BACKGROUND: The risk of bleeding during extracorporeal membrane oxygenation (ECMO) is a potential deterrent in performing tracheostomy at many centers. To evaluate the safety of surgical tracheostomy (ST) in critically ill patients supported by ECMO, we reviewed the clinical correlation between preoperative coagulation status and bleeding complication-related ST during ECMO. METHODS: From April 1, 2012 to March 31, 2016, ST was performed on 38 patients supported by ECMO. We retrospectively reviewed and analyzed the medical records including complications related to ST. RESULTS: Heparin was administered to 23 patients (60.5%) for anticoagulation during ECMO, but 15 patients (39.5%) underwent ECMO without anticoagulation. Of the 23 patients administered anticoagulation therapy, heparin infusion was briefly paused in 13 prior to ST. The median platelet count, international normalized ratio, and activated partial thromboplastin time before ST were 126 ×109/L (range, 46 to 434 ×109/L), 1.2 (range, 1 to 2.3) and 62 seconds (27 to 114.2 seconds), respectively. No peri-procedural clotting complications related to ECMO were observed. Two patients (5.3%) suffering from ST-related major bleeding required surgical hemostasis. Minor bleeding after ST occurred in two cases (5.3%). No significant difference was found according to anticoagulation management (P = 0.723). No fatality was attributable to ST. CONCLUSIONS: The complication rates of ST in the patients supported by ECMO were low. Therefore, ST performed by an experienced operator, and with careful optimization of coagulation status, is a relatively safe procedure; the use of ST with ECMO should thus not be dismissed on account of the potential for bleeding caused by the administration of anticoagulants.
Anticoagulants ; Critical Illness ; Extracorporeal Membrane Oxygenation* ; Hemorrhage ; Hemostasis, Surgical ; Heparin ; Humans ; International Normalized Ratio ; Medical Records ; Partial Thromboplastin Time ; Platelet Count ; Retrospective Studies ; Tracheostomy*

BACKGROUND: Extracorporeal membrane oxygenation (ECMO) has been successfully used as a method for the interhospital transportation of critically ill patients. In South Korea, a well-established ECMO interhospital transport system is lacking due to limited resources. We developed a simplified ECMO transport system without mechanical ventilation for use by public emergency medical services. METHODS: Eighteen patients utilized our ECMO transport system from December 2011 to September 2015. We retrospectively analyzed the indications for ECMO, the patient status during transport, and the patient outcomes. RESULTS: All transport was conducted on the ground by ambulance. The distances covered ranged from 26 to 408 km (mean, 65.9±88.1 km) and the average transport time was 56.1±57.3 minutes (range, 30 to 280 minutes). All patients were transported without adverse events. After transport, 4 patients (22.2%) underwent lung transplantation because of interstitial lung disease. Eight patients who had severe acute respiratory distress syndrome showed recovery of heart and lung function after ECMO therapy. A total of 13 patients (70.6%) were successfully taken off ECMO, and 11 patients (61.1%) survived. CONCLUSION: Our ECMO transport system without mechanical ventilation can be considered a safe and useful method for interhospital transport and could be a good alternative option for ECMO transport in Korean hospitals with limited resources.
Ambulances ; Critical Illness* ; Emergency Medical Services ; Extracorporeal Membrane Oxygenation* ; Heart ; Humans ; Korea ; Lung ; Lung Diseases, Interstitial ; Lung Transplantation ; Methods ; Patient Transfer ; Respiration, Artificial ; Respiratory Distress Syndrome, Adult ; Retrospective Studies ; Transportation ; Ventilators, Mechanical*

