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Medicina
Special Issues
Emerging Technology for Monitoring and Treatment in Critical Care
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Emerging Technology for Monitoring and Treatment in Critical Care

A special issue of Medicina (ISSN 1648-9144). This special issue belongs to the section "Emergency Medicine".

Deadline for manuscript submissions: closed (5 November 2022) | Viewed by 16676

Special Issue Editors

Dr. João Gonçalves-Pereira

E-Mail Website
Guest Editor
Grupo de Infecção e Sepsis, Porto, Portugal
Interests: antibiotics; sepsis; critical care
Dr. Paulo Mergulhão

E-Mail Website
Guest Editor
Hospital dos Lusíadas, Oporto, Portugal
Interests: critical care; emergency; sepsis; invasive ventilation

Special Issue Information

Dear Colleagues,

Medical care has been evolving at a very rapid pace over time and in multiple areas. One of the disciplines where this is most visible is in Intensive Care Medicine (ICM). Being one the most recent specialities of medical practice and having been born out of the necessity to provide mechanical support to failing organs, namely the respiratory muscles during the poliomyelitis epidemic in Denmark during the 1950’s, ICM has always had a very strong technological component and ICUs are often early adopters of innovative diagnostic and therapeutic techniques.

In fact, the ability of ICM to support life and organ functions of a growing number of patients, including those with complex comorbid diseases and a rising age, is largely based on increasingly complex technology applied to the human health. Although technology applies to almost every medical speciality, those medical advances are commonly translated to critical care, as this area concentrates the most severe and difficult to treat patients.

Therapeutic interventions, such as extracorporeal oxygenation and CO2 removal, continuous haemodialysis and hemoperfusion, plasmapheresis, along with complex monitorization (invasive and non-invasive) and point of care laboratory devices, allows better treatment and full recovery of an increased number of patients with what were previously known to be lethal pathologies.

Complex medical interventions, either diagnostic or therapeutic are becoming part of routine intensive care practice. A better understanding of the patient physiopathology allows the clinician to have a better decision tool for each patient and brings together the concept of Precision Medicine, not only tailoring the treatment to each patient condition but also adapting therapy to patient evolution in a real time way.

Nevertheless, the introduction of the different devices in clinical practice is, sometimes, flawed with a lack of proper clinical studies or experience. To understand what really brings health benefits to the individual patient is an important part of the scientific approach.

The purpose of this special issue is to bring light and share experiences on novel technologies applied to the critically ill patient, including monitoring devices, either invasive, mini-invasive or non-invasive, point-of-care diagnostic technology and therapeutic devices (including for single organ support). We are especially interested in the evaluation of health benefits and risks for each new technology and in the advances to the individualization of care, including selection of patients who might benefit from each intervention.

We also look for out-of-the-box approaches to optimize the use of human medical resources and decrease the need for night shifts, without jeopardizing patient’ safety.

The scope of this issue is deliberately broad to encourage the coverage of a wide range of topics and perspectives related to the individual care of critically ill patients.

Dr. João Gonçalves-Pereira
Dr. Paulo Mergulhão
Guest Editors

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. Medicina 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 1800 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

  • invasive monitoring
  • hemodynamic monitoring
  • extracorporeal circulation
  • extracorporeal oxygenation
  • invasive hemodynamic support
  • point-of-care laboratory devices
  • extracorporeal blood purification
  • artificial intelligence
  • early detection of events
  • remote monitoring

Published Papers (6 papers)

