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Background: The recent use of artificial intelligence (AI) in medical research is noteworthy. However, most research has focused on medical imaging. Although the importance of laboratory tests in the clinical field is acknowledged by clinicians, they are undervalued in medical AI research. Our study aims to develop an early prediction AI model for pneumonia mortality, primarily using laboratory test results. Materials and methods: We developed a mortality prediction model using initial laboratory results and basic clinical information of patients with pneumonia. Several machine learning (ML) models and a deep learning method-multilayer perceptron (MLP)-were selected for model development. The area under the receiver operating characteristic curve (AUROC) and F1-score were optimized to improve model performance. In addition, an ensemble model was developed by blending several models to improve the prediction performance. We used 80,940 data instances for model development. Results: Among the ML models, XGBoost exhibited the best performance (AUROC = 0.8989, accuracy = 0.88, F1-score = 0.80). MLP achieved an AUROC of 0.8498, accuracy of 0.86, and F1-score of 0.75. The performance of the ensemble model was the best among the developed models, with an AUROC of 0.9006, accuracy of 0.90, and F1-score of 0.81. Several laboratory tests were conducted to identify risk factors that affect pneumonia mortality using the "Feature importance" technique and SHapley Additive exPlanations. We identified several laboratory results, including systolic blood pressure, serum glucose level, age, aspartate aminotransferase-to-alanine aminotransferase ratio, and monocyte-to-lymphocyte ratio, as significant predictors of mortality in patients with pneumonia. Conclusions: Our study demonstrates that the ensemble model, incorporating XGBoost, CatBoost, and LGBM techniques, outperforms individual ML and deep learning models in predicting pneumonia mortality. Our findings emphasize the importance of integrating AI techniques to leverage laboratory test data effectively, offering a promising direction for advancing AI applications in medical research and clinical decision-making.
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BACKGROUND: The decision to discontinue intensive care unit (ICU) treatment during the end-oflife stage has recently become a significant concern in Korea, with an observed increase in life-sustaining treatment (LST) withdrawal. There is a growing demand for evidence-based support for patients, families, and clinicians in making LST decisions. This study aimed to identify factors influencing LST decisions in ICU inpatients and to analyze their impact on healthcare utilization. METHODS: We retrospectively reviewed medical records of ICU patients with neurological disorders, infectious disorders, or cancer who were treated at a single university hospital between January 1, 2019 and July 7, 2021. Factors influencing the decision to withdraw LST were compared between those who withdrew LST and those who did not. RESULTS: Among 54,699 hospital admissions, LST was withdrawn in 550 cases (1%). Cancer was the most common diagnosis, followed by pneumonia and cerebral infarction. Among ICU inpatients, LST was withdrawn from 215 (withdrawal group). The withdrawal group was older (78 vs. 75 years, P=0.002), had longer total hospital stays (16 vs. 11 days, P<0.001), and higher ICU readmission rates than the control group. There were no significant differences in the healthcare costs of ICU stay between the two groups. Most LST decisions (86%) were made by family. CONCLUSIONS: The decisions to withdraw LST of ICU inpatients were influenced by age, readmission, and disease category. ICU costs were similar between the withdrawal and control groups. Further research is needed to tailor LST decisions in the ICU.
