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A prediction model for postoperative urinary retention after thoracic surgery
BACKGROUND: Urinary retention remains a frequent postoperative complication, associated with patient discomfort and delayed discharge following general thoracic surgery (GTS). We aimed to develop and prospectively validate a predictive model of postoperative urinary retention (POUR) among GTS patien...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9390440/ https://www.ncbi.nlm.nih.gov/pubmed/36003757 http://dx.doi.org/10.1016/j.xjon.2021.05.006 |
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author | Wei, Benjamin Asban, Ammar Xie, Rongbing Sollie, Zachary Deng, Luqin DeLay, Thomas K. Swicord, William B. Kumar, Rajat Kirklin, James K. Donahue, James |
author_facet | Wei, Benjamin Asban, Ammar Xie, Rongbing Sollie, Zachary Deng, Luqin DeLay, Thomas K. Swicord, William B. Kumar, Rajat Kirklin, James K. Donahue, James |
author_sort | Wei, Benjamin |
collection | PubMed |
description | BACKGROUND: Urinary retention remains a frequent postoperative complication, associated with patient discomfort and delayed discharge following general thoracic surgery (GTS). We aimed to develop and prospectively validate a predictive model of postoperative urinary retention (POUR) among GTS patients. METHODS: We retrospectively developed a predictive model using data from the Society of Thoracic Surgeons GTS Database at our institution. The patient study cohort included adults undergoing elective in-patient surgical procedures without a history of renal failure or Foley catheter on entry to the recovery suite (August 2013 to March 2017). Multivariable logistic regression models identified factors associated with urinary retention, and a nomogram to aid medical decision making was developed. The predictive model was validated in a cohort of GTS patients between April 2017 and November 2018 using receiver operating characteristic (ROC) analysis. RESULTS: The predictive model was developed from 1484 GTS patients, 284 of whom (19%) experienced postoperative urinary retention within 24 hours of the operation. Risk factors for POUR included older age, male sex, higher preoperative creatinine, chronic obstructive pulmonary disease, primary diagnosis, primary procedure, and use of postoperative patient-controlled analgesia. A logistic nomogram for estimating the risk of POUR was created and validated in 646 patients, 65 of whom (10%) had urinary retention. The ROC curves of development and validation models had similar favorable c-statistics (0.77 vs 0.72; P > .05). CONCLUSIONS: Postoperative urinary retention occurs in nearly 20% of patients undergoing major GTS. Using a validated predictive model may help by targeting certain patients with prophylactic measures to prevent this complication. |
format | Online Article Text |
id | pubmed-9390440 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-93904402022-08-23 A prediction model for postoperative urinary retention after thoracic surgery Wei, Benjamin Asban, Ammar Xie, Rongbing Sollie, Zachary Deng, Luqin DeLay, Thomas K. Swicord, William B. Kumar, Rajat Kirklin, James K. Donahue, James JTCVS Open Thoracic: Perioperative Management BACKGROUND: Urinary retention remains a frequent postoperative complication, associated with patient discomfort and delayed discharge following general thoracic surgery (GTS). We aimed to develop and prospectively validate a predictive model of postoperative urinary retention (POUR) among GTS patients. METHODS: We retrospectively developed a predictive model using data from the Society of Thoracic Surgeons GTS Database at our institution. The patient study cohort included adults undergoing elective in-patient surgical procedures without a history of renal failure or Foley catheter on entry to the recovery suite (August 2013 to March 2017). Multivariable logistic regression models identified factors associated with urinary retention, and a nomogram to aid medical decision making was developed. The predictive model was validated in a cohort of GTS patients between April 2017 and November 2018 using receiver operating characteristic (ROC) analysis. RESULTS: The predictive model was developed from 1484 GTS patients, 284 of whom (19%) experienced postoperative urinary retention within 24 hours of the operation. Risk factors for POUR included older age, male sex, higher preoperative creatinine, chronic obstructive pulmonary disease, primary diagnosis, primary procedure, and use of postoperative patient-controlled analgesia. A logistic nomogram for estimating the risk of POUR was created and validated in 646 patients, 65 of whom (10%) had urinary retention. The ROC curves of development and validation models had similar favorable c-statistics (0.77 vs 0.72; P > .05). CONCLUSIONS: Postoperative urinary retention occurs in nearly 20% of patients undergoing major GTS. Using a validated predictive model may help by targeting certain patients with prophylactic measures to prevent this complication. Elsevier 2021-05-26 /pmc/articles/PMC9390440/ /pubmed/36003757 http://dx.doi.org/10.1016/j.xjon.2021.05.006 Text en © 2021 The Authors. Published by Elsevier Inc. on behalf of The American Association for Thoracic Surgery. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Thoracic: Perioperative Management Wei, Benjamin Asban, Ammar Xie, Rongbing Sollie, Zachary Deng, Luqin DeLay, Thomas K. Swicord, William B. Kumar, Rajat Kirklin, James K. Donahue, James A prediction model for postoperative urinary retention after thoracic surgery |
title | A prediction model for postoperative urinary retention after thoracic surgery |
title_full | A prediction model for postoperative urinary retention after thoracic surgery |
title_fullStr | A prediction model for postoperative urinary retention after thoracic surgery |
title_full_unstemmed | A prediction model for postoperative urinary retention after thoracic surgery |
title_short | A prediction model for postoperative urinary retention after thoracic surgery |
title_sort | prediction model for postoperative urinary retention after thoracic surgery |
topic | Thoracic: Perioperative Management |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9390440/ https://www.ncbi.nlm.nih.gov/pubmed/36003757 http://dx.doi.org/10.1016/j.xjon.2021.05.006 |
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