Textbook outcome in patients with biliary duct injury during cholecystectomy.

BACKGROUND: Iatrogenic bile duct injury (BDI) during cholecystectomy is associated with a complex and heterogeneous management owing to the burden of morbidity until their definitive treatment. This study aimed to define the textbook outcomes (TOs) after BDI with the purpose to indicate the ideal treatment and to improve it management. METHODS: We collected data from patients with an BDI between 1990 and 2022 from 27 hospitals. TO was defined as a successful conservative treatment of the iatrogenic BDI or only minor complications after BDI or patients in whom the first repair resolves the iatrogenic BDI without complications or with minor complications. RESULTS: We included 808 patients and a total of 394 patients (46.9%) achieved TO. Overall complications in TO and non-TO groups were 11.9% and 86%, respectively (P < .001). Major complications and mortality in the non-TO group were 57.4% and 9.2%, respectively. The use of end-to-end bile duct anastomosis repair was higher in the non-TO group (23.1 vs 7.8, P < .001). Factors associated with achieving a TO were injury in a specialized center (adjusted odds ratio [aOR], 4.01; 95% CI, 2.68-5.99; P < .001), transfer for a first repair (aOR, 5.72; 95% CI, 3.51-9.34; P < .001), conservative management (aOR, 5.00; 95% CI, 1.63-15.36; P = .005), or surgical management (aOR, 2.45; 95% CI, 1.50-4.00; P < .001). CONCLUSION: TO largely depends on where the BDI is managed and the type of injury. It allows hepatobiliary centers to identify domains of improvement of perioperative management of patients with BDI.

Machine Learning-Based Analysis in the Management of Iatrogenic Bile Duct Injury During Cholecystectomy: a Nationwide Multicenter Study.

BACKGROUND: Iatrogenic bile duct injury (IBDI) is a challenging surgical complication. IBDI management can be guided by artificial intelligence models. Our study identified the factors associated with successful initial repair of IBDI and predicted the success of definitive repair based on patient risk levels. METHODS: This is a retrospective multi-institution cohort of patients with IBDI after cholecystectomy conducted between 1990 and 2020. We implemented a decision tree analysis to determine the factors that contribute to successful initial repair and developed a risk-scoring model based on the Comprehensive Complication Index. RESULTS: We analyzed 748 patients across 22 hospitals. Our decision tree model was 82.8% accurate in predicting the success of the initial repair. Non-type E (p < 0.01), treatment in specialized centers (p < 0.01), and surgical repair (p < 0.001) were associated with better prognosis. The risk-scoring model was 82.3% (79.0-85.3%, 95% confidence interval [CI]) and 71.7% (63.8-78.7%, 95% CI) accurate in predicting success in the development and validation cohorts, respectively. Surgical repair, successful initial repair, and repair between 2 and 6 weeks were associated with better outcomes. DISCUSSION: Machine learning algorithms for IBDI are a novel tool may help to improve the decision-making process and guide management of these patients.

Benefit Finding in Cardiac Patients: Relationships with Emotional Well-Being and Resources after Controlling for Physical Functional Impairment.

Benefit finding (BF) is defined as the individual's perception of positive change as a result of coping with an adverse life event. The beneficial effects of BF on well-being could be because BF favors the improvement of resources like self-efficacy, social support and effective coping. The main objective of this longitudinal 8 week study was to explore, in a sample of cardiac patients (n = 51), the combined contribution of BF and these resources to the positive affect. Moreover, we wanted to check whether these resources were derived from BF or, on the contrary, these resources were antecedents of BF. Results showed that after controlling for functional capacity, only effective coping could predict the positive affect at Time 1 (ß = .32, p < .05), while the BF predicted it at Time 2 (ß = .23, p < .001). Only social support predicted BF (ß = .26, p < .05), but not the opposite. We discussed the desirability of promoting these processes to improve the emotional state of cardiac patients.