marra ◽  
Alberto Boni

2016 ◽  
pp. 273-289
Author(s):  
Yash J. Avashia ◽  
Amir Tahernia ◽  
Detlev Erdmann ◽  
Michael R. Zenn

2018 ◽  
Vol 36 (30_suppl) ◽  
pp. 240-240
Author(s):  
Samantha Tam ◽  
Wenli Dong ◽  
Ira L Martin ◽  
David Matthew Adelman ◽  
Randal S. Weber ◽  
...  

240 Background: With increasing health care costs, risk-adjusted quality outcomes are essential. The American College of Surgeons – National Surgical Quality Improvement Program (ACS-NSQIP) is a robust perioperative risk-adjustment platform, but lacks capture of oncologic- and specialty-specific variables and has limited utility for risk adjustment in head and neck oncologic surgery. This study uses the specialty-specific Head and Neck-Reconstructive Surgery (HNSR) NSQIP to develop risk-adjusted models for patients undergoing head and neck oncologic surgery with reconstruction. Methods: Multiple logistic regression modelling using data from patients in the HNSR NSQIP between 8/2012-10/2016 identified predictors of postoperative morbidity. Final models were validated using a cohort of patients treated between 10/2016-12/2017. The concordance index (c-index) was used to evaluate the model performance. Results: The modelling cohort included 1095 patients and the validation cohort included 407. Models were created to predict probability of postoperative complications (presence of fistula, ventilator dependence > 48 hours, pneumonia, deep/superficial surgical site infection); presence of gastrostomy-jejunostomy (GJ), nasoenteric (NE), or tracheostomy tube at 30 days postoperatively; conversion from NE to GJ tube; unplanned return to the operating room; and length of stay > 7 days. Most discriminant models were those predicting presence of GJ tube (model c-index [MCI] = 0.91; validation c-index[VCI] = 0.93), NE tube (MCI= 0.83; VCI= 0.84), and conversion from NE to GJ tube (MCI= 0.86; VCI= 0.80). Prediction models were least discriminant for ventilator dependence (MCI= 0.63; VCI= 0.45), fistula (MCI= 0.58; VCI= 0.54), and unplanned return to the operating room (MCI= 0.59; VCI= 0.51). Conclusions: Reliable and discriminant risk prediction models were able to be created for a variety of perioperative complications incorporating oncologic- and specialty-specific variables in the HNSR NSQIP. These models help inform risk stratification strategies for patients undergoing head and neck reconstructive surgery and the development of a specialty-specific preoperative risk calculators.


2017 ◽  
Vol 214 (3) ◽  
pp. 495-500 ◽  
Author(s):  
Erin Cordeiro ◽  
Toni Zhong ◽  
Timothy Jackson ◽  
Tulin Cil

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