Discriminating Characteristics of Community-Dwelling Elderly at High and Low Risk for Frailty

2002 ◽  
Vol 10 (4) ◽  
pp. 413-431 ◽  
Author(s):  
Laura S. Ho ◽  
Harriet G. Williams ◽  
Emily A.W. Hardwick

The study’s objective was to examine the health status, physical activity behaviors, and performance-based functional abilities of individuals classified as being at high or low risk for frailty and to determine which of these characteristics discriminates between the 2 groups. Participants were 78 community-dwelling individuals with an average age of 74 years; 37 were categorized as being at high risk and 42 at low risk for frailty. Logistic-regression analysis indicated that individuals classified as being at high risk for frailty were more likely to have visited the doctor more than 3 times in the past year, experienced a cardiac event, taken more than 4 medications a day, and participated in little or no physical activity. High-risk individuals were more likely to have poor balance, difficulty with mobility, decreased range of motion, poor unimanual dexterity, and difficulty performing activities of daily living than were those classified as being at low risk for frailty.

2017 ◽  
Vol 45 (5) ◽  
pp. 619-623
Author(s):  
K. A. Cook ◽  
P. A. MacIntyre ◽  
J. R. McAlpine

The perioperative risks and factors associated with adverse cardiac outcomes in patients with dilated cardiomyopathy undergoing non-cardiac surgery are unknown. Interrogation of the Nelson Hospital transthoracic echocardiogram database identified 127 patients with dilated cardiomyopathy who satisfied the study criteria and underwent non-cardiac surgery between June 1999 and July 2013. Demographic and clinical data along with postoperative death within 30 days or a major adverse cardiac event were retrieved and analysed. The mean age was 75.9 years. Seventy-one percent of the patients had severe impairment of left ventricular function and 35% had a severely dilated left ventricle. A major adverse cardiac event occurred in 18.1% of patients and 5.5% of patients died within 30 days of surgery. Increased surgical risk and absence of cerebrovascular disease were associated with adverse outcome (P <0.001, P <0.05, respectively). Forty-three and a half percent (43.5%) of patients undergoing high-risk surgery had an adverse outcome compared to 36.1% and 5.9% for moderate and low-risk surgery, respectively. A major adverse cardiac event was observed in 26.7% of patients with cardiovascular disease compared to 9.8% of patients without cardiovascular disease. We were unable to exclude an influence of other potential risk factors due to the retrospective observational nature of the study. These findings highlight a potential increase in complications with moderate or high surgical risk, whilst are reassuring in demonstrating the relative safety of low-risk surgery in this group of high-risk patients.


2001 ◽  
Vol 9 (1) ◽  
pp. 32-42 ◽  
Author(s):  
Sandra K. Hunter ◽  
Martin W. Thompson ◽  
Roger D. Adams

The purposes of this study were to investigate the rate of change with age of simple lower-limb reaction time (RT) in women and determine the relationship among RT. strength, and physical activity. Independent, community-dwelling women aged 20–89 years (N = 217) were assessed for knee-extension RT, maximal voluntary isometric contractions of the knee extensors (KE), and physical activity level. Trend analysis by ANOVA and regression analysis on RT were performed. Lower-limb RT increased and KE strength and physical activity level decreased linearly across age groups (p < .001). Active women had faster RTs than those of inactive women of the same age (p < .01). From multiple-regression analysis on RT, only 1 predictor variable. KE strength, emerged. Stronger women had faster RTs than those of weaker women (p < .0001), regardless of age and physical activity. Although RT was slower in older women, higher levels of strength and physical activity were associated with faster RTs in this group.


2021 ◽  
Author(s):  
Jinrong Wei ◽  
Qianshu Dou ◽  
Futing Ba ◽  
Guo-Qin Jiang

Abstract Purpose: The purpose of this study is to established a prognosis model based on the expression profiles of lncRNAs and mRNAs for breast cancers.Methods: Single Variable Cox Proportional Risk Regression analysis and difference analysis were applied to screen survival-related and differently expressed lncRNAs and mRNAs between tumor and normal tissues from TCGA data. GO and KEGG analysis were applied for top 30 survival-related genes. LncRNA/mRNA co-expressed network was constructed based on correlation analysis. LASSO analysis and Multivariate Stepwise Cox Regression analysis were applied to establish the prognosis model. RT-PCR experiments were applied to verify the correctness of the analysis results. Relative components of the TME in breast cancers with high and low risk groups were analysed by xCell and Cox proportional risk regression analysis. The ceRNA network was constructed by calculating the Pearson correlation coefficient (PCC) for miRNA-mRNA and miRNA-lncRNA using paired miRNA, mRNA, and lncRNA expression profile data.Results:Venn diagrams showed that there were 60 genes and 54 lncRNAs that were differently expressed and related with survival. Through lncRNA/mRNA co-expressed network construction, 19 lncRNA and 16 mRNA hub genes were gained. The genes were then included in LASSO and multivariate Cox proportional hazard regression analysis, and finally, 3 lncRNAs (LINC01497, LINC02766, LINC02528) and 2 mRNAs (C20orf85, CST1) were selected as prognosis predictive genes. According to the median risk score of the 5 candidates, patients were divided into high-risk group and low-risk group. The results of RT-PCR were consistent with the analysis results. The proportions of Adipocytes, Endothelial cells, HSCs, Fibroblasts were significantly lower in low risk score tissues compared with the high risk score tissues, while the proportions of M1 macrophages, MSCs, Th2 cells were significantly higher. A lncRNA-miRNA-mRNA ceRNA network containing 3 lncRNAs, 2 mRNAs, and 158 miRNAs was finally constructed, preliminarily revealed a proper mechanism of the 5 molecules playing important roles in breast cancer progression and prognosis prediction.Conclusion: We found that LINC01497, LINC02766, LINC02528 and C20orf85, CST1 may serve as a powerful prognostic tool to optimize the prognosis evaluation system of breast cancer.


