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|Title:||Risk factors for wound dehiscence following radical cystectomy: a prediction model||Authors:||Nasrallah, Ali A.
Abou Heidar, Nassib F.
Najdi, Jad A.
El Hajj, Albert
|Affiliations:||Faculty of Medicine||Keywords:||Cystectomy
Surgical wound dehiscence
Urinary bladder neoplasms
|Issue Date:||2021||Part of:||Therapeutic Advances in Urology||Volume:||13||Abstract:||
Objectives: Radical cystectomy (RC) is a complex urologic procedure performed for the treatment of bladder cancer and causes significant morbidity. Wound dehiscence (WD) is a major complication associated with RC and is associated with multiple risk factors. The objectives of this study are to identify clinical risk factors for incidence of WD and develop a risk-prediction model to aid in patient risk-stratification and improvement of perioperative care. Materials and Methods: The American College of Surgeons – National Surgical Quality Improvement Program (ACS-NSQIP) database was used to derive the study cohort. A univariate analysis provided nine variables eligible for multivariate model entry. A stepwise logistic regression analysis was conducted and refined considering clinical relevance of the variables, and then bootstrapped with 1000 samples, resulting in a five-factor model. Model performance and calibration were assessed by a receiver operated curve (ROC) analysis and the Hosmer–Lemeshow test for goodness of fit, respectively. Results: A cohort of 11,703 patients was identified from years 2005 to 2017, with 342 (2.8%) incidences of WD within 30 days of operation. The final five-factor model included male gender [odds ratio (OR) = 2.5, p < 0.001], surgical site infection (OR = 6.3, p < 0.001), smoking (OR = 1.8, p < 0.001), chronic obstructive pulmonary disease (COPD) (OR = 1.9, p < 0.001), and weight class; morbidly obese patients had triple the odds of WD (OR = 2.9, p < 0.001). The ROC analysis provided a C-statistic of 0.76 and calibration R2 was 0.99. Conclusion: The study yields a statistically robust and clinically beneficial five-factor model for estimation of WD incidence risk following RC, with good performance and excellent calibration. These factors may assist in identifying high-risk patients, providing preoperative counseling and thus leading to improvement in perioperative care.
|URI:||https://scholarhub.balamand.edu.lb/handle/uob/5276||ISSN:||17562872||DOI:||10.1177/17562872211060570||Ezproxy URL:||Link to full text||Type:||Journal Article|
|Appears in Collections:||Faculty of Medicine|
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