Clinical Characteristics and Prognosis of Older Patients with Coronavirus Disease 2019 Requiring Mechanical Ventilation.

An older age is associated with severe progression and poor prognosis in coronavirus disease 2019 (COVID-19), and mechanical ventilation is often required. The specific characteristics of older patients undergoing mechanical ventilation and their prognostic factors are largely unknown. We aimed to identify potential prognostic factors in this group to inform treatment decisions. This retrospective cohort study collected data from patients with COVID-19 at 22 medical centers. Univariate and multivariate Cox regression analyses were performed to assess factors that influence mortality. We allocated 434 patients in geriatric (≥80 years) and elderly (65-79 years) groups. The former group scored significantly higher than the elderly group in the clinical frailty scale and sequential organ failure assessment, indicating more severe organ dysfunction. Significantly lower administration rates of tocilizumab and extracorporeal membrane oxygenation and higher intensive care unit (ICU) and in-hospital mortality were noted in the geriatric group. The factors associated with ICU and in-hospital mortality included high creatinine levels, the use of continuous renal replacement therapy, prone positioning, and the administration of life-sustaining treatments. These results highlight significant age-related differences in the management and prognosis of critically ill older patients with COVID-19. Increased mortality rates and organ dysfunction in geriatric patients undergoing mechanical ventilation necessitate age-appropriate treatment strategies to improve their prognoses.

Prevalences and Interrelationships of Post COVID-19 Fatigue, Sleep Disturbances, and Depression in Healthy Young and Middle-Aged Adults.

Background: An evaluation of the persistence of symptoms following COVID-19 in economically active young and middle-aged adults is crucial due to its significant socioeconomic impact resulting from compromised work performance. Methods: A prospective, multicenter study at 12 South Korean hospitals from January to December 2022 involved telephone interviews along with validated questionnaires. Results: Among 696 participants with a median age of 32 and no prior diagnoses, 30% of participants experienced persistent fatigue, while 21.4% suffered from sleep disturbance at 6 months following infection. Additionally, approximately 25% of the participants exhibited depression that endured for up to 6 months. Symptomatic individuals at 3 months exhibited a significantly higher prevalence of persistent fatigue, sleep disturbances, and depression at 6 months compared to those who remained asymptomatic. Notably, sleep disturbance and persistent fatigue at 3 months emerged as significant independent predictors of the presence of depression at 6 months. Conclusions: Even among young and middle-aged healthy adults, prolonged fatigue, sleep disturbance, and depression exhibit a significant prevalence and persisted for up to 6 months. Therefore, implementing a workplace management protocol for these symptoms is essential to mitigate the socioeconomic burden caused by the impairment of work efficiency.

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. Logistic analysis was used to identify the factors associated with CRRT implementation. RESULTS: Of the 640 patients with COVID-19 who required MV, 123 (19.2%) underwent CRRT. Compared to the non-CRRT group, the CRRT group was older and exhibited higher sequential organ failure assessment scores. The incidence of hypertension, diabetes, cardiovascular disease, chronic neurological disease, and chronic kidney disease was also higher in the CRRT group. Moreover, the CRRT group had higher intensive care unit (ICU) (75.6% vs. 26.9%, p < 0.001) and in-hospital (79.7% vs. 29.6%, p < 0.001) mortality rates. CRRT implementation was identified as an independent risk factor for both ICU mortality (hazard ratio [HR]:1.833, 95% confidence interval [CI]:1.342-2.505, p < 0.001) and in-hospital mortality (HR: 2.228, 95% CI: 1.648-3.014, p < 0.001). Refractory respiratory failure (n = 99, 19.1%) was the most common cause of death in the non-CRRT death group, and shock with multi-organ failure (n = 50, 40.7%) was the most common cause of death in the CRRT death group. Shock with multi-organ failure and cardiac death were significantly more common in the CRRT death group, compared to non-CRRT death group. CONCLUSION: This study indicates that CRRT is associated with higher ICU and in-hospital mortality rates in patients with COVID-19 who require MV. Notably, the primary cause of death in the CRRT group was shock with multi-organ failure, emphasizing the severe clinical course for these patients, while refractory respiratory failure was most common in non-CRRT patients.