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BACKGROUND: This study aimed to understand the health-related quality of life (HRQoL) of patients with aneurysmal subarachnoid hemorrhage (aSAH) classified as having "good outcomes" and determine associated sociodemographic, psychological, and clinical factors. METHODS: Participants were 86 patients with aSAH with modified Rankin Scale (mRS) scores of 0-2 in our hospital between February 2003 and April 2014. Participants completed self-report questionnaires examining sociodemographic characteristics and the following self-rating scales: the hospital anxiety and depression scale, Pittsburgh sleep quality index, and EuroQoL-5 Dimension Index (EQ-5D). Further, we retrospectively reviewed clinical data from medical records and radiologic images. Average EQ-5D scores for each variable were compared using Student's t-test and analysis of variance. Correlations between EQ-5D and continuous variables were examined using Pearson correlation analysis. Factors associated with EQ-5D were then examined using univariate and stepwise multivariate analyses through simple and multiple regression. RESULTS: The mean age of the 86 participants was 56.87 ± 10.28 years (range: 29-79 years), while the mean EQ-5D value was 0.738 ± 0.169. There were 54 women (62.8 %) and 33 men (37.2 %). The participants had depressive symptoms (30.2 %), anxiety (10.5 %), and sleep problems (51.2 %). Regarding sociodemographic variables, educational level (p = 0.017) and monthly income (p = 0.037) were positively correlated with HRQoL. Depressive symptoms (r = -0.505, p < 0.001), anxiety (r = -0.498, p < 0.001), sleep problems (r = -0.265, p = 017), and mRS (r = -0.352, p = 0.001) were negatively correlated with HRQoL. Depressive symptoms, diabetes mellitus, and past psychiatric history explained 48.8 % of the variance in HRQoL in good outcome aSAH according to stepwise multiple regression analysis. CONCLUSIONS: Patients with good outcome aSAH had low EQ-5D values, which were negatively correlated with depressive symptoms, anxiety, and sleep problems. In addition, HRQoL in good outcome aSAH is associated with depressive symptoms, diabetes mellitus, and past psychiatric disease history. Depressive symptoms, anxiety, and sleep problems are frequent in patients with good outcome aSAH, and mediation of these factors may help improve HRQoL.
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Diabetes Mellitus , Transtornos do Sono-Vigília , Hemorragia Subaracnóidea , Masculino , Humanos , Feminino , Adulto , Pessoa de Meia-Idade , Idoso , Qualidade de Vida/psicologia , Hemorragia Subaracnóidea/complicações , Hemorragia Subaracnóidea/psicologia , Depressão/diagnóstico , Estudos Retrospectivos , Inquéritos e Questionários , Transtornos do Sono-Vigília/etiologia , Nível de SaúdeRESUMO
Gastric mucosa is important to protect the gastric damage against external factors. We previously reported the gastro-protective effects of steamed and freeze-dried mature silkworm larval powder (SMSP) in ethanol-treated rats. However, the factors that promote mucosal formation still remain unclarified. In this study, we evaluated the effect of SMSP on the restoration and maintenance of gastric mucosal layer as well as anti-inflammatory response in ethanol-induced stomach injury in rats. A significant decrease of ulcer indexes, histopathological scores and pro-inflammatory cytokine levels was observed in SMSP-treated group. In addition, SMSP protected the mucosal layer from ethanol-induced gastric damage by increasing the expression of nitric oxide synthases and heat shock proteins, along with promoting genes related gastric mucosal protection and biosynthesis including mucin 5AC and trefoil factors. These results demonstrate that SMSP attenuates the pro-inflammatory responses and strengthens the gastric mucosal layer, thus exhibiting gastro-protective effect against ethanol-induced gastric injury in rats.
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BACKGROUND: An artificial-intelligence (AI) model for predicting the prognosis or mortality of coronavirus disease 2019 (COVID-19) patients will allow efficient allocation of limited medical resources. We developed an early mortality prediction ensemble model for COVID-19 using AI models with initial chest X-ray and electronic health record (EHR) data. RESULTS: We used convolutional neural network (CNN) models (Inception-ResNet-V2 and EfficientNet) for chest X-ray analysis and multilayer perceptron (MLP), Extreme Gradient Boosting (XGBoost), and random forest (RF) models for EHR data analysis. The Gradient-weighted Class Activation Mapping and Shapley Additive Explanations (SHAP) methods were used to determine the effects of these features on COVID-19. We developed an ensemble model (Area under the receiver operating characteristic curve of 0.8698) using a soft voting method with weight differences for CNN, XGBoost, MLP, and RF models. To resolve the data imbalance, we conducted F1-score optimization by adjusting the cutoff values to optimize the model performance (F1 score of 0.77). CONCLUSIONS: Our study is meaningful in that we developed an early mortality prediction model using only the initial chest X-ray and EHR data of COVID-19 patients. Early prediction of the clinical courses of patients is helpful for not only treatment but also bed management. Our results confirmed the performance improvement of the ensemble model achieved by combining AI models. Through the SHAP method, laboratory tests that indicate the factors affecting COVID-19 mortality were discovered, highlighting the importance of these tests in managing COVID-19 patients.