2021 ◽  
Vol 12 ◽  
Author(s):  
Xiaoping Li ◽  
Jishang Chen ◽  
Qihe Yu ◽  
Hui Huang ◽  
Zhuangsheng Liu ◽  
...  

Background: A surge in newly diagnosed breast cancer has overwhelmed the public health system worldwide. Joint effort had beed made to discover the genetic mechanism of these disease globally. Accumulated research has revealed autophagy may act as a vital part in the pathogenesis of breast cancer.Objective: Aim to construct a prognostic model based on autophagy-related lncRNAs and investigate their potential mechanisms in breast cancer.Methods: The transcriptome data and clinical information of patients with breast cancer were obtained from The Cancer Genome Atlas (TCGA) database. Autophagy-related genes were obtained from the Human Autophagy Database (HADb). Long non-coding RNAs (lncRNAs) related to autophagy were acquired through the Pearson correlation analysis. Univariate Cox regression analysis as well as the least absolute shrinkage and selection operator (LASSO) regression analysis were used to identify autophagy-related lncRNAs with prognostic value. We constructed a risk scoring model to assess the prognostic significance of the autophagy-related lncRNAs signatures. The nomogram was then established based on the risk score and clinical indicators. Through the calibration curve, the concordance index (C-index) and receiver operating characteristic (ROC) curve analysis were evaluated to obtain the model's predictive performance. Subgroup analysis was performed to evaluate the differential ability of the model. Subsequently, gene set enrichment analysis was conducted to investigate the potential functions of these lncRNAs.Results: We attained 1,164 breast cancer samples from the TCGA database and 231 autophagy-related genes from the HAD database. Through correlation analysis, 179 autophagy-related lncRNAs were finally identified. Univariate Cox regression analysis and LASSO regression analysis further screened 18 prognosis-associated lncRNAs. The risk scoring model was constructed to divide patients into high-risk and low-risk groups. It was found that the low-risk group had better overall survival (OS) than those of the high-risk group. Then, the nomogram model including age, tumor stage, TNM stage and risk score was established. The evaluation index (C-index: 0.78, 3-year OS AUC: 0.813 and 5-year OS AUC: 0.785) showed that the nomogram had excellent predictive power. Subgroup analysis showed there were difference in OS between high-risk and low-risk patients in different subgroups (stage I-II, ER positive, Her-2 negative and non-TNBC subgroups; all P &lt; 0.05). According to the results of gene set enrichment analysis, these lncRNAs were involved in the regulation of multicellular organismal macromolecule metabolic process in multicellular organisms, nucleotide excision repair, oxidative phosphorylation, and TGF-β signaling pathway.Conclusions: We identified 18 autophagy-related lncRNAs with prognostic value in breast cancer, which may regulate tumor growth and progression in multiple ways.


2021 ◽  
Author(s):  
Ankai Xu ◽  
Jinti Lin ◽  
Wei Yu ◽  
Jiakang Jin ◽  
Bing Liu ◽  
...  

Abstract Background: This study aims to perform bioinformatics analysis of programmed cell death-related genes (PCDGs) in osteosarcoma, and to construct a multi-gene signature for predicting the prognosis.Methods: The functional enrichment analysis was applied for prognostic PCDGs, and PPI network as well as drug-gene interactions were constructed. In order to set up the prognosis evaluation system, we established a prognosis model by integrating PCDGs. The Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression analysis as well as the multivariate Cox proportional hazard regression analysis were used to construct the five-genes signature (MUC1, TCF7L2, TGFB2, TRIAP1, CBS) for prediction in Gene Expression Omnibus (GEO) cohort. According to the median risk score, survival analysis was conducted to evaluate the prognostic value of the risk score in GEO cohort. Next, by combining other clinic-pathological independent prognostic factor, stage at diagnosis, a nomogram was established to predict individual survival probability. Result: GO analysis showed that the 15 prognostic PCDGs were mainly enriched in apoptotic signaling pathway, regulation of secretion and p53 signaling pathway. KEGG analysis showed that aforesaid genes were mainly related to PI3K-Akt signaling pathway, diverse neoplasms signaling pathway and hepatitis B. Drug-gene interactions displayed available drugs for influencing osteosarcoma via programmed cell death, such as adalimumab, tacrolimus and sirolimus. The risk score was constructed based on 5 genes and patients were significantly divided into high-risk and low-risk groups according to overall survival. In multivariate Cox regression analysis, risk score was still an independent prognostic factor (HR = 2.526, 95% CI = 1.597−3.994, P < 0.001). Cumulative curve showed that low-risk score patients were significantly had better prognosis than that of patients with high-risk score (P < 0.001). The external independent TARGET cohort proved the validity of risk score model and the nomograph.Conclusion: From the facet of programmed cell death, we provided a multi-gene signatureand the nomograph for the prognostic predictors of osteosarcoma patients, and available drugs displayed may provide promising treatment strategies.


2018 ◽  
Vol 15 (1) ◽  
pp. 292-298
Author(s):  
Etty Indriani ◽  
Cahyani Tunggal Sari

This research analyzes behavioral finance, especially the behavior of investors in Yogyakarta, Indonesia Region. The performance of investor behavior is examined based on the LQ 45 stocks return on Indonesia Stock Exchange and questionnaires that are spread out to five securities agents in Yogyakarta.The performance of LQ 45 stocks return is compared to the questionnaire analysis in the “Belief” part at the first and second stages. The first result shows that LQ 45 stocks are profitable. