Journal of clinical monitoring and computing
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J Clin Monit Comput · Dec 2023
Evaluation of the effectiveness of analgesia nociception index (ANI) predictability for surgical stimuli under personal analgesic sufficiency status (PASS) measured by pre-tetanus-induced ANI: a pilot study.
The Analgesia Nociception Index (ANI) is a promising monitor to evaluate the balance of nociception and anti-nociception based on heart rate variability. This prospective, interventional, monocentric pilot study aimed to verify the effectiveness of the personal analgesic sufficiency status (PASS) measured by pre-tetanus-induced ANI variation for surgical stimuli. After Ethics approval and informed consent, participants were anesthetized with sevoflurane and increased effect-site concentrations of remifentanil step by step (2, 4, 6 ng ml-1). ⋯ The PASS under pre-tetanus-induced ANI identification didn't meet the analgesic needs under surgical stimuli. Further investigations are required to provide a reliable prediction of individualized analgesia by objective nociception monitors. Trial registration NCT05063461.
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J Clin Monit Comput · Dec 2023
LetterTechnical note: pre-positioning lower limb SSEP during semi-sitting positioning in posterior fossa surgery- does it matter?
Intra-operative monitoring has been a crucial tool in modern neurosurgery as it allows to optimize surgical outcome whilst reducing neurological deficits. Somatosensory evoked potentials are routinely monitored in most spinal and brain surgeries due to providing invaluable information regarding the functional integrity of sensory pathways. ⋯ Nonetheless, we report a case study of a patient in whom lower limb SSEPs were independently affected from upper limb SSEPs during positioning. In this respect, we suggest that both upper and lower limb SSEPs monitoring should be considered during semi-sitting positioning in patients undergoing posterior fossa surgery.
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Perioperative medicine is changing, and its goals are expanding. More and more attention is paid to the surgical experience and the patient's quality of life. ⋯ However, creating perioperative programs capable of integrating traditional perioperative data with these scales is not easy. New technologies, particularly artificial intelligence, thanks to their ability to recognise, interpret, process or simulate human feelings, emotions and moods, could provide the necessary tools to combine all perioperative aspects, placing the patients and their needs at the centre of the process.