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COVID-19 , Aprendizado Profundo , Humanos , Registros Eletrônicos de Saúde , COVID-19/diagnóstico por imagem , Raios X , Inteligência ArtificialRESUMO
BACKGROUND: Non-Coronavirus disease 2019 (COVID-19) pneumonia and COVID-19 have similar clinical features but last for different periods, and consequently, require different treatment protocols. Therefore, they must be differentially diagnosed. This study uses artificial intelligence (AI) to classify the two forms of pneumonia using mainly laboratory test data. METHODS: Various AI models are applied, including boosting models known for deftly solving classification problems. In addition, important features that affect the classification prediction performance are identified using the feature importance technique and SHapley Additive exPlanations method. Despite the data imbalance, the developed model exhibits robust performance. RESULTS: eXtreme gradient boosting, category boosting, and light gradient boosted machine yield an area under the receiver operating characteristic of 0.99 or more, accuracy of 0.96-0.97, and F1-score of 0.96-0.97. In addition, D-dimer, eosinophil, glucose, aspartate aminotransferase, and basophil, which are rather nonspecific laboratory test results, are demonstrated to be important features in differentiating the two disease groups. CONCLUSIONS: The boosting model, which excels in producing classification models using categorical data, excels in developing classification models using linear numerical data, such as laboratory tests. Finally, the proposed model can be applied in various fields to solve classification problems.
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COVID-19 , Pneumonia , Humanos , COVID-19/diagnóstico , Diagnóstico Diferencial , Inteligência Artificial , Pneumonia/diagnóstico , Aprendizado de Máquina , Teste para COVID-19RESUMO
BACKGROUND: Despite reports that the closed intensive care unit (ICU) system improves clinical outcomes, it has not been widely applied for various reasons. This study aimed to propose a better ICU system for critically ill patients by comparing the experience of open surgical ICU (OSICU) and closed surgical ICU (CSICU) systems in the same institution. METHODS AND FINDINGS: Our institution converted the ICU system from "open" to "closed" in February 2020, and enrolled patients were classified into the OSICU and CSICU groups at that time from March 2019 to February 2022. A total of 751 patients were categorized into the OSICU (n = 191) and CSICU (n = 560) groups. The mean age of the patients was 67 years in the OSICU group and 72 years in the CSICU group (p < 0.05). The acute physiology and chronic health evaluation II score was 21.8 ± 7.65 in the CSICU group, which was higher than the score 17.4 ± 7.97 in the OSICU group (p < 0.05). The sequential organ failure assessment scores were 2.0 ± 2.29 in the OSICU group and 4.1 ± 3.06 in the CSICU group (p < 0.05). After correction for bias by logistic regression analysis for all-cause mortality, the odds ratio in the CSICU group was 0.089 (95% confidence interval [CI]: 0.014-0.568, p < 0.05). CONCLUSIONS: Despite considering the various factors of increased patient severity, a CSICU system is more beneficial for critically ill patients. Therefore, we propose that the CSICU system be applied worldwide.
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Estado Terminal , Unidades de Terapia Intensiva , Humanos , Idoso , Fatores de Risco , Escores de Disfunção Orgânica , Estudos RetrospectivosRESUMO
BACKGROUND: Sepsis and septic shock remain the leading causes of death in critically ill patients worldwide. Various biomarkers are available to determine the prognosis and therapeutic effects of sepsis. In this study, we investigated the effectiveness of presepsin as a sepsis biomarker. METHODS: Patients admitted to the intensive care unit with major or minor diagnosis of sepsis were categorized into survival and non-survival groups. The white blood cell count and serum C-reactive protein, procalcitonin, and presepsin levels were measured in all patients. RESULTS: The study included 40 patients (survival group, 32; non-survival group, 8; mortality rate, 20%). The maximum serum presepsin levels measured during intensive care unit admission were significantly higher in the non-survival group (median [interquartile range]: 4,205.5 pg/ml [1,155.8-10,094.0] vs. 741.5 pg/ml [520.0-1,317.5], P<0.05). No statistically significant intergroup differences were observed in the maximum, minimum, and mean values of the white blood cell count, as well as serum C-reactive protein, and procalcitonin levels. Based on the receiver operating characteristic curve, the area under the curve for presepsin as a predictor of sepsis mortality was 0.764. At a cut-off value of 1,898.5 pg/ml, the sensitivity and specificity of presepsin for prediction of sepsis-induced mortality were 75.0% and 87.5%, respectively. CONCLUSIONS: Early diagnosis of sepsis and prediction of sepsis-induced mortality are important for prompt initiation of treatment. Presepsin may serve as an effective biomarker for prediction of sepsis-induced mortality and for evaluation of treatment effectiveness.