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Research

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11 pages, 1751 KiB  
Article
Is There a Risk of Misinterpretation of Potassium Concentration from Undetectable Hemolysis Using a POCT Blood Gas Analyzer in the Emergency Department?
by Marianna Nigro, Gabriele Valli, Maria Luisa Marchionne, Dario Sattarinia, Fabiana Silvestrini, Daniele De Pietro, Simone Fazzini, Giorgia Roselli, Andrea Spallino, Valentina Praticò, Enrico Mirante, Ersilia Castaldo, Francesco Rocco Pugliese, Claudia Cicchini, Carlo Ancona, Francesca De Marco, Maria Pia Ruggieri and Salvatore Di Somma
Medicina 2023, 59(1), 66; https://doi.org/10.3390/medicina59010066 - 28 Dec 2022
Cited by 4 | Viewed by 2277
Abstract
Background and Objectives: Hemolysis is reported to be present in up to 10% of blood gas specimens in the central lab; however, few data on the incidence of hemolysis using a point-of-care testing (POCT) blood gas analysis are available in the setting [...] Read more.
Background and Objectives: Hemolysis is reported to be present in up to 10% of blood gas specimens in the central lab; however, few data on the incidence of hemolysis using a point-of-care testing (POCT) blood gas analysis are available in the setting of the emergency department. The aims of this study were: (1) to analyze the prevalence of hemolysis in blood gas samples collected in the ED using a POCT device; and (2) to evaluate the impact of hemolysis on blood sample results and its clinical consequences. Materials and Methods: We collected 525 consecutive POCT arterial blood gas samples using syringes with electrolyte-balanced heparin within 3 different EDs in the metropolitan area of Rome. Immediately after the collection, the blood samples were checked for the presence of hemolysis with a POCT instrument (i.e., HEMCHECK, H-10 ®). The samples were then subsequently processed for blood gasses, and an electrolytes analysis by a second operator blinded for the hemolysis results. A venous blood sample was simultaneously collected, analyzed for it’s potassium value, and used as a reference. Results: Of the samples, 472 were considered for the statistics, while 53 were excluded due to the high percentage of hemolysis due to operator fault in carrying out the measurement. The final mean hemolysis per operator was 12% (±13% SD), and the total final hemolysis was 14.4%.Potassium (K+) was significantly higher in the hemolyzed group compared with the non-hemolyzed sample (4.60 ± 0.11 vs. 3.99 ± 0.03 mEq/L; p < 0.001), and there were differences between arterial potassium versus venous potassium (D(a-v) K+, 0.29 ± 0.06 vs.−0.19 ± 0.02 mEq/L, p < 0.01). A Bland–Altman analysis confirmed that hemolysis significantly overestimated blood potassium level. Conclusion: Almost 12% of POCT blood gas analysis samples performed in the ED could be hemolyzed, and the presence of this hemolysis is not routinely detected. This could cause an error in the interpretation of the results, leading to the consideration of potassium concentrations being below the lower limit within the normal limits and also leading to the diagnosis of false hyperkalemia, which would have potential clinical consequences in therapeutic decision-making in the ED. The routine use of a POCT hemolysis detector could help prevent any misdiagnoses. Full article
(This article belongs to the Special Issue Emerging Technology for Monitoring and Treatment in Critical Care)
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9 pages, 2546 KiB  
Article
Prediction of Prognosis in Patients with Trauma by Using Machine Learning
by Kuo-Chang Lee, Chien-Chin Hsu, Tzu-Chieh Lin, Hsiu-Fen Chiang, Gwo-Jiun Horng and Kuo-Tai Chen
Medicina 2022, 58(10), 1379; https://doi.org/10.3390/medicina58101379 - 01 Oct 2022
Cited by 3 | Viewed by 1512
Abstract
Background and Objectives: We developed a machine learning algorithm to analyze trauma-related data and predict the mortality and chronic care needs of patients with trauma. Materials and Methods: We recruited admitted patients with trauma during 2015 and 2016 and collected their clinical data. [...] Read more.
Background and Objectives: We developed a machine learning algorithm to analyze trauma-related data and predict the mortality and chronic care needs of patients with trauma. Materials and Methods: We recruited admitted patients with trauma during 2015 and 2016 and collected their clinical data. Then, we subjected this database to different machine learning techniques and chose the one with the highest accuracy by using cross-validation. The primary endpoint was mortality, and the secondary endpoint was requirement for chronic care. Results: Data of 5871 patients were collected. We then used the eXtreme Gradient Boosting (xGBT) machine learning model to create two algorithms: a complete model and a short-term model. The complete model exhibited an 86% recall for recovery, 30% for chronic care, 67% for mortality, and 80% for complications; the short-term model fitted for ED displayed an 89% recall for recovery, 25% for chronic care, and 41% for mortality. Conclusions: We developed a machine learning algorithm that displayed good recall for the healthy recovery group but unsatisfactory results for those requiring chronic care or having a risk of mortality. The prediction power of this algorithm may be improved by implementing features such as age group classification, severity selection, and score calibration of trauma-related variables. Full article
(This article belongs to the Special Issue Emerging Technology for Monitoring and Treatment in Critical Care)
