Survival Status Of Patients Research Articles

Effect of Type 2 Diabetes on the Development of Acute Respiratory Distress Syndrome (ARDS) in Patients with Lung Cancer After Surgery and Its Prognosis.

Type 2 diabetes mellitus (T2DM) is associated with the occurrence of lung cancer. Postoperative lung cancer complications with acute respiratory distress syndrome (ARDS) are characterized by rapid onset and severe disease. This study aimed to analyze the effect of T2DM on the occurrence of ARDS in patients with lung cancer after surgery and its prognosis and further investigate the risk factors of postoperative complications of ARDS. A total of 530 patients who developed lung cancer from December 2016 to December 2021 were retrospectively analyzed. The t- and chi-square tests were used to determine the relationship between whether the patients had combined diabetes and other clinical characteristics. Binary logistic and Cox risk regressions were used to analyze the independent risk factors for the development of ARDS in patients after surgery and the effect of each factor on the survival status of patients, respectively. Fifty-three cases of ARDS occurred after lung cancer surgery, with an incidence of 10%. Binary logistic regression analysis demonstrated that the independent influencing factors that determined the occurrence of ARDS after surgery were the presence or absence of combined diabetes (odds ratio [OR] = 3.888, P<0.001), history of radiotherapy (OR = 2.039, P = 0.024), surgery mode (OR = 2.521, P = 0.002), and so on. Moreover, Cox risk regression analysis demonstrated that the presence or absence of combined diabetes (OR = 1.389, P = 0.039) and occurrence of ARDS (OR = 2.028, P = 0.037) were independent influencing factors on the patient survival time. In lung cancer patients with T2DM, postoperative ARDS is more likely to occur, and both diabetes and postoperative ARDS are risk factors affecting the survival of patients with lung cancer. Preoperative and postoperative glycemic control and improved pulmonary ventilation should be enhanced to minimize the chance of ARDS.

Survival and predictors of mortality among acute leukemia patients on follow-up in Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia: A 5-year retrospective cohort study.

Although Ethiopia has more than 78% of leukemia cases and a significant burden of the disease, the survival of leukemia patients in the country is poorly recognized. The purpose of this study was to assess the survival and predictors of acute leukemia patients. A 5-year retrospective cohort study was conducted including all acute Leukemia patients who visited Tikur Anbessa Specialized Hospital between January 2015 and December 2019. Data were retrieved from patient's medical records between March and April 2020. Using SPSS version 25, the Kaplan-Meier curve and Cox regression models were employed to analyze the data. A total of 119 patients with acute leukemia were retrospectively evaluated for 60 months, having 196 person-years of risk. About 46 deaths (38.7%) were recorded over the follow-up period, giving a mortality incidence rate of 23.5 (95% CL:18-52) per 100 person-years. The median survival time was 35 months (95% CI, 28.3-41.7). At 60 months of follow-up, the predicted overall survival rate after diagnosis for acute leukemia was 21%. The adjusted hazard ratio for acute leukemia subtypes (aHR:4.9, 95% CI:2.3-10.4), history of relapse (aHR:3.9, 95% CI:1.0-7.9), participant age (aHR:1.25, 95% CI:1-1.75), hepatomegaly (aHR:2.7, 95% CI:1.36-5.36), and splenomegaly (aHR:2.29, 95% CI:1.2-4.4). The 5-year overall survival rate was found to be 21%. The finding was remarkably lower than other published reports. Survival among acute leukemia patients was significantly associated with older age, history of relapse, hepatomegaly, splenomegaly, as well as certain subtypes. Therefore, improving early detection and initiation of treatment for all acute leukemia patients is necessary in order to improve patient's survival status.