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BACKGROUND: The criteria for brain death determination have not been unified globally, and there is no global consensus on the apnea test, which is essential for determining brain death. Since the apnea test is associated with many complications, we aimed to determine an optimal duration of the apnea test. METHODS: We analyzed the results of the apnea test performed for brain death determination between August 2013 and February 2021 at a single institution in South Korea. Elevations in the partial pressure of carbon dioxide and mean arterial blood pressure fluctuations over time in the apnea test were recorded. RESULTS: In the 1st and 2nd tests, the mean partial pressure of carbon dioxide increased by more than 20 mmHg at 3 min after the apnea test compared to before the test (P < 0.05). At 4 min in the 1st test and 5 min in the 2nd test, the partial pressure of carbon dioxide exceeded 60 mmHg (P < 0.05). The fluctuation in the mean arterial blood pressure observed for 5 min during the apnea test was not significant. There was no significant fluctuation in the mean arterial blood pressure over time in the apnea test between patients with normal chest radiography findings and those with abnormal chest radiography findings (P = 0.888). CONCLUSIONS: Our study proposes that a short-term apnea test protocol is valid for the preservation of organs for donation.
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Apneia , Morte Encefálica , Apneia/diagnóstico , Pressão Arterial , Morte Encefálica/diagnóstico , Dióxido de Carbono , Humanos , Pressão ParcialRESUMO
Influenza infection induces lung epithelial cell injury via programmed cell death. Glutathione, a potent antioxidant, has been reported to be associated with influenza infection. We hypothesized that lung epithelial cell death during influenza infection is regulated by glutathione metabolism. Eight-week-old male and female BALB/c mice were infected with influenza (PR8: A/PR/8/34 [H1N1]) via intranasal instillation. Metabolomic analyses were performed on whole lung lysate after influenza infection. For in vitro analysis, Beas-2B cells were infected with influenza. RNA was extracted, and QuantiTect Primer Assay was used to assess gene expression. Glutathione concentrations were assessed by colorimetric assay. Influenza infection resulted in increased inflammation and epithelial cell injury in our murine model, leading to increased morbidity and mortality. In both our in vivo and in vitro models, influenza infection was found to induce apoptosis and necroptosis. Influenza infection led to decreased glutathione metabolism and reduced glutathione reductase activity in lung epithelial cells. Genetic inhibition of glutathione reductase suppressed apoptosis and necroptosis of lung epithelial cells. Pharmacologic inhibition of glutathione reductase reduced airway inflammation, lung injury, and cell death in our murine influenza model. Our results demonstrate that glutathione reductase activity is suppressed during influenza. Glutathione reductase inhibition prevents epithelial cell death and morbidity in our murine influenza model. Our results suggest that glutathione reductase-dependent glutathione metabolism may play an important role in the host response to viral infection by regulating lung epithelial cell death.
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Vírus da Influenza A Subtipo H1N1 , Influenza Humana , Lesão Pulmonar , Infecções por Orthomyxoviridae , Animais , Antioxidantes/metabolismo , Feminino , Glutationa/metabolismo , Glutationa Redutase/metabolismo , Humanos , Vírus da Influenza A Subtipo H1N1/metabolismo , Influenza Humana/metabolismo , Pulmão/metabolismo , Lesão Pulmonar/metabolismo , Masculino , Camundongos , Camundongos Endogâmicos BALB C , Infecções por Orthomyxoviridae/metabolismo , RNA/metabolismoRESUMO
This study was designed to develop machine-learning models to predict COVID-19 mortality and identify its key features based on clinical characteristics and laboratory tests. For this, deep-learning (DL) and machine-learning (ML) models were developed using receiver operating characteristic (ROC) area under the curve (AUC) and F1 score optimization of 87 parameters. Of the two, the DL model exhibited better performance (AUC 0.8721, accuracy 0.84, and F1 score 0.76). However, we also blended DL with ML, and the ensemble model performed the best (AUC 0.8811, accuracy 0.85, and F1 score 0.77). The DL model is generally unable to extract feature importance; however, we succeeded by using the Shapley Additive exPlanations method for each model. This study demonstrated both the applicability of DL and ML models for classifying COVID-19 mortality using hospital-structured data and that the ensemble model had the best predictive ability.
