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García Sánchez F, Mudarra García N. Evaluation of postoperative results after a presurgical optimisation programme. Perioper Med (Lond) 2024; 13:73. [PMID: 39010120 PMCID: PMC11247769 DOI: 10.1186/s13741-024-00430-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 06/24/2024] [Indexed: 07/17/2024] Open
Abstract
BACKGROUND Presurgical optimisation programmes decrease the risk of postoperative complications, reduce hospital stays and speed up patient recovery. They usually involve a multidisciplinary team addressing physical, nutritional and psychosocial issues. The objective of this study was to assess the results of implementing a presurgical optimisation programme led by a liaison nurse in patients undergoing major surgery in a primary general hospital. METHODS An observational, retrospective, descriptive, cross-sectional, comparative study based on the revision of patients' health records undergoing major surgery between January 2019 and December 2022. Patients entering the presurgical optimisation programme (intervention group) were compared with patients receiving usual medical care (control group). The presurgical optimisation programme consisted of oral nutritional supplementation, physical exercise, strengthening of lung capacity and psychological and emotional support. Frequency (%) of surgery complications and use of healthcare resources (duration of hospitalisation, time spent in the intensive care unit (ICU), and readmission) at day 30 were recorded. Descriptive statistics were applied. RESULTS Two hundred eleven patients (58.5% men, mean age: 65.76 years (SD 11.5), 75.2%. non-smokers; mean body mass index (BMI): 28.32 (SD 5.38); mean Nutritional Risk Score (NRS) 3.71 (SD 1.35; oncology diagnosis: 88.6%) were included: 135 in the intervention group, and 76 in the control group. The average duration of the presurgical optimisation programme was 20 days (SD 5). Frequency of postoperative complications was 25% (n = 33) in the intervention group and 52.6% (n = 40) in the control group (p < 0.001) [odds ratio (OR) = 3.4; 95% confidence interval (CI) (1.8; 6.2)]. 14.5% (n = 19) of patients in the intervention group and 34.2% (n = 26) in the control group had remote postoperative complications [OR = 3.1; 95% CI (1.6; 6.2)]. Patients in the intervention group spent fewer days in the hospital [mean 8.34 (SD 6.70) vs 11.63 (SD 10.63)], and there were fewer readmissions at 30 days (7.6% vs 19.7%) compared with the control group. CONCLUSIONS A presurgical optimisation programme led by a liaison nurse decreases the rate of immediate and late surgical complications and reduces hospital stays and readmissions in patients undergoing major surgery.
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Affiliation(s)
- Francisco García Sánchez
- Surgical Prehabilitation Unit, Infanta Cristina University Hospital., Avenida 9 de Junio 2. Parla., Madrid, 28981, Spain.
- IDIPHISA. Medical Department. Faculty of Medicine, University Complutense of Madrid, Madrid, Spain.
| | - Natalia Mudarra García
- Surgical Prehabilitation Unit, Infanta Cristina University Hospital., Avenida 9 de Junio 2. Parla., Madrid, 28981, Spain
- IDIPHISA. Nurse Department. Faculty of Nurse. University Complutense of Madrid, Madrid, Spain
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Coeckelenbergh S, Boelefahr S, Alexander B, Perrin L, Rinehart J, Joosten A, Barvais L. Closed-loop anesthesia: foundations and applications in contemporary perioperative medicine. J Clin Monit Comput 2024; 38:487-504. [PMID: 38184504 DOI: 10.1007/s10877-023-01111-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Accepted: 11/21/2023] [Indexed: 01/08/2024]
Abstract
A closed-loop automatically controls a variable using the principle of feedback. Automation within anesthesia typically aims to improve the stability of a controlled variable and reduce workload associated with simple repetitive tasks. This approach attempts to limit errors due to distractions or fatigue while simultaneously increasing compliance to evidence based perioperative protocols. The ultimate goal is to use these advantages over manual care to improve patient outcome. For more than twenty years, clinical studies in anesthesia have demonstrated the superiority of closed-loop systems compared to manual control for stabilizing a single variable, reducing practitioner workload, and safely administering therapies. This research has focused on various closed-loops that coupled inputs and outputs such as the processed electroencephalogram with propofol, blood pressure with vasopressors, and dynamic predictors of fluid responsiveness with fluid therapy. Recently, multiple simultaneous independent closed-loop systems have been tested in practice and one study has demonstrated a clinical benefit on postoperative cognitive dysfunction. Despite their advantages, these tools still require that a well-trained practitioner maintains situation awareness, understands how closed-loop systems react to each variable, and is ready to retake control if the closed-loop systems fail. In the future, multiple input multiple output closed-loop systems will control anesthetic, fluid and vasopressor titration and may perhaps integrate other key systems, such as the anesthesia machine. Human supervision will nonetheless always be indispensable as situation awareness, communication, and prediction of events remain irreplaceable human factors.