BET inhibitors as a therapeutic intervention in gastrointestinal gene signature-positive castration-resistant prostate cancer.

A subgroup of castration-resistant prostate cancer (CRPC) aberrantly expresses a gastrointestinal (GI) transcriptome governed by two GI-lineage-restricted transcription factors, HNF1A and HNF4G. In this study, we found that expression of GI transcriptome in CRPC correlates with adverse clinical outcomes to androgen receptor signaling inhibitor treatment and shorter overall survival. Bromo- and extra-terminal domain inhibitors (BETi) downregulated HNF1A, HNF4G, and the GI transcriptome in multiple CRPC models, including cell lines, patient-derived organoids, and patient-derived xenografts, while AR and the androgen-dependent transcriptome were largely spared. Accordingly, BETi selectively inhibited growth of GI transcriptome-positive preclinical models of prostate cancer. Mechanistically, BETi inhibited BRD4 binding at enhancers globally, including both AR and HNF4G bound enhancers while gene expression was selectively perturbed. Restoration of HNF4G expression in the presence of BETi rescued target gene expression without rescuing BRD4 binding. This suggests that inhibition of master transcription factors expression underlies the selective transcriptional effects of BETi. SIGNIFICANCE: GI transcriptome expression in CRPC is regulated by the HNF1A-HNF4G-BRD4 axis and correlates with worse clinical outcomes. Accordingly, BET inhibitors significantly reduce tumor cell growth in multiple GI-transcriptome-positive preclinical models of CRPC. Our studies point that expression of GI transcriptome could serve as a predictive biomarker to BETi therapy response.

Risk Factors for the Mortality of Patients With Coronavirus Disease 2019 Requiring Extracorporeal Membrane Oxygenation in a Non-Centralized Setting: A Nationwide Study.

BACKGROUND: Limited data are available on the mortality rates of patients receiving extracorporeal membrane oxygenation (ECMO) support for coronavirus disease 2019 (COVID-19). We aimed to analyze the relationship between COVID-19 and clinical outcomes for patients receiving ECMO. METHODS: We retrospectively investigated patients with COVID-19 pneumonia requiring ECMO in 19 hospitals across Korea from January 1, 2020 to August 31, 2021. The primary outcome was the 90-day mortality after ECMO initiation. We performed multivariate analysis using a logistic regression model to estimate the odds ratio (OR) of 90-day mortality. Survival differences were analyzed using the Kaplan-Meier (KM) method. RESULTS: Of 127 patients with COVID-19 pneumonia who received ECMO, 70 patients (55.1%) died within 90 days of ECMO initiation. The median age was 64 years, and 63% of patients were male. The incidence of ECMO was increased with age but was decreased after 70 years of age. However, the survival rate was decreased linearly with age. In multivariate analysis, age (OR, 1.048; 95% confidence interval [CI], 1.010-1.089; P = 0.014) and receipt of continuous renal replacement therapy (CRRT) (OR, 3.069; 95% CI, 1.312-7.180; P = 0.010) were significantly associated with an increased risk of 90-day mortality. KM curves showed significant differences in survival between groups according to age (65 years) (log-rank P = 0.021) and receipt of CRRT (log-rank P = 0.004). CONCLUSION: Older age and receipt of CRRT were associated with higher mortality rates among patients with COVID-19 who received ECMO.

Unique Changes in the Lung Microbiome following the Development of Chronic Lung Allograft Dysfunction.