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8 pages, 929 KiB  
Article
Endovascular Treatment of Gastrointestinal Hemorrhage
by Martin Vorčák, Ján Sýkora, Martin Ďuríček, Peter Bánovčin, Marián Grendár and Kamil Zeleňák
Medicina 2022, 58(3), 424; https://doi.org/10.3390/medicina58030424 - 14 Mar 2022
Cited by 4 | Viewed by 2352
Abstract
Background and Objectives: Severe non-variceal gastrointestinal bleeding is a life-threatening condition with complicated treatment if endoscopic therapy fails. In such cases, transcatheter arterial embolization is recommended. The technical and clinical effects of this technique were analyzed in this group of patients, as [...] Read more.
Background and Objectives: Severe non-variceal gastrointestinal bleeding is a life-threatening condition with complicated treatment if endoscopic therapy fails. In such cases, transcatheter arterial embolization is recommended. The technical and clinical effects of this technique were analyzed in this group of patients, as well as its complication rate and 30-day mortality. Materials and Methods: Patient data over a one-decade period (from 2010 to 2019) were analyzed retrospectively; 27 patients (18 men and 9 women; median age 61 years) treated by endovascular embolization in our institution, with clinically significant gastrointestinal hemorrhage after unsuccessful or impossible endoscopic treatment, were identified, and their data were collected. Results: The source of bleeding was found in 88% of patients, but embolization was performed in 96% of them. The overall technical success rate was 96.8%, and the clinical success was 88.5%. Re-bleeding occurred in eight cases, five of whom had re-embolization that was technically successful in four cases. The incidence of re-bleeding was significantly higher in patients with two or more comorbidities (p = 0.043). There was one serious complication (4%) in the group, and minor difficulties occurred in 18% of patients; 30-day mortality reached 22%. Mortality was significantly higher in the group of patients with re-bleeding (p = 0.044). Conclusions: Transcatheter arterial embolization is a mini-invasive method with high technical success in patients with endoscopically untreatable gastrointestinal bleeding; it is also suitable for high-risk cases. Mortality (to a significant extent) depends on the occurrence of re-bleeding and the patient’s comorbidities. Full article
(This article belongs to the Special Issue Emerging Technology for Monitoring and Treatment in Critical Care)
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12 pages, 1441 KiB  
Article
The Feasibility of a Machine Learning Approach in Predicting Successful Ventilator Mode Shifting for Adult Patients in the Medical Intensive Care Unit
by Kuang-Hua Cheng, Mei-Chu Tan, Yu-Jen Chang, Cheng-Wei Lin, Yi-Han Lin, Tzu-Min Chang and Li-Kuo Kuo
Medicina 2022, 58(3), 360; https://doi.org/10.3390/medicina58030360 - 01 Mar 2022
Cited by 6 | Viewed by 2287
Abstract
Background and Objectives: Traditional assessment of the readiness for the weaning from the mechanical ventilator (MV) needs respiratory parameters in a spontaneous breath. Exempted from the MV disconnecting and manual measurements of weaning parameters, a prediction model based on parameters from MV [...] Read more.
Background and Objectives: Traditional assessment of the readiness for the weaning from the mechanical ventilator (MV) needs respiratory parameters in a spontaneous breath. Exempted from the MV disconnecting and manual measurements of weaning parameters, a prediction model based on parameters from MV and electronic medical records (EMRs) may help the assessment before spontaneous breath trials. The study aimed to develop prediction models using machine learning techniques with parameters from the ventilator and EMRs for predicting successful ventilator mode shifting in the medical intensive care unit. Materials and Methods: A retrospective analysis of 1483 adult patients with mechanical ventilators for acute respiratory failure in three medical intensive care units between April 2015 and October 2017 was conducted by machine learning techniques to establish the predicting models. The input candidate parameters included ventilator setting and measurements, patients’ demographics, arterial blood gas, laboratory results, and vital signs. Several classification algorithms were evaluated to fit the models, including Lasso Regression, Ridge Regression, Elastic Net, Random Forest, Extreme Gradient Boosting (XGBoost), Support Vector Machine, and Artificial Neural Network according to the area under the Receiver Operating Characteristic curves (AUROC). Results: Two models were built to predict the success shifting from full to partial support ventilation (WPMV model) or from partial support to the T-piece trial (sSBT model). In total, 3 MV and 13 nonpulmonary features were selected for the WPMV model with the XGBoost algorithm. The sSBT model was built with 8 MV and 4 nonpulmonary features with the Random Forest algorithm. The AUROC of the WPMV model and sSBT model were 0.76 and 0.79, respectively. Conclusions: The weaning predictions using machine learning and parameters from MV and EMRs have acceptable performance. Without manual measurements, a decision-making system would be feasible for the continuous prediction of mode shifting when the novel models process real-time data from MV and EMRs. Full article
(This article belongs to the Special Issue Emerging Technology for Monitoring and Treatment in Critical Care)
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Review