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Affiliation(s)
- Sean Coeckelenbergh
- Department of Anesthesiology and Intensive Care, Hôpitaux Universitaires Paris-Saclay, Université Paris-Saclay, Hôpital Paul-Brousse, Assistance Publique Hôpitaux de Paris, Villejuif, France.
- Outcomes Research Consortium, Cleveland, OH, USA.
| | - Sebastian Boelefahr
- Department of Anesthesiology and Intensive Care, Klinikum Aschaffenburg-Alzenau, Frankfurt University and Wuerzburg University Affiliated Academic Training Hospital, Aschaffenburg, Germany
| | - Brenton Alexander
- Department of Anesthesiology & Perioperative Care, University of California San Diego, San Diego, CA, USA
| | - Laurent Perrin
- Department of Anaesthesia and Resuscitation, Erasme University Hospital, Université Libre de Bruxelles, Brussels, Belgium
| | - Joseph Rinehart
- Outcomes Research Consortium, Cleveland, OH, USA
- Department of Anesthesiology & Perioperative Care, University of California Irvine, Irvine, CA, USA
| | - Alexandre Joosten
- Department of Anesthesiology & Perioperative Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Luc Barvais
- Department of Anaesthesia and Resuscitation, Erasme University Hospital, Université Libre de Bruxelles, Brussels, Belgium
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Hemmerling TM, Jeffries SD. Robotic Anesthesia: A Vision for 2050. Anesth Analg 2024; 138:239-251. [PMID: 38215704 DOI: 10.1213/ane.0000000000006835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2024]
Abstract
The last 2 decades have brought important developments in anesthetic technology, including robotic anesthesia. Anesthesiologists titrate the administration of pharmacological agents to the patients' physiology and the needs of surgery, using a variety of sophisticated equipment (we use the term "pilots of the human biosphere"). In anesthesia, increased safety seems coupled with increased technology and innovation. This article gives an overview of the technological developments over the past decades, both in terms of pharmacological and mechanical robots, which have laid the groundwork for robotic anesthesia: target-controlled drug infusion systems, closed-loop administration of anesthesia and sedation, mechanical robots for intubation, and the latest development in the world of communication with the arrival of artificial intelligence (AI)-derived chatbots are presented.
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Affiliation(s)
- Thomas M Hemmerling
- From the Department of Experimental Surgery, McGill University Health Center, Montreal, Quebec, Canada
- Department of Anesthesia, McGill University, Montreal, Quebec, Canada
| | - Sean D Jeffries
- From the Department of Experimental Surgery, McGill University Health Center, Montreal, Quebec, Canada
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Reddy VS, Stout DM, Fletcher R, Barksdale A, Parikshak M, Johns C, Gerdisch M. Advanced artificial intelligence-guided hemodynamic management within cardiac enhanced recovery after surgery pathways: A multi-institution review. JTCVS OPEN 2023; 16:480-489. [PMID: 38204636 PMCID: PMC10774974 DOI: 10.1016/j.xjon.2023.06.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 05/31/2023] [Accepted: 06/07/2023] [Indexed: 01/12/2024]
Abstract
Objective The study objective was to report early outcomes of integrating Hypotension Prediction Index-guided hemodynamic management within a cardiac enhanced recovery pathway on total initial ventilation hours and length of stay in the intensive care unit. Methods A multicenter, historical control, observational analysis of implementation of a hemodynamic management tool within enhanced recovery pathways was conducted by identifying cardiac surgery cases from 3 sites during 2 time periods, August 1 to December 31, 2019 (preprogram), and April 1 to August 31, 2021 (program). Reoperations, emergency (salvage), or cases requiring mechanical assist were excluded. Data were extracted from electronic medical records and chart reviews. Two primary outcome variables were length of stay in the intensive care unit (using Society of Thoracic Surgeons definitions) and acute kidney injury (using modified Kidney Disease Improving Global Outcomes criteria). One secondary outcome variable, total initial ventilation hours, used Society of Thoracic Surgeons definitions. Differences in length of stay in the intensive care unit and total ventilation time were analyzed using Kruskal-Wallis and stepwise multiple linear regression. Acute kidney injury stage used chi-square and stepwise cumulative logistic regression. Results A total of 1404 cases (795 preprogram; 609 program) were identified. Overall reductions of 6.8 and 4.4 hours in intensive care unit length of stay (P = .08) and ventilation time (P = .03) were found, respectively. No significant association between proportion of patients identified with acute kidney injury by stage and period was found. Conclusions Adding artificial intelligence-guided hemodynamic management to cardiac enhanced recovery pathways resulted in associated reduced time in the intensive care unit for patients undergoing nonemergency cardiac surgery across institutions in a real-world setting.