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Purpose: Chemotherapy-induced peripheral neuropathy (CIPN) is one of the common reasons that colorectal cancer patients cannot maintain their routine chemotherapy schedules. Some medications are used for pain relief; however, the effect of medication is disappointing. We carried out this study to confirm that a rehabilitation program using minor muscles might provide a valuable aid in symptom relief of CIPN. Methods: Eleven colorectal cancer patients participated in the basic craftwork program which encouraged the use of the minor muscles of the hands to make and decorate the handicrafts and it was held for 2 hours once a week, for a total of four times. There were no limitations in the stage of cancer or types of chemotherapy to participate the program. Questionnaires were obtained from participants before and after the basic handicrafts program. Results: Of the 11 patients (3 men, 8 women; mean age, 53.0±11.2 years), six received 5-fluorouracil (5-FU) chemotherapy, four received FOLFOX4 (combination of 5-FU, leucovorin, and oxaliplatin) chemotherapy, and one received 5-FU, FOLFOX4, and FOLFIRI (combination of 5-FU, leucovorin, and irinotecan) chemotherapy sequentially. Patients attended the program a mean of 3.8±0.4 times. Common symptoms of CIPN were "throbbing pain," "aching pain," and "numbness." The mean score of the questionnaires between pre- and post-program was 34.1±31.7 points and 24.4±21.5 points each, and it was significantly decreased (P=0.040). Conclusion: Patients often suffered from CIPN symptoms like throbbing or aching pain and numbness during their adjuvant chemotherapy. A rehabilitation program using minor muscles for CIPN is expected to be effective.
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BACKGROUND The transplant community is seeking ways to encourage organ donation after cardiac arrest to solve the problem of the insufficiency of organs available for the increasing number of people awaiting transplantation. This study aimed to determine whether the life-sustaining treatment (LST) decision system, implemented in Korea on February 4, 2018, can address the shortage of organ donations. MATERIAL AND METHODS We retrospectively analyzed the medical records of the 442 patients who had filled out forms for the LST decision at Ewha Womans University Mokdong Hospital from April 2018 to December 2019, and classified the eligibility of organ and tissue donation according to the Korean Organ Donation Agency criteria. RESULTS We included 442 patients in this study. Among them, 238 (53.8%) were men, and 204 (46.2%) were women. The average age of the patients was 71.8 years (the youngest and oldest were aged 23 years and 103 years, respectively). Of these, 110 patients (24.9%) decided on their own to discontinue LST, whereas 332 (75.1%) decided to discontinue with their family's consent. This study demonstrated that 50% of patients who were not brain-dead and discontinued LST were eligible for organ donation. However, the patients and caregivers were not aware of this option because the current law does not allow the discussion of such donations. CONCLUSIONS A discussion regarding donation after circulatory death is recommended to solve the problem of insufficient organ donation.