The importance of lung microbiome changes in developing chronic lung allograft dysfunction (CLAD) after lung transplantation is poorly understood. The lung microbiome-immune interaction may be critical in developing CLAD. In this context, examining alterations in the microbiome and immune cells of the lungs following CLAD, in comparison to the lung condition immediately after transplantation, can offer valuable insights. Four adult patients who underwent lung retransplantation between January 2019 and June 2020 were included in this study. Lung tissues were collected from the same four individuals at two different time points: at the time of the first transplant and at the time of the explantation of CLAD lungs at retransplantation due to CLAD. We analyzed whole-genome sequencing using the Kraken2 algorithm and quantified the cell fractionation from the bulk tissue gene expression profile for each lung tissue. Finally, we compared the differences in lung microbiome and immune cells between the lung tissues of these two time points. The median age of the recipients was 57 years, and most (75%) had undergone lung transplants for idiopathic pulmonary fibrosis. All patients were administered basiliximab for induction therapy and were maintained on three immunosuppressants. The median CLAD-free survival term was 693.5 days, and the median time to redo the lung transplant was 843.5 days. Bacterial diversity was significantly lower in the CLAD lungs than at transplantation. Bacterial diversity tended to decrease according to the severity of the CLAD. Aerococcus, Caldiericum, Croceibacter, Leptolyngbya, and Pulveribacter genera were uniquely identified in CLAD, whereas no taxa were identified in lungs at transplantation. In particular, six taxa, including Croceibacter atlanticus, Caldiserium exile, Dolichospermum compactum, Stappia sp. ES.058, Kinetoplastibacterium sorsogonicusi, and Pulveribacter suum were uniquely detected in CLAD. Among immune cells, CD8+ T cells were significantly increased, while neutrophils were decreased in the CLAD lung. In conclusion, unique changes in lung microbiome and immune cell composition were confirmed in lung tissue after CLAD compared to at transplantation.

Development of a Novel Biomarker for the Progression of Idiopathic Pulmonary Fibrosis.

The progression of idiopathic pulmonary fibrosis (IPF) is diverse and unpredictable. We identified and validated a new biomarker for IPF progression. To identify a candidate gene to predict progression, we assessed differentially expressed genes in patients with advanced IPF compared with early IPF and controls in three lung sample cohorts. Candidate gene expression was confirmed using immunohistochemistry and Western blotting of lung tissue samples from an independent IPF clinical cohort. Biomarker potential was assessed using an enzyme-linked immunosorbent assay of serum samples from the retrospective validation cohort. We verified that the final candidate gene reflected the progression of IPF in a prospective validation cohort. In the RNA-seq comparative analysis of lung tissues, CD276, COL7A1, CTSB, GLI2, PIK3R2, PRAF2, IGF2BP3, and NUPR1 were up-regulated, and ADAMTS8 was down-regulated in the samples of advanced IPF. Only CTSB showed significant differences in expression based on Western blotting (n = 12; p < 0.001) and immunohistochemistry between the three groups of the independent IPF cohort. In the retrospective validation cohort (n = 78), serum CTSB levels were higher in the progressive group (n = 25) than in the control (n = 29, mean 7.37 ng/mL vs. 2.70 ng/mL, p < 0.001) and nonprogressive groups (n = 24, mean 7.37 ng/mL vs. 2.56 ng/mL, p < 0.001). In the prospective validation cohort (n = 129), serum CTSB levels were higher in the progressive group than in the nonprogressive group (mean 8.30 ng/mL vs. 3.00 ng/mL, p < 0.001). After adjusting for baseline FVC, we found that CTSB was independently associated with IPF progression (adjusted OR = 2.61, p < 0.001). Serum CTSB levels significantly predicted IPF progression (AUC = 0.944, p < 0.001). Serum CTSB level significantly distinguished the progression of IPF from the non-progression of IPF or healthy control.

Functional Aspects of the Obesity Paradox in Patients with Severe Coronavirus Disease-2019: A Retrospective, Multicenter Study.

