Red Cell Distribution Width as a Predictor of Survival in Patients with Hepatocellular Carcinoma.

Background and Objectives. Hepatocellular carcinoma (HCC) and the intrahepatic biliary tract cancers are estimated to rank sixth for incidence among solid cancers worldwide, and third for mortality rates. A critical issue remains the need for accurate biomarkers for risk stratification and overall prognosis. The aim of this study was to investigate the ability of a biomarker of heterogeneity of the size of red blood cells, the red cell distribution width (RDW), to predict survival in patients with HCC. Materials and Methods. A consecutive series of patients with a histologic diagnosis of HCC were included into this study irrespective of their age, stage of the disease, and treatment administered, and followed-up for a period of three years. Demographic, anthropometric [age, sex, body mass index (BMI)], and clinical data (Charlson Comorbidity Index, Child-Pugh score, etc.), along with laboratory tests were retrieved from clinical records. Results. One-hundred and four patients were included in this study. Among them, 54 (69%) were deceased at the end of the follow-up. Higher RDW values, but not other hematological and biochemical parameters, were significantly associated with mortality in both univariate and multivariate analysis. The optimal RDW cut-off value identified with the Youden test for survival was 14.7%, with 65% sensitivity and 74% specificity (AUC = 0.718, 95% CI 0.622-0.802, p < 0.001). Kaplan-Meier survival curves showed significantly lower survival with higher RDW values (HR = 3.5204; 95% CI 1.9680-6.2975, p < 0.0001) with a mean survival of 30.9 ± 9.67 months for patients with RDW ≤ 14.7% and 22.3 ± 11.4 months for patients with RDW > 14.7%. Conclusions. The results of our study showed that RDW can perform better than other blood-based biomarkers in independently predicting prognosis in patients with HCC.

Association between ischemia-modified albumin (IMA) and peripheral endothelial dysfunction in rheumatoid arthritis patients.

The identification of circulating biomarkers of endothelial dysfunction (ED), a precursor to atherosclerosis, in rheumatoid arthritis (RA) would facilitate early risk stratification and prevention strategies. Ischemia-modified albumin (IMA) has emerged as a potential biomarker of oxidative stress, ischemia, and ED. However, studies examining the relationship between IMA and ED in RA patients are lacking. We measured serum IMA concentrations by using an albumin cobalt binding test and peripheral vasodilatory capacity by EndoPAT in 113 RA patients without previous cardiovascular events enrolled in the EDRA study (ClinicalTrials.gov: NCT02341066). The mean peripheral vasodilatory capacity, expressed by the log of reactive hyperemia index (logRHI), was 0.82, corresponding to 27% RA patients having ED. The mean plasma concentrations of IMA were 0.478 absorbance units. We observed a significant and inverse association between peripheral vasodilatory capacity and serum IMA concentrations (rho = - 0.22, p = 0.02). In univariate logistic regression, ED was significantly associated with serum IMA concentrations [OR 1173 (95% CI 1.3568 to 101,364), p = 0.040) and higher disease activity. In multivariate logistic regression, the independent association between ED and IMA remained significant after correction for disease activity and other RA-confounders [OR 2252 (95% CI 1.0596 to 4,787,505), p = 0.048 in Model 1; OR 7221 (95% CI 4.1539 to 12,552,859), p = 0.02 in Model 2]. Conclusions: This study suggests that IMA is a promising biomarker of ED in RA. Further research is needed to confirm our findings and determine the clinical utility of IMA in detecting and managing early atherosclerosis in RA patients.

Metformin-mediated epigenetic modifications in diabetes and associated conditions: Biological and clinical relevance.

An intricate interplay between genetic and environmental factors contributes to the development of type 2 diabetes (T2D) and its complications. Therefore, it is not surprising that the epigenome also plays a crucial role in the pathogenesis of T2D. Hyperglycemia can indeed trigger epigenetic modifications, thereby regulating different gene expression patterns. Such epigenetic changes can persist after normalizing serum glucose concentrations, suggesting the presence of a 'metabolic memory' of previous hyperglycemia which may also be epigenetically regulated. Metformin, a derivative of biguanide known to reduce serum glucose concentrations in patients with T2D, appears to exert additional pleiotropic effects that are mediated by multiple epigenetic modifications. Such modifications have been reported in various organs, tissues, and cellular compartments and appear to account for the effects of metformin on glycemic control as well as local and systemic inflammation, oxidant stress, and fibrosis. This review discusses the emerging evidence regarding the reported metformin-mediated epigenetic modifications, particularly on short and long non-coding RNAs, DNA methylation, and histone proteins post-translational modifications, their biological and clinical significance, potential therapeutic applications, and future research directions.