Noninvasive Radiation Markers Based on Lung Cancer CT Images and Dosimetry Features to Predict the Immune Response to Radiotherapy in Tumor Microenvironment

For lung cancer patients with complex conditions, doctors need to determine treatment plan in combination with changes of immune response during radiotherapy. It was urgent to find a strategy to predict immune response to intervene the treatment at an early stage. The radiotherapy process and tumor microenvironment status of 105 lung cancer patients were tracked and recorded in our hospital from 2019 to 2022, public database TCGA-LUAD/LUSC queue of TCIA image data was downloaded as external verification set. Data was analyzed according to the following methods: First, the 3D slicer software was used to process the CT imageomics data, and the doseomics information was calculated by DVHmetrics package from R software. Then Python was brought in to develop a non-invasive radiation scoring system through machine learning methods (T-test, LASSO, random forest and Xgboost). Finally, combined with the clinical information related to the patient's immune response, a nomogram was made to study the correlation between the score markers and the ratio of CD4 cells/CD8 cells in the tumor microenvironment, the prognosis of lung cancer, as well as the incidence of radiation pneumonia. The radiation markers score formula was obtained with CT imageomics and DVH dosimics features, which achieved an AUC of 0.67-0.75 in predicting CD4/CD8 condition in tumor microenvironment after radiotherapy. It was worth noticing that in predicting the prognosis of lung cancer, it was difficult to distinguish between the radiation score and the patient's survival status (P>0.05). However, we found that the radiation pneumonitis of lung cancer patients in the low score group (42.6%) was significantly higher than that in the high score group (13.4%). Radiation markers score was a non-invasive method to evaluate the immune response of patients with lung cancer, which can be used to predict the incidence of radiation pneumonitis.

Acral Lentiginous Melanoma: A Clinicoprognostic Study of 149 Cases at a Single Institution.

The objective of this study is to investigate the epidemiological features, clinical characteristics, and pathological characteristics of acral lentiginous melanoma (ALM) and identify prognostic factors. A total of 149 patients diagnosed with ALM between August 2008 and December 2019 at the National Cancer Center (NCC) of China were retrospectively analyzed. Follow-up data on patient survival status were collected. Survival curves were generated using the Kaplan-Meier method, and statistical significance was assessed using the log-rank test. Additionally, a Cox proportional hazards model was constructed to identify prognostic factors. All patients included in this study were of Chinese ethnicity, with an average age of 52.4 ± 14.8 years (range, 15-80years) at the time of diagnosis. No gender predilection or genetic susceptibility was observed. The plantar region was the most frequently affected site among primary lesions. Notably, only 17 (11.4%) patients reported a history of trauma. Statistical analysis revealed that a lesion duration of ≤2.5years, Breslow thickness >4.0mm, high mitotic rate (>6mm-2), presence of vascular invasion, and regional lymph node metastasis were identified as independent prognostic factors. Our findings indicate that a lesion duration of ≤2.5years, Breslow thickness >4.0mm, high mitotic rate (>6mm-2), presence of vascular invasion, and regional lymph node metastasis are significantly associated with a poorer prognosis for patients with ALM.

Survival status and risk factors for mortality among multidrug-resistant tuberculosis patients in Addis Ababa, Ethiopia: A retrospective follow-up study

BackgroundTuberculosis continues to be a major health concern around the world. It kills an estimated 1.6 million people each year. The World Health Organization (WHO) removed Ethiopia from its list of thirty countries having a high prevalence of MDR/RR-TB in 2021. As a result, the aim of this study was to assess the current context of survival status and risk factors of multidrug-resistant tuberculosis patients in Addis Ababa, Ethiopia, in 2022. MethodsAn institutional-based retrospective cohort study with 245 patients was undertaken using multidrug-resistant tuberculosis patients who were recruited from January 1st, 2018 to December 30th, 2021, in St. Peter's specialized hospital. To find independent predictors of survival status, Cox regression analysis was used. An adjusted hazard ratio with a 95% confidence interval and a p-value of < 0.05 was used to establish association and statistical significance. ResultsThe result of the study revealed that the incidence of mortality in this study was 13.1% (95% CI: 10.3–16.5). Moreover, being male (AOR = 3.7: 95% CI = 1.2, 11.4), old age (AOR = 14: 95% CI = 3.0, 60.4), site of TB (AOR = 0.2: 95% CI = 0.03, 0.6), and presence of comorbidity (AOR = 9.2: 95% CI = 2.4, 35.3), were independent predictors of time to death. ConclusionGenerally, the death rate among research participants was high. Moreover, male gender, old age, site of tuberculosis, and presence of other comorbidity were predictors of mortality among MDR-TB patients.

