TY - JOUR A1 - Henckert, David A1 - Malorgio, Amos A1 - Schweiger, Giovanna A1 - Raimann, Florian J. A1 - Piekarski, Florian A1 - Zacharowski, Kai A1 - Hottenrott, Sebastian A1 - Meybohm, Patrick A1 - Tscholl, David W. A1 - Spahn, Donat R. A1 - Roche, Tadzio R. T1 - Attitudes of anesthesiologists toward artificial intelligence in anesthesia: a multicenter, mixed qualitative–quantitative study JF - Journal of Clinical Medicine N2 - Artificial intelligence (AI) is predicted to play an increasingly important role in perioperative medicine in the very near future. However, little is known about what anesthesiologists know and think about AI in this context. This is important because the successful introduction of new technologies depends on the understanding and cooperation of end users. We sought to investigate how much anesthesiologists know about AI and what they think about the introduction of AI-based technologies into the clinical setting. In order to better understand what anesthesiologists think of AI, we recruited 21 anesthesiologists from 2 university hospitals for face-to-face structured interviews. The interview transcripts were subdivided sentence-by-sentence into discrete statements, and statements were then grouped into key themes. Subsequently, a survey of closed questions based on these themes was sent to 70 anesthesiologists from 3 university hospitals for rating. In the interviews, the base level of knowledge of AI was good at 86 of 90 statements (96%), although awareness of the potential applications of AI in anesthesia was poor at only 7 of 42 statements (17%). Regarding the implementation of AI in anesthesia, statements were split roughly evenly between pros (46 of 105, 44%) and cons (59 of 105, 56%). Interviewees considered that AI could usefully be used in diverse tasks such as risk stratification, the prediction of vital sign changes, or as a treatment guide. The validity of these themes was probed in a follow-up survey of 70 anesthesiologists with a response rate of 70%, which confirmed an overall positive view of AI in this group. Anesthesiologists hold a range of opinions, both positive and negative, regarding the application of AI in their field of work. Survey-based studies do not always uncover the full breadth of nuance of opinion amongst clinicians. Engagement with specific concerns, both technical and ethical, will prove important as this technology moves from research to the clinic. KW - artificial intelligence KW - machine learning KW - anesthesia KW - anesthesiology KW - qualitative research KW - clinical decision support Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-311189 SN - 2077-0383 VL - 12 IS - 6 ER - TY - JOUR A1 - Schweiger, Giovanna A1 - Malorgio, Amos A1 - Henckert, David A1 - Braun, Julia A1 - Meybohm, Patrick A1 - Hottenrott, Sebastian A1 - Froehlich, Corinna A1 - Zacharowski, Kai A1 - Raimann, Florian J. A1 - Piekarski, Florian A1 - Noethiger, Christoph B. A1 - Spahn, Donat R. A1 - Tscholl, David W. A1 - Roche, Tadzio R. T1 - Visual Blood, a 3D animated computer model to optimize the interpretation of blood gas analysis JF - Bioengineering N2 - Acid–base homeostasis is crucial for all physiological processes in the body and is evaluated using arterial blood gas (ABG) analysis. Screens or printouts of ABG results require the interpretation of many textual elements and numbers, which may delay intuitive comprehension. To optimise the presentation of the results for the specific strengths of human perception, we developed Visual Blood, an animated virtual model of ABG results. In this study, we compared its performance with a conventional result printout. Seventy physicians from three European university hospitals participated in a computer-based simulation study. Initially, after an educational video, we tested the participants’ ability to assign individual Visual Blood visualisations to their corresponding ABG parameters. As the primary outcome, we tested caregivers’ ability to correctly diagnose simulated clinical ABG scenarios with Visual Blood or conventional ABG printouts. For user feedback, participants rated their agreement with statements at the end of the study. Physicians correctly assigned 90% of the individual Visual Blood visualisations. Regarding the primary outcome, the participants made the correct diagnosis 86% of the time when using Visual Blood, compared to 68% when using the conventional ABG printout. A mixed logistic regression model showed an odds ratio for correct diagnosis of 3.4 (95%CI 2.00–5.79, p < 0.001) and an odds ratio for perceived diagnostic confidence of 1.88 (95%CI 1.67–2.11, p < 0.001) in favour of Visual Blood. A linear mixed model showed a coefficient for perceived workload of −3.2 (95%CI −3.77 to −2.64) in favour of Visual Blood. Fifty-one of seventy (73%) participants agreed or strongly agreed that Visual Blood was easy to use, and fifty-five of seventy (79%) agreed that it was fun to use. In conclusion, Visual Blood improved physicians’ ability to diagnose ABG results. It also increased perceived diagnostic confidence and reduced perceived workload. This study adds to the growing body of research showing that decision-support tools developed around human cognitive abilities can streamline