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Affiliation(s)
- V. Seenu Reddy
- Cardiothoracic Surgery, TriStar Centennial Medical Center, Nashville, Tenn
| | - David M. Stout
- Cardiovascular Anesthesiology, Swedish Heart and Vascular Institute, Seattle, Wash
| | - Robert Fletcher
- Biostatistics, Swedish Heart and Vascular Institute, Seattle, Wash
| | - Andrew Barksdale
- Cardiothoracic Surgery, Franciscan Health Indianapolis, Indianapolis, Ind
| | - Manesh Parikshak
- Cardiothoracic Surgery, Franciscan Health Indianapolis, Indianapolis, Ind
| | - Chanice Johns
- Cardiothoracic Surgery, Franciscan Health Indianapolis, Indianapolis, Ind
| | - Marc Gerdisch
- Cardiothoracic Surgery, Franciscan Health Indianapolis, Indianapolis, Ind
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Cochand L, Filipovic MG, Huber M, Luedi MM, Urman RD, Bello C. Systems Anesthesiology: Systems of Care Delivery and Optimization in the Operating Room. Anesthesiol Clin 2023; 41:847-861. [PMID: 37838388 DOI: 10.1016/j.anclin.2023.05.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2023]
Abstract
Anesthesiology presents a challenge to a traditional simplifying approach given the ever-increasing amount of medical data and a more demanding environment. Systems anesthesiology is a modern approach to perioperative care, integrating the complexity of multifactorial knowledge and data to achieve a more adequate representation of reality, while including both patient-related medical aspects as well as economic and organizational challenges. We discuss the value of some innovative technologies such as the emergence of anesthesia information systems, the use of tele-medicine, predictive monitoring, or closed-loop systems as it pertains to the changes in the current standards of care in anesthesiology. Furthermore, we highlight the importance of systems anesthesiology in operating room planning, anesthesia research, and education.
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Affiliation(s)
- Laure Cochand
- Department of Anesthesiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Mark G Filipovic
- Department of Anesthesiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Markus Huber
- Department of Anesthesiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Markus M Luedi
- Department of Anesthesiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Richard D Urman
- Department of Anesthesiology, The Ohio State University College of Medicine, OH, USA.