Predictors and outcomes of recurrent retroperitoneal liposarcoma with multiple tumors.

Retroperitoneal liposarcoma (RLS) is a rare but severe disease. Repeated postoperative recurrence with multiple tumors is a therapeutic dilemma. The clinical outcomes and survival predictors of recurrent RLS with multiple tumors remain to be explored. Patients with recurrent RLS were retrospectively analyzed. Univariate and multivariate analysis was performed to find independent prognostic factors that were correlated with Overall survival (OS) or progression-free survival (PFS). Factors significant in univariate analysis were further included into multivariate Cox proportional hazards regression model. The nomogram model was built to predict the survival status of patients. Variables that were significant in multivariable analysis were added to the internally validated nomogram models. The analysis of OS and PFS was performed by Kaplan-Meier analysis and log-rank test. A total of 113 recurrent RLS patients with multiple tumors were enrolled in the study. The 1-, 3-, and 5-years OS (PFS) rates were 70.7% (76.1%), 35.9% (76.1%), and 30.9% (76.1%), respectively. Univariate and multivariate analyses showed that number of surgeries, resection methods, tumor size, status of pathological differentiation, pathological subtypes, and recurrence patterns were important prognostic factors for OS or PFS (each p < 0.05). Nomogram models were established to efficiently predict the prognostic status of patients. Patients with the local recurrence (LR) pattern had a poor prognosis and would derive no survival benefit from combined organ resection and R0/R1 resection (each p < 0.05). RLS patients recurrence with multiple tumors had a poor prognosis. Those patients should be followed up more frequently after surgery. The strategies of aggressive resection may not improve the survival of patients with LR pattern in the retroperitoneum. Prognostic factors in the efficient nomogram models should be considered in the individualized clinical management of recurrent RLS with multiple tumors.

Epicardial adipose and pre-sternal subcutaneous tissues associated with extent of pneumonia and hospitalization in COVID-19

Objectives: The aims of this study were, to analyze epicardial adipose tissue and pre-sternal adipose tissue thicknesses and the relationship of the ratio of these two parameters with radiological progression, age, gender, concomitant diseases, hospitalization, length of hospital stay, need for intensive care and survival status of COVID-19 patients. Methods: In this retrospective study, a total number of 204 PCR-positive COVID-19 patients, who have initial lung computed tomography (CT) and a second CT within 15 days due to prolonged symptoms or suspected complications were included. According to patterns of lung involvement at the time of diagnosis, patients were divided into 4 groups. In initial CT scans, epicardial adipose tissue and pre-sternal subcutaneous adipose tissue thickness were measured. Progression or regression of the disease is evaluated by comparing the findings in initial and control CTs. Results: The mean age, epicardial adipose tissue thickness (EAT), pre-sternal adipose tissue thickness (PAT), and the EAT/PAT ratio of patients with involvement in both lungs were found to be higher than those in patients with one lung or without lung involvement and there was a statistically significant positive correlation between them. Conclusions: This study is thought to be the first in which epicardial adipose tissue and pre-sternal adipose tissue were evaluated together in COVID-19 patients. Epicardial adipose tissue is a metabolically active organ and measurement in initial CT scans may give an easy and quick idea of the evolution of the disease.