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Transplante de Órgãos , Obtenção de Tecidos e Órgãos , Idoso , Morte Encefálica , Feminino , Humanos , Masculino , República da Coreia , Estudos Retrospectivos , Doadores de TecidosRESUMO
Rationale: The Sequential Organ Failure Assessment (SOFA) tool is a commonly used measure of illness severity. Calculation of the respiratory subscore of SOFA is frequently limited by missing arterial oxygen pressure (PaO2) data. Although missing PaO2 data are commonly replaced with normal values, the performance of different methods of substituting PaO2 for SOFA calculation is unclear. Objectives: The study objective was to compare the performance of different substitution strategies for missing PaO2 data for SOFA score calculation. Methods: This retrospective cohort study was performed using the Weill Cornell Critical Care Database for Advanced Research from a tertiary care hospital in the United States. All adult patients admitted to an intensive care unit (ICU) from 2011 to 2019 with an available respiratory SOFA score were included. We analyzed the availability of the PaO2/fraction of inspired oxygen (FiO2) ratio on the first day of ICU admission. In those without a PaO2/FiO2 ratio available, the ratio of oxygen saturation as measured by pulse oximetry to FiO2 was used to calculate a respiratory SOFA subscore according to four methods (linear substitution [Rice], nonlinear substitution [Severinghaus], modified respiratory SOFA, and multiple imputation by chained equations [MICE]) as well as the missing-as-normal technique. We then compared how well the different total SOFA scores discriminated in-hospital mortality. We performed several subgroup and sensitivity analyses. Results: We identified 35,260 unique visits, of which 9,172 included predominant respiratory failure. PaO2 data were available for 14,939 (47%). The area under the receiver operating characteristic curve for each substitution technique for discriminating in-hospital mortality was higher than that for the missing-as-normal technique (0.78 [0.77-0.79]) in all analyses (modified, 0.80 [0.79-0.81]; Rice, 0.80 [0.79-0.81]; Severinghaus, 0.80 [0.79-0.81]; and MICE, 0.80 [0.79-0.81]) (P < 0.01). Each substitution method had a higher accuracy for discriminating in-hospital mortality (MICE, 0.67; Rice, 0.67; modified, 0.66; and Severinghaus, 0.66) than the missing-as-normal technique. Model calibration for in-hospital mortality was less precise for the missing-as-normal technique than for the other substitution techniques at the lower range of SOFA and among the subgroups. Conclusions: Using physiologic and statistical substitution methods improved the total SOFA score's ability to discriminate mortality compared with the missing-as-normal technique. Treating missing data as normal may result in underreporting the severity of illness compared with using substitution. The simplicity of a direct oxygen saturation as measured by pulse oximetry/FiO2 ratio-modified SOFA technique makes it an attractive choice for electronic health record-based research. This knowledge can inform comparisons of severity of illness across studies that used different techniques.
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Escores de Disfunção Orgânica , Oximetria , Humanos , Unidades de Terapia Intensiva , Oxigênio , Prognóstico , Curva ROC , Estudos RetrospectivosRESUMO
Influenza epidemics remain a leading cause of morbidity and mortality worldwide. In the current study, we investigated the impact of chronological ageing on tryptophan metabolism in response to influenza infection.Examination of metabolites present in plasma collected from critically ill patients identified tryptophan metabolism as an important metabolic pathway utilised specifically in response to influenza. Using a murine model of influenza infection to further these findings illustrated that there was decreased production of kynurenine in aged lung in an indoleamine-pyrrole 2,3-dioxygenase-dependent manner that was associated with increased inflammatory and diminished regulatory responses. Specifically, within the first 7â days of influenza, there was a decrease in kynurenine pathway mediated metabolism of tryptophan, which resulted in a subsequent increase in ketone body catabolism in aged alveolar macrophages. Treatment of aged mice with mitoquinol, a mitochondrial targeted antioxidant, improved mitochondrial function and restored tryptophan metabolism.Taken together, our data provide additional evidence as to why older persons are more susceptible to influenza and suggest a possible therapeutic to improve immunometabolic responses in this population.
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Influenza Humana , Triptofano , Idoso , Idoso de 80 Anos ou mais , Animais , Humanos , Indolamina-Pirrol 2,3,-Dioxigenase , Cinurenina , Pulmão , CamundongosRESUMO
BACKGROUND: This study examined the experience of withholding or withdrawing life-sustaining treatment in patients hospitalized in the intensive care units (ICUs) of a tertiary care center. It also considers the role that intensivists play in the decision-making process regarding the withdrawal of life-sustaining treatment. METHODS: We retrospectively analyzed the medical records of 227 patients who decided to withhold or withdraw life-sustaining treatment while hospitalized at Ewha Womans University Medical Center Mokdong between April 9 and December 31, 2018. RESULTS: The 227 hospitalized patients included in the analysis withheld or withdrew from life-sustaining treatment. The department in which life-sustaining treatment was withheld or withdrawn most frequently was hemato-oncology (26.4%). Among these patients, the most common diagnosis was gastrointestinal tract cancer (29.1%). A majority of patients (64.3%) chose not to receive any life-sustaining treatment. Of the 80 patients in the ICU, intensivists participated in the decision to withhold or withdraw life-sustaining treatment in 34 cases. There were higher proportions of treatment withdrawal and ICU-to-ward transfers among the cases in whom intensivists participated in decision making compared to those cases in whom intensivists did not participate (50.0% vs. 4.3% and 52.9% vs. 19.6%, respectively). CONCLUSIONS: Through their participation in end-of-life discussions, intensivists can help patients' families to make decisions about withholding or withdrawing life-sustaining treatment and possibly avoiding futile treatments for these patients.
