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Cavaliere F, Allegri M, Apan A, Calderini E, Carassiti M, Cohen E, Coluzzi F, Di Marco P, Langeron O, Rossi M, Spieth P, Turnbull D. A year in review in Minerva Anestesiologica 2019. Anesthesia, analgesia, and perioperative medicine. Minerva Anestesiol 2021; 86:225-239. [PMID: 32118384 DOI: 10.23736/s0375-9393.20.14424-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Franco Cavaliere
- Department of Cardiovascular and Thoracic Sciences, A. Gemelli University Polyclinic, IRCCS and Foundation, Sacred Heart Catholic University, Rome, Italy -
| | - Massimo Allegri
- Unità Operativa Terapia del Dolore della Colonna e dello Sportivo, Policlinic of Monza, Monza, Italy.,Italian Pain Group, Milan, Italy
| | - Alparslan Apan
- Department of Anesthesiology and Intensive Care, Faculty of Medicine, University of Giresun, Giresun, Turkey
| | - Edoardo Calderini
- Unit of Women-Child Anesthesia and Intensive Care, Maggiore Polyclinic Hospital, Ca' Granda IRCCS and Foundation, Milan, Italy
| | - Massimiliano Carassiti
- Unit of Anesthesia, Intensive Care and Pain Management, Campus Bio-Medico University Hospital, Rome, Italy
| | - Edmond Cohen
- Department of Anesthesiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Thoracic Surgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Flaminia Coluzzi
- Unit of Anesthesia, Department of Medical and Surgical Sciences and Biotechnologies, Intensive Care and Pain Medicine, Sapienza University, Rome, Italy
| | - Pierangelo Di Marco
- Department of Cardiovascular, Respiratory, Nephrological, Anesthesiologic, and Geriatric Sciences, Sapienza University, Rome, Italy
| | - Olivier Langeron
- Department of Anesthesia and Intensive Care, Henri Mondor University Hospital, Sorbonne University, Assistance Publique-Hôpitaux de Paris, Créteil, France
| | - Marco Rossi
- Institute of Anesthesia and Intensive Care, Sacred Heart Catholic University, Rome, Italy
| | - Peter Spieth
- Department of Anesthesiology and Critical Care Medicine, University Hospital of Dresden, Dresden, Germany
| | - David Turnbull
- Department of Anaesthetics and Neuro Critical Care, Royal Hallamshire Hospital, Sheffield, UK
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EEG-derived pain threshold index for prediction of postoperative pain in patients undergoing laparoscopic urological surgery: a comparison with surgical pleth index. J Clin Monit Comput 2020; 35:1395-1402. [PMID: 33044610 DOI: 10.1007/s10877-020-00604-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Accepted: 10/05/2020] [Indexed: 01/05/2023]
Abstract
Recently a novel pain recognition indicator derived from electroencephalogram(EEG) signals, pain threshold index(PTI) has been developed. The aim of this study was to determine whether PTI can be used for prediction of postoperative acute pain while surgical pleth index(SPI) applied as control. Eighty patients undergoing laparoscopic urological surgery under general anesthesia were enrolled. Data of SPI, PTI and a sedative index-wavelet index(WLI) were recorded within last 10 min at the end of surgery. The postoperative pain scores (NRS, numerical rating scale) were obtained. The Bland-Altman analysis was used for evaluation of consistency between PTI and SPI, whereas receiver-operating characteristic (ROC) curves was used for the mean values of PTI, SPI, and WLI to distinguish between mild (NRS 0-3) and moderate-severe (NRS 4-10) pain, and calculate their "best-fit" cut-off values. Data from 76 patients were included for final analysis. There was a good agreement between SPI and PTI values at the end of surgery. The ROC analysis showed a cut-off PTI value of 53 to discriminate between mild and moderate-to-severe pain, while SPI is 44 for this discrimination. Further analysis indicated that PTI had a best predictive accuracy reflected by highest area under curve (AUC)(0.772, 95% CI: 0.661-0.860)with sensitivity(62.50%) and specificity(90.91%) and a best positive predictive value(83.3%,95% CI: 68.4-98.2%). PTI obtained at the end of surgery, which have better predictive accuracy for postoperative pain than SPI, could differentiate the patients with moderate-to-severe pain from those with mild pain after they awaken from anesthesia.Clinical trial registration Chinese Clinical Trials Registry: ChiCTR1900024789.
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