PREDICTHEON. Monitoring patients undergoing sedation-analgesia

Pedro Gambús Cerrillo

IDIBAPS, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Spain

Research
The use of sedation-analgesia for diagnostic or therapeutic procedures is becoming more ubiquitous in healthcare centers. Patients ask for sedation to avoid pain or distress during medical procedures. Drug administration must be accurately controlled to guarantee adequate sedation-analgesia levels and fast recovery in all patients while avoiding collateral side effects that can sometimes be severe. Currently, monitoring and control of patients in this setting is conducted with the same methods utilized for general anasthesia procedures based on the display of vital signs, as there is no specific methods for sedation-analgesia monitoring. Therefore, a new monitoring system for sedation-analgesia would greatly reduce the risks associated to the procedures, enhancing patient safety.

Aim
To provide anesthesiologists with a new specific monitoring system for patients undergoing sedation-analgesia. The system will provide continuous predictions of the different effects on sedation level, respiratory depression and cognitive functions as well how fast recovery from such effects would take. Information will be displayed in real-time.

Problem to Solve
Patients who require sedation-analgesia are usually outpatients that should be able to resume normal life as soon as possible. However, emergent diagnostic procedures on acute situations might also require the use of sedation-analgesia for an accurate diagnosis. In both cases the effects of the drugs used for sedation-analgesia must be carefully quantified and titrated to individual needs to avoid excessive and severe physiological alterations, which could be potentially lethal.

Quantification of drug effect under sedation is traditionally performed using monitors displaying current vital signs. The sedative effect is milder than a general anesthesia, as the level of unconsciousness is lighter. In addition, respiration must be spontaneous and effective under sedation, hence an appropriate device to monitor such states and predicting future behavior is necessary.

Innovation
The proposed individualized monitoring system provides the clinician with real-time predictive information about sedative state, respiratory, and cognitive effects of the sedative-analgesic drugs administered. Predictions are based on mathematical models of drug effects estimated from prior data collected in patients.

Level of Innovation
The development of monitoring solutions for sedation-analgesia constitutes a novel approach, as it has traditionally been performed as a general anesthesia. In addition, the prediction of the level of sedation ahead of time and the time to full recovery are other novel aspects that the proposed technology offers. Overall, clinicians will have a very powerful and useful tool to monitor sedation-analgesia.