BACKGROUND: Extracorporeal membrane oxygenation (ECMO) strategy is proposed to reduce the ventilator-induced lung injury in acute respiratory distress syndrome (ARDS). As ECMO use has increased, a number of studies on prognostic factors have been published. Age is estimated to be an important prognostic factor. However, clinical evidences about ECMO use in elderly patients are limited. Therefore, we investigated clinical courses and outcomes of ECMO in elderly patients with ARDS. METHODS: We reviewed medical records of patients with severe ARDS who required ECMO support. Study patients were classified into an elderly group (> or = 65 years) and a non-elderly group (< 65 years). Baseline characteristics, ECMO related outcomes and associated factors were retrospectively analyzed according to group. RESULTS: From February 2011 to June 2013, a total of 31 patients with severe ARDS were treated with ECMO. Overall, 14 (45.2%) were weaned from ECMO, 9 (29.0%) survived to the general ward and 7 (22.6%) survived to discharge. Among the 18 elderly group patients, 7 (38.9%) were weaned from ECMO, 4 (22.2%) were survived to the general ward and 2 (11.1%) were survived to discharge. Overall intensive care unit survival was inversely correlated with concomitant acute kidney injury or septic shock. CONCLUSIONS: In this study, ECMO outcome was poor in severe ARDS patients aged over 65 years. Therefore, the routine use of ECMO in elderly patients with severe ARDS is not warranted except in highly selective cases.
Acute Kidney Injury ; Aged* ; Extracorporeal Membrane Oxygenation ; Humans ; Intensive Care Units ; Medical Records ; Patients' Rooms ; Respiratory Distress Syndrome, Adult* ; Retrospective Studies ; Shock, Septic ; Ventilator-Induced Lung Injury

PURPOSE: The purpose of this study was to demonstrate effects of a critical pathway (CP) for stroke patients seen in emergency rooms (ER). METHODS: The CP developed by the CP committee consisted of 8 criteria: behavior of doctors and nurses, laboratory tests, Image testing, medication, treatment, activity, and nutrition. According to application of CP, a control group (n=17) and experimental group (n=17) were defined. Time was checked by the electronic medical records. RESULTS: Use of CP for stroke patients in the ER, resulted in a decreased length of stay in ER (t=2.341, p=.026), and time required for image testing (t=2.623, p=.021), and an increased number of patients using rtPA (chi2=4.802, p=.049). Time required for neurology doctor contact, for neurology doctor to see patient in the ER, and for report of blood tests decreased, but there were no statistical significance. CONCLUSION: Quick responses are most important in the ER, so CP for these patients is a very effective patient management tool. To reduce delay in stroke diagnosis, continuous education programs for similar symptoms are necessary. CPs for other patients in the ER should be developed, and studies on cost and satisfaction, as well as length of stay, should be done.
Critical Pathways ; Electronics ; Electrons ; Emergencies ; Hematologic Tests ; Humans ; Length of Stay ; Neurology ; Stroke

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. We developed the MaxBenefit LAS, combining a waitlist mortality model and a post-transplant survival model using elastic-net Cox regression, was assessed using area under the curve (AUC) values and Uno’s C-index. Its performance was compared to the US LAS in an independent cohort. Results: The waitlist mortality model showed strong predictive performance with AUC values of 0.834 and 0.818 in the training and validation cohorts, respectively. The post-transplant survival model also demonstrated good predictive ability (AUC: 0.708 and 0.685). The MaxBenefit LAS effectively stratified patients by risk, with higher scores correlating with increased waitlist mortality and decreased post-transplant mortality. The MaxBenefit LAS outperformed the conventional LAS in predicting waitlist death and identifying candidates with higher transplant benefits. Conclusion The MaxBenefit LAS offers a promising approach to optimizing lung allocation by balancing the urgency of candidates with their likelihood of survival post-transplant. This novel system has the potential to improve outcomes for lung transplant recipients and reduce waitlist mortality, providing a more equitable allocation of donor lungs.

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. We developed the MaxBenefit LAS, combining a waitlist mortality model and a post-transplant survival model using elastic-net Cox regression, was assessed using area under the curve (AUC) values and Uno’s C-index. Its performance was compared to the US LAS in an independent cohort. Results: The waitlist mortality model showed strong predictive performance with AUC values of 0.834 and 0.818 in the training and validation cohorts, respectively. The post-transplant survival model also demonstrated good predictive ability (AUC: 0.708 and 0.685). The MaxBenefit LAS effectively stratified patients by risk, with higher scores correlating with increased waitlist mortality and decreased post-transplant mortality. The MaxBenefit LAS outperformed the conventional LAS in predicting waitlist death and identifying candidates with higher transplant benefits. Conclusion The MaxBenefit LAS offers a promising approach to optimizing lung allocation by balancing the urgency of candidates with their likelihood of survival post-transplant. This novel system has the potential to improve outcomes for lung transplant recipients and reduce waitlist mortality, providing a more equitable allocation of donor lungs.

