文章基本信息

标题：Bayesian hierarchical nonlinear modelling of intra-abdominal volume during pneumoperitoneum for laparoscopic surgery
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作者：Gabriel Calvo ; Carmen Armero ; Virgilio Gómez-Rubio 等
期刊名称：SORT-Statistics and Operations Research Transactions
印刷版ISSN：2013-8830
出版年度：2021
卷号：45
期号：2
页码：143-162
语种：Portuguese
出版社：SORT- Statistics and Operations Research Transactions
摘要：Laparoscopy is an operation carried out in the abdomen through small incisions with visual control by a camera. This technique needs the abdomen to be insufflated with carbon dioxide to obtain a working space for surgical instruments’ manipulation. Identifying the critical point at which insufflation should be limited is crucial to maximizing surgical working space and minimizing injurious effects. A Bayesian nonlinear growth mixed-effects model for the relationship between the insufflation pressure and the intra–abdominal volume generated is discussed as well as its plausibility to represent the data.
关键词：intra-abdominal pressure;logistic growth function;Markov chain;Monte Carlo methods;random effects