BACKGROUND: Results of studies investigating the association between body mass index (BMI) and mortality in patients with coronavirus disease-2019 (COVID-19) have been conflicting. METHODS: This multicenter, retrospective observational study, conducted between January 2020 and August 2021, evaluated the impact of obesity on outcomes in patients with severe COVID-19 in a Korean national cohort. A total of 1,114 patients were enrolled from 22 tertiary referral hospitals or university-affiliated hospitals, of whom 1,099 were included in the analysis, excluding 15 with unavailable height and weight information. The effect(s) of BMI on patients with severe COVID-19 were analyzed. RESULTS: According to the World Health Organization BMI classification, 59 patients were underweight, 541 were normal, 389 were overweight, and 110 were obese. The overall 28-day mortality rate was 15.3%, and there was no significant difference according to BMI. Univariate Cox analysis revealed that BMI was associated with 28-day mortality (hazard ratio, 0.96; p=0.045), but not in the multivariate analysis. Additionally, patients were divided into two groups based on BMI ≥25 kg/m2 and underwent propensity score matching analysis, in which the two groups exhibited no significant difference in mortality at 28 days. The median (interquartile range) clinical frailty scale score at discharge was higher in nonobese patients (3 [3 to 5] vs. 4 [3 to 6], p<0.001). The proportion of frail patients at discharge was significantly higher in the nonobese group (28.1% vs. 46.8%, p<0.001). CONCLUSION: The obesity paradox was not evident in this cohort of patients with severe COVID-19. However, functional outcomes at discharge were better in the obese group.

Development and Validation of Deep-Learning-Based Sepsis and Septic Shock Early Prediction System (DeepSEPS) Using Real-World ICU Data.

BACKGROUND: Successful sepsis treatment depends on early diagnosis. We aimed to develop and validate a system to predict sepsis and septic shock in real time using deep learning. METHODS: Clinical data were retrospectively collected from electronic medical records (EMRs). Data from 2010 to 2019 were used as development data, and data from 2020 to 2021 were used as validation data. The collected EMRs consisted of eight vital signs, 13 laboratory data points, and three demographic information items. We validated the deep-learning-based sepsis and septic shock early prediction system (DeepSEPS) using the validation datasets and compared our system with other traditional early warning scoring systems, such as the national early warning score, sequential organ failure assessment (SOFA), and quick sequential organ failure assessment. RESULTS: DeepSEPS achieved even higher area under receiver operating characteristic curve (AUROC) values (0.7888 and 0.8494 for sepsis and septic shock, respectively) than SOFA. The prediction performance of traditional scoring systems was enhanced because the early prediction time point was close to the onset time of sepsis; however, the DeepSEPS scoring system consistently outperformed all conventional scoring systems at all time points. Furthermore, at the time of onset of sepsis and septic shock, DeepSEPS showed the highest AUROC (0.9346). CONCLUSIONS: The sepsis and septic shock early warning system developed in this study exhibited a performance that is worth considering when predicting sepsis and septic shock compared to other traditional early warning scoring systems. DeepSEPS showed better performance than existing sepsis prediction programs. This novel real-time system that simultaneously predicts sepsis and septic shock requires further validation.

Early prediction of need for invasive mechanical ventilation in the neonatal intensive care unit using artificial intelligence and electronic health records: a clinical study.

