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Diagnostics
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Diagnostics in the Emergency and Critical Care Medicine
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Diagnostics in the Emergency and Critical Care Medicine

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 17640

Special Issue Editor

Dr. Zhongheng Zhang

E-Mail Website
Guest Editor
Department of Emergency Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou 310016, China
Interests: emergency and critical care medicine; AI
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

This Special Issue aims to improve the care of patients with emergency and critical illness by acquiring, discussing, distributing, and promoting evidence-based information relevant to emergency physicians and intensivists. In particular, we welcome articles related to the diagnostics of emergency and critical care patients, including but not limited to the risk stratification of the critically ill syndrome, diagnosis of a certain disease/complication/syndrome, and risk stratification.

The issue will publish original articles, reviews, technical notes, case reports, and interesting images covering all aspects of emergency and critical care medicine, including but not limited to trauma, anesthesiology, respiratory failure, sepsis, cardiovascular disease, healthcare-associated infections prevention, and end-of-life care.

Prof. Dr. Zhongheng Zhang
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. Diagnostics is an international peer-reviewed open access semimonthly 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

  • diagnostics
  • emergency and critical care medicine
  • trauma
  • anesthesiology
  • respiratory failure
  • sepsis
  • cardiovascular disease
  • healthcare-associated infection prevention
  • end-of-life care

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

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Research

11 pages, 759 KiB  
Article
Lower Late Development Rate of Acute Respiratory Distress Syndrome in Patients with Lower Mechanical Power or Driving Pressure
by Ya-Chi Lee, Pi-Hua Liu, Shih-Wei Lin, Chung-Chieh Yu, Chien-Ming Chu and Huang-Pin Wu
Diagnostics 2024, 14(17), 1969; https://doi.org/10.3390/diagnostics14171969 - 6 Sep 2024
Viewed by 612
Abstract
For patients on ventilation without acute respiratory distress syndrome (ARDS), there are, as yet, limited data on ventilation strategies. We hypothesized that driving pressure (DP) and mechanical power (MP) may play key roles for the late development of ARDS in patients without initial [...] Read more.
For patients on ventilation without acute respiratory distress syndrome (ARDS), there are, as yet, limited data on ventilation strategies. We hypothesized that driving pressure (DP) and mechanical power (MP) may play key roles for the late development of ARDS in patients without initial ARDS. A post hoc analysis of a database from our previous cohort was performed. The mean DP/MP was computed from the data before ARDS development or until ventilator support was discontinued within 28 days. The association between DP/MP and late development of ARDS within 28 days was determined. One hundred and twelve patients were enrolled, among whom seven developed ARDS. Univariate Cox regression showed that congestive heart failure (CHF) history and higher levels of mean MP and DP were associated with ARDS development. Multivariate models revealed that the mean MP and mean DP were still factors independently associated with ARDS development at hazard ratios of 1.177 and 1.226 after adjusting for the CHF effect. Areas under the receiver operating characteristic curves for mean DP/MP in predicting ARDS development were 0.813 and 0.759, respectively. In conclusion, high mean DP and MP values may be key factors associated with late ARDS development. The mean DP had a better predicted value for the development of ARDS than the mean MP. Full article
(This article belongs to the Special Issue Diagnostics in the Emergency and Critical Care Medicine)
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11 pages, 2465 KiB  
Article
Accuracy of Intra-Axial Brain Tumor Characterization in the Emergency MRI Reports: A Retrospective Human Performance Benchmarking Pilot Study
by Aapo Sirén, Elina Turkia, Mikko Nyman and Jussi Hirvonen
Diagnostics 2024, 14(16), 1791; https://doi.org/10.3390/diagnostics14161791 - 16 Aug 2024
Viewed by 403
Abstract
Demand for emergency neuroimaging is increasing. Even magnetic resonance imaging (MRI) is often performed outside office hours, sometimes revealing more uncommon entities like brain tumors. The scientific literature studying artificial intelligence (AI) methods for classifying brain tumors on imaging is growing, but knowledge [...] Read more.
Demand for emergency neuroimaging is increasing. Even magnetic resonance imaging (MRI) is often performed outside office hours, sometimes revealing more uncommon entities like brain tumors. The scientific literature studying artificial intelligence (AI) methods for classifying brain tumors on imaging is growing, but knowledge about the radiologist’s performance on this task is surprisingly scarce. Our study aimed to tentatively fill this knowledge gap. We hypothesized that the radiologist could classify intra-axial brain tumors at the emergency department with clinically acceptable accuracy. We retrospectively examined emergency brain MRI reports from 2013 to 2021, the inclusion criteria being (1) emergency brain MRI, (2) no previously known intra-axial brain tumor, and (3) suspicion of an intra-axial brain tumor on emergency MRI report. The tumor type suggestion and the final clinical diagnosis were pooled into groups: (1) glial tumors, (2) metastasis, (3) lymphoma, and (4) other tumors. The final study sample included 150 patients, of which 108 had histopathological tumor type confirmation. Among the patients with histopathological tumor type confirmation, the accuracy of the MRI reports in classifying the tumor type was 0.86 for gliomas against other tumor types, 0.89 for metastases, and 0.99 for lymphomas. We found the result encouraging, given the prolific need for emergency imaging. Full article
(This article belongs to the Special Issue Diagnostics in the Emergency and Critical Care Medicine)
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11 pages, 1686 KiB  
Article
Distinguishing Childhood Asthma Exacerbations from Stable Asthma: The Utility of Inflammatory White Blood Cell Biomarkers
by Ali Alsuheel Asseri
Diagnostics 2024, 14(15), 1663; https://doi.org/10.3390/diagnostics14151663 - 1 Aug 2024
Viewed by 618
Abstract
Background: Asthma is a chronic inflammatory condition characterized by episodes of acute asthma exacerbations (AAEs), in addition to chronic airway inflammation, which has a huge impact on both the affected patients and their parents. The main objective of this study was to explore [...] Read more.
Background: Asthma is a chronic inflammatory condition characterized by episodes of acute asthma exacerbations (AAEs), in addition to chronic airway inflammation, which has a huge impact on both the affected patients and their parents. The main objective of this study was to explore the utility of available white-blood-cell-derived inflammatory markers in diagnosing AAEs and identifying children at risk for severe exacerbations requiring admission to the pediatric intensive care unit (PICU). Methods: This study was a retrospective cohort study. The medical records of 128 children diagnosed with asthma exacerbation and 131 children with stable asthma between the ages of 2 and 12 years were reviewed. Results: A total of 259 participants were enrolled. Children with AAE demonstrated significantly higher white blood cell counts (WBC: 10.0 ± 4.2 × 103/μL vs. 7.1 ± 2.2 × 103/μL, p < 0.001), absolute neutrophil counts (ANC: 7398.5 ± 4600 cells/μL vs. 2634.8 ± 1448 cells/μL, p < 0.001), and neutrophil-to-lymphocyte ratios (NLR: 7.0 ± 6.8 vs. 0.9 ± 0.7, p < 0.001) but significantly lower absolute lymphocyte counts (ALC: 1794.1 ± 1536 × 103/μL vs. 3552.9 ± 1509 × 103/μL, p < 0.001). Interestingly, blood eosinophil count displayed an opposite trend: children with stable asthma had significantly more eosinophils compared to those experiencing an exacerbation (370.1 ± 342.7 cells/mm3 vs. 0.9 ± 1.9 cells/mm3, p < 0.001). Two criteria that are indicative of AAE were identified: NLR values greater than 1.2, with good discriminative ability (area under the curve [AUC] 0.90; 95% confidence interval [CI] 0.85–0.94; sensitivity 82.5%; specificity 79.5%), and ANC values exceeding 3866, with moderate discriminative ability (AUC 0.86; 95% CI 0.81–0.91; sensitivity 75.0%; specificity 82.3%). Moreover, a comparative analysis of these markers (NLR, ANC, PLR, WBC, AEC, and ALC) in patients with AAE did not demonstrate significant differences between those requiring PICU admission and those who did not require it. Conclusions: This study contributes two major findings. The first is that NLR, ANC, WBC, and PLR are significantly higher in AAE patients compared to those with stable asthma. The second is that children with stable asthma have higher AEC and ALC levels compared to those with AAE. Furthermore, this study has revealed that the studied markers (NLR, ANC, PLR, WBC, AEC, and ALC) did not differentiate between AAE patients requiring PICU admission and those managed in the general ward, suggesting a need for alternative predictive factors. Full article
(This article belongs to the Special Issue Diagnostics in the Emergency and Critical Care Medicine)
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14 pages, 962 KiB  
Article
Clinical Impact of the BIOFIRE Blood Culture Identification 2 Panel in Adult Patients with Bloodstream Infection: A Multicentre Observational Study in the United Arab Emirates
by Abiola Senok, Laila Al Dabal, Mubarak Alfaresi, Maya Habous, Handan Celiloglu, Safia Bashiri, Naama Almaazmi, Hassan Ahmed, Ayman A. Mohmed, Omar Bahaaldin, Maimona Ahmed Elsiddig Elimam, Irfan Hussain Rizvi, Victory Olowoyeye, Michaela Powell and Basel Salama
Diagnostics 2023, 13(14), 2433; https://doi.org/10.3390/diagnostics13142433 - 21 Jul 2023
Cited by 4 | Viewed by 14872
Abstract
Rapid pathogen identification is key to the proper management of patients with bloodstream infections (BSIs), especially in the intensive care setting. This multicentre study compared the time to pathogen identification results in 185 patients admitted to intensive care with a confirmed BSI, using [...] Read more.
Rapid pathogen identification is key to the proper management of patients with bloodstream infections (BSIs), especially in the intensive care setting. This multicentre study compared the time to pathogen identification results in 185 patients admitted to intensive care with a confirmed BSI, using conventional methods (n = 99 patients) and upon implementation of the BIOFIRE® Blood Culture Identification 2 (BCID2) Panel, a rapid molecular test allowing for the simultaneous identification of 43 BSI-related nucleic acids targets (n = 86 patients). The median time to result informing optimal antibiotic therapy was significantly shorter following the implementation of the BCID2 Panel (92 vs. 28 h pre vs. post BCID2 implementation; p < 0.0001). BCID2 usage in addition to conventional methods led to the identification of at least one pathogen in 98.8% patients vs. 87.9% using conventional methods alone (p = 0.003) and was associated with a lower 30-day mortality (17.3% vs. 31.6%, respectively; p = 0.019). This study at three intensive care units in the United Arab Emirates therefore demonstrates that, in addition to conventional microbiological methods and an effective antimicrobial stewardship program, the BCID2 Panel could improve the clinical outcome of patients admitted to the intensive care unit with a confirmed BSI. Full article
(This article belongs to the Special Issue Diagnostics in the Emergency and Critical Care Medicine)
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