Applying precision medicine principles to the management of multimorbidity: the utility of comorbidity networks, graph machine learning, and knowledge graphs.

The current management of patients with multimorbidity is suboptimal, with either a single-disease approach to care or treatment guideline adaptations that result in poor adherence due to their complexity. Although this has resulted in calls for more holistic and personalized approaches to prescribing, progress toward these goals has remained slow. With the rapid advancement of machine learning (ML) methods, promising approaches now also exist to accelerate the advance of precision medicine in multimorbidity. These include analyzing disease comorbidity networks, using knowledge graphs that integrate knowledge from different medical domains, and applying network analysis and graph ML. Multimorbidity disease networks have been used to improve disease diagnosis, treatment recommendations, and patient prognosis. Knowledge graphs that combine different medical entities connected by multiple relationship types integrate data from different sources, allowing for complex interactions and creating a continuous flow of information. Network analysis and graph ML can then extract the topology and structure of networks and reveal hidden properties, including disease phenotypes, network hubs, and pathways; predict drugs for repurposing; and determine safe and more holistic treatments. In this article, we describe the basic concepts of creating bipartite and unipartite disease and patient networks and review the use of knowledge graphs, graph algorithms, graph embedding methods, and graph ML within the context of multimorbidity. Specifically, we provide an overview of the application of graph theory for studying multimorbidity, the methods employed to extract knowledge from graphs, and examples of the application of disease networks for determining the structure and pathways of multimorbidity, identifying disease phenotypes, predicting health outcomes, and selecting safe and effective treatments. In today's modern data-hungry, ML-focused world, such network-based techniques are likely to be at the forefront of developing robust clinical decision support tools for safer and more holistic approaches to treating older patients with multimorbidity.

C-reactive protein and 10-year cardiovascular risk in rheumatoid arthritis.

OBJECTIVES: To evaluate the association between C-reactive protein (CRP) and 10-year risk of cardiovascular (CV) events using the Expanded Cardiovascular Risk Prediction Score for Rheumatoid Arthritis (ERS-RA), based on conventional and RA-specific risk factors but not CRP, in RA patients without previous cardiovascular events. METHODS: ERS-RA was calculated in 1,251 "Cardiovascular Obesity and Rheumatic Disease Study (CORDIS)" database patients [(age 60.4(9.3) years; 78% female; disease duration, 11.6(8) years; CDAI, 9(9); CRP, 6.8(12) mg/L]. RESULTS: The mean (SD) 10-year risk of CV events was 12.9% (10). After adjusting for the use of DMARDs and biologics, CRP concentrations were significantly associated with 10-year risk of CV events (coefficient=0.005 for each 10 mg/L CRP increment; 95%CI 0.000-0.111; p = 0.047). In mediation analysis, the association between CRP and ERS-RA was not explained by disease activity. CONCLUSION: In a large cohort of RA patients without previous cardiovascular events, a 20 mg/L increase in CRP concentrations was associated with a 1% increase in 10-year risk of CV events. This suggests that actively targeting residual inflammatory risk beyond conventional and RA-specific risk factors might further reduce CV event rates in RA patients.

Placebo response in psoriatic arthritis clinical trials: a systematic review and meta-analysis.