caregivers’ decision-making and may improve patient care. KW - blood gas analysis KW - medical devices KW - point-of-care-testing KW - situational awareness KW - technology Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-304150 SN - 2306-5354 VL - 10 IS - 3 ER - TY - JOUR A1 - Schmitt, Elke A1 - Meybohm, Patrick A1 - Neef, Vanessa A1 - Baumgarten, Peter A1 - Bayer, Alexandra A1 - Choorapoikayil, Suma A1 - Friederich, Patrick A1 - Friedrich, Jens A1 - Geisen, Christof A1 - Güresir, Erdem A1 - Grünewald, Matthias A1 - Gutjahr, Martin A1 - Helmer, Philipp A1 - Herrmann, Eva A1 - Müller, Markus A1 - Narita, Diana A1 - Raadts, Ansgar A1 - Schwendner, Klaus A1 - Seifried, Erhard A1 - Stark, Patrick A1 - Steinbicker, Andrea U. A1 - Thoma, Josef A1 - Velten, Markus A1 - Weigt, Henry A1 - Wiesenack, Christoph A1 - Wittmann, Maria A1 - Zacharowski, Kai A1 - Piekarski, Florian T1 - Preoperative anaemia and red blood cell transfusion in patients with aneurysmal subarachnoid and intracerebral haemorrhage - a multicentre subanalysis of the German PBM Network Registry JF - Acta Neurochirurgica N2 - Purpose Anaemia is common in patients presenting with aneurysmal subarachnoid (aSAH) and intracerebral haemorrhage (ICH). In surgical patients, anaemia was identified as an idenpendent risk factor for postoperative mortality, prolonged hospital length of stay (LOS) and increased risk of red blood cell (RBC) transfusion. This multicentre cohort observation study describes the incidence and effects of preoperative anaemia in this critical patient collective for a 10-year period. Methods This multicentre observational study included adult in-hospital surgical patients diagnosed with aSAH or ICH of 21 German hospitals (discharged from 1 January 2010 to 30 September 2020). Descriptive, univariate and multivariate analyses were performed to investigate the incidence and association of preoperative anaemia with RBC transfusion, in-hospital mortality and postoperative complications in patients with aSAH and ICH. Results A total of n = 9081 patients were analysed (aSAH n = 5008; ICH n = 4073). Preoperative anaemia was present at 28.3% in aSAH and 40.9% in ICH. RBC transfusion rates were 29.9% in aSAH and 29.3% in ICH. Multivariate analysis revealed that preoperative anaemia is associated with a higher risk for RBC transfusion (OR = 3.25 in aSAH, OR = 4.16 in ICH, p < 0.001), for in-hospital mortality (OR = 1.48 in aSAH, OR = 1.53 in ICH, p < 0.001) and for several postoperative complications. Conclusions Preoperative anaemia is associated with increased RBC transfusion rates, in-hospital mortality and postoperative complications in patients with aSAH and ICH. KW - aneurysmal subarachnoid haemorrhage KW - intracerebral haemorrhage KW - anaemia KW - red blood cell transfusion KW - patient blood management Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-346754 VL - 164 ER - TY - JOUR A1 - Neef, Vanessa A1 - Meisenzahl, David A1 - Kessler, Paul A1 - Raimann, Florian J. A1 - Piekarski, Florian A1 - Choorapoikayil, Suma A1 - Fleege, Christoph A1 - Zacharowski, Kai D. A1 - Meybohm, Patrick A1 - Meurer, Andrea T1 - Implementation of an anaemia walk‐in clinic: Feasibility and preliminary data from the Orthopedic University Hospital JF - Transfusion Medicine N2 - Background Approximately one in three patients suffers from preoperative anaemia. Even though haemoglobin is measured before surgery, anaemia management is not implemented in every hospital. Objective Here, we demonstrate the implementation of an anaemia walk‐in clinic at an Orthopedic University Hospital. To improve the diagnosis of iron deficiency (ID), we examined whether reticulocyte haemoglobin (Ret‐He) could be a useful additional parameter. Material and Methods In August 2019, an anaemia walk‐in clinic was established. Between September and December 2019, major orthopaedic surgical patients were screened for preoperative anaemia. The primary endpoint was the incidence of preoperative anaemia. Secondary endpoints included Ret‐He level, red blood cell (RBC) transfusion rate, in‐hospital length of stay and anaemia at hospital discharge. Results A total of 104 patients were screened for anaemia. Preoperative anaemia rate was 20.6%. Intravenous iron was supplemented in 23 patients. Transfusion of RBC units per patient (1.7 ± 1.2 vs. 0.2 ± 0.9; p = 0.004) and hospital length of stay (13.1 ± 4.8 days vs. 10.6 ± 5.1 days; p = 0.068) was increased in anaemic patients compared to non‐anaemic patients. Ret‐He values were significantly lower in patients with ID anaemia (33.3 pg [28.6–40.2 pg]) compared to patients with ID (35.3 pg [28.9–38.6 pg]; p = 0.015) or patients without anaemia (35.4 pg [30.2–39.4 pg]; p = 0.001). Conclusion Preoperative anaemia is common in orthopaedic patients. Our results proved the feasibility of an anaemia walk‐in clinic to manage preoperative anaemia. Furthermore, our analysis supports the use of Ret‐He as an additional parameter for the diagnosis of ID in surgical patients. KW - anaemia walk‐in clinic KW - blood transfusion KW - iron deficiency KW - orthopaedic patients KW - patient blood management KW - reticulocyte haemoglobin Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-224594 VL - 30 IS - 6 SP - 467 EP - 474 ER -