Evaluate prognostic accuracy of SOFA component score for mortality among adults with sepsis by machine learning method.

INTRODUCTION: Sepsis has the characteristics of high incidence, high mortality of ICU patients. Early assessment of disease severity and risk stratification of death in patients with sepsis, and further targeted intervention are very important. The purpose of this study was to develop machine learning models based on sequential organ failure assessment (SOFA) components to early predict in-hospital mortality in ICU patients with sepsis and evaluate model performance. METHODS: Patients admitted to ICU with sepsis diagnosis were extracted from MIMIC-IV database for retrospective analysis, and were randomly divided into training set and test set in accordance with 2:1. Six variables were included in this study, all of which were from the scores of 6 organ systems in SOFA score. The machine learning model was trained in the training set and evaluated in the validation set. Six machine learning methods including linear regression analysis, least absolute shrinkage and selection operator (LASSO), Logistic regression analysis (LR), Gaussian Naive Bayes (GNB) and support vector machines (SVM) were used to construct the death risk prediction models, and the accuracy, area under the receiver operating characteristic curve (AUROC), Decision Curve Analysis (DCA) and K-fold cross-validation were used to evaluate the prediction performance of developed models. RESULT: A total of 23,889 patients with sepsis were enrolled, of whom 3659 died in hospital. Three feature variables including renal system score, central nervous system score and cardio vascular system score were used to establish prediction models. The accuracy of the LR, GNB, SVM were 0.851, 0.844 and 0.862, respectively, which were better than linear regression analysis (0.123) and LASSO (0.130). The AUROCs of LR, GNB and SVM were 0.76, 0.76 and 0.67, respectively. K-fold cross validation showed that the average AUROCs of LR, GNB and SVM were 0.757 ± 0.005, 0.762 ± 0.006, 0.630 ± 0.013, respectively. For the probability threshold of 5-50%, LY and GNB models both showed positive net benefits. CONCLUSION: The two machine learning-based models (LR and GNB models) based on SOFA components can be used to predict in-hospital mortality of septic patients admitted to ICU.

Plasma metagenomic next-generation sequencing of microbial cell-free DNA detects pathogens in patients with suspected infected pancreatic necrosis.

BACKGROUND: Infected pancreatic necrosis (IPN) is a life-threatening complication of acute pancreatitis (AP). Timely diagnosis of IPN could facilitate appropriate treatment, but there is a lack of reliable non-invasive screening tests. In this study, we aimed to evaluate the diagnostic value of plasma metagenomic next-generation sequencing (mNGS) based on circulating microbial cell-free DNA in patients with suspected IPN. METHODS: From October 2020 to October 2021, 44 suspected IPN patients who underwent plasma mNGS were reviewed. Confirmatory diagnosis of IPN within two weeks after the index blood sampling was considered the reference standard. The confirmation of IPN relied on the microbiological results of drains obtained from the necrotic collections. The distribution of the pathogens identified by plasma mNGS was analyzed. Positive percent agreement (PPA) and negative percent agreement (NPA) were evaluated based on the conformity between the overall mNGS results and culture results of IPN drains. In addition, the clinical outcomes were compared between mNGS positive and negative patients. RESULTS: Across all the study samples, thirteen species of bacteria and five species of fungi were detected by mNGS. The positivity rate of plasma mNGS was 54.55% (24/44). Of the 24 mNGS positive cases, twenty (83.33%, 95% CI, 68.42-98.24%) were consistent with the culture results of IPN drains. The PPA and NPA of plasma mNGS for IPN were 80.0% (20/25; 95% CI, 64.32-95.68%) and 89.47% (17/19; 95% CI, 75.67-100%), respectively. Compared with the mNGS negative group, patients in the positive group had more new-onset septic shock [12 (50.0%) vs. 4 (20.0%), p = 0.039]. CONCLUSION: IPN relevant pathogens can be identified by plasma mNGS, potentially facilitating appropriate treatment. The clinical application of mNGS in this cohort appears feasible.

Identification of early biomarkers of transcriptomics in alveolar macrophage for the prognosis of intubated ARDS patients.

BACKGROUND: Currently, the rate of morbidity and mortality in acute respiratory distress syndrome (ARDS) remains high. One of the potential reasons for the poor and ineffective therapies is the lack of early and credible indicator of risk prediction that would help specific treatment of severely affected ARDS patients. Nevertheless, assessment of the clinical outcomes with transcriptomics of ARDS by alveolar macrophage has not been performed. METHODS: The expression data GSE116560 was obtained from the Gene Expression Omnibus databases (GEO) in NCBI. This dataset consists of 68 BAL samples from 35 subjects that were collected within 48 h of ARDS. Differentially expressed genes (DEGs) of different outcomes were analyzed using R software. The top 10 DEGs that were up- or down-regulated were analyzed using receiver operating characteristic (ROC) analysis. Kaplan-Meier survival analysis within two categories according to cut-off and the value of prediction of the clinical outcomes via DEGs was verified. GO enrichment, KEGG pathway analysis, and protein-protein interaction were also used for functional annotation of key genes. RESULTS: 24,526 genes were obtained, including 235 up-regulated and 292 down-regulated DEGs. The gene ADORA3 was chosen as the most obvious value to predict the outcome according to the ROC and survival analysis. For functional annotation, ADORA3 was significantly augmented in sphingolipid signaling pathway, cGMP-PKG signaling pathway, and neuroactive ligand-receptor interaction. Four genes (ADORA3, GNB1, NTS, and RHO), with 4 nodes and 6 edges, had the highest score in these clusters in the protein-protein interaction network. CONCLUSIONS: Our results show that the prognostic prediction of early biomarkers of transcriptomics as identified in alveolar macrophage in ARDS can be extended for mechanically ventilated critically ill patients. In the long term, generalizing the concept of biomarkers of transcriptomics in alveolar macrophage could add to improving precision-based strategies in the ICU patients and may also lead to identifying improved strategy for critically ill patients.

COVID-19 and coagulation dysfunction in adults: A systematic review and meta-analysis.

The outbreak of 2019 novel coronavirus disease (COVID-19) has posed a grave threat to the global public health. The COVID-19-induced infection is closely related to coagulation dysfunction in the affected patients. This paper attempts to conduct a meta-analysis and systematically review the blood coagulation indicators in patients with severe COVID-19. A meta-analysis of eligible studies was performed to compare the blood coagulation indicators in patients with severe and nonsevere COVID-19. PubMed, Embase, Web of Science, and the Cochrane Library were searched for studies published between 1 December 2019 and 7 May 2020. A total of 13 studies with 1341 adult patients were enrolled in this analysis. Platelet (weighted mean difference [WMD] = -24.83, 95% confidence interval [CI]: -34.12 to -15.54; P < .001), d-dimer (WMD = 0.19, 95% CI: 0.09-0.29; P < .001), and fibrinogen (WMD = 1.02, 95% CI: 0.50-1.54; P < .001) were significantly associated with the severity in patients with COVID-19. The meta-analysis revealed that no correlation was evident between an increased severity risk of COVID-19 and activated partial thromboplastin time (WMD = -1.56, 95% CI: -5.77 to 2.64; P = .468) or prothrombin time (WMD = 0.19, 95% CI: -0.13 to 0.51; P = .243). The single arm meta-analysis showed that compared with the nonsevere group, the severe group had a lower pooled platelet (165.12 [95% CI: 157.38-172.85] vs 190.09 [95% CI: 179.45-200.74]), higher d-dimer (0.49 [95% CI: 0.33-0.64] vs 0.27 [95% CI: 0.20-0.34]), and higher fibrinogen (4.34 [95% CI: 1.98-6.70] vs 3.19 [95% CI: 1.13-5.24]). Coagulation dysfunction is closely related to the severity of patients with COVID-19, in which low platelet, high d-dimer, and fibrinogen upon admission may serve as risk indicators for increased aggression of the disease. These findings are of great clinical value for timely and effective treatment of the COVID-19 cases.

Identification of transcriptomics biomarkers for the early prediction of the prognosis of septic shock from pneumopathies.

BACKGROUND: Identifying the biological subclasses of septic shock might provide specific targeted therapies for the treatment and prognosis of septic shock. It might be possible to find biological markers for the early prediction of septic shock prognosis. METHODS: The data were obtained from the Gene Expression Omnibus databases (GEO) in NCBI. GO enrichment and KEGG pathway analyses were performed to investigate the functional annotation of up- and downregulated DEGs. ROC curves were drawn, and their areas under the curves (AUCs) were determined to evaluate the predictive value of the key genes. RESULTS: 117 DEGs were obtained, including 36 up- and 81 downregulated DEGs. The AUC for the MME gene was 0.879, as a key gene with the most obvious upregulation in septic shock. The AUC for the THBS1 gene was 0.889, as a key downregulated gene with the most obvious downregulation in septic shock. CONCLUSIONS: The upregulation of MME via the renin-angiotensin system pathway and the downregulation of THBS1 through the PI3K-Akt signaling pathway might have implications for the early prediction of prognosis of septic shock in patients with pneumopathies.

miR-34b-5p promotes renal cell inflammation and apoptosis by inhibiting aquaporin-2 in sepsis-induced acute kidney injury.

OBJECTIVE: This study was designed to uncover the mechanism of miR-34b-5p-mediated aquaporin-2 (AQP2) in sepsis-induced injury using human renal tubular epithelial cells (HK-2). METHODS: Serum levels of miR-34b-5p, TNF-α, IL-1ß, IL-6, serum creatinine (SCr), and blood urea nitrogen (BUN) in septic patients with acute kidney injury (AKI) and healthy controls were detected. Lipopolysaccharide (LPS) was used to induce sepsis in HK-2 cells. LPS-induced HK-2 cells were transfected with miR-34b-5p inhibitor, miR-34b-5p mimic, pcDNA3.1-AQP2, si-AQP2, miR-34b-5p inhibitor + si-NC, or miR-34b-5p inhibitor + si-AQP2. The expressions of miR-34b-5p, AQP2, Bax, Bcl-2, cleaved caspase-3, TNF-α, IL-1ß, and IL-6 in HK-2 cells were detected. TUNEL staining revealed the apoptosis of HK-2 cells. Dual-luciferase reporter assay verified the binding between miR-34b-5p and AQP2. RESULTS: The expression of miR-34b-5p and the inflammatory responses were augmented in septic AKI patients. miR-34b-5p was up-regulated and AQP2 was down-regulated in LPS-induced HK-2 cells. miR-34b-5p inhibition or AQP2 overexpression ameliorated apoptosis and inflammation in LPS-induced HK-2 cells. In contrast, overexpressing miR-34b-5p deteriorated LPS-induced injury in HK-2 cells. AQP2 was a downstream target of miR-34b-5p. AQP2 silencing abolished the suppressive effects of miR-34b-5p inhibition on LPS-induced apoptosis and inflammatory response in HK-2 cells. CONCLUSION: miR-34b-5p inhibits AQP2 to promote LPS-induced injury in HK-2 cells.

USP5 promotes lipopolysaccharide-induced apoptosis and inflammatory response by stabilizing the TXNIP protein.

BACKGROUND: The role of thioredoxin-interacting protein (TXNIP) in lipopolysaccharide-induced liver injury in mice has been reported, but the underlying mechanisms are poorly understood. METHODS: We overexpressed deubiquitinase in cells overexpressing TXNIP and then detected the level of TXNIP to screen out the deubiquitinase regulating TXNIP; the interaction between TXNIP and deubiquitinase was verified by coimmunoprecipitation. After knockdown of a deubiquitinase and overexpression of TXNIP in Huh7 and HepG2 cells, lipopolysaccharide was used to establish a cellular inflammatory model to explore the role of deubiquitinase and TXNIP in hepatocyte inflammation. RESULTS: In this study, we discovered that ubiquitin-specific protease 5 (USP5) interacts with TXNIP and stabilizes it through deubiquitylation in Huh-7 and HepG2 cells after treatment with lipopolysaccharide. In lipopolysaccharide-treated Huh-7 and HepG2 cells, USP5 knockdown increased cell viability, reduced apoptosis, and decreased the expression of inflammatory factors, including NLRP3, IL-1ß, IL-18, ASC, and procaspase-1. Overexpression of TXNIP reversed the phenotype induced by knockdown USP5. CONCLUSIONS: In summary, USP5 promotes lipopolysaccharide-induced apoptosis and inflammatory response by stabilizing the TXNIP protein.