OBJECTIVE: To determine the placebo response rate in PsA randomized clinical trials (RCTs), its contributing factors and impact on the effect size of active treatments. METHODS: We searched multiple databases, from inception to 20 December 2020, for placebo-controlled RCTs in PsA. We used a random-effects meta-analysis to pool the response rates for the ACR20 criteria in the placebo arm, determined the risk difference for treatment vs placebo, and used meta-regression to determine the factors associated with placebo response rates. The risk of bias was assessed in duplicate. The study protocol was registered with PROSPERO: CRD42021226000. RESULTS: We included 42 RCTs (5050 patients receiving placebo) published between 2000 and 2020. The risk of bias was low in 28 trials, high in four, and with some concerns in 10. The pooled placebo response rate was 20.3% (95% CI: 18.6%, 22.1%; predicted intervals, 11.7-29.0%), with significant between-trial heterogeneity (I2 = 56.8%, P < 0.005). The pooled risk difference for treatment vs placebo was 27% (95% CI: 24%, 31%). In the multivariable meta-regression, there was a 15% (95% CI: 2.9%, 29.8%) increase in the odds of achieving the placebo response for each 5-year increment in publication year (P = 0.016). In addition, the active treatment risk difference decreased for every 5-year increment in publication year (ß = -0.053, 95% CI: -0.099, -0.007; P = 0.024) but was not associated with the placebo response. CONCLUSION: Despite increasing over time, the placebo response for ACR20 in PsA RCTs was not associated with the active treatment effect size.

Blood Cell Count Biomarkers, Risk, and Outcomes of Ischemia-Related Lower Limb Amputations: A Systematic Review.

Lower limb amputations due to ischemia represent an important health care and social issue. However, there are currently no specific biomarkers able to predict the risk of amputation and postamputation complications and prognosis. We conducted a systematic review of studies investigating whether blood cell count indexes of systemic inflammation are linked to the risk and the outcome of lower limb amputations due to ischemia. Overall, in 22 studies involving 8832 patients selected for review, several blood cell count indexes, particularly the neutrophil lymphocyte ratio, showed some promise in terms of predicting amputations and general outcomes of conservative and surgical treatments, as well as postamputation complications and prognosis. However, largely due to methodological limitations, further prospective studies are required to establish the clinical utility and applicability of blood cell indexes in the routine management of patients with ischemia-related lower limb amputations.

Red Blood Cell Distribution Width (RDW) Correlates to the Anatomical Location of Colorectal Cancer. Implications for Clinical Use.

PURPOSE: The pathological, clinical, and therapeutic features of colorectal cancer (CRC) depend on its anatomical localization. We investigated possible associations between the red blood cell distribution width (RDW) and CRC localization. METHODS: Two-hundred eighty-eight consecutive patients with CRC were retrospectively studied. Demographic, clinical, pathological and laboratory data were retrieved from clinical records and reports. RESULTS: Median RDW values were significantly higher in patients with right-sided CRC when compared to those with CRC in other localizations (16.2, IQR: 14.5-20.0 vs 13.8, IQR: 13.0-16.1, p < 0.0001). Anisocytosis was statistically associated to haemoglobin (Hb), mean haemoglobin concentration (MHC), and mean corpuscular volume (MCV) values in all the patient groups examined. A cut-off value of 14.3% was associated with right-sided localization with sensitivity and specificity of 76.3% and 64.2%, respectively (AUC 0.71). CONCLUSION: Median RDW values were significantly higher in right-sided CRC when compared to other tumour locations, and may represent an additional marker for differential diagnosis.

Estimated 10-year cardiovascular risk in a large Italian cohort of rheumatoid arthritis patients: Data from the Cardiovascular Obesity and Rheumatic DISease (CORDIS) Study Group.

BACKGROUND: Several cardiovascular (CV) risk algorithms are available to predict CV events in the general population. However, their performance in patients with rheumatoid arthritis (RA) might differ from the general population. This cross-sectional multicentre study aimed to estimate the 10-year CV risk using two different algorithms in a large RA cohort and in patients with osteoarthritis (OA). METHODS: In a consecutive series of RA patients and matched OA controls without prior CV events, clinical and serologic data and traditional CV risk factors were recorded. The 10-year CV risk was assessed with the Systematic COronary Risk Evaluation (SCORE) and the "Progetto Cuore" algorithms. RESULTS: 1,467 RA patients and 342 OA subjects were included. RA patients were more frequently diabetic (9.9% vs 6.4%; p=0.04) and smokers (20.4% vs 12.5%; p=0.002) but had lower prevalence of obesity (15% vs 21%; p=0.003). Dyslipidaemia was more prevalent in OA (32.5% vs 21.7%; p<0.0001). The 10-year estimated CV risk was 1.6% (95%CI 1.3-1.9) in RA and 1.4% (95%CI 1.3-1.6) in OA (p=0.002) according to SCORE and 6.5% (95%CI 6.1-6.9) in RA and 4.4% (95%CI 3.9-5.1) in OA (p<0.001) according to "Progetto Cuore". Regardless of the score used, RA patients had a 3- to-4-fold increased 10-year risk of CV events compared to OA subjects. CONCLUSION: RA patients have a significantly higher 10-year risk of CV events than OA subjects. In addition to effective disease control and joint damage prevention, specific protective measures targeting modifiable traditional CV risk factors should be implemented in RA.

