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Diagnosis and Treatment of Pneumonia in the Intensive Care Unit
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Diagnosis and Treatment of Pneumonia in the Intensive Care Unit

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Intensive Care".

Deadline for manuscript submissions: closed (20 August 2024) | Viewed by 6370

Special Issue Editor

Dr. Kristian Christos Ngamsri

E-Mail Website
Guest Editor
Department of Anesthesiology and Intensive Care Medicine, University Hospital of Tübingen, Hoppe-Seyler-Straße 3, 72076 Tübingen, Germany
Interests: acute lung injury; intensive care medicine; cardiac anesthesia; echocardiography; antibiotics

Special Issue Information

Dear Colleagues,

Pneumonia acquired in intensive care units (ICUs), especially ventilator-associated pneumonia (VAP), is a life-threatening infection in critically ill patients. The estimated incidence varies by definition, population and screening methods. Various studies have advanced our understanding of the pathogenesis, risk factors, prognosis and health costs of this disease, but questions relating the diagnosis and treatment remain unanswered. However, continuous research and the fast development of technologies in intensive medicine leave physicians with the need to summarize and collect the newest information on epidemiology, diagnostics, monitoring and therapeutic strategies in ICU-associated pneumonia and VAP.

This Special Issue aims to highlight novelties in the diagnosis and treatment of ICU-associated pneumonia and VAP, including all the research to help clinicians improve the pneumonia-associated outcomes in critically ill patients.

Dr. Kristian Christos Ngamsri
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 Clinical Medicine 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

  • pneumonia
  • ICU-associated pneumonia
  • ventilator-associated pneumonia
  • mechanical ventilation
  • intensive care medicine
  • intensive care unit
  • critical care

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

Published Papers (3 papers)

