A prediction model for postoperative urinary retention after thoracic surgeryCentral MessagePerspective
Benjamin Wei, MD,
Ammar Asban, MD, MAS,
Rongbing Xie, DrPH, MPH,
Zachary Sollie, BS,
Luqin Deng, PhD, MS,
Thomas K. DeLay, BS,
William B. Swicord, BS,
Rajat Kumar, MD,
James K. Kirklin, MD,
James Donahue, MD
Affiliations
Benjamin Wei, MD
Address for reprints: Benjamin Wei, MD, Zeigler Research Building, 707 19th St S, Birmingham, AL 35233.; Department of Cardiothoracic Surgery, University of Alabama at Birmingham School of Medicine, UAB Hospital, Birmingham, Ala
Ammar Asban, MD, MAS
Department of Cardiothoracic Surgery, University of Alabama at Birmingham School of Medicine, UAB Hospital, Birmingham, Ala
Rongbing Xie, DrPH, MPH
Department of Cardiothoracic Surgery, University of Alabama at Birmingham School of Medicine, UAB Hospital, Birmingham, Ala
Zachary Sollie, BS
Department of Cardiothoracic Surgery, University of Alabama at Birmingham School of Medicine, UAB Hospital, Birmingham, Ala
Luqin Deng, PhD, MS
Department of Cardiothoracic Surgery, University of Alabama at Birmingham School of Medicine, UAB Hospital, Birmingham, Ala
Thomas K. DeLay, BS
Department of Cardiothoracic Surgery, University of Alabama at Birmingham School of Medicine, UAB Hospital, Birmingham, Ala
William B. Swicord, BS
Department of Cardiothoracic Surgery, University of Alabama at Birmingham School of Medicine, UAB Hospital, Birmingham, Ala
Rajat Kumar, MD
Department of Cardiothoracic Surgery, University of Alabama at Birmingham School of Medicine, UAB Hospital, Birmingham, Ala
James K. Kirklin, MD
Department of Cardiothoracic Surgery, University of Alabama at Birmingham School of Medicine, UAB Hospital, Birmingham, Ala
James Donahue, MD
Department of Cardiothoracic Surgery, University of Alabama at Birmingham School of Medicine, UAB Hospital, Birmingham, Ala
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.
