scholarly journals Prediction of sarcopenia using a battery of circulating biomarkers

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rizwan Qaisar ◽  
Asima Karim ◽  
Tahir Muhammad ◽  
Islam Shah ◽  
Javaidullah Khan
Keyword(s):  
Cumulative Risk ◽  
High Risk Group ◽  
Risk Scores ◽  
Chronic Obstructive ◽  
Healthy Controls ◽  
Circulating Biomarkers ◽  
Fatty Acid Binding ◽  
Skeletal Muscle Index ◽  
Amino Terminal ◽  
European Working

AbstractLoss of muscle mass and strength with aging, termed sarcopenia is accelerated in several comorbidities including chronic heart failure (CHF) and chronic obstructive pulmonary diseases (COPD). However, the effective circulating biomarkers to accurately diagnose and assess sarcopenia are not known. We recruited male healthy controls and patients with CHF and COPD (n = 81–87/group), aged 55–74 years. Sarcopenia was clinically identified based on hand-grip strength, appendicular skeletal muscle index and physical capacity as recommended by the European working group for sarcopenia. The serum levels of amino-terminal pro-peptide of type-III procollagen, c-terminal agrin fragment-22, osteonectin, irisin, fatty acid-binding protein-3 and macrophage migration inhibitory factor were significantly different between healthy controls and patients with CHF and COPD. Risk scores for individual biomarkers were calculated by logistic regressions and combined into a cumulative risk score. The median cutoff value of 3.86 was used to divide subjects into high- and low-risk groups for sarcopenia with the area under the curve of 0.793 (95% CI = 0.738–0.845, p < 0.001). A significantly higher incidence of clinical sarcopenia was found in high-risk group. Taken together, the battery of biomarkers can be an effective tool in the early diagnosis and assessment of sarcopenia.

scholarly journals The Cumulative Risk of Chemical and Nonchemical Exposures on Birth Outcomes in Healthy Women: The Fetal Growth Study

2019 ◽  
Vol 16 (19) ◽  
pp. 3700 ◽  
Author(s):  
Leah Zilversmit Pao ◽  
Emily W. Harville ◽  
Jeffrey K. Wickliffe ◽  
Arti Shankar ◽  
Pierre Buekens
Keyword(s):  
Birth Outcomes ◽  
Fetal Growth ◽  
Cumulative Risk ◽  
Logistic Models ◽  
Growth Curves ◽  
Adverse Outcomes ◽  
Risk Scores ◽  
Growth Study ◽  
Race Ethnicity ◽  
Pregnancy Weight

Metals, stress, and sociodemographics are commonly studied separately for their effects on birth outcomes, yet often jointly contribute to adverse outcomes. This study analyzes two methods for measuring cumulative risk to understand how maternal chemical and nonchemical stressors may contribute to small for gestational age (SGA). SGA was calculated using sex-specific fetal growth curves for infants of pregnant mothers (n = 2562) enrolled in the National Institute of Child Health and Human Development (NICHD) Fetal Growth Study. The exposures (maternal lead, mercury, cadmium, Cohen’s perceived stress, Edinburgh depression scores, race/ethnicity, income, and education) were grouped into three domains: metals, psychosocial stress, and sociodemographics. In Method 1 we created cumulative risk scores using tertiles. Method 2 employed weighted quantile sum (WQS) regression. For each method, logistic models were built with three exposure domains individually and race/ethnicity, adjusting for age, parity, pregnancy weight gain, and marital status. The adjusted effect of overall cumulative risk with three domains, was also modeled using each method. Sociodemographics was the only exposure associated with SGA in unadjusted models ((odds ratio) OR: 1.35, 95% (confidence interval) CI: 1.08, 1.68). The three cumulative variables in adjusted models were not significant individually, but the overall index was associated with SGA (OR: 1.17, 95% CI: 1.02, 1.35). In the WQS model, only the sociodemographics domain was significantly associated with SGA. Sociodemographics tended to be the strongest risk factor for SGA in both risk score and WQS models.

scholarly journals Predicting COVID-19 mortality with electronic medical records

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Hossein Estiri ◽  
Zachary H. Strasser ◽  
Jeffy G. Klann ◽  
Pourandokht Naseri ◽  
Kavishwar B. Wagholikar ◽  
...  
Keyword(s):  
Risk Factors ◽  
Medical Information ◽  
Age Groups ◽  
Prognostic Models ◽  
Smoking History ◽  
Risk Scores ◽  
Gradient Boosting ◽  
Chronic Obstructive ◽  
Clinical Expertise ◽  
History Of

AbstractThis study aims to predict death after COVID-19 using only the past medical information routinely collected in electronic health records (EHRs) and to understand the differences in risk factors across age groups. Combining computational methods and clinical expertise, we curated clusters that represent 46 clinical conditions as potential risk factors for death after a COVID-19 infection. We trained age-stratified generalized linear models (GLMs) with component-wise gradient boosting to predict the probability of death based on what we know from the patients before they contracted the virus. Despite only relying on previously documented demographics and comorbidities, our models demonstrated similar performance to other prognostic models that require an assortment of symptoms, laboratory values, and images at the time of diagnosis or during the course of the illness. In general, we found age as the most important predictor of mortality in COVID-19 patients. A history of pneumonia, which is rarely asked in typical epidemiology studies, was one of the most important risk factors for predicting COVID-19 mortality. A history of diabetes with complications and cancer (breast and prostate) were notable risk factors for patients between the ages of 45 and 65 years. In patients aged 65–85 years, diseases that affect the pulmonary system, including interstitial lung disease, chronic obstructive pulmonary disease, lung cancer, and a smoking history, were important for predicting mortality. The ability to compute precise individual-level risk scores exclusively based on the EHR is crucial for effectively allocating and distributing resources, such as prioritizing vaccination among the general population.

scholarly journals Lower Healthy Eating Index-2005 dietary quality scores in older women with rheumatoid arthritis v. healthy controls

2010 ◽  
Vol 13 (8) ◽  
pp. 1170-1177 ◽  
Author(s):  
Megan E Grimstvedt ◽  
Kathleen Woolf ◽  
Brandy-Joe Milliron ◽  
Melinda M Manore
Keyword(s):  
Rheumatoid Arthritis ◽  
Nutritional Status ◽  
Older Women ◽  
Healthy Eating ◽  
Healthy Eating Index ◽  
High Risk Group ◽  
Dietary Guidelines ◽  
Dietary Quality ◽  
Healthy Controls ◽  
Cross Sectional

AbstractObjectiveTo assess the dietary quality of older women with and without rheumatoid arthritis (RA) using the Healthy Eating Index-2005 (HEI-2005) to identify potential strategies to improve the nutritional status.DesignCross-sectional. Diet was assessed using 7 d food records and analysed for nutrient composition (Food Processor v. 7·11). Diet quality was determined using the HEI-2005, a measure of compliance with 2005 US Dietary Guidelines. Individuals with RA completed a self-reported evaluation of arthritis (pain scale and disability index). Independent two-tailed t tests or Mann–Whitney tests compared the differences between groups and correlations were computed between HEI-2005 and measures of disease reactivity.SettingArizona, USA.SubjectsOlder (≥ 55 years) women (n 108) with RA (n 52) and healthy controls (HC; n 56).ResultsThere were no differences between groups in age, weight, or BMI (kg/m2). HC participants had higher mean HEI-2005 scores for whole fruit (cups; P = 0·02), total fruit (cups; P = 0·05), whole grains (oz; P = 0·004), oil (g; P = 0·05) and total HEI score (P = 0·04) than the RA group. In the RA group, these same HEI components were inversely correlated with disability index (r = −0·20, P = 0·04). Participants with RA reported lower mean intakes of carbohydrate (g; P = 0·02), fibre (g; P = 0·01) and vitamin C (mg; P = 0·04).ConclusionsThis is the first study examining the dietary quality in older women with and without RA using the HEI-2005. Living with RA was associated with significantly lower dietary quality. Since even small changes in dietary quality can translate into better nutritional status, future interventions should focus on increasing dietary quality in this high-risk group.

scholarly journals Paraoxonase 1 and Chronic Obstructive Pulmonary Disease: A Meta-Analysis