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Research

14 pages, 3801 KiB  
Article
Lactate to Albumin Ratio and Mortality in Patients with Severe Coronavirus Disease-2019 Admitted to an Intensive Care Unit
by Stelios Kokkoris, Aikaterini Gkoufa, Dimitrios E. Katsaros, Stavros Karageorgiou, Fotios Kavallieratos, Dimitrios Tsilivarakis, Georgia Dimopoulou, Evangelia Theodorou, Eleftheria Mizi, Anastasia Kotanidou, Ioanna Dimopoulou and Christina Routsi
J. Clin. Med. 2024, 13(23), 7106; https://doi.org/10.3390/jcm13237106 - 24 Nov 2024
Viewed by 1168
Abstract
Aim: This study sought to evaluate the effectiveness of lactate/albumin ratio for ICU mortality prediction in a large cohort of patients with severe Coronavirus Disease-2019 (COVID-19) admitted to an intensive care unit (ICU). Methods: This is a single-center retrospective cohort study of prospectively [...] Read more.
Aim: This study sought to evaluate the effectiveness of lactate/albumin ratio for ICU mortality prediction in a large cohort of patients with severe Coronavirus Disease-2019 (COVID-19) admitted to an intensive care unit (ICU). Methods: This is a single-center retrospective cohort study of prospectively collected data derived from the COVID-19 dataset for all critically ill patients admitted to an academic ICU. Data were used to determine the relation between lactate/albumin ratio and other laboratory parameters measured on the first day of the ICU stay and to evaluate the prognostic performance for ICU mortality prediction. Results: A total of 805 ICU patients were included, and the median age (IQR) was 67 (57–76) years, with 68% being male. ICU mortality was 48%, and the median lactate/albumin ratio was 0.53 (0.39–0.59). A survival analysis showed that patients with higher lactate/albumin ratio values had significantly lower survival rates (Log Rank p < 0.001). A multivariable analysis revealed that the lactate/albumin ratio was an independent risk factor for ICU mortality with a hazard ratio of 1.39 (CI: 1.27–1.52). The lactate/albumin ratio showed a receiver operating characteristics area under the curve (ROC-AUC) value to predict ICU mortality significantly higher than that of lactate alone (0.71 vs. 0.68, DeLong test p < 0.001). The optimal lactate/albumin ratio cut-off for predicting ICU mortality was 0.57, with 63% sensitivity and 73% specificity. A subgroup analysis revealed that the lactate/albumin ratio was significantly associated with mortality across different patient groups, including age and sex categories, and those with or without hypertension and coronary heart disease. Conclusions: Lactate/albumin ratio is a reliable prognostic marker in critically ill COVID-19 patients and could predict ICU mortality more accurately than lactate alone. Full article
(This article belongs to the Special Issue Diagnosis and Treatment of Pneumonia in the Intensive Care Unit)
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23 pages, 2454 KiB  
Article
Predicting ICU Readmission from Electronic Health Records via BERTopic with Long Short Term Memory Network Approach
by Chih-Chou Chiu, Chung-Min Wu, Te-Nien Chien, Ling-Jing Kao and Chengcheng Li
J. Clin. Med. 2024, 13(18), 5503; https://doi.org/10.3390/jcm13185503 - 18 Sep 2024
Cited by 4 | Viewed by 3280
Abstract
Background: The increasing rate of intensive care unit (ICU) readmissions poses significant challenges in healthcare, impacting both costs and patient outcomes. Predicting patient readmission after discharge is crucial for improving medical quality and reducing expenses. Traditional analyses of electronic health record (EHR) data [...] Read more.
Background: The increasing rate of intensive care unit (ICU) readmissions poses significant challenges in healthcare, impacting both costs and patient outcomes. Predicting patient readmission after discharge is crucial for improving medical quality and reducing expenses. Traditional analyses of electronic health record (EHR) data have primarily focused on numerical data, often neglecting valuable text data. Methods: This study employs a hybrid model combining BERTopic and Long Short-Term Memory (LSTM) networks to predict ICU readmissions. Leveraging the MIMIC-III database, we utilize both quantitative and text data to enhance predictive capabilities. Our approach integrates the strengths of unsupervised topic modeling with supervised deep learning, extracting potential topics from patient records and transforming discharge summaries into topic vectors for more interpretable and personalized predictions. Results: Utilizing a comprehensive dataset of 36,232 ICU patient records, our model achieved an AUROC score of 0.80, thereby surpassing the performance of traditional machine learning models. The implementation of BERTopic facilitated effective utilization of unstructured data, generating themes that effectively guide the selection of relevant predictive factors for patient readmission prognosis. This significantly enhanced the model’s interpretative accuracy and predictive capability. Additionally, the integration of importance ranking methods into our machine learning framework allowed for an in-depth analysis of the significance of various variables. This approach provided crucial insights into how different input variables interact and impact predictions of patient readmission across various clinical contexts. Conclusions: The practical application of BERTopic technology in our hybrid model contributes to more efficient patient management and serves as a valuable tool for developing tailored treatment strategies and resource optimization. This study highlights the significance of integrating unstructured text data with traditional quantitative data to develop more accurate and interpretable predictive models in healthcare, emphasizing the importance of individualized care and cost-effective healthcare paradigms. Full article
(This article belongs to the Special Issue Diagnosis and Treatment of Pneumonia in the Intensive Care Unit)
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11 pages, 930 KiB  
Article
Radiologic Evaluation of Oral Health Status in Patients Admitted to the Intensive Care Unit: A Multi-Institutional Retrospective Study
by Yesel Kim
J. Clin. Med. 2024, 13(13), 3913; https://doi.org/10.3390/jcm13133913 - 3 Jul 2024
Viewed by 1469
Abstract
Introduction: Surveys distributed among intensive care unit (ICU) nurses reveal a significant need for dental care, with many acknowledging poor oral hygiene management. Poor oral health in ICU patients is linked to systemic problems, including aspiration pneumonia, necessitating pre-intervention assessments for bacterial diseases [...] Read more.
Introduction: Surveys distributed among intensive care unit (ICU) nurses reveal a significant need for dental care, with many acknowledging poor oral hygiene management. Poor oral health in ICU patients is linked to systemic problems, including aspiration pneumonia, necessitating pre-intervention assessments for bacterial diseases and dental risks. This study aims to evaluate the oral health status of ICU patients across three institutions through retrospective analysis. Methods: This retrospective study assessed the oral health status of ICU patients, using computed tomography (CT) images from three institutions over ten years. Through CT images, the oral status was evaluated in terms of total and lost tooth count and the presence of oral lesions (periapical lesions, cysts and tumors, caries, tartar, moderate to severe periodontal bone loss, tooth fractures). Variables included gender, age, the duration of ICU stay, and types of ICU. Statistical analysis was performed using chi-square tests, independent-sample t-tests, and logistic regression analysis. Results: Of the 450 participants, 430 were analyzed, revealing a prevalence of oral lesions in 67.0% of subjects. The prevalence of oral lesions was higher in males (71.5%) than females (57.7%, p = 0.006), and higher in those aged 40 and above (72.1%) compared to those under the age of 40 (47.8%, p < 0.001). This study found significant differences in oral health status based on gender, age, and ICU type, with surgical ICU patients generally having better oral health. Risk factors for oral lesions included gender, age, and duration of ICU stay. Conclusions: Most ICU patients have at least one oral lesion, regardless of the reason for their ICU admission. In particular, male ICU patients aged 40 and above have a higher prevalence of oral lesions, necessitating careful oral health assessment and treatment. Full article
(This article belongs to the Special Issue Diagnosis and Treatment of Pneumonia in the Intensive Care Unit)
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