Prediction of prognosis of patients with hepatocellular carcinoma based on immune-related score

BackgroundImmune-related scores are currently used for prognostic evaluation and as an immunotherapy reference in various cancers. However, the relationship between immune-related score and hepatocellular carcinoma (HCC) prognosis has not yet been investigated. This study aimed to explore the clinical application value of immune-related score for predicting HCC prognosis-related indicators including disease-free survival (DFS) and overall survival (OS), and to construct a clinical nomogram prediction model related to verification. MethodsThis study included 284 HCC patients who were selected from the Cancer Genome Atlas (TCGA) database and linked to the immune-related score downloaded from the public platform. A Cox proportional hazards regression model was used to estimate the adjusted risk ratio, and a nomogram was constructed based on multivariate analysis results and clinical significance. The model was internally verified by bootstrap. The performance of the prediction model was evaluated using the C-index and calibration curves. ResultsPatients were divided into three subgroups according to the immune-related score level. Compared with patients in the low immune-related score group, the DFS of patients in the medium and high immune-related score groups was significantly prolonged (HR: 0.53, 95% CI: 0.32–0.87; HR: 0.37, 95% CI: 0.21–0.63, respectively). The OS of patients in the medium and high immune-related score groups was also significantly prolonged (HR: 0.43, 95% CI: 0.20–0.95, p = 0.038; HR: 0.29, 95% CI: 0.14–0.58, p < 0.001, respectively). The C-indexes for predicting DFS and OS were 0.687 (95% CI: 0.665–0.700) and 0.743 (95% CI: 0.709–0.776), respectively. The calibration curves of 3-year and 5-year DFS and OS showed that the results predicted by the nomogram were in good agreement with the actual observations. ConclusionsModerate/high-grade immune-related score was significantly associated with better DFS and OS in HCC patients. In addition, a nomogram for prognosis estimation can help clinicians predict the survival status of patients.

Construction of an aging-related risk signature in high-grade serous ovarian cancer for predicting survival outcome and immunogenicity.

Studies have shown that aging significantly impacts tumorigenesis, survival outcome, and treatment efficacy in various tumors, covering high-grade serous ovarian cancer (HGSOC). Therefore, the objective for this investigation is to construct an aging-relevant risk signature for the first time, which will help evaluate the immunogenicity and survival status for patients with HGSOC. Totaling 1727 patients with HGSOC, along with their mRNA genomic data and clinical survival data, were obtained based on 5 independent cohorts. The Lasso-Cox regression model was utilized to identify the aging genes that had the most significant impact on prognosis. The risk signature was developed by integrating the determined gene expression and accordant model weights. Additionally, immunocytes in the microenvironment, signaling pathways, and immune-relevant signatures were assessed based on distinct risk subgroups. Finally, 2 cohorts that underwent treatment with immune checkpoint inhibitor (ICI) were employed to confirm the effects of identified risk signature on ICI efficacy. An aging signature was constructed from 12 relevant genes, which showed improved survival outcomes in low-risk HGSOC patients across discovery and 4 validation cohorts (all P < .05). The low-risk subgroup showed better immunocyte infiltration and higher enrichment of immune pathways and ICI predictors based on further immunology analysis. Notably, in the immunotherapeutic cohorts, low-risk aging signature was observed to link to better immunotherapeutic outcomes and increased response rates. Together, our constructed signature of aging has the potential to assess not only the prognosis outcome and immunogenicity, but also, importantly, the efficacy of ICI treatment. This signature provides valuable insights for prognosis prediction and immunotherapeutic effect evaluation, ultimately promoting individualized treatment for HGSOC patients.

Vitamin D and smell impairment, routine histology for unilateral tonsillar enlargement, and a machine learning model for predicting the three-year survival status of patients with hypopharyngeal squamous cell carcinoma.

Vitamin D and smell impairment, routine histology for unilateral tonsillar enlargement, and a machine learning model for predicting the three-year survival status of patients with hypopharyngeal squamous cell carcinoma.

The Development of Immunotherapy for the Treatment of Recurrent Glioblastoma.