Biomarkers for the early prediction of contrast-induced nephropathy after percutaneous coronary intervention in adults: A systematic review and meta-analysis.

Contrast-induced nephropathy (CIN) is a complication of patients undergoing percutaneous coronary intervention (PCI). Promising biomarkers for the early prediction of CIN can significantly improve outcomes of these patients. We searched PubMed, EMBASE, Web of Science, and Cochrane Library for studies. Trials reporting an area under the curve (AUC) for the utility of novel biomarkers in the early prediction of CIN in adults after PCI were included. In total, 42 studies comprising 11,984 adult patients undergoing PCI met the criteria. Four urinary biomarkers and four blood biomarkers were included. For urine biomarkers, the pooled AUCs for neutrophil gelatinase-associated lipocalin (NGAL), interleukin-18 (IL-18), liver-type fatty acid-binding protein (L-FABP), and kidney injury molecule-1 (KIM-1) were 0.91 (95% CI 0.89-0.94), 0.79 (0.75-0.82), 0.78 (0.74-0.82), and 0.79 (0.76-0.83), respectively. The blood biomarkers NGAL, cystatin C, brain natriuretic peptide (BNP), and C-reactive protein (CRP) had pooled AUCs of 0.93 (0.91-0.95), 0.92 (0.89-0.94), 0.78 (0.74-0.81), and 0.75 (0.71-0.79), respectively. Subgroup analysis showed that blood NGAL in early CIN predictive time (<6 h) was more effective in predicting CIN. The efficiency of cystatin C in predicting CIN was reduced, whereas that of L-FABP was increased among chronic kidney disease (CKD) patients.

An application based on bioinformatics and machine learning for risk prediction of sepsis at first clinical presentation using transcriptomic data.

Background: Linking genotypic changes to phenotypic traits based on machine learning methods has various challenges. In this study, we developed a workflow based on bioinformatics and machine learning methods using transcriptomic data for sepsis obtained at the first clinical presentation for predicting the risk of sepsis. By combining bioinformatics with machine learning methods, we have attempted to overcome current challenges in predicting disease risk using transcriptomic data. Methods: High-throughput sequencing transcriptomic data processing and gene annotation were performed using R software. Machine learning models were constructed, and model performance was evaluated by machine learning methods in Python. The models were visualized and interpreted using the Shapley Additive explanation (SHAP) method. Results: Based on the preset parameters and using recursive feature elimination implemented via machine learning, the top 10 optimal genes were screened for the establishment of the machine learning models. In a comparison of model performance, CatBoost was selected as the optimal model. We explored the significance of each gene in the model and the interaction between each gene through SHAP analysis. Conclusion: The combination of CatBoost and SHAP may serve as the best-performing machine learning model for predicting transcriptomic and sepsis risks. The workflow outlined may provide a new approach and direction in exploring the mechanisms associated with genes and sepsis risk.

[A case-control study on the risk factors for lower respiratory tract infection by Stenotrophomonas maltophilia in a medical intensive care unit].

