Abstract
Laparoscopy is a surgical procedure carried out in the abdomen or pelvis through small incisions with the help of a camera to view the organs in the abdomen or permit small-scale surgery. This technique needs the abdomen to be insufflated with carbon dioxide (\(\text {CO}_2\)) 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. Bayesian nonlinear growth mixed-effects models are applied to data coming from a repeated measures design. The study allows to assess the relationship between the insufflation pressure and the intra-abdominal volume as well as to draw inferences and predictions for the main outcomes of the process.
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Acknowledgements
This paper was supported by research grant PID2019-106341GB-I00 funded by Ministerio de Ciencia e Innovación (Spain) and the Project MECESBAYES (SBPLY/17/180501/ 000491) funded by the Consejería de Educación, Cultura y Deportes, Junta de Comunidades de Castilla-La Mancha (Spain). Gabriel Calvo is also supported by grant FPU18/03101 from the Ministerio de Ciencia e Innovación (MCI, Spain). Merck Sharp & Dohme funded the IPPColLapse II study (Protocol Code No. 53607).
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Calvo, G., Armero, C., Gómez-Rubio, V., Mazzinari, G. (2022). Bayesian Growth Curve Model for Studying the Intra-abdominal Volume During Pneumoperitoneum for Laparoscopic Surgery. In: Argiento, R., Camerlenghi, F., Paganin, S. (eds) New Frontiers in Bayesian Statistics. BAYSM 2021. Springer Proceedings in Mathematics & Statistics, vol 405. Springer, Cham. https://doi.org/10.1007/978-3-031-16427-9_11
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DOI: https://doi.org/10.1007/978-3-031-16427-9_11
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