Recurrent glioblastoma (rGBM) is a highly aggressive form of brain cancer that poses a significant challenge for treatment in neuro-oncology, and the survival status of patients after relapse usually means rapid deterioration, thus becoming the leading cause of death among patients. In recent years, immunotherapy has emerged as a promising strategy for the treatment of recurrent glioblastoma by stimulating the body's immune system to recognize and attack cancer cells, which could be used in combination with other treatments such as surgery, radiation, and chemotherapy to improve outcomes for patients with recurrent glioblastoma. This therapy combines several key methods such as the use of monoclonal antibodies, chimeric antigen receptor T cell (CAR-T) therapy, checkpoint inhibitors, oncolytic viral therapy cancer vaccines, and combination strategies. In this review, we mainly document the latest immunotherapies for the treatment of glioblastoma and especially focus on rGBM.

Overall Survival, BRAF, RAS, and MSI Status in Patients Who Underwent Cetuximab After Refractory Chemotherapy for Metastatic Colorectal Cancer.

Evaluate overall survival (OS), RAS, BRAF, and MSI frequencies in patients with metastatic colorectal cancer (mCRC), refractory to chemotherapy, and finally treated with cetuximab. A retrospective cohort study to evaluate 211 mCRC patients with wild-type KRAS treated with cetuximab. BRAF V600E, KRAS, NRAS gene mutations, and MSI status were identified using PCR techniques in a population of pre-treated patients who were refractory to fluoropyrimidines, oxaliplatin, and irinotecan. In addition, we evaluated the mutation frequency of the BRAF and NRAS genes and the MSI status of this population. Uni- and multivariate analyses were performed for independent prognostic factors of OS. The median OS was 10.4months, 6.6months for patients with right and 11.5months for left colon cancers (p = 0.02). The frequencies of mutations were BRAF at 3.9% (median OS of 4.9months), NRAS at 3.38% (median OS of 6.9months), and MSI-High status at 3.3% (median OS of 4.6months). The OS, NRAS, and MSI frequencies were similar to those found in other studies that evaluated cetuximab in poly-treated patients and were associated with lower survival rates in univariate analyses. The frequency of BRAF mutations was lower than that found in previous studies. The only variable that remained significant for OS in the multivariate model was tumour laterality, with patients with right colon cancer presenting a worse prognosis (HR = 2.81). Although BRAF, NRAS mutations, and MSI-High status were associated with shorter OS in univariate analyses, only tumour laterality remained an independent prognostic factor in the multivariate analysis.

Development of a prognostic model for personalized prediction of colon adenocarcinoma (COAD) patient outcomes using methylation-driven genes.

The objective of this study was to identify methylation-driven genes and explore their prognostic value in colon adenocarcinoma (COAD). The Cancer Genome Atlas (TCGA) database was used to acquire collated COAD transcriptome gene expression matrix (containing 59,427 transcripts), transcriptome gene methylation level matrix (containing 29,602 methylated modified genes), which included 517 samples containing 41 samples of normal tissue (NT) &476 samples of COAD, and patient clinical information files (including patient survival time, survival status, age, gender and tumor stage, etc.), for all COAD samples. A total of 9807 differentially expressed genes (DEGs) were obtained by DEG analysis of the COAD transcriptional expression matrix, of which 5874 were up-regulated and 3933 were down-regulated. And 46 methylation-driven DEGs (MD-DEGs) in COAD were obtained by DEG analysis, differential analysis of gene methylation levels, and correlation analysis between them. Next, three prognostic associated MD-DEGs (PMD-DEGs) (IDUA, ZBTB18 and C5orf38) were identified by Cox regression analysis, and a prognostic model composed of the three PMD-DEGs was constructed by least absolute shrinkage and selection operator (LASSO) regression analysis and cross-validation analysis. In addition, survival analysis, the receiver operating characteristics (ROC) curve analysis and independent prognostic analysis were used to evaluate and verify that the prognostic model we constructed could accurately and independently predict the prognosis of COAD patients. Finally, we constructed a nomogram based on the prognosis model to accurately and personalized predict the survival prognosis of COAD patients. In conclusion, we identified the methylation driver gene of COAD and constructed a prognostic model and nomogram to personalized predict the prognosis of patients, which opened a new prospect for accurate diagnosis and treatment in clinical practice.

