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Novel Challenges and Advances in Anesthesiology and Critical Care
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Novel Challenges and Advances in Anesthesiology and Critical Care

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Personalized Critical Care".

Deadline for manuscript submissions: closed (20 January 2024) | Viewed by 9786

Special Issue Editor

Dr. Michalina Kołodziejczak

E-Mail Website
Guest Editor
Department of Anesthesiology and Intensive Care, Collegium Medicum Bydgoszcz, Nicolaus Copernicus University Torun, Antoni Jurasz University Hospital No.1, Bydgoszcz, Poland
Interests: cardiovascular medicine; personalized medicine; artificial intelligence; multidisciplinary team care; heart failure
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Anesthesiology and critical care, since their origin, have required a personalized approach toward the most vulnerable patients. A plethora of advancements in technology and medicine allowed for their dynamic development and the more comprehensive management of patients within multidisciplinary teams than ever. The global pandemic of the coronavirus disease in 2019 (COVID-19) put a major strain on population health and healthcare systems and providers. While the main waves of infections belong to the past, we are still observing its aftermath. Those individual patients who survived SARS-CoV-2 virus infection but are struggling with complications, as well as patients suffering from the advancement of chronic diseases or the development of oncological maladies, contribute to an increased burden during anesthesia and critical care management. Therefore, in this Special Issue, we aim to address current challenges and advancements experienced by anaesthesiologists or intensivists. We encourage the submission of reviews and original articles that address clinical advancements and ongoing challenges and emphasize the direction of the development of modern anaesthesiology and critical care.

Dr. Michalina Kołodziejczak
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Personalized Medicine is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • personalized medicine
  • anesthesiology
  • critical care
  • mechanical ventilation
  • extracorporeal membrane oxygenation

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Published Papers (4 papers)

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Research

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12 pages, 1333 KiB  
Article
Physiological Modeling of Hemodynamic Responses to Sodium Nitroprusside
by Joseph Rinehart, Sean Coeckelenbergh, Ishita Srivastava, Maxime Cannesson and Alexandre Joosten
J. Pers. Med. 2023, 13(7), 1101; https://doi.org/10.3390/jpm13071101 - 6 Jul 2023
Cited by 1 | Viewed by 1589
Abstract
Background: Computational modeling of physiology has become a routine element in the development, evaluation, and safety testing of many types of medical devices. Members of the Food and Drug Administration have recently published a manuscript detailing the development, validation, and sensitivity testing of [...] Read more.
Background: Computational modeling of physiology has become a routine element in the development, evaluation, and safety testing of many types of medical devices. Members of the Food and Drug Administration have recently published a manuscript detailing the development, validation, and sensitivity testing of a computational model for blood volume, cardiac stroke volume, and blood pressure, noting that such a model might be useful in the development of closed-loop fluid administration systems. In the present study, we have expanded on this model to include the pharmacologic effect of sodium nitroprusside and calibrated the model against our previous experimental animal model data. Methods: Beginning with the model elements in the original publication, we added six new parameters to control the effect of sodium nitroprusside: two for the onset time and clearance rates, two for the stroke volume effect (which includes venodilation as a “hidden” element), and two for the direct effect on arterial blood pressure. Using this new model, we then calibrated the predictive performance against previously collected animal study data using nitroprusside infusions to simulate shock with the primary emphasis on MAP. Root-mean-squared error (RMSE) was calculated, and the performance was compared to the performance of the model in the original study. Results: RMSE of model-predicted MAP to actual MAP was lower than that reported in the original model, but higher for SV and CO. The individually fit models showed lower RMSE than using the population average values for parameters, suggesting the fitting process was effective in identifying improved parameters. Use of partially fit models after removal of the lowest variance population parameters showed a very minor decrement in improvement over the fully fit models. Conclusion: The new model added the clinical effects of SNP and was successfully calibrated against experimental data with an RMSE of <10% for mean arterial pressure. Model-predicted MAP showed an error similar to that seen in the original base model when using fluid shifts, heart rate, and drug dose as model inputs. Full article
(This article belongs to the Special Issue Novel Challenges and Advances in Anesthesiology and Critical Care)
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12 pages, 2279 KiB  
Article
Comparison of the Incidence of Postoperative Acute Kidney Injury Following the Administration of Remimazolam or Sevoflurane in Elderly Patients Undergoing Total Knee Arthroplasty: A Randomized Controlled Trial
by Sangho Lee, Hee Yong Kang, Ye Na Ahn and Ann Hee You
J. Pers. Med. 2023, 13(5), 789; https://doi.org/10.3390/jpm13050789 - 1 May 2023
Cited by 6 | Viewed by 2200
Abstract
Background: We evaluated the incidence of postoperative acute kidney injury (AKI) and complications when remimazolam (RMMZ) or sevoflurane (SEVO) were used in elderly patients undergoing total knee arthroplasty. Methods: Seventy-eight participants aged ≥65 were randomly allocated to either the RMMZ or SEVO group. [...] Read more.
Background: We evaluated the incidence of postoperative acute kidney injury (AKI) and complications when remimazolam (RMMZ) or sevoflurane (SEVO) were used in elderly patients undergoing total knee arthroplasty. Methods: Seventy-eight participants aged ≥65 were randomly allocated to either the RMMZ or SEVO group. The primary outcome was the incidence of AKI on postoperative day (POD) 2. The secondary outcomes included intraoperative heart rate (HR), blood pressure (BP), total drug administered, emergence time, postoperative complications on POD 2, and hospital length of stay (HLOS). Results: The incidence of AKI was comparable between the RMMZ and SEVO groups. The doses of intraoperative remifentanil, vasodilators, and additional sedatives were significantly higher in the RMMZ group than in the SEVO group. Overall intraoperative HR and BP tended to remain higher in the RMMZ group. The emergence time in the operating room was significantly faster in the RMMZ group; however, the time required for an Aldrete score ≥ 9 was comparable between the RMMZ and SEVO groups. Postoperative complications and HLOS were comparable between the RMMZ and SEVO groups. Conclusion: RMMZ may be recommended for patients who are expected to decrease in intraoperative vital signs. However, stable hemodynamics with RMMZ were not sufficient to influence the prevention of AKI. Full article
(This article belongs to the Special Issue Novel Challenges and Advances in Anesthesiology and Critical Care)
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Review

