@article{BergauerAkbasBraunetal.2023, author = {Bergauer, Lisa and Akbas, Samira and Braun, Julia and Ganter, Michael T. and Meybohm, Patrick and Hottenrott, Sebastian and Zacharowski, Kai and Raimann, Florian J. and Rivas, Eva and L{\´o}pez-Baamonde, Manuel and Spahn, Donat R. and Noethiger, Christoph B. and Tscholl, David W. and Roche, Tadzio R.}, title = {Visual Blood, visualisation of blood gas analysis in virtual reality, leads to more correct diagnoses: a computer-based, multicentre, simulation study}, series = {Bioengineering}, volume = {10}, journal = {Bioengineering}, number = {3}, issn = {2306-5354}, doi = {10.3390/bioengineering10030340}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-310979}, year = {2023}, abstract = {Interpreting blood gas analysis results can be challenging for the clinician, especially in stressful situations under time pressure. To foster fast and correct interpretation of blood gas results, we developed Visual Blood. This computer-based, multicentre, noninferiority study compared Visual Blood and conventional arterial blood gas (ABG) printouts. We presented six scenarios to anaesthesiologists, once with Visual Blood and once with the conventional ABG printout. The primary outcome was ABG parameter perception. The secondary outcomes included correct clinical diagnoses, perceived diagnostic confidence, and perceived workload. To analyse the results, we used mixed models and matched odds ratios. Analysing 300 within-subject cases, we showed noninferiority of Visual Blood compared to ABG printouts concerning the rate of correctly perceived ABG parameters (rate ratio, 0.96; 95\% CI, 0.92-1.00; p = 0.06). Additionally, the study revealed two times higher odds of making the correct clinical diagnosis using Visual Blood (OR, 2.16; 95\% CI, 1.42-3.29; p < 0.001) than using ABG printouts. There was no or, respectively, weak evidence for a difference in diagnostic confidence (OR, 0.84; 95\% CI, 0.58-1.21; p = 0.34) and perceived workload (Coefficient, 2.44; 95\% CI, -0.09-4.98; p = 0.06). This study showed that participants did not perceive the ABG parameters better, but using Visual Blood resulted in more correct clinical diagnoses than using conventional ABG printouts. This suggests that Visual Blood allows for a higher level of situation awareness beyond individual parameters' perception. However, the study also highlighted the limitations of today's virtual reality headsets and Visual Blood.}, language = {en} } @article{SchweigerMalorgioHenckertetal.2023, author = {Schweiger, Giovanna and Malorgio, Amos and Henckert, David and Braun, Julia and Meybohm, Patrick and Hottenrott, Sebastian and Froehlich, Corinna and Zacharowski, Kai and Raimann, Florian J. and Piekarski, Florian and Noethiger, Christoph B. and Spahn, Donat R. and Tscholl, David W. and Roche, Tadzio R.}, title = {Visual Blood, a 3D animated computer model to optimize the interpretation of blood gas analysis}, series = {Bioengineering}, volume = {10}, journal = {Bioengineering}, number = {3}, issn = {2306-5354}, doi = {10.3390/bioengineering10030293}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-304150}, year = {2023}, abstract = {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.}, language = {en} } @article{NeefMeisenzahlKessleretal.2020, author = {Neef, Vanessa and Meisenzahl, David and Kessler, Paul and Raimann, Florian J. and Piekarski, Florian and Choorapoikayil, Suma and Fleege, Christoph and Zacharowski, Kai D. and Meybohm, Patrick and Meurer, Andrea}, title = {Implementation of an anaemia walk-in clinic: Feasibility and preliminary data from the Orthopedic University Hospital}, series = {Transfusion Medicine}, volume = {30}, journal = {Transfusion Medicine}, number = {6}, doi = {10.1111/tme.12740}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-224594}, pages = {467 -- 474}, year = {2020}, abstract = {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.}, language = {en} } @article{HenckertMalorgioSchweigeretal.2023, author = {Henckert, David and Malorgio, Amos and Schweiger, Giovanna and Raimann, Florian J. and Piekarski, Florian and Zacharowski, Kai and Hottenrott, Sebastian and Meybohm, Patrick and Tscholl, David W. and Spahn, Donat R. and Roche, Tadzio R.}, title = {Attitudes of anesthesiologists toward artificial intelligence in anesthesia: a multicenter, mixed qualitative-quantitative study}, series = {Journal of Clinical Medicine}, volume = {12}, journal = {Journal of Clinical Medicine}, number = {6}, issn = {2077-0383}, doi = {10.3390/jcm12062096}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-311189}, year = {2023}, abstract = {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.}, language = {en} }