Pub Date : 1900-01-01DOI: 10.1097/ea9.0000000000000031
E. Bignami, Michele Russo, Valentina Bellini, P. Berchialla, G. Cammarota, M. Cascella, C. Compagnone, F. Sanfilippo, S. Maggiore, J. Montomoli, L. Vetrugno, E. Boero, A. Cortegiani, A. Giarratano, P. Pelosi, E. De Robertis
The potential role of artificial intelligence in enhancing human life and medical practice is under investigation but the knowledge of the topic among healthcare providers is under-investigated. To investigate knowledge of artificial intelligence in physicians working in the field of anaesthesiology, intensive care, and pain medicine. As secondary outcomes, we investigated the main concerns on the implementation of artificial intelligence. Online survey. Anaesthesiology, intensive care and pain medicine. We invited clinicians specialised in anaesthesia, resuscitation, intensive care and pain medicine who were active members of the European Society of Anaesthesiology and Intensive Care (ESAIC). Online survey from 28 June 2022 to 29 October 2022. Primary outcome was to investigate knowledge of artificial intelligence and telemedicine of participants. A total of 4465 e-mails were sent and 220 specialists, age 46.5 ± 10.2; 128 men (58.2%) responded to the survey. In general, some knowledge of artificial intelligence and machine learning was reported by 207 of 220 (94.1%) and 180 of 220 (81.8%) members, respectively. In anaesthesiology, 168 of 220 (76.4%) and 151 of 220 (68.6%) have heard of artificial intelligence and machine learning. In intensive care, 154 of 220 (70.0%) and 133 of 220 (60.5%) had heard of artificial intelligence and machine learning, while these figures were much lower in pain medicine [artificial intelligence: only 70/220 (31.8%) and machine learning 67/220 (30.5%)]. The main barriers to implementing these tools in clinical practice were: lack of knowledge of algorithms leading to the results; few validation studies available and not enough knowledge of artificial intelligence. Knowledge of telemedicine was reported in 212 of 220 (96.4%) members. Most anaesthesiologists are aware of artificial intelligence and machine learning. General thinking about the application of artificial intelligence in anaesthesiology, intensive care and pain management was positive overall, with most participants not considering this tool as a threat to their profession.
{"title":"Artificial intelligence and telemedicine in the field of anaesthesiology, intensive care and pain medicine","authors":"E. Bignami, Michele Russo, Valentina Bellini, P. Berchialla, G. Cammarota, M. Cascella, C. Compagnone, F. Sanfilippo, S. Maggiore, J. Montomoli, L. Vetrugno, E. Boero, A. Cortegiani, A. Giarratano, P. Pelosi, E. De Robertis","doi":"10.1097/ea9.0000000000000031","DOIUrl":"https://doi.org/10.1097/ea9.0000000000000031","url":null,"abstract":"The potential role of artificial intelligence in enhancing human life and medical practice is under investigation but the knowledge of the topic among healthcare providers is under-investigated. To investigate knowledge of artificial intelligence in physicians working in the field of anaesthesiology, intensive care, and pain medicine. As secondary outcomes, we investigated the main concerns on the implementation of artificial intelligence. Online survey. Anaesthesiology, intensive care and pain medicine. We invited clinicians specialised in anaesthesia, resuscitation, intensive care and pain medicine who were active members of the European Society of Anaesthesiology and Intensive Care (ESAIC). Online survey from 28 June 2022 to 29 October 2022. Primary outcome was to investigate knowledge of artificial intelligence and telemedicine of participants. A total of 4465 e-mails were sent and 220 specialists, age 46.5 ± 10.2; 128 men (58.2%) responded to the survey. In general, some knowledge of artificial intelligence and machine learning was reported by 207 of 220 (94.1%) and 180 of 220 (81.8%) members, respectively. In anaesthesiology, 168 of 220 (76.4%) and 151 of 220 (68.6%) have heard of artificial intelligence and machine learning. In intensive care, 154 of 220 (70.0%) and 133 of 220 (60.5%) had heard of artificial intelligence and machine learning, while these figures were much lower in pain medicine [artificial intelligence: only 70/220 (31.8%) and machine learning 67/220 (30.5%)]. The main barriers to implementing these tools in clinical practice were: lack of knowledge of algorithms leading to the results; few validation studies available and not enough knowledge of artificial intelligence. Knowledge of telemedicine was reported in 212 of 220 (96.4%) members. Most anaesthesiologists are aware of artificial intelligence and machine learning. General thinking about the application of artificial intelligence in anaesthesiology, intensive care and pain management was positive overall, with most participants not considering this tool as a threat to their profession.","PeriodicalId":300330,"journal":{"name":"European Journal of Anaesthesiology Intensive Care","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127607702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1097/ea9.0000000000000013
P. B. Cox, T. Pisters, Dianne de Korte-de Boer, Christoph H. Pennings, J. Melenhorst, W. Buhre
{"title":"Thoracic epidural analgesia vs. patient-controlled intravenous analgesia for patients undergoing open or laparoscopic colorectal cancer surgery","authors":"P. B. Cox, T. Pisters, Dianne de Korte-de Boer, Christoph H. Pennings, J. Melenhorst, W. Buhre","doi":"10.1097/ea9.0000000000000013","DOIUrl":"https://doi.org/10.1097/ea9.0000000000000013","url":null,"abstract":"","PeriodicalId":300330,"journal":{"name":"European Journal of Anaesthesiology Intensive Care","volume":"170 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132414376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1097/ea9.0000000000000021
Kensuke Shimada, M. Iwagami, K. Makito, D. Shigemi, K. Uda, M. Ishimaru, J. Komiyama, K. Morita, H. Matsui, K. Fushimi, H. Yasunaga, Makoto Tanaka, N. Tamiya
{"title":"The comparison of caesarean section bleeding between volatile and total intravenous anaesthesia in a Japanese nationwide database","authors":"Kensuke Shimada, M. Iwagami, K. Makito, D. Shigemi, K. Uda, M. Ishimaru, J. Komiyama, K. Morita, H. Matsui, K. Fushimi, H. Yasunaga, Makoto Tanaka, N. Tamiya","doi":"10.1097/ea9.0000000000000021","DOIUrl":"https://doi.org/10.1097/ea9.0000000000000021","url":null,"abstract":"","PeriodicalId":300330,"journal":{"name":"European Journal of Anaesthesiology Intensive Care","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134125112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1097/ea9.0000000000000023
Alexis Bikfalvi, Charlotte Faes, S. Freys, Girish P. Joshi, M. Van de Velde, E. Albrecht
{"title":"PROSPECT guideline for haemorrhoid surgery","authors":"Alexis Bikfalvi, Charlotte Faes, S. Freys, Girish P. Joshi, M. Van de Velde, E. Albrecht","doi":"10.1097/ea9.0000000000000023","DOIUrl":"https://doi.org/10.1097/ea9.0000000000000023","url":null,"abstract":"","PeriodicalId":300330,"journal":{"name":"European Journal of Anaesthesiology Intensive Care","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131277918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1097/ea9.0000000000000011
M. Soehle, A. Wolter, M. Thudium, S. Frede, M. Coburn
{"title":"Different behaviour of target-controlled infusion pumps despite apparently using the same Schnider pharmacokinetic model","authors":"M. Soehle, A. Wolter, M. Thudium, S. Frede, M. Coburn","doi":"10.1097/ea9.0000000000000011","DOIUrl":"https://doi.org/10.1097/ea9.0000000000000011","url":null,"abstract":"","PeriodicalId":300330,"journal":{"name":"European Journal of Anaesthesiology Intensive Care","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129603421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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