Antioxidants ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1891
Author(s):  
Jun Watanabe ◽  
Kazuhiko Kotani ◽  
Alejandro Gugliucci
Keyword(s):  
Chronic Obstructive Pulmonary Disease ◽  
Pulmonary Disease ◽  
Meta Analysis ◽  
Paraoxonase 1 ◽  
Pon1 Activity ◽  
Chronic Obstructive ◽  
Healthy Controls ◽  
Obstructive Pulmonary Disease ◽  
Paraoxonase Activity ◽  
Severe Copd

Oxidative stress is a driving factor in the pathophysiology of chronic obstructive pulmonary disease (COPD). While paraoxonase 1 (PON1) is an antioxidant enzyme and a potential biomarker of this disease, data regarding the status of PON-1 in COPD are inconclusive. In this regard, to shed light on this issue, we performed a meta-analysis of data on PON1 activity in COPD. Electronic databases (MEDLINE, Embase and CENTRAL) were searched for available studies on PON1 activity in patients with stable COPD published before October 2021. A meta-analysis was performed using random-effects models. Twelve studies (12 studies on paraoxonase and three on arylesterase) were identified. Patients with COPD had lower levels of paraoxonase activity (standard mean difference [SMD] −0.77, 95% confidence interval [CI] −1.35 to −0.18) and arylesterase activity (SMD −1.15, 95% CI −1.95 to −0.36) in comparison to healthy controls. In subgroup analyses, paraoxonase activity was lower in patients of studies as consisted of mainly non-severe COPD (SMD −1.42, 95% CI −2.04 to −0.79) and, by contrast, slightly higher in patients of studies including severe COPD (SMD 0.33, 95% CI 0.02 to 0.64) in comparison to healthy controls. Arylesterase activity showed a similar trend. Overall, PON1 activity was lower in patients with COPD, suggesting that PON1-related antioxidant defense is impaired in COPD. Future studies are warranted.

scholarly journals Effect of COVID-19 Pandemic on Anxiety in Rheumatology Patients Taking Immunosuppressive Drugs

2020 ◽  
Author(s):  
Tugba Izci Duran ◽  
Seyyid Bilal Acikgoz ◽  
Cemal Gurbuz ◽  
Aysegul Ucar ◽  
Gokhan Yavuzbilge ◽  
...  
Keyword(s):  
Musculoskeletal Diseases ◽  
Demographic Data ◽  
Immunosuppressive Drugs ◽  
High Risk Group ◽  
Anxiety Symptoms ◽  
Healthy Controls ◽  
Treatment Team ◽  
Additional Information ◽  
Education Levels ◽  
Anxiety Levels

Abstract Introduction: Coronavirus disease 2019 (COVID-19) pandemic is a public health emergency that is causing international concern. Patients with medical comorbidities are more likely to be infected and have a worse prognosis. The purpose of this study was to determine the prevalence of anxiety due to COVID-19 pandemic in patients with rheumatic and musculoskeletal diseases (RMDs) who used immunosuppressive drugs during the initial stage of the COVID-19 pandemic and to identify the risk and protective factors that cause anxiety.Methods: A total of 145 patients with RMDs aged ≥18 years who used regular immunosuppressive drugs and 95 healthy controls were included in the study. An anonymous survey comprising questions regarding the COVID-19 pandemic was used, and the Beck anxiety inventory (BAI) was used to measure the anxiety levels of participants. Additional information was collected such as demographic data, current RMDs, immunosuppressive drugs used, information and concerns about COVID-19, and the source of information about COVID-19.Results: About 42.1% patients reported that the epidemic caused concern due to the drug they were using, and 33.8% rated their concerns as moderate and severe. The BAI scores of patients and healthy controls were 4 (0-52) and 3 (0-18) respectively. According to the BAI scores, 16.5% patients had moderate to severe anxiety symptoms; and comparison of the groups showed that the anxiety level of the patient group was significantly higher (38.6% vs. 18.9%, p=0.001). Female had more anxiety symptoms in both groups (p<0.005). In addition, anxiety was lower in patients with higher education levels (p=0.039).Conclusion: It should be ensured that patients in the high-risk group are not provided false information, the patients are individually informed, and they trust the treatment team. Providing online or smartphone-based psychoeducation and psychological interventions may be considered for these patients with high anxiety levels.

scholarly journals A Novel Ferroptosis-Related Gene Signature Robustly Predicts Clinical Prognosis And Tumor Immunity in Patients With Kidney Renal Clear Cell Carcinoma

2021 ◽  
Author(s):  
Wei Song ◽  
Weiting Kang ◽  
Qi Zhang
Keyword(s):  
High Risk ◽  
Clear Cell ◽  
Risk Group ◽  
Gene Signature ◽  
Renal Clear Cell Carcinoma ◽  
High Risk Group ◽  
Risk Scores ◽  
Related Gene ◽  
Clinical Prognosis ◽  
Validation Set

Abstract Objective: This study aimed to construct a ferroptosis-related gene signature to predict clinical prognosis and tumor immunity in patients with kidney renal clear cell carcinoma (KIRC).Methods: The mRNA expression profiles and corresponding clinical data of KIRC patients were downloaded from The Cancer Genome Atlas (TCGA), which were randomly divided into training (398 patients) and validation set (132 patients). The iron death related (IDR) prediction model was constructed based on training set and 60 ferroptosis-related genes from previous literatures, followed by prognostic performance evaluation and verification using the validation set. Moreover, functional enrichment, immune cell infiltration, metagene clusters correlation, and TIDE scoring analyses were performed. Results: In total, 23 ferroptosis-related genes were significantly associated with overall survival (OS). The IDR prediction model (a 10-gene signature) was then constructed to stratify patients into two risk groups. The OS of KIRC patients with high-risk scores was significantly shorter than those with low-risk scores. Moreover, the risk score was confirmed as an independent prognostic predictor for OS. The positive and negative correlated genes with this model were significantly enriched in p53 signaling pathway, and cGMP-PKG signaling pathway. The patients in the high-risk group had higher ratios of plasma cells, T cells CD8, and T cells regulatory Tregs. Furthermore, IgG, HCK, LCK, and Interferson metagenes were significantly correlated with risk score. By TIDE score analysis, patients in the high-risk group could benefit from immunotherapy.Conclusions: The identified ferroptosis-related gene signature is significantly correlated with clinical prognosis and immune immunity in KIRC patients.

scholarly journals Prognostic model of head and neck squamous cell carcinoma based on 12 ferroptosis-related genes

2021 ◽  
Author(s):  
Sijia Li ◽  
Hongyang Zhang ◽  
Wei Li
Keyword(s):  
Regression Analysis ◽  
Risk Score ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Risk Scores ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Model Based ◽  
Cox Analysis

Abstract Background: The purpose of our study is establishing a model based on ferroptosis-related genes predicting the prognosis of patients with head and neck squamous cell carcinoma (HNSCC).Methods: In our study, transcriptome and clinical data of HNSCC patients were from The Cancer Genome Atlas, ferroptosis-related genes and pathways were from Ferroptosis Signatures Database. Differentially expressed genes (DEGs) were screened by comparing tumor and adjacent normal tissues. Functional enrichment analysis of DEGs, protein-protein interaction network and gene mutation examination were applied. Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression were used to identified DEGs. The model was constructed by multivariate Cox regression analysis and verified by Kaplan-Meier analysis. The relationship between risk scores and other clinical features was also analyzed. Univariate and multivariate Cox analysis was used to verified the independence of our model. The model was evaluated by receiver operating characteristic analysis and calculation of the area under the curve (AUC). A nomogram model based on risk score, age, gender and TNM stages was constructed.Results: We analyzed data including 500 tumor tissues and 44 adjacent normal tissues and 259 ferroptosis-related genes, then obtained 73 DEGs. Univariate Cox regression analysis screened out 16 genes related to overall survival, and LASSO analysis fingered out 12 of them with prognostic value. A risk score model based on these 12 genes was constructed by multivariate Cox regression analysis. According to the median risk score, patients were divided into high-risk group and low-risk group. The survival rate of high-risk group was significantly lower than that of low-risk group in Kaplan-Meier curve. Risk scores were related to T and grade. Univariate and multivariate Cox analysis showed our model was an independent prognostic factor. The AUC was 0.669. The nomogram showed high accuracy predicting the prognosis of HNSCC patients.Conclusion: Our model based on 12 ferroptosis-related genes performed excellently in predicting the prognosis of HNSCC patients. Ferroptosis-related genes may be promising biomarkers for HNSCC treatment and prognosis.

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