| | - Corina Bello
- Department of Anesthesiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
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Chan KC, Wu LL, Han SC, Chen JS, Cheng YJ. Efficacy of intraoperative thoracoscopic intercostal nerve blocks in nonintubated and intubated video-assisted thoracic surgery: A randomized study. J Formos Med Assoc 2023; 122:986-993. [PMID: 37330304 DOI: 10.1016/j.jfma.2023.05.025] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 04/05/2023] [Accepted: 05/22/2023] [Indexed: 06/19/2023] Open
Abstract
BACKGROUND The efficacy of thoracoscopic intercostal nerve blocks (TINBs) for noxious stimulation from video-assisted thoracic surgery (VATS) remains unclear. The efficacy of TINBs may also be different between nonintubated VATS (NIVATS) and intubated VATS (IVATS). We aim to compare the efficacy of TINBs on analgesia and sedation for NIVATS and IVATs intraoperatively. METHODS Sixty patients randomized to the NIVATS or IVATS group (30 each) received target-controlled propofol and remifentanil infusions, with bispectral index (BIS) maintained at 40-60, and multilevel (T3-T8) TINBs before surgical manipulations. Intraoperative monitoring data, including pulse oximetry, mean arterial pressure (MAP), heart rate, BIS, density spectral arrays (DSAs), and propofol and remifentanil effect-site concentration (Ce) at different time points. A two way ANOVA with post hoc analysis was applied to analyze the differences and interactions of groups and time points. RESULTS In both groups, DSA monitoring revealed burst suppression and α dropout immediately after the TINBs. The Ce of the propofol infusion had to be reduced within 5 min post-TINBs in both NIVATS (p < 0.001) and IVATS (p = 0.252) groups. The Ce of remifentanil infusion was significantly reduced after TINBs in both groups (p < 0.001), and was significantly lower in NIVATS (p < 0.001) without group interactions. CONCLUSION The surgeon-performed intraoperative multilevel TINBs allow reduced anesthetic and analgesic requirement for VATS. With lower requirement of remifentanil infusion, NIVATS presents a significantly higher risk of hypotension after TINBs. DSA is beneficial for providing real-time data that facilitate the preemptive management, especially for NIVATS.
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Affiliation(s)
- Kuang-Cheng Chan
- Department of Anesthesiology, National Taiwan University Hospital, Taipei, Taiwan
| | - Li-Lin Wu
- Department of Anesthesiology, National Taiwan University Cancer Center, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Su-Chuan Han
- Department of Anesthesiology, National Taiwan University Cancer Center, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Jin-Shing Chen
- Department of Surgery, National Taiwan University Cancer Center, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Ya-Jung Cheng
- Department of Anesthesiology, National Taiwan University Cancer Center, National Taiwan University College of Medicine, Taipei, Taiwan.
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Tognoli E, Luigi M. Using the TI.VA algorithm to titrate the depth of general anaesthesia: a first-in-humans study. BJA OPEN 2023; 7:100203. [PMID: 37638086 PMCID: PMC10457467 DOI: 10.1016/j.bjao.2023.100203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 05/26/2023] [Indexed: 08/29/2023]
Abstract
Background The dose of anaesthetic and opioid drugs must be continuously adjusted after the induction of general anaesthesia to maintain an adequate depth of anaesthesia. The TI.VA algorithm is a multiple-input/multiple-output algorithm designed to optimise the balance between anaesthetic and opioid concentrations during general anaesthesia. It applies vector analysis to a two-dimensional matrix to quantify any inadequacy of the depth of anaesthesia at any given moment and determine any drug dose adjustments required to achieve an adequate depth of anaesthesia. This study aimed to capture preliminary data on the performance and safety of the TI.VA algorithm during total i.v. anaesthesia in patients. Methods This prospective study enrolled nine patients with breast cancer scheduled to undergo surgery. General anaesthesia was induced under manual control using propofol and remifentanil. Anaesthesia was guided using the TI.VA algorithm from skin incision until surgical resection was completed. The quality of anaesthesia was assessed through an analysis of performance errors. A bispectral index global score (GSBIS) <50 was considered an acceptable target for algorithm performance. Results All nine procedures were completed without any adverse events and none of the patients recalled any intraoperative event. Overall, we analysed 3417 monitoring points corresponding to 285 min of surgery. All patients presented a GSBIS below the cut-off value of 50. Conclusions The TI.VA algorithm provides adequate control of clinical anaesthesia. A more sophisticated prototype needs to be developed before the trial is expanded to include larger patient populations. Clinical trial registration NCT05199883.
