Machine Learning for 1-Year Graft Failure Prediction in Lung Transplant Recipients: The Korean Organ Transplantation Registry.

Background: In regions with limited donor availability, optimizing efficiency in lung transplant decision-making is crucial. Preoperative prediction of 1-year graft failure can enhance candidate selection and clinical decision-making.

Methods: We utilized data from the Korean Organ Transplantation Registry to develop and validate a deep learning-based model for predicting 1-year graft failure after lung transplantation.

Electrical impedance tomography-based evaluation of regional lung ventilation according to ventilation strategy during cardiopulmonary bypass in minimally invasive cardiac surgery: a prospective randomized controlled trial.

Background: Despite the potential benefits of minimally invasive cardiac surgery (MICS), cardiopulmonary bypass (CPB) during MICS can cause pulmonary complications. However, the optimal ventilation strategy for the left lung under CPB during MICS remains unclear. Thus, this study aimed to evaluate differences in postoperative pulmonary ventilation and complications according to ventilation strategy during MICS.

Role of the QuantiFERON-Monitor in Assessing the Immune Status of Patients with Acute Respiratory Failure in Adult Intensive Care Units: A Prospective, Observational Study.

Background: The utility of the QuantiFERON-Monitor (QFM, Qiagen), a tool developed to assess general immune function, remains insufficiently explored in critically ill patients with acute respiratory failure (ARF). Therefore, we used the QFM to evaluate the immune function of patients with ARF at intensive care unit (ICU) admission and monitored QFM changes based on disease severity and clinical outcome correlations.

Methods: We evaluated the immune function of 99 patients with ARF in an ICU setting.

Machine Learning for 1-Year Mortality Prediction in Lung Transplant Recipients: ISHLT Registry.

Optimizing lung transplant candidate selection is crucial for maximizing resource efficiency and improving patient outcomes. Using data from the International Society for Heart and Lung Transplantation (ISHLT) registry (29,364 patients), we developed a deep learning model to predict 1-year survival after lung transplantation. Initially, 25 pretransplant factors were identified, and their importance was assessed using SHapley Additive exPlanations values.

Association of Fc gamma-binding protein rs1464897604 polymorphism with bronchiolitis obliterans syndrome in lung transplant recipients.

Background: Bronchiolitis obliterans syndrome (BOS) is a major challenge after lung transplantation (LT) and hematopoietic stem cell transplantation (HSCT), sharing pathological similarities but lacking identified common genetic mutations.

Methods: We conducted a comparative analysis of whole-genome sequencing data from lung tissue samples of patients with BOS after LT and HSCT to identify shared and distinct genetic alterations. Common variants were validated using Sanger sequencing of peripheral blood samples.

Association of Extended Steroid Treatment With Bloodstream Infection in Critically Ill Patients With COVID-19: A National, Multicenter, Propensity Score-Matched Study.

Background: The impact of steroid treatment on mortality outcomes in patients with coronavirus disease 2019 (COVID-19) has been widely demonstrated, while its effect on secondary infections, such as bloodstream infections (BSIs), is controversial. Recent studies have reported the survival benefits of using steroids for a standard duration compared to extended use, though their impact on the risk of BSIs remains debated. This study investigated whether extended steroid use is associated with the risk of BSIs and mortality in critically ill patients with COVID-19.

Predicting Healthcare-Associated Infection in Patients with Pneumonia via QuantiFERON-Monitoring.

Objective: A functional immune system is essential for recovery from pneumonia; hence, measuring and monitoring immune-status indicators is clinically important. This study aimed to determine whether QuantiFERON monitoring (QMF) could predict healthcare-associated infection (HCAI) according to the immune-status of patients with pneumonia.

Methods: Prospective, observational, single-center study, patients ≥19 years hospitalized for pneumonia between October 2020 and November 2021.

Development of a Machine Learning-Powered Optimized Lung Allocation System for Maximum Benefits in Lung Transplantation: A Korean National Data.

Background: An ideal lung allocation system should reduce waiting list deaths, improve transplant survival, and ensure equitable organ allocation. This study aimed to develop a novel lung allocation score (LAS) system, the MaxBenefit LAS, to maximize transplant benefits.

Methods: This study retrospectively analyzed data from the Korean Network for Organ Sharing database, including 1,599 lung transplant candidates between September 2009 and December 2020.

Relationship between the Geriatric Nutrition Risk Index and the Prognosis of Severe Coronavirus Disease 2019 in Korea.

Background: Malnutrition exacerbates the prognosis of numerous diseases; however, its specific impact on severe coronavirus disease 2019 (COVID-19) outcomes remains insufficiently explored.

Methods: This multicenter study in Korea evaluated the nutritional status of 1,088 adults with severe COVID-19 using the Geriatric Nutritional Risk Index (GNRI) based on serum albumin levels and body weight. The patients were categorized into two groups: GNRI >98 (no-risk) and GNRI ≤98 (risk).

Correction: Biofilm microbiome in extracorporeal membrane oxygenator catheters.

[This corrects the article DOI: 10.1371/journal.pone.

Integrative Genomic and Transcriptomic Analysis in Acute Interstitial Pneumonia.

Acute Interstitial Pneumonia (AIP) represents a severe form of diffuse lung injury within the idiopathic interstitial pneumonia spectrum. Given the limited understanding of its molecular basis, this study aims to elucidate AIP's genomic and transcriptomic profiles to uncover its pathophysiological underpinnings and identify potential therapeutic targets. We conducted a comprehensive analysis of genomic and transcriptomic data from lung tissues of 15 AIP patients.

Treatment outcomes and healthcare resource utilization in critically ill COVID-19 patients in Korea: A nationwide multicenter cohort study.

COVID-19 pandemic was accompanied by many healthcare-related issues. Concrete national data regarding the care performance of critical ill cases of COVID-19 does not exist in Korea. The current study aimed to describe the treatment outcome and healthcare resource utilization of critically ill COVID-19 patients.

Navigating the Modern Landscape of Sepsis: Advances in Diagnosis and Treatment.

Sepsis poses a significant threat to human health due to its high morbidity and mortality rates worldwide. Traditional diagnostic methods for identifying sepsis or its causative organisms are time-consuming and contribute to a high mortality rate. Biomarkers have been developed to overcome these limitations and are currently used for sepsis diagnosis, prognosis prediction, and treatment response assessment.

Clinical characteristics and prognosis of patients with COVID-19 on mechanical ventilation undergoing continuous renal replacement therapy.

Background: The coronavirus disease (COVID-19) pandemic has significantly strained global healthcare, particularly in the management of patients requiring mechanical ventilation (MV) and continuous renal replacement therapy (CRRT). This study investigated the characteristics and prognoses of these patients.

Methods: This multicenter retrospective cohort study gathered data from patients with COVID-19 across 26 medical centers.