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Silkworm, Bombyx mori, contains high amounts of beneficial nutrients, including amino acids, proteins, essential minerals, and omega-3 fatty acids. We have previously reported a technique for producing steamed and freeze-dried mature silkworm larval powder (SMSP), which makes it easier to digest mature silkworm. In this study, we investigated the preventive effects of SMSP on alcoholic fatty liver disease and elucidated its mechanism of action. Male Sprague-Dawley rats treated with SMSP (50 mg/kg) or normal diet (AIN-76A) were administered 25% ethanol (3 g/kg body weight) by oral gavage for 4 weeks. SMSP administration for 4 weeks significantly decreased hepatic fat accumulation in ethanol-treated rats by modulating lipogenesis and fatty acid oxidation-related molecules such as sirtuin 1, AMP-activated protein kinase, and acetyl-CoA carboxylase 1. Moreover, SMSP administration significantly diminished the levels of triglyceride in liver tissues by as much as 35%, as well as lowering the serum levels of triglyceride, gamma glutamyl transpeptidase, alanine transaminase, and aspartate aminotransferase in ethanol-treated rats. SMSP supplementation also decreased the pro-inflammatory tumor necrosis factor-alpha and interleukin 1 beta levels and cytochrome P450 2E1 generating oxidative stress. These results suggest that SMSP administration may be possible for the prevention of alcoholic liver disease.
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BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a rapidly progressive, fatal lung disease that affects older adults. One of the detrimental natural histories of IPF is acute exacerbation of IPF (AE-IPF), of which bacterial infection is reported to play an important role. However, the mechanism by which bacterial infection modulates the fibrotic response remains unclear. OBJECTIVES: Altered glucose metabolism has been implicated in the pathogenesis of fibrotic lung diseases. We have previously demonstrated that glucose transporter 1 (GLUT1)-dependent glycolysis regulates fibrogenesis in a murine fibrosis model. To expand on these findings, we hypothesised that GLUT1-dependent glycolysis regulates acute exacerbation of lung fibrogenesis during bacterial infection via AIM2 inflammasome activation. RESULTS: In our current study, using a murine model of Streptococcus pneumoniae (S. pneumoniae) infection, we investigated the potential role of GLUT1 on mediating fibrotic responses to an acute exacerbation during bleomycin-induced fibrosis. The results of our current study illustrate that GLUT1 deficiency ameliorates S. pneumoniae-mediated exacerbation of lung fibrosis (wild type (WT)/phosphate buffered saline (PBS), n=3; WT/S. pneumoniae, n=3; WT/Bleomycin, n=5 ; WT/Bleomycin+S. pneumoniae, n=7; LysM-Cre-Glut1fl/f /PBS, n=3; LysM-Cre-Glut1fl/fl /S. pneumoniae, n=3; LysM-Cre-Glut1fl/fl /Bleomycin, n=6; LysM-Cre-Glut1fl/fl /Bleomycin+S. pneumoniae, n=9, p=0.041). Further, the AIM2 inflammasome, a multiprotein complex essential for sensing cytosolic bacterial DNA as a danger signal, is an important regulator of this GLUT1-mediated fibrosis and genetic deficiency of AIM2 reduced bleomycin-induced fibrosis after S. pneumoniae infection (WT/PBS, n=6; WT/Bleomycin+S. pneumoniae, n=15; Aim2-/-/PBS, n=6, Aim2-/-/Bleomycin+S. pneumoniae, n=11, p=0.034). GLUT1 deficiency reduced expression and function of the AIM2 inflammasome, and AIM2-deficient mice showed substantial reduction of lung fibrosis after S. pneumoniae infection. CONCLUSION: Our results demonstrate that GLUT1-dependent glycolysis promotes exacerbation of lung fibrogenesis during S. pneumoniae infection via AIM2 inflammasome activation.
