Marco Gemma1, Fulvia Pennoni2, Marco Braga3. 1. Anesthesia and Intensive Care, Fatebenefratelli Hospital, Piazza Principessa Clotilde, 3, 20121, Milan, Italy. 2. Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Via degli Arcimboldi, 8, 20126, Milan, Italy. fulvia.pennoni@unimib.it. 3. Department of Surgery, University of Milano-Bicocca, San Gerardo Hospital, Via Pergolesi G. B., 33, 20900, Monza, Italy.
Abstract
BACKGROUND: Previous Enhanced Recovery After Surgery (ERAS®) studies have not always taken into account that ERAS interventions depend on baseline covariates and that several confounding variables affect the composite outcomes. METHOD: A causal latent variable model is proposed to analyze data obtained prospectively concerning 1261 patients undergoing elective colorectal surgery within the ERAS protocol. Primary outcomes (composite of any complication, surgical site infection, medical complications, early ready for discharge (TRD), early actual discharge) and secondary outcomes (composite of late bowel function recovery, IV fluid resumption, nasogastric tube replacement, postoperative nausea and vomiting, re-intervention, re-admission, death) are considered along with their multiple dimensions. RESULTS: Concerning the primary outcomes, our results evidence three subpopulations of patients: one with probable good outcome, one with possibly prolonged TRD and discharge without complications, and the other one with probable complications and prolonged TRD and discharge. Epidural anesthesia, waiving surgical drainage, and early ambulation, IV fluid stop and urinary catheter removal act favorably, while preoperative hospital stay and blood transfusion act negatively. Concerning the secondary outcomes our results evidence two subpopulations of patients: one with high probability of good outcome and one with high probability of complications. Epidural anesthesia, waiving surgical drainage, early ambulation and IV fluid stop act favorably, while blood transfusion acts negatively also with respect to these secondary outcomes. CONCLUSION: The multivariate causal latent class two-parameter logistic model, a modern statistical method overcoming drawbacks of traditional models to estimate the average causal effects on the treated, allows us to disentangle subpopulations of patients and to evaluate ERAS interventions.
BACKGROUND: Previous Enhanced Recovery After Surgery (ERAS®) studies have not always taken into account that ERAS interventions depend on baseline covariates and that several confounding variables affect the composite outcomes. METHOD: A causal latent variable model is proposed to analyze data obtained prospectively concerning 1261 patients undergoing elective colorectal surgery within the ERAS protocol. Primary outcomes (composite of any complication, surgical site infection, medical complications, early ready for discharge (TRD), early actual discharge) and secondary outcomes (composite of late bowel function recovery, IV fluid resumption, nasogastric tube replacement, postoperative nausea and vomiting, re-intervention, re-admission, death) are considered along with their multiple dimensions. RESULTS: Concerning the primary outcomes, our results evidence three subpopulations of patients: one with probable good outcome, one with possibly prolonged TRD and discharge without complications, and the other one with probable complications and prolonged TRD and discharge. Epidural anesthesia, waiving surgical drainage, and early ambulation, IV fluid stop and urinary catheter removal act favorably, while preoperative hospital stay and blood transfusion act negatively. Concerning the secondary outcomes our results evidence two subpopulations of patients: one with high probability of good outcome and one with high probability of complications. Epidural anesthesia, waiving surgical drainage, early ambulation and IV fluid stop act favorably, while blood transfusion acts negatively also with respect to these secondary outcomes. CONCLUSION: The multivariate causal latent class two-parameter logistic model, a modern statistical method overcoming drawbacks of traditional models to estimate the average causal effects on the treated, allows us to disentangle subpopulations of patients and to evaluate ERAS interventions.
Authors: Stefano Turi; Marco Gemma; Marco Braga; Roberta Monzani; Danilo Radrizzani; Luigi Beretta Journal: Int J Colorectal Dis Date: 2019-03-29 Impact factor: 2.571
Authors: Daniel F McCaffrey; Beth Ann Griffin; Daniel Almirall; Mary Ellen Slaughter; Rajeev Ramchand; Lane F Burgette Journal: Stat Med Date: 2013-03-18 Impact factor: 2.373
Authors: Richard H Parrish; Rachelle Findley; Kevin M Elias; Brian Kramer; Eric G Johnson; Leah Gramlich; Gregg S Nelson Journal: Ann Med Surg (Lond) Date: 2021-12-14