Prevalence and risk factors of moderate to severe hepatic steatosis in patients with rheumatoid arthritis: an ultrasonography cross-sectional case-control study.

BACKGROUND: The independent association between hepatic steatosis and rheumatoid arthritis is poorly defined. METHODS: The presence of moderate to severe steatosis was assessed, using liver ultrasonography, in 364 consecutive non-diabetic subjects (223 patients with rheumatoid arthritis and 141 age- and sex-matched healthy controls). Adjusted multiple regression analysis was performed to explore the association between rheumatoid arthritis and moderate to severe steatosis in the overall sample and identify independent risk factors in the rheumatoid arthritis subgroup. RESULTS: The prevalence of moderate to severe steatosis in the overall sample was 31.3%, with a significantly higher prevalence in patients with rheumatoid arthritis than healthy controls (38.7% versus 19.7%, p < 0.0001). After adjustment for sex, age, cholesterol, triglycerides, body mass index, waist, hypertension and smoke, rheumatoid arthritis remained significantly associated with moderate to severe steatosis [odds ratio (95% confidence interval) = 2.24 (1.31, 3.84); p = 0.003]. In the rheumatoid arthritis group, male sex, higher body mass index, higher triglycerides concentrations and higher cumulative dosage of methotrexate [odds ratio (95% confidence interval) = 1.11 (1.01, 1.23); p = 0.026] were significantly associated with moderate to severe steatosis, while systemic inflammation, disease activity, use of steroids and biologics were not. CONCLUSION: Rheumatoid arthritis is independently associated with moderate to severe steatosis, with male sex, higher body mass index and cumulative dose of methotrexate being predisposing factors. Further prospective studies are warranted to confirm our findings and to investigate the effect of steatosis on liver outcomes in the rheumatoid arthritis population.

Circulating Superoxide Dismutase Concentrations in Obstructive Sleep Apnoea (OSA): A Systematic Review and Meta-Analysis.

Obstructive Sleep Apnoea (OSA) is characterized by a pro-oxidant state that results from the recurrent hypoxia-reoxygenation cycles. Superoxide dismutase (SOD), a key antioxidant enzyme involved in the detoxification of superoxide radicals, could represent a reliable marker to monitor the antioxidant defences in OSA. In order to capture and critically appraise the available evidence, we performed a systematic review and meta-analysis of studies reporting SOD concentrations in OSA patients and non-OSA controls in the electronic databases Pubmed, Web of Science, Scopus and Google Scholar. In total, 13 studies in 847 OSA patients and 438 non-OSA controls were included in the meta-analysis. Blood SOD concentrations were significantly lower in OSA patients (SMD = 0.87, p < 0.001). By contrast, serum/plasma SOD concentrations were not significantly different between the two groups. Although extreme between-study heterogeneity was observed, the SMD was not substantially modified when individual studies were sequentially removed. In conclusion, we observed that whole blood, but not serum/plasma, SOD concentrations were significantly lower in OSA patients compared with controls. Our meta-analysis suggests an impaired antioxidant defence in OSA that is more robustly assessed in the corpuscular biological matrix and provides useful background information for further studies investigating the association between SOD changes and clinical status in OSA.

The Aggregate Index of Systemic Inflammation (AISI): A Novel Prognostic Biomarker in Idiopathic Pulmonary Fibrosis.

