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  • 1
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    Online Resource
    Hemostatis Analyzer-Supported Hemotherapy Algorithm in Cardiac Surgery: Protocol for a Randomized Controlled Monocentric Trial
    JMIR Publications Inc. ; 2020
    In:  JMIR Research Protocols Vol. 9, No. 4 ( 2020-4-21), p. e17206-
    Details
    In: JMIR Research Protocols, JMIR Publications Inc., Vol. 9, No. 4 ( 2020-4-21), p. e17206-
    Abstract: Point of care devices for performing targeted coagulation substitution in patients who are bleeding have become increasingly important in recent years. New on the market is the Quantra. It is a device that uses sonorheometry, a sonic estimation of elasticity via resonance, which is a novel ultrasound-based technology that measures viscoelastic properties of whole blood. Several studies have already shown the comparability of the Quantra with devices already established on the market, such as the rotational thromboelastometry (ROTEM) device. Objective In contrast to existing studies, this study is the first prospective interventional study using this new system in a cardiac surgical patient cohort. We will investigate the noninferiority between an already existing coagulation algorithm based on the ROTEM/Multiplate system and a new algorithm based on the Quantra system for the treatment of coagulopathic cardiac surgical patients. Methods The study is divided into two phases. In an initial observation phase, whole blood samples of 20 patients obtained at three defined time points (prior to surgery, after completion of cardiopulmonary bypass, and on arrival in the intensive care unit) will be analyzed using both the ROTEM/Multiplate and Quantra systems. The obtained threshold values will be used to develop a novel algorithm for hemotherapy. In a second intervention phase, the new algorithm will be tested for noninferiority against an algorithm used routinely for years in our department. Results The main objective of the examination is the cumulative loss of blood within 24 hours after surgery. Statistical calculations based on the literature and in-house data suggest that the new algorithm is not inferior if the difference in cumulative blood loss is 〈 150 mL/24 hours. Conclusions Because of the comparability of the Quantra sonorheometry system with the ROTEM measurement methods, the existing hemotherapy treatment algorithm can be adapted to the Quantra device with proof of noninferiority. Trial Registration ClinicalTrials.gov NCT03902275; https://clinicaltrials.gov/ct2/show/NCT03902275 International Registered Report Identifier (IRRID) DERR1-10.2196/17206
    Type of Medium: Online Resource
    ISSN: 1929-0748
    URL: Article
    DOI: 10.2196/17206
    Language: English
    Publisher: JMIR Publications Inc.
    Publication Date: 2020
    detail.hit.zdb_id: 2719222-2
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  • 2
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    Effects of an Animated Blood Clot Technology (Visual Clot) on the Decision-Making of Users Inexperienced in Viscoelastic Testing: Multicenter Trial
    JMIR Publications Inc. ; 2021
    In:  Journal of Medical Internet Research Vol. 23, No. 5 ( 2021-5-3), p. e27124-
    Details
    In: Journal of Medical Internet Research, JMIR Publications Inc., Vol. 23, No. 5 ( 2021-5-3), p. e27124-
    Abstract: Viscoelastic test–guided coagulation management has become increasingly important in assessing hemostasis. We developed Visual Clot, an animated, 3D blood clot that illustrates raw rotational thromboelastometry (ROTEM) parameters in a user-centered and situation awareness–oriented method. Objective This study aimed to evaluate the applicability of Visual Clot by examining its effects on users that are novices in viscoelastic-guided resuscitation. Methods We conducted an investigator-initiated, international, multicenter study between September 16, 2020, and October 6, 2020, in 5 tertiary care hospitals in central Europe. We randomly recruited medical students and inexperienced resident physicians without significant prior exposure to viscoelastic testing. The 7 participants per center managed 9 different ROTEM outputs twice, once as standard ROTEM tracings and once as the corresponding Visual Clot. We randomly presented the 18 viscoelastic cases and asked the participants for their therapeutic decisions. We assessed the performance, diagnostic confidence, and perceived workload in managing the tasks using mixed statistical models and adjusted for possible confounding factors. Results Analyzing a total of 630 results, we found that the participants solved more cases correctly (odds ratio [OR] 33.66, 95% CI 21.13-53.64; P 〈 .001), exhibited more diagnostic confidence (OR 206.2, 95% CI 93.5-454.75; P 〈 .001), and perceived less workload (coefficient –41.63; 95% CI –43.91 to –39.36; P 〈 .001) using Visual Clot compared to using standard ROTEM tracings. Conclusions This study emphasizes the practical benefit of presenting viscoelastic test results in a user-centered way. Visual Clot may allow inexperienced users to be involved in the decision-making process to treat bleeding-associated coagulopathy. The increased diagnostic confidence, diagnostic certainty, reduced workload, and positive user feedback associated with this visualization may promote the further adoption of viscoelastic methods in diverse health care settings.
