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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/178442
Predicting optimal anesthesia level from propofol and remifentanil concentration: analysis of covariate factors for individualization
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Abstract
General anesthesia involves some targeting effects which aim to prevent the patient from suffering
against the therapeutic aggression. These effects are hypnosis, analgesia, amnesia and immobility
and to achieve them a combination of drugs is delivered into the patient, from which propofol and
remifentanil are highlighted.
In the operating room, monitoring systems are used to assess the depth of anesthesia in real time.
This monitoring includes basic systems such as arterial blood pressure, oxygenation or
electrocardiogram and electroencephalogram derived measures, which are more complex; from
this last group, BIS index is a good indicator. Being able to predict the anesthetic depth from a set
of input variables could be valuable during the surgery, as it would help the anesthesiologists to
prevent adverse effects, and it would help the post-operative recovery.
Knowing this, the aim of this project is to predict the probability to be in the optimal level of
anesthesia, which is related to the BIS index. This probability is obtained from the input
concentration of propofol and remifentanil, a hypnotic and an analgesic drug respectively, and from
the demographic variables such as age, height or gender. To do so, a Logistic Regression model
will be built with data from patients undergoing general anesthesia in Cirurgia Major Ambulatòria
(CMA) in Hospital Clínic.
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Treballs Finals de Grau d'Enginyeria Biomèdica. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona. Curs: 2020-2021. Tutor: Pedro Gambús Cerrillo. Tutor Extern: Sebastián Jaramillo Selman
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REY PRIETO, Marta. Predicting optimal anesthesia level from propofol and remifentanil concentration: analysis of covariate factors for individualization. [consulted: 12 of October of 2026]. Available at: https://hdl.handle.net/2445/178442