Predicting Best Performers After Minimally Invasive Left Pancreatectomy: Insights From a National Cohort.
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Pastier Clément, Chouillard Marc-Anthony, De Ponthaud Charles, Nassar Alexandra, Dokmak Safi, Bertrand Thibaud, De Martino Julien, Castel Antoine, De Rosa Raffaele, Boubaddi Mehdi, Iben-Khayat Abdallah, Giannone Fabio, Jolly Elsa, Garnier Jonathan, Louis-Gaubert Clément, Mazzotta Alessandro D, André Marie, Gagnière Johan, Viennet Manon, Souche François-Régis, Kianmanesh Reza, Lupinacci Renato Micelli, Regimbeau Jean-Marc, Paye François, Addeo Pietro, Laurent Alexis, Vandermeulen Morgan, Caiazzo Robert, El Amrani Mehdi, Tresallet Christophe, Doussot Alexandre, Bouquot Morgane, Jouffret Lionel, Pinto Amandine, Valverde Alain, Vece Rodolfo Romero, Fara Régis, Mahfouf Samir, Darnis Benjamin, Chamakhi Amine, Thereaux Jeremie, Lubrano Jean, Girard Edouard, Veziant Julie, Birnbaum David Jérémie, Danion Jérôme, Corté Helene, Zemour Johanna, Piardi Tullio, de Carbonnières Anne, Ragot Emilia, Le Bian Alban Zarzavadjian, David Patrice, Brunaud Laurent, Lermite Emilie, Chreim Laura, Charlaix Ana Lucia, Gugenheim Jean, Schwarz Lilian, Bigourdan Jean Marc, Le Roy Bertrand, Karam Elias, Rhaiem Rami, Fabre Jean-Michel, Lequeu Jean-Baptiste, Noirault Marie, Ayav Ahmet, Soubrane Olivier, Regenet Nicolas, Turrini Olivier, Muscari Fabrice, Pessaux Patrick, Thébault Baudouin, Laurent Christophe, Sulpice Laurent, Sauvanet Alain, Fuks David, Gaujoux Sébastien, AFC-23 study group
Аннотация
SUMMARY BACKGROUND DATA: Postoperative course after MILP can be assessed through the Ideal Outcome (IO), but no predictive tool is currently available.
METHODS: MILP performed between 2010-2022 across 55 French centers were included. 90-days IO required absence of mortality, severe complications, postoperative pancreatic fistula grade B/C (CR-POPF), reoperation, readmission, and length of stay (LOS)≤75 th percentile; Best Performer (BP) was IO with LOS≤25 th p. Predictors were evaluated using multivariable logistic regression and extreme gradient boosting (XGB). Model performance was assessed with nested cross-validation and 1,000-iteration bootstrap resampling.
RESULTS: Among 2,092 MILP, mortality was 1.3%, reoperation 5.6%, severe morbidity 17.9%, CR-POPF 18.8%, and readmission 15.3%; median LOS 9 days [IQR 7-13]. IO and BP occurred in 59.6% and 28.1%. Following a stepwise strategy, starting with a preoperative multivariable logistic regression model (AUC 0.57), then a preoperative-only XGBoost model (AUC 0.59), improved by inclusion of intraoperative variables (AUC 0.62); finally, after refining the endpoint to Best Performer (IO+LOS ≤25th percentile), the final XGBoost model achieved an AUC of 0.72 (95%CI 0.70-0.74). SHAP analysis identified center-volume and operative duration as the strongest contributors, followed by age, BMI, conversion, blood loss, and splenectomy. At the optimal threshold, sensitivity reached 0.78, specificity 0.57, PPV 0.41, and NPV 0.87. An online risk calculator is at disposal.
CONCLUSIONS: Predicting ideal postoperative trajectory after MILP remains challenging; identifying determinants may help optimize postoperative pathways by integrating preoperative and intraoperative determinants of recovery.