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19 pages, 2966 KiB  
Review
Biochemical Changes in Cardiopulmonary Bypass in Cardiac Surgery: New Insights
by Luan Oliveira Ferreira, Victoria Winkler Vasconcelos, Janielle de Sousa Lima, Jaime Rodrigues Vieira Neto, Giovana Escribano da Costa, Jordana de Castro Esteves, Sallatiel Cabral de Sousa, Jonathan Almeida Moura, Felipe Ruda Silva Santos, João Monteiro Leitão Filho, Matheus Ramos Protásio, Pollyana Sousa Araújo, Cláudio José da Silva Lemos, Karina Dias Resende and Dielly Catrina Favacho Lopes
J. Pers. Med. 2023, 13(10), 1506; https://doi.org/10.3390/jpm13101506 - 18 Oct 2023
Cited by 7 | Viewed by 3140
Abstract
Patients undergoing coronary revascularization with extracorporeal circulation or cardiopulmonary bypass (CPB) may develop several biochemical changes in the microcirculation that lead to a systemic inflammatory response. Surgical incision, post-CPB reperfusion injury and blood contact with non-endothelial membranes can activate inflammatory signaling pathways that [...] Read more.
Patients undergoing coronary revascularization with extracorporeal circulation or cardiopulmonary bypass (CPB) may develop several biochemical changes in the microcirculation that lead to a systemic inflammatory response. Surgical incision, post-CPB reperfusion injury and blood contact with non-endothelial membranes can activate inflammatory signaling pathways that lead to the production and activation of inflammatory cells, with cytokine production and oxidative stress. This inflammatory storm can cause damage to vital organs, especially the heart, and thus lead to complications in the postoperative period. In addition to the organic pathophysiology during and after the period of exposure to extracorporeal circulation, this review addresses new perspectives for intraoperative treatment and management that may lead to a reduction in this inflammatory storm and thereby improve the prognosis and possibly reduce the mortality of these patients. Full article
(This article belongs to the Special Issue Novel Challenges and Advances in Anesthesiology and Critical Care)
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9 pages, 547 KiB  
Review
Artificial Intelligence in the Intensive Care Unit: Present and Future in the COVID-19 Era
by Michalina Marta Kołodziejczak, Katarzyna Sierakowska, Yurii Tkachenko and Piotr Kowalski
J. Pers. Med. 2023, 13(6), 891; https://doi.org/10.3390/jpm13060891 - 25 May 2023
Cited by 1 | Viewed by 2285
Abstract
The development of artificial intelligence (AI) allows for the construction of technologies capable of implementing functions that represent the human mind, senses, and problem-solving skills, leading to automation, rapid data analysis, and acceleration of tasks. These solutions has been initially implemented in medical [...] Read more.
The development of artificial intelligence (AI) allows for the construction of technologies capable of implementing functions that represent the human mind, senses, and problem-solving skills, leading to automation, rapid data analysis, and acceleration of tasks. These solutions has been initially implemented in medical fields relying on image analysis; however, technological development and interdisciplinary collaboration allows for the introduction of AI-based enhancements to further medical specialties. During the COVID-19 pandemic, novel technologies established on big data analysis experienced a rapid expansion. Yet, despite the possibilities of advancements with these AI technologies, there are number of shortcomings that need to be resolved to assert the highest and the safest level of performance, especially in the setting of the intensive care unit (ICU). Within the ICU, numerous factors and data affect clinical decision making and work management that could be managed by AI-based technologies. Early detection of a patient’s deterioration, identification of unknown prognostic parameters, or even improvement of work organization are a few of many areas where patients and medical personnel can benefit from solutions developed with AI. Full article
(This article belongs to the Special Issue Novel Challenges and Advances in Anesthesiology and Critical Care)
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