Variable patterns of disease progression are typically observed in patients with idiopathic pulmonary fibrosis (IPF). We sought to determine the prognostic capacity of blood cell count indexes, derived from routine complete blood cell (CBC) count, in a cohort of IPF patients. The neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic inflammation index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI) were calculated at baseline in a consecutive series of 82 IPF patients followed for four years. After adjusting for age, gender, body mass index, smoking status, and disease stage, only the AISI was significantly associated with mortality (HR 1.0013, 95% CI 1.0003-1.0023, p = 0.015). Patients with AISI <434 and ≥434 had a median survival from the diagnosis of 35.3 ± 15.2 and 26.6 ± 16.3 months (p = 0.015), and a four-year survival rate of 54% and 34%, respectively. The AISI, easily derivable from routine laboratory tests, is independently associated with mortality in patients with IPF. Prospective studies in larger cohorts are required to confirm this association.

Use of Multiprognostic Index Domain Scores, Clinical Data, and Machine Learning to Improve 12-Month Mortality Risk Prediction in Older Hospitalized Patients: Prospective Cohort Study.

BACKGROUND: The Multidimensional Prognostic Index (MPI) is an aggregate, comprehensive, geriatric assessment scoring system derived from eight domains that predict adverse outcomes, including 12-month mortality. However, the prediction accuracy of using the three MPI categories (mild, moderate, and severe risk) was relatively poor in a study of older hospitalized Australian patients. Prediction modeling using the component domains of the MPI together with additional clinical features and machine learning (ML) algorithms might improve prediction accuracy. OBJECTIVE: This study aims to assess whether the accuracy of prediction for 12-month mortality using logistic regression with maximum likelihood estimation (LR-MLE) with the 3-category MPI together with age and gender (feature set 1) can be improved with the addition of 10 clinical features (sodium, hemoglobin, albumin, creatinine, urea, urea-to-creatinine ratio, estimated glomerular filtration rate, C-reactive protein, BMI, and anticholinergic risk score; feature set 2) and the replacement of the 3-category MPI in feature sets 1 and 2 with the eight separate MPI domains (feature sets 3 and 4, respectively), and to assess the prediction accuracy of the ML algorithms using the same feature sets. METHODS: MPI and clinical features were collected from patients aged 65 years and above who were admitted to either the general medical or acute care of the elderly wards of a South Australian hospital between September 2015 and February 2017. The diagnostic accuracy of LR-MLE was assessed together with nine ML algorithms: decision trees, random forests, extreme gradient boosting (XGBoost), support-vector machines, naïve Bayes, K-nearest neighbors, ridge regression, logistic regression without regularization, and neural networks. A 70:30 training set:test set split of the data and a grid search of hyper-parameters with 10-fold cross-validation-was used during model training. The area under the curve was used as the primary measure of accuracy. RESULTS: A total of 737 patients (female: 370/737, 50.2%; male: 367/737, 49.8%) with a median age of 80 (IQR 72-86) years had complete MPI data recorded on admission and had completed the 12-month follow-up. The area under the receiver operating curve for LR-MLE was 0.632, 0.688, 0.738, and 0.757 for feature sets 1 to 4, respectively. The best overall accuracy for the nine ML algorithms was obtained using the XGBoost algorithm (0.635, 0.706, 0.756, and 0.757 for feature sets 1 to 4, respectively). CONCLUSIONS: The use of MPI domains with LR-MLE considerably improved the prediction accuracy compared with that obtained using the traditional 3-category MPI. The XGBoost ML algorithm slightly improved accuracy compared with LR-MLE, and adding clinical data improved accuracy. These results build on previous work on the MPI and suggest that implementing risk scores based on MPI domains and clinical data by using ML prediction models can support clinical decision-making with respect to risk stratification for the follow-up care of older hospitalized patients.

EndMT Regulation by Small RNAs in Diabetes-Associated Fibrotic Conditions: Potential Link With Oxidative Stress.