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. We developed the MaxBenefit LAS, combining a waitlist mortality model and a post-transplant survival model using elastic-net Cox regression, was assessed using area under the curve (AUC) values and Uno’s C-index. Its performance was compared to the US LAS in an independent cohort. Results: The waitlist mortality model showed strong predictive performance with AUC values of 0.834 and 0.818 in the training and validation cohorts, respectively. The post-transplant survival model also demonstrated good predictive ability (AUC: 0.708 and 0.685). The MaxBenefit LAS effectively stratified patients by risk, with higher scores correlating with increased waitlist mortality and decreased post-transplant mortality. The MaxBenefit LAS outperformed the conventional LAS in predicting waitlist death and identifying candidates with higher transplant benefits. Conclusion The MaxBenefit LAS offers a promising approach to optimizing lung allocation by balancing the urgency of candidates with their likelihood of survival post-transplant. This novel system has the potential to improve outcomes for lung transplant recipients and reduce waitlist mortality, providing a more equitable allocation of donor lungs.

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. We developed the MaxBenefit LAS, combining a waitlist mortality model and a post-transplant survival model using elastic-net Cox regression, was assessed using area under the curve (AUC) values and Uno’s C-index. Its performance was compared to the US LAS in an independent cohort. Results: The waitlist mortality model showed strong predictive performance with AUC values of 0.834 and 0.818 in the training and validation cohorts, respectively. The post-transplant survival model also demonstrated good predictive ability (AUC: 0.708 and 0.685). The MaxBenefit LAS effectively stratified patients by risk, with higher scores correlating with increased waitlist mortality and decreased post-transplant mortality. The MaxBenefit LAS outperformed the conventional LAS in predicting waitlist death and identifying candidates with higher transplant benefits. Conclusion The MaxBenefit LAS offers a promising approach to optimizing lung allocation by balancing the urgency of candidates with their likelihood of survival post-transplant. This novel system has the potential to improve outcomes for lung transplant recipients and reduce waitlist mortality, providing a more equitable allocation of donor lungs.

Despite the increasing demand for lung transplants, donor lungs remain in short supply. Although organ donations have been steadily increasing in Korea, with the utilization rate for donor lungs increasing to 40% in recent years, many potential donor organs remain unused. To match the increasing number of patients on the lung transplant waitlist, it is essential to increase the donor procurement rate through optimal management. Improvements in donor lung management programs can lead to expansion of the donor pool and optimal posttransplant outcomes. This review focuses on basic protocols for the optimal management of donor lungs and summarizes coronavirus disease 2019-related considerations for donor lung evaluation.

Periodontal ligament(PDL) cells and human gingival fibroblasts(HGFs) play important roles in development, regeneration, normal function, and pathologic alteration. PDL cells and HGFs have the similarity related with general characteristics of fibroblast such as spindle shaped morphology, the presence of vimentin intermediate filament and the synthesis of interstitial collagens and fibronectin. There were many studies about the differences between PDL cells and HGFs, but they were not about whole gene level. In this study, we tried to explain the differences of gene expression profiles between PDL cells and HGFs, and the differences among three individuals by screening gene expression patterns of PDL cells and HGFs, using cDNA microarray. Although there were some variants among three experiments, a set of genes were consistentely and differentially expressed in one cell type. Among 3,063 genes, 49 genes were more highly expressed in PDL cells and 12 genes were more highly expressed in HGFs. The genes related with cell structure and motility were expressed more highly in PDL cells. These are cofilin 1, proteoglycan 1 secretory granule, collagen type I(alpha1), adducin gamma subunit, collagen type III(alpha1), fibronectin, lumican(keratan sulfate proteoglycan), and alpha-smooth muscle actin. Tissue inhibitor of metalloproteinase known as the enzyme controlling extracellular matrix with matrix metalloproteinase is more highly expressed in PDL cells, osteoprotegerin known as osteoclastogenesis inhibitory factor is more highly expressed in HGFs. We performed northern blot to verify cDNA microarray results on selected genes such as tissue inhibitor of metalloproteinase, fibronectin, osteoprogeterin. The result of northern blot analysis showed that each cell expressed the genes in similar pattern with cDNA microarray result. This result indicates that cDNA microarray is a reliable method in screening of gene expression profiles.
Actins ; Blotting, Northern ; Cofilin 1 ; Collagen ; Extracellular Matrix ; Fibroblasts* ; Fibronectins ; Gene Expression ; Humans* ; Intermediate Filaments ; Mass Screening* ; Oligonucleotide Array Sequence Analysis ; Osteoprotegerin ; Periodontal Ligament* ; Proteoglycans ; Regeneration ; Secretory Vesicles ; Transcriptome ; Vimentin