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Transportador de Glucose Tipo 1/metabolismo , Glicólise , Fibrose Pulmonar Idiopática/metabolismo , Inflamassomos/metabolismo , Pulmão/patologia , Infecções Pneumocócicas/metabolismo , Animais , Bleomicina , Modelos Animais de Doenças , Progressão da Doença , Fibrose , Técnicas de Inativação de Genes , Transportador de Glucose Tipo 1/genética , Humanos , Fibrose Pulmonar Idiopática/induzido quimicamente , Fibrose Pulmonar Idiopática/patologia , Inflamassomos/genética , Camundongos , Infecções Pneumocócicas/complicaçõesRESUMO
The apnea test is an essential examination for the determination of brain death; however, hypotension, hypoxemia, and other complications during the apnea test can affect the stability of brain-dead patients, as well as organ function for recipients. Therefore, it is necessary to establish standard guidelines for apnea testing.The modified apnea test (MAT) comprises delivery of 100% oxygen through the endotracheal tube connected to manual resuscitator (Ambu bag) with the positive end-expiratory pressure (PEEP) valve after disconnection of the mechanical ventilator for maintenance of PEEP. Forty-nine instances of the conventional apnea test (CAT) were performed in 25 brain-dead patients; 77 instances of the MAT were performed in 39 brain-dead patients.The mean duration of the apnea test was 3.5â±â1.4âminutes in the CAT group and 3.0â±â1.2âminutes in the MAT group. There were no significant changes in PaCO2, PaO2, or pH between the CAT and MAT groups (Pâ=â.341, .593, and .503, respectively). In overweight patients (body mass index ≥ 23âkg/m), MAT prevented dramatic reductions in PaO2 and SaO2 (Pâ<â.05 for both). In the patients who had hypoxic brain injury due to hanging, differences in PaO2 and SaO2 in the MAT group were significantly smaller than in the CAT group (Pâ<â.05).Although MAT, which was invented to maintain PEEP, was not efficient for all brain-dead patients, it could be helpful in selected patient groups, such as overweight patients or those who had hypoxic injury due to hanging. And clinicians should consider short-term apnea test to avoid unnecessarily prolonged hypoxemia.
Assuntos
Apneia/diagnóstico , Gasometria/métodos , Morte Encefálica/diagnóstico , Respiração com Pressão Positiva/métodos , Apneia/complicações , Feminino , Humanos , Hipóxia Encefálica/complicações , Masculino , Pessoa de Meia-Idade , Sobrepeso/complicaçõesRESUMO
BACKGROUND The aim of this study is to report our experience of brain-dead donor management by a dedicated intensivist who had wide experience in treatment of hemodynamically unstable patient and to suggest a role for intensivists in organ donation. MATERIAL AND METHODS The management of brain-dead donors was performed by experienced intensivists. The hospital medical records and data from the Korean Network of Organ Sharing from August 2013 to December 2016 were reviewed retrospectively. RESULTS Fifty-four brain death patients (3.2% of KONOS nationwide data) donated organs in our institution during 41 months. Dedicated intensivists managed deceased patients for the whole duration (2.81±1.21 days) of management, not only with conservative therapies like fluid resuscitation, vasopressor, or hormonal replacement, but also with pulmonary artery catheter insertion for cardiac output monitoring (n=47, 87.0%) and continuous renal replacement therapy (n=22, 40.7%). The number of donors increased each year. The mean number of retrieved organs in each deceased donor was 3.98±1.55, more than the national average (3.26) and comparable to the higher level among the recent worldwide data. The number of donations by organ was: 23 hearts (4.9% of nationwide data), 17 lungs (7.5% of nationwide data), 102 kidneys (3.3% of nationwide data), 47 livers (3.1% of nationwide data), 6 pancreases (2.9% of nationwide data), 1 pancreatic duct (11.1% of nationwide data), and 1 small intestine (12.5% of nationwide data). CONCLUSIONS Management by dedicated intensivists will improve not only the number of actual organ donors, but also the number of harvested organs.