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11 pages, 615 KiB  
Review
Airway and Respiratory Devices in the Prevention of Ventilator-Associated Pneumonia
by Luis Coelho, Patricia Moniz, Gonçalo Guerreiro and Pedro Póvoa
Medicina 2023, 59(2), 199; https://doi.org/10.3390/medicina59020199 - 19 Jan 2023
Cited by 5 | Viewed by 3927
Abstract
Ventilator-associated pneumonia (VAP) is the most common ICU-acquired infection among patients under mechanical ventilation (MV). It may occur in up to 50% of mechanically ventilated patients and is associated with an increased duration of MV, antibiotic consumption, increased morbidity, and mortality. VAP prevention [...] Read more.
Ventilator-associated pneumonia (VAP) is the most common ICU-acquired infection among patients under mechanical ventilation (MV). It may occur in up to 50% of mechanically ventilated patients and is associated with an increased duration of MV, antibiotic consumption, increased morbidity, and mortality. VAP prevention is a multifaceted priority of the intensive care team. The use of specialized artificial airways and other devices can have an impact on the prevention of VAP. However, these devices can also have adverse effects, and aspects of their efficacy in the prevention of VAP are still a matter of debate. This article provides a narrative review of how different airway and respiratory devices may help to reduce the incidence of VAP. Full article
(This article belongs to the Special Issue Emerging Technology for Monitoring and Treatment in Critical Care)
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17 pages, 1487 KiB  
Review
Monitoring of the Forgotten Immune System during Critical Illness—A Narrative Review
by Maria A. Serrano, André M. C. Gomes and Susana M. Fernandes
Medicina 2023, 59(1), 61; https://doi.org/10.3390/medicina59010061 - 28 Dec 2022
Cited by 6 | Viewed by 3791
Abstract
Immune organ failure is frequent in critical illness independent of its cause and has been acknowledged for a long time. Most patients admitted to the ICU, whether featuring infection, trauma, or other tissue injury, have high levels of alarmins expression in tissues or [...] Read more.
Immune organ failure is frequent in critical illness independent of its cause and has been acknowledged for a long time. Most patients admitted to the ICU, whether featuring infection, trauma, or other tissue injury, have high levels of alarmins expression in tissues or systemically which then activate innate and adaptive responses. Although necessary, this response is frequently maladaptive and leads to organ dysfunction. In addition, the counter-response aiming to restore homeostasis and repair injury can also be detrimental and contribute to persistent chronic illness. Despite intensive research on this topic in the last 40 years, the immune system is not routinely monitored in critical care units. In this narrative review we will first discuss the inflammatory response after acute illness and the players of maladaptive response, focusing on neutrophils, monocytes, and T cells. We will then go through commonly used biomarkers, like C-reactive protein, procalcitonin and pancreatic stone protein (PSP) and what they monitor. Next, we will discuss the strengths and limitations of flow cytometry and related techniques as an essential tool for more in-depth immune monitoring and end with a presentation of the most promising cell associated markers, namely HLA-DR expression on monocytes, neutrophil expression of CD64 and PD-1 expression on T cells. In sum, immune monitoring critically ill patients is a forgotten and missing piece in the monitoring capacity of intensive care units. New technology, including bed-side equipment and in deep cell phenotyping using emerging multiplexing techniques will likely allow the definition of endotypes and a more personalized care in the future. Full article
(This article belongs to the Special Issue Emerging Technology for Monitoring and Treatment in Critical Care)
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