BACKGROUND: Respiratory support is crucial for newborns with underdeveloped lung. The clinical outcomes of patients depend on the clinician's ability to recognize the status underlying the presented symptoms and signs. With the increasing number of high-risk infants, artificial intelligence (AI) should be considered as a tool for personalized neonatal care. Continuous monitoring of vital signs is essential in cardiorespiratory care. In this study, we developed deep learning (DL) prediction models for rapid and accurate detection of mechanical ventilation requirements in neonates using electronic health records (EHR). METHODS: We utilized data from the neonatal intensive care unit in a single center, collected between March 3, 2012, and March 4, 2022, including 1,394 patient records used for model development, consisting of 505 and 889 patients with and without invasive mechanical ventilation (IMV) support, respectively. The proposed model architecture includes feature embedding using feature-wise fully connected (FC) layers, followed by three bidirectional long short-term memory (LSTM) layers. RESULTS: A mean gestational age (GA) was 36.61 ± 3.25 weeks, and the mean birth weight was 2,734.01 ± 784.98 g. The IMV group had lower GA, birth weight, and longer hospitalization duration than the non-IMV group (P < 0.05). Our proposed model, tested on a dataset from March 4, 2019, to March 4, 2022. The mean AUROC of our proposed model for IMV support prediction performance demonstrated 0.861 (95%CI, 0.853-0.869). It is superior to conventional approaches, such as newborn early warning score systems (NEWS), Random Forest, and eXtreme gradient boosting (XGBoost) with 0.611 (95%CI, 0.600-0.622), 0.837 (95%CI, 0.828-0.845), and 0.0.831 (95%CI, 0.821-0.845), respectively. The highest AUPRC value is shown in the proposed model at 0.327 (95%CI, 0.308-0.347). The proposed model performed more accurate predictions as gestational age decreased. Additionally, the model exhibited the lowest alarm rate while maintaining the same sensitivity level. CONCLUSION: Deep learning approaches can help accurately standardize the prediction of invasive mechanical ventilation for neonatal patients and facilitate advanced neonatal care. The results of predictive, recall, and alarm performances of the proposed model outperformed the other models.

Empiric Anti-Pseudomonal ß-Lactam Monotherapy Versus Fluoroquinolone Combination Therapy in Patients With Hospital-Acquired Pneumonia: A Multicenter Cohort Study With Propensity Score Matching.

BACKGROUND: There is insufficient data on the benefits of empiric antibiotic combinations for hospital-acquired pneumonia (HAP). We aimed to investigate whether empiric anti-pseudomonal combination therapy with fluoroquinolones decreases mortality in patients with HAP. METHODS: This multicenter, retrospective cohort study included adult patients admitted to 16 tertiary and general hospitals in Korea between January 1 and December 31, 2019. Patients with risk factors for combination therapy were divided into anti-pseudomonal non-carbapenem ß-lactam monotherapy and fluoroquinolone combination therapy groups. Primary outcome was 30-day mortality. Propensity score matching (PSM) was used to reduce selection bias. RESULTS: In total, 631 patients with HAP were enrolled. Monotherapy was prescribed in 54.7% (n = 345) of the patients, and combination therapy was prescribed in 45.3% (n = 286). There was no significant difference in 30-day mortality between the two groups (16.8% vs. 18.2%, P = 0.729) or even after the PSM (17.5% vs. 18.2%, P = 0.913). After the PSM, adjusted hazard ratio for 30-day mortality from the combination therapy was 1.646 (95% confidence interval, 0.782-3.461; P = 0.189) in the Cox proportional hazards model. Moreover, there was no significant difference in the appropriateness of initial empiric antibiotics between the two groups (55.0% vs. 56.8%, P = 0.898). The proportion of multidrug-resistant (MDR) pathogens was high in both groups. CONCLUSION: Empiric anti-pseudomonal fluoroquinolone combination therapy showed no survival benefit compared to ß-lactam monotherapy in patients with HAP. Caution is needed regarding the routine combination of fluoroquinolones in the empiric treatment of HAP patients with a high risk of MDR.

Erratum: Correction of Affiliations in the Article "Validity of Outcome Prediction Scoring Systems in Korean Patients with Severe Adult Respiratory Distress Syndrome Receiving Extracorporeal Membrane Oxygenation Therapy".

This corrects the article on p. 932 in vol. 31, PMID: 27247503.

Predictors of mortality and transfusion requirements in venoarterial extracorporeal membrane oxygenation patients.