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Affiliation(s)
- Emiliano Tognoli
- Department of Anaesthesiology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy
| | - Mariani Luigi
- Unit of Clinical Epidemiology and Trial Organisation, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy
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Karer G, Škrjanc I. Improved Individualized Patient-Oriented Depth-of-Hypnosis Measurement Based on Bispectral Index. SENSORS (BASEL, SWITZERLAND) 2022; 23:293. [PMID: 36616891 PMCID: PMC9824030 DOI: 10.3390/s23010293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 12/21/2022] [Accepted: 12/22/2022] [Indexed: 06/17/2023]
Abstract
Total intravenous anesthesia is an anesthesiologic technique where all substances are injected intravenously. The main task of the anesthesiologist is to assess the depth of anesthesia, or, more specifically, the depth of hypnosis (DoH), and accordingly adjust the dose of intravenous anesthetic agents. However, it is not possible to directly measure the anesthetic agent concentrations or the DoH, so the anesthesiologist must rely on various vital signs and EEG-based measurements, such as the bispectral (BIS) index. The ability to better measure DoH is directly applicable in clinical practice-it improves the anesthesiologist's assessment of the patient state regarding anesthetic agent concentrations and, consequently, the effects, as well as provides the basis for closed-loop control algorithms. This article introduces a novel structure for modeling DoH, which employs a residual dynamic model. The improved model can take into account the patient's individual sensitivity to the anesthetic agent, which is not the case when using the available population-data-based models. The improved model was tested using real clinical data. The results show that the predictions of the BIS-index trajectory were improved considerably. The proposed model thus seems to provide a good basis for a more patient-oriented individualized assessment of DoH, which should lead to better administration methods that will relieve the anesthesiologist's workload and will benefit the patient by providing improved safety, individualized treatment, and, thus, alleviation of possible adverse effects during and after surgery.
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Abotaleb AM, ElSharkawy MS, Almawardy HG. Bilateral sphenopalatine ganglion block with adrenaline additive for post-dural puncture headache in orthopedic patients: A randomized controlled trial. EGYPTIAN JOURNAL OF ANAESTHESIA 2022. [DOI: 10.1080/11101849.2022.2077051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022] Open
Affiliation(s)
- Amany Mohamed Abotaleb
- Anesthesiology, Surgical Intensive Care and Pain Medicine, Faculty of Medicine, Tanta University, Tanta, Egypt
| | - Mohammed Said ElSharkawy
- Anesthesiology, Surgical Intensive Care and Pain Medicine, Faculty of Medicine, Tanta University, Tanta, Egypt
| | - Hussen Gamal Almawardy
- Anesthesiology, Surgical Intensive Care and Pain Medicine, Faculty of Medicine, Tanta University, Tanta, Egypt
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Schiavo M, Padula F, Latronico N, Paltenghi M, Visioli A. A modified PID-based control scheme for depth-of-hypnosis control: Design and experimental results. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2022; 219:106763. [PMID: 35349908 DOI: 10.1016/j.cmpb.2022.106763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 03/05/2022] [Accepted: 03/17/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND AND OBJECTIVE Many methodologies have been proposed for the control of total intravenous anesthesia in general surgery, as this yields a reduced stress for the anesthesiologist and an increased safety for the patient. The objective of this work is to design a PID-based control system for the regulation of the depth of hypnosis by propofol and remifentanil coadministration that takes into account the clinical practice. METHODS With respect to a standard PID control system, additional functionalities have been implemented in order to consider specific requirements related to the clinical practice. In particular, suitable boluses are determined and used in the induction phase and a nonzero baseline infusion is used in the maintenance phase when the predicted effect-site concentration drops below a safety threshold. RESULTS The modified controller has been experimentally assessed on a group of 10 patients receiving general anesthesia for elective plastic surgery. The control system has been able to induce and maintain adequate anesthesia without any manual intervention from the anesthesiologist. CONCLUSIONS Results confirm the effectiveness of the overall design approach and, in particular, highlight that the new version of the control system, with respect to a standard PID controller, provides significant advantages from a clinical standpoint.
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Affiliation(s)
- Michele Schiavo
- Dipartimento di Ingegneria dell'Informazione, University of Brescia, Brescia, Italy.
| | - Fabrizio Padula
- Curtin Centre for Optimisation and Decision Science, Curtin University, Perth, Australia.
| | - Nicola Latronico
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy; Department of Anesthesiology, Critical Care and Emergency Spedali Civili di Brescia, Brescia, Italy.
| | - Massimiliano Paltenghi
- Department of Anesthesiology, Critical Care and Emergency Spedali Civili di Brescia, Brescia, Italy.
| | - Antonio Visioli
- Dipartimento di Ingegneria Meccanica e Industriale University of Brescia, Brescia, Italy.
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