Diabetes-associated complications, such as retinopathy, nephropathy, cardiomyopathy, and atherosclerosis, the main consequences of long-term hyperglycemia, often lead to organ dysfunction, disability, and increased mortality. A common denominator of these complications is the myofibroblast-driven excessive deposition of extracellular matrix proteins. Although fibroblast appears to be the primary source of myofibroblasts, other cells, including endothelial cells, can generate myofibroblasts through a process known as endothelial to mesenchymal transition (EndMT). During EndMT, endothelial cells lose their typical phenotype to acquire mesenchymal features, characterized by the development of invasive and migratory abilities as well as the expression of typical mesenchymal products such as α-smooth muscle actin and type I collagen. EndMT is involved in many chronic and fibrotic diseases and appears to be regulated by complex molecular mechanisms and different signaling pathways. Recent evidence suggests that small RNAs, in particular microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), are crucial mediators of EndMT. Furthermore, EndMT and miRNAs are both affected by oxidative stress, another key player in the pathophysiology of diabetic fibrotic complications. In this review, we provide an overview of the primary redox signals underpinning the diabetic-associated fibrotic process. Then, we discuss the current knowledge on the role of small RNAs in the regulation of EndMT in diabetic retinopathy, nephropathy, cardiomyopathy, and atherosclerosis and highlight potential links between oxidative stress and the dyad small RNAs-EndMT in driving these pathological states.

Current smoking predicts inadequate response to methotrexate monotherapy in rheumatoid arthritis patients naïve to DMARDs: Results from a retrospective cohort study.

ABSTRACT: Identifying predictors of inadequate response to methotrexate (MTX) in rheumatoid arthritis (RA) is key to move from a "trial and error" to a "personalized medicine" treatment approach where patients less likely to adequately respond to MTX monotherapy could start combination therapy at an earlier stage. This study aimed to identify potential predictors of inadequate response to MTX in RA patients naïve to disease modifying anti-rheumatic drugs.Data from a real-life cohort of newly diagnosed RA patients starting MTX (baseline, T0) as first-line therapy were analyzed. Outcomes, assessed after 6 months (T1), were defined as failure to achieve a disease activity score 28 (DAS28) low disease activity (LDA) or a good/moderate response to MTX, according to the European League Against Rheumatism (EULAR) response criteria. Logistic regression was used to assess the associations between baseline variables and the study outcomes.Overall, 294 patients (60.5% females, median age 54.5 years) with a median disease duration of 7.9 months were recruited. At T1, 47.3% of subjects failed to achieve LDA, and 29.3% did not have any EULAR-response. In multivariate analysis, significant associations were observed between no LDA and current smoking (adjusted odds ratio [adjOR] 1.79, P = .037), female gender (adjOR 1.68, P = .048), and higher DAS28 (adjOR 1.31, P = .013); and between no EULAR-response and current smoking (adjOR: 2.04, P = .019), age (adjOR: 0.72 per 10-years increases, P = .001), and higher erythrocyte sedimentation rate (adjOR: 0.49; P = .020). By contrast, there were no associations between past smoker status and study outcomes.In summary, in our real-life cohort of disease modifying anti-rheumatic drug naïve RA patients, current smoking habit independently predicts inadequate response to MTX. This, together with other independent predictors of response to treatment identified in our study, might assist with personalized monitoring in RA patients. Further studies are required to investigate whether smoking quitting strategies enhance the therapeutic response to MTX.

The PaO2/FiO2 ratio on admission is independently associated with prolonged hospitalization in COVID-19 patients.

INTRODUCTION: The early identification of factors that predict the length of hospital stay (HS) in patients affected by coronavirus desease (COVID-19) might assist therapeutic decisions and patient flow management. METHODOLOGY: We collected, at the time of admission, routine clinical, laboratory, and imaging parameters of hypoxia, lung damage, inflammation, and organ dysfunction in a consecutive series of 50 COVID-19 patients admitted to the Respiratory Disease and Infectious Disease Units of the University Hospital of Sassari (North-Sardinia, Italy) and alive on discharge. RESULTS: Prolonged HS (PHS, >21 days) patients had significantly lower PaO2/FiO2 ratio and lymphocytes, and significantly higher Chest CT severity score, C-reactive protein (CRP) and lactic dehydrogenase (LDH) when compared to non-PHS patients. In univariate logistic regression, Chest CT severity score (OR = 1.1891, p = 0.007), intensity of care (OR = 2.1350, p = 0.022), PaO2/FiO2 ratio (OR = 0.9802, p = 0.007), CRP (OR = 1.0952, p = 0.042) and platelet to lymphocyte ratio (OR = 1.0039, p = 0.036) were significantly associated with PHS. However, in multivariate logistic regression, only the PaO2/FiO2 ratio remained significantly correlated with PHS (OR = 0.9164; 95% CI 0.8479-0.9904, p = 0.0275). In ROC curve analysis, using a threshold of 248, the PaO2/FiO2 ratio predicted PHS with sensitivity and specificity of 60% and 91%, respectively (AUC = 0.780, 95% CI 0.637-0.886 p = 0.002). CONCLUSIONS: The PaO2/FiO2 ratio on admission is independently associated with PHS in COVID-19 patients. Larger prospective studies are needed to confirm this finding.