OBJECTIVE: To explore the risk factors for lower respiratory tract infection by Stenotrophomonas maltophilia in the medical intensive care unit (MICU) in Fujian Provincial Hospital. METHODS: A 1:4 matched case-control study was carried out in the MICU in Fujian Provincial Hospital. Thirty-five patients with hospital-acquired lower respiratory tract infection by Stenotrophomonas maltophilia from 2007 to 2010 were included as cases, and 140 patients without lower respiratory tract infection served as controls. The case group included 22 cases with respiratory diseases, 4 with cerebrovascular diseases, 4 with cardiovascular diseases, 1 with hemorrhage of the digestive tract, 1 with acute pancreatitis, 1 with chronic kidney disease, 1 with cervical cancer and 1 with Alzheimer's disease. While the control group included 30 cases with respiratory diseases, 44 with cerebrovascular diseases, 14 with cardiovascular diseases, 2 with malignant tumors and 50 with others. Patients' information, general situation before being admitted to MICU, drug therapy, invasive procedures and hospital-acquired infection were analyzed. Conditional logistic regression was performed to identify independent risk factors. RESULTS: Univariate analysis showed that factors such as more than 4 underlying diseases (OR = 4.63), APACHE-II score ≥ 20(OR = 10.29), stay in the general ward more than 1 week before being admitted to MICU, treatment with more than 3 kinds of antibiotics (OR = 8.03), endotracheal intubation (OR = 4.10) or tracheotomy (OR = 50.29) and mechanical ventilation (OR = 7.95) were risk factors for hospital-acquired lower respiratory tract infection by Stenotrophomonas maltophilia. Multivariate logistic regression showed that variables such as APACHE-II score (OR = 8.39), kinds of antibiotics used (OR = 5.96) and tracheotomy (OR = 28.92) were independent risk factors (P < 0.01). CONCLUSIONS: Underlying diseases, the severity of diseases, tracheotomy, mechanical ventilation, and the use of wide-spectrum antibiotics are important risk factors for lower respiratory tract infection by Stenotrophomonas maltophilia in MICU. To identify these factors and take preventive measures earlier may be useful for decreasing Stenotrophomonas maltophilia infection-related mortality.

Optimal Mean Arterial Pressure Within 24 Hours of Admission for Patients With Intermediate-Risk and High-Risk Pulmonary Embolism.

We aimed to determine whether the average mean arterial pressure (aMAP) in the first 24 hours of hospital admission is useful in predicting short-term outcomes of patients with intermediate- and high-risk pulmonary embolism (PE). We conducted a single-center retrospective study. From May 2012 to April 2019, 122 patients with intermediate- and high-risk PE were included. The primary outcome was in-hospital mortality. The secondary outcome was adverse events. Receiver operating characteristic (ROC) curves and cutoff values for aMAP predicting in-hospital death were computed. According to cutoff values, we categorized 5 groups defined as follows: group 1: aMAP < 70 mm Hg; group 2: 70 mm Hg ≤ aMAP < 80 mm Hg; group 3: 80 mm Hg ≤ aMAP < 90 mm Hg; group 4: 90 mm Hg ≤ aMAP <100 mm Hg; and group 5: aMAP ≥ 100 mm Hg. Cox regression models were calculated to investigate associations between aMAP and in-hospital death. In the study group of 122 patients, 15 (12.30%) patients died in the hospital due to PE. The ROC analysis for MAP predicting in-hospital death revealed an area under the curve of 0.729 with a cutoff value of 79.4 mm Hg. Cox regression models showed a significant association between in-hospital death and aMAP group 1 (ref), aMAP group 2 (odds ratio [OR] = 1.680, 95% CI: 0.020-140.335), aMAP group 3 (OR = 0.003, 95% CI: 0.0001-0.343), aMAP group 4 (OR = 0.006, 95% CI: 0.0001-1.671), and aMAP group 5 (OR = 0.003, 95% CI: 0.0001-9.744). In particular, those with an aMAP of 80 to 90 mm Hg had minimum adverse events. The optimal range of MAP for patients with intermediate- and high-risk PE may be 80 to 90 mm Hg.

[Hsa-let-7b-5p Inhibits Proliferation of Human Leukemia THP-1 Cells via FTO/m6A/MYC Signaling Pathway].

OBJECTIVE: To investigate the down-regulation effect of let-7b-5p on the expression of FTO in acute myeloid leukemia cell line THP-1 and inhibitory effect on THP-1 proliferation via m6A/MYC signaling pathway. METHODS: The acute myeloid leukemia cell line THP-1 and the normal human peripheral blood mononuclear cells (PBMNC) were selected as subjects. The expression of let-7b-5p and FTO mRNA in those cells was detected by qPCR, further the expression of FTO protein in those cells was detected by Western blot. And, the luciferase reporter gene assay was used to verify the targeting effect of let-7b-5p on FTO. Finally, THP-1 cells were transfected respectively with let-7b-5p mimic, and PBMNC with let-7b-5p inhibitor, there after the C-MYC mRNA m6A enrichment level in transfected cells was analyzed by dot blot, the expression levels of let-7b-5p, FTO and c-MYC were assayed by RT-PCR, the expressions of FTO and c-MYC protein were verified by Western blot, and the proliferation level of cells after transfection was detected by MTT assay. RESULTS: Compared with PBMNC, the expression of let-7b-5p in THP-1 significantly decreased, while the expression of FTO was significantly increased (P<0.05). After transfection with let-7b-5p mimic combined with FTO 3'-UTR, the luciferase activity of transfected THP-1 cells significantly decreased, but the luciferase activity significantly increased after transfection with mutant 3'-UTR, which was significantly different from the negative control group(blank vector) (P<0.05). Let-7b-5p inhibitor down-regulated c-MYC mRNA m6A enrichment, and then up-regulated the expression of FTO in transfected PBMNC cells, the effects of which were significant (P<0.05). However, let-7b-5p mimic up-regulated c-MYC mRNA m6A enrichment level and down-regulated the expression of FTO in the transfected THP-1 cells, and the cell proliferation rate was significantly lower than that in the negative control group (blank vector) (P<0.05). CONCLUSION: Human acute myeloid leukemia cell line THP-1 low expresses the let-7b-5p, which regulates c-MYC expression through let-7b-5p-/FTO-/m6A axis and promotes the proliferation of leukemia cell line THP-1.

Significance of Early Postoperative Arterial Lactic Acid, Inferior Vena Cava Variability, and Central Venous Pressure in Hypovolemic Shock.

INTRODUCTION: Up to one-third of patients admitted to the ICU are in circulatory shock, and early recognition of the condition is vital if subsequent tissue injuries are to be avoided. We would like to know what role the arterial lactic acid, inferior vena cava variability, and CVP (central venous pressure) play in the early stages of shock. METHODS: This is a retrospective study of patients who underwent surgical resuscitation in the Department of Critical Care Medicine. We use the ROC (receiver-operating characteristic) curve to evaluate the significance of each indicator in the diagnosis. For correlation analysis between groups, we first use linear regression for processing and then analysis with correlation. RESULTS: The ROC curve analysis shows that the area under the curve of the lactic acid group was 0.9272, the area under the curve of the inferior vena cava variability group was 0.8652, and the area under the curve of the CVP group was 0.633. Correlation analysis shows that the inferior vena cava variability and arterial lactic acid Pearson's r = 0.2863 and CVP and arterial lactic acid Pearson's r = 0.0729. CONCLUSION: The diagnostic value of arterial lactate is still very high and can still be used as an early warning indicator to help clinicians be alert to the microcirculatory disorders that have emerged quietly. The degree of inferior vena cava variability is linearly related to arterial lactic acid and can also be used as a reference indicator for early evaluation of shock. The diagnostic value of CVP is obviously lower.

Sepsis leads to thyroid impairment and dysfunction in rat model.

Sepsis was a systemic response to a local infection. Apoptosis was observed in the experimental sepsis. In this study, cecal ligation and puncture (CLP)-induced sepsis was established in rats. We found that sepsis decreased thyroid hormone levels, including triiodothyronine (T3), thyroxine (T4), free T3 (fT3), and free T4 (fT4). Besides, we detected the increasing expression level of Caspase-3 and increasing ratio of TUNEL positive cells in the thyroid after sepsis. Furthermore, a series of pathological ultrastructural changes were observed in thyroid follicular epithelial cells by CLP-induced sepsis. This study established a sepsis animal model and provided the cellular and molecular basis for decoding the pathological mechanism in thyroid with the occurrence of sepsis.