Bayesian hierarchical nonlinear modelling of intra-abdominal volume during pneumoperitoneum for laparoscopic surgery
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 insuff...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universitat Autònoma de Barcelona |
| Repositorio: | Dipòsit Digital de Documents de la UAB |
| Idioma: | inglés |
| OAI Identifier: | oai:ddd.uab.cat:250119 |
| Acceso en línea: | https://ddd.uab.cat/record/250119 https://dx.doi.org/urn:doi:10.2436/20.8080.02.113 |
| Access Level: | acceso abierto |
| Palabra clave: | Intra-abdominal pressure Logistic growth function Markov chain Monte Carlo methods Random effects |
| Sumario: | 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. |
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