SARS-CoV-2 and endothelial cell interaction in COVID-19: molecular perspectives.

SARS-CoV-2 is the agent responsible for the coronavirus disease (COVID-19), which has been declared a pandemic by the World Health Organization. The clinical evolution of COVID-19 ranges from asymptomatic infection to death. Older people and patients with underlying medical conditions, particularly diabetes, cardiovascular and chronic respiratory diseases are more susceptible to develop severe forms of COVID-19. Significant endothelial damage has been reported in COVID-19 and growing evidence supports the key pathophysiological role of this alteration in the onset and the progression of the disease. In particular, the impaired vascular homeostasis secondary to the structural and functional damage of the endothelium and its main component, the endothelial cells, contributes to the systemic proinflammatory state and the multiorgan involvement observed in COVID-19 patients. This review summarizes the current evidence supporting the proposition that the endothelium is a key target of SARS-CoV-2, with a focus on the molecular mechanisms involved in the interaction between SARS-CoV-2 and endothelial cells.

Serum albumin concentrations are associated with disease severity and outcomes in coronavirus 19 disease (COVID-19): a systematic review and meta-analysis.

Coronavirus disease 2019 (COVID-19), an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is responsible for the most threatening pandemic in modern history. The aim of this systematic review and meta-analysis was to investigate the associations between serum albumin concentrations and COVID-19 disease severity and adverse outcomes. A systematic literature search was conducted in PubMed, from inception to October 30, 2020. Sixty-seven studies in 19,760 COVID-19 patients (6141 with severe disease or poor outcome) were selected for analysis. Pooled results showed that serum albumin concentrations were significantly lower in patients with severe disease or poor outcome (standard mean difference, SMD: - 0.99 g/L; 95% CI, - 1.11 to - 0.88, p < 0.001). In multivariate meta-regression analysis, age (t = - 2.13, p = 0.043), publication geographic area (t = 2.16, p = 0.040), white blood cell count (t = - 2.77, p = 0.008) and C-reactive protein (t = - 2.43, p = 0.019) were significant contributors of between-study variance. Therefore, lower serum albumin concentrations are significantly associated with disease severity and adverse outcomes in COVID-19 patients. The assessment of serum albumin concentrations might assist with early risk stratification and selection of appropriate care pathways in this group.

Current therapeutic strategies in connective tissue disease-related interstitial lung disease: introduction to the special issue.

This Editorial introduces the Special Issue on the efficacy and safety of current treatment strategies for patients with connective tissue disease-related interstitial lung disease, including the use of immunosuppressants, such as cyclophosphamide, mycophenolate mofetil and rituximab, and antifibrotic drugs.

Emerging cellular and molecular determinants of idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF), the most common form of idiopathic interstitial pneumonia, is a progressive, irreversible, and typically lethal disease characterized by an abnormal fibrotic response involving vast areas of the lungs. Given the poor knowledge of the mechanisms underpinning IPF onset and progression, a better understanding of the cellular processes and molecular pathways involved is essential for the development of effective therapies, currently lacking. Besides a number of established IPF-associated risk factors, such as cigarette smoking, environmental factors, comorbidities, and viral infections, several other processes have been linked with this devastating disease. Apoptosis, senescence, epithelial-mesenchymal transition, endothelial-mesenchymal transition, and epithelial cell migration have been shown to play a key role in IPF-associated tissue remodeling. Moreover, molecules, such as chemokines, cytokines, growth factors, adenosine, glycosaminoglycans, non-coding RNAs, and cellular processes including oxidative stress, mitochondrial dysfunction, endoplasmic reticulum stress, hypoxia, and alternative polyadenylation have been linked with IPF development. Importantly, strategies targeting these processes have been investigated to modulate abnormal cellular phenotypes and maintain tissue homeostasis in the lung. This review provides an update regarding the emerging cellular and molecular mechanisms involved in the onset and progression of IPF.