    Type of Medium: Online Resource
    ISSN: 1438-8871
    URL: Article
    DOI: 10.2196/27124
    Language: English
    Publisher: JMIR Publications Inc.
    Publication Date: 2021
    detail.hit.zdb_id: 2028830-X
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  • 3
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    Expectations of Anesthesiology and Intensive Care Professionals Toward Artificial Intelligence: Observational Study
    JMIR Publications Inc. ; 2023
    In:  JMIR Formative Research Vol. 7 ( 2023-6-12), p. e43896-
    Details
    In: JMIR Formative Research, JMIR Publications Inc., Vol. 7 ( 2023-6-12), p. e43896-
    Abstract: Artificial intelligence (AI) applications offer numerous opportunities to improve health care. To be used in the intensive care unit, AI must meet the needs of staff, and potential barriers must be addressed through joint action by all stakeholders. It is thus critical to assess the needs and concerns of anesthesiologists and intensive care physicians related to AI in health care throughout Europe. Objective This Europe-wide, cross-sectional observational study investigates how potential users of AI systems in anesthesiology and intensive care assess the opportunities and risks of the new technology. The web-based questionnaire was based on the established analytic model of acceptance of innovations by Rogers to record 5 stages of innovation acceptance. Methods The questionnaire was sent twice in 2 months (March 11, 2021, and November 5, 2021) through the European Society of Anaesthesiology and Intensive Care (ESAIC) member email distribution list. A total of 9294 ESAIC members were reached, of whom 728 filled out the questionnaire (response rate 728/9294, 8%). Due to missing data, 27 questionnaires were excluded. The analyses were conducted with 701 participants. Results A total of 701 questionnaires (female: n=299, 42%) were analyzed. Overall, 265 (37.8%) of the participants have been in contact with AI and evaluated the benefits of this technology higher (mean 3.22, SD 0.39) than participants who stated no previous contact (mean 3.01, SD 0.48). Physicians see the most benefits of AI application in early warning systems (335/701, 48% strongly agreed, and 358/701, 51% agreed). Major potential disadvantages were technical problems (236/701, 34% strongly agreed, and 410/701, 58% agreed) and handling difficulties (126/701, 18% strongly agreed, and 462/701, 66% agreed), both of which could be addressed by Europe-wide digitalization and education. In addition, the lack of a secure legal basis for the research and use of medical AI in the European Union leads doctors to expect problems with legal liability (186/701, 27% strongly agreed, and 374/701, 53% agreed) and data protection (148/701, 21% strongly agreed, and 343/701, 49% agreed). Conclusions Anesthesiologists and intensive care personnel are open to AI applications in their professional field and expect numerous benefits for staff and patients. Regional differences in the digitalization of the private sector are not reflected in the acceptance of AI among health care professionals. Physicians anticipate technical difficulties and lack a stable legal basis for the use of AI. Training for medical staff could increase the benefits of AI in professional medicine. Therefore, we suggest that the development and implementation of AI in health care require a solid technical, legal, and ethical basis, as well as adequate education and training of users.
    Type of Medium: Online Resource
    ISSN: 2561-326X
    URL: Article
    DOI: 10.2196/43896
    Language: English
    Publisher: JMIR Publications Inc.
    Publication Date: 2023
    detail.hit.zdb_id: 2941716-8
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