Survival status and predictors of mortality among adult Stroke patients admitted to Jimma University Medical Center, South west Ethiopia: A retrospective Cohort study.

Stroke is the leading cause of cardiovascular disease death in sub-Saharan Africa and the second leading cause of mortality worldwide. In 2016, 6.23% of all fatalities in Ethiopia were stroke-related. To assess survival status and predictors of mortality among adult stroke patients admitted to Jimma University Medical Center from April 1/2017 to March 31/2022. A retrospective cohort study was conducted on 480 adult stroke patients selected by simple random sampling from patients admitted to the Jimma University Medical Center Stroke Unit from April 1, 2017 to March 31, 2022. Data were extracted from May to June 2022 and entered Epi-data v.3.1 and analyzed by R v.4.2. The Kaplan-Meier curve with Log rank test was used to estimate survival time and to compare survival experience between categories of explanatory variables. The Cox regression model was computed to identify predictors of survival status in stroke patients. Then the 95% CI of the hazard ratio was set with corresponding p-value < 0.05 to declare statistical significance. During 4350 person-days of follow-up; 88 (18.33%) patients died; resulting in an incidence mortality of 20.23 per 1000 person-days, with a median survival time of 38 days. Glasgow coma score <8 on admission (AHR = 7.71; 95% CI: 3.78, 15.69), dyslipidemia (AHR = 3.96; 95% CI: 2.04, 7.69), aspiration pneumonia (AHR 2.30; 95% CI: 1.23-4.26), and increased intracranial pressure (AHR = 4.27; 95% CI: 2.33, 7.81), were the independent predictors of the time until death. The incidence of stroke mortality was higher at the seven and fourteen days. Glasgow Coma Scale, increased intracranial pressure, dyslipidemia, and aspiration pneumonia were independent predictors of mortality.

TMEM41A overexpression correlates with poor prognosis and immune alterations in patients with endometrial carcinoma.

Expression levels of transmembrane protein 41A (TMEM41A) are related to the progression of malignant tumors. However, the association between TMEM41A expression and endometrial carcinoma (EC) remains unclear. This study aims to identify the roles of TMEM41A expression in the prognosis of patients with EC and its correlation with EC progression. The TMEM41A expression and its correlation with the survival of patients with EC were assessed. Cox regression analysis was used to identify the prognostic factors, while nomograms were used to examine the association between the prognostic factors and the survival of patients with EC. Finally, the link between TMEM41A level and immune microenvironment and RNA modifications was investigated in EC. TMEM41A was overexpressed in EC. TMEM41A overexpression could diagnose the EC and evaluate the poor prognosis of patients. Overexpression of TMEM41A was associated with clinical stage, age, weight, histological subtype, tumor grade, and survival status of patients with EC. Clinical stage, age, tumor grade, radiotherapy, and TMEM41A overexpression were factors of poor prognosis in patients with EC. The nomograms revealed the correlation between the TMEM41A level and survival time of patients with EC at 1, 3, and 5 years. Furthermore, TMEM41A overexpression was significantly correlated with the level of the stromal score, immune score, estimate score, NK CD56 bright cells, iDC, NK cells, eosinophils, pDC, T cells, TReg, cytotoxic cells, mast cells, Th17 cells, neutrophils, aDC, NK CD56 dim cells, TFH, Th2 cells, CD8 T cells, macrophages, immune cell markers, and RNA modifications. TMEM41A is overexpressed in EC tissues and is associated with the prognosis, immune microenvironment, and RNA modification. Our preliminary studies indicate that overexpression of TMEM41A can potentially serve as a biomarker for EC treatment.

Multi-center validation of an immune-related lncRNA signature for predicting survival and immune status of patients with renal cell carcinoma: an integrating machine learning-derived study.