OBJECTIVE: The aim of this study was to evaluate the prognostic impact of variables, including thrombocytopenia and the amount of platelet transfusion, for predicting survival in venoarterial extracorporeal membrane oxygenation (ECMO) recipients. Additionally, we aimed to identify the predictors of increased transfusion requirement during venoarterial ECMO support. METHODS: All patients who received venoarterial ECMO between December 2008 and March 2020 were retrospectively analyzed. Univariate and multivariate Cox regressions were used to evaluate in-hospital mortality according to variables including thrombocytopenia and daily average of platelet concentrate transfusion. Stepwise multiple linear regression analysis was used to identify independent predictors for transfusion requirements. RESULTS: Analysis of 218 patients demonstrated severe thrombocytopenia as an independent predictor of in-hospital mortality (hazard ratio = 2.840, 95% CI: 1.593-5.063, P < .001), along with age, pre-ECMO cardiac arrest, and pH. In contrast, the amount of platelet transfusion was not associated with in-hospital mortality. Multiple variables, including the type of indication for ECMO were associated with transfusion requirements. CONCLUSION: Our findings identified severe thrombocytopenia as an independent prognostic factor of in-hospital mortality. However, daily average platelet transfusion was not associated with survival outcomes. Additionally, our study identified predictive variables of increased transfusion requirements.

Cortical astrocytes modulate dominance behavior in male mice by regulating synaptic excitatory and inhibitory balance.

Social hierarchy is established as an outcome of individual social behaviors, such as dominance behavior during long-term interactions with others. Astrocytes are implicated in optimizing the balance between excitatory and inhibitory (E/I) neuronal activity, which may influence social behavior. However, the contribution of astrocytes in the prefrontal cortex to dominance behavior is unclear. Here we show that dorsomedial prefrontal cortical (dmPFC) astrocytes modulate E/I balance and dominance behavior in adult male mice using in vivo fiber photometry and two-photon microscopy. Optogenetic and chemogenetic activation or inhibition of dmPFC astrocytes show that astrocytes bidirectionally control male mouse dominance behavior, affecting social rank. Dominant and subordinate male mice present distinct prefrontal synaptic E/I balance, regulated by astrocyte activity. Mechanistically, we show that dmPFC astrocytes control cortical E/I balance by simultaneously enhancing presynaptic-excitatory and reducing postsynaptic-inhibitory transmission via astrocyte-derived glutamate and ATP release, respectively. Our findings show how dmPFC astrocyte-neuron communication can be involved in the establishment of social hierarchy in adult male mice.

Initial Tumor Necrosis Factor-Alpha and Endothelial Activation Are Associated with Hemorrhagic Complications during Extracorporeal Membrane Oxygenation.

Studies on inflammatory markers, endothelial activation, and bleeding during extracorporeal membrane oxygenation (ECMO) are lacking. Blood samples were prospectively collected after ECMO initiation from 150 adult patients who underwent ECMO for respiratory failure between 2018 and 2021. After excluding patients who died early (within 48 h), 132 patients were finally included. Their tumor necrosis factor-alpha (TNF-α), tissue factor (TF), soluble thrombomodulin (sTM), and E-selectin levels were measured. A Cox proportional hazards regression model was used to estimate the hazard ratio for hemorrhagic complications during ECMO. The 132 patients were divided into hemorrhagic (n = 23, H group) and non-complication (n = 109, N group) groups. The sequential organ failure assessment score, hemoglobin level, and ECMO type were included as covariates in all Cox models to exclude the effects of clinical factors. After adjusting for these factors, initial TNF-α, TF, sTM, E-selectin, and activated protein C levels were significantly associated with hemorrhagic complications (all p < 0.001). TNF-α, TF, and E-selectin better predicted hemorrhagic complications than the model that included only the aforementioned clinical factors (clinical factors only (area under the curve [AUC]: 0.804), reference; TNF-α (AUC: 0.914); TF (AUC: 0.915); E-selectin (AUC: 0.869)). Conclusions: TNF-α levels were significantly predictive of hemorrhagic complications during ECMO.