Long noncoding RNAs (lncRNAs) have been reported to play an important role in tumor immune modification. Nonetheless, the clinical implication of immune-associated lncRNAs in renal cell carcinoma (RCC) remains to be further explored. 76 combinations of machine learning algorithms were integrated to develop and validate a machine learning-derived immune-related lncRNA signature (MDILS) in five independent cohorts (n = 801). We collected 28 published signatures and collated clinical variables for comparison with MDILS to verify its efficacy. Subsequently, molecular mechanisms, immune status, mutation landscape, and pharmacological profile were further investigated in different stratified patients. Patients with high MDILS displayed worse overall survival than those with low MDILS. The MDILS could independently predict overall survival and convey robust performance across five cohorts. MDILS has a significantly better performance compared with traditional clinical variables and 28 published signatures. Patients with low MDILS exhibited more abundant immune infiltration and higher potency of immunotherapeutic response, while patients with high MDILS might be more sensitive to multiple chemotherapeutic drugs (e.g., sunitinib and axitinib). MDILS is a robust and promising tool to facilitate clinical decision-making and precision treatment of RCC.

Thromboelastography Parameter and Its Association with Survival of COVID-19 Patients: A Retrospective Cross-Sectional Study

Introduction: Coagulopathy associated with Coronavirus disease 2019 (COVID-19) may cause life-threatening complications, especially in severe or critically ill COVID-19 patients. Thromboelastography (TEG) is an effective, dynamic, and reliable test to assess the complete coagulation process. This study aimed to determine the association between selected TEG parameters and survival in COVID-19 patients. Methods: This study was a retrospective observational study using data from medical records of COVID-19 patients who were hospitalized in Dr. Soetomo Hospital, Surabaya, Indonesia. There were 94 COVID-19 patients consisting of 76 survivors and 18 non-survivors. The association between TEG results and certain TEG parameters with survival status was considered significant if the p-value ≤ 0.05. Results: Increased coagulation activity had a significant association with the survival status of COVID-19 patients (p=0.04). There were no significant differences in all TEG parameters between COVID-19 patients who survived and those who did not survive (p &gt; 0.05). Based on the TEG analysis tree, the most TEG results found were secondary fibrinolysis (21.3%) and fibrinolytic shutdown (24.5%). No significant association was found between the coagulability and fibrinolysis abnormality with the survival status in COVID-19 patients (p &gt; 0.05). Conclusion: There was no significant difference in TEG results between COVID-19 survivors and non-survivors. However, based on the TEG result, an increase in coagulation activity is associated with a lower survival rate. Further study with detailed timing of TEG examination, disease severity and comorbidities stratification in COVID-19 patients may be needed.

Role of Coagulation Parameters and Inflammatory Biomarkers in Coronavirus Disease 2019 Patients: A Demystifying Endeavor

BACKGROUND: Coronavirus disease 2019 (COVID-19) globally known as COVID-19 is a heterogeneous disease caused by the severe acute respiratory syndrome coronavirus 2. COVID-19 patients having severe disease and are critically ill are more prone to have abnormal coagulation prolife. It may lead to thromboinflammation in severe conditions. AIM: The aim is to evaluate the utility of coagulation parameters and inflammatory biomarkers in COVID-19 patients in the study conducted for 6 months duration. MATERIALS AND METHODS: It was a retrospective observational study conducted from April 2021 to September 2021 in a rural tertiary care referral Institute. Available data of the baseline values of coagulation parameters (platelet count [PLC], prothrombin time [PT], international normalized ratio [INR], partial thromboplastin time [PTT] and D-dimer) and inflammatory markers (C-reactive protein [CRP], serum lactate dehydrogenase [LDH], and serum ferritin) were evaluated with respect to the clinical severity of the disease and also the survival status of COVID-19 patients. RESULTS: One hundred and fifty-five cases of COVID-19-positive patients were analyzed. PT, INR, PTT, D-dimer, CRP, LDH, and ferritin had higher mean in severe cases than the nonsevere cases. PLC had higher mean in the severe cases than the nonsevere cases. PT, INR, PTT, D-dimer, CRP, LDH and ferritin had higher mean in nonsurvivors than the survivors. PLC had lower mean in nonsurvivors than the survivors. CONCLUSION: Baseline values of PT, INR, PTT, D-dimer, LDH, and ferritin may be considered reliable indicators of severity of COVID-19 disease. Baseline values of D-dimer, LDH, and ferritin may be considered a reliable indicator of survival of patients suffering from COVID-19 infection.

Role of β-catenin in PD-L1 expression of nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is a particular type of tumor connected to Epstein-Barr virus infection, genetic, and environmental factors. It is typically discovered late, with few therapeutic options and poor clinical outcomes. Cellular immune responses can be attenuated when programmed death ligand 1 (PD-L1) and programmed cell death protein 1 (PD-1) are combined. Although PD-1 inhibitors have a different anti-tumor response rate than chemotherapy alone, they can nevertheless considerably outperform chemotherapy in patients with metastatic or recurrent NPC. The nuclear β-catenin can bind to the CD274 promoter region, promoting transcription and upregulating the expression of tumor-specific PD-L1. Separation of β-catenin from E-cadherin and translocation it into nucleus were both aided by β-catenin phosphorylates at the Tyr654 site. Its function in NPC and the expression of PD-L1 have not yet been investigated. This study investigated the predictive significance of PD-L1 and p-β-cateninTyr654 expressions in NPC. Our findings indicated that patients with distant metastases or poor prognoses exhibited higher levels of PD-L1 and p-β-cateninTyr654 expressions. According to Cox multivariate prognostic analysis, PD-L1 was also an effective indicator for predicting the survival status of patients with NPC. We subsequently demonstrated that PD-L1 transcription and protein production could be downregulated by targeting inhibition of the level of β-catenin in NPC cells. This is for developing the β-catenin or TCF4 inhibitor as a potential new option for immune checkpoint immunosuppression in NPC.

SRSF1 induces glioma progression and has a potential diagnostic application in grading primary glioma.

Glioma is the most common intracranial tumor of the central nervous system in adults; however, the diagnosis of glioma, and its grading and histological subtyping, is challenging for pathologists. The present study assessed serine and arginine rich splicing factor 1 (SRSF1) expression in 224 glioma cases in the Chinese Glioma Genome Atlas (CGGA) database, and verified its expression by immunohistochemical analysis of specimens from 70 clinical patients. In addition, the prognostic potential of SRSF1 concerning the survival status of patients was evaluated. In vitro, the biological role of SRSF1 was assessed using MTT, colony formation, wound healing and Transwell assays. The results revealed that SRSF1 expression was significantly associated with the grading and the histopathological subtype of glioma. As determined using a receiver operating characteristic curve analysis, the specificity of SRSF1 for glioblastoma (GBM) and World Health Organization (WHO) grade 3 astrocytoma was 40 and 48%, respectively, whereas the sensitivity was 100 and 85%. By contrast, pilocytic astrocytoma tumors exhibited negative immunoexpression of SRSF1. Additionally, Kaplan-Meier survival analysis indicated that high SRSF1 expression predicted a worse prognosis for patients with glioma in both the CGGA and clinical cohorts. In vitro, the results demonstrated that SRSF1 promoted the proliferation, invasion and migration of U87MG and U251 cells. These data suggested that immunohistochemical analysis of SRSF1 expression is highly sensitive and specific in the diagnosis of GBM and WHO grade 3 astrocytoma, and may have an important role in glioma grading. Furthermore, the lack of SRSF1 is a potential diagnostic biomarker for pilocytic astrocytoma. However, neither in oligodendroglioma and astrocytoma, nor in GBM was an association detected between SRSF1 expression and IDH1 mutations or 1p/19q co-deletion. These findings indicated that SRSF1 may serve as a prognostic factor in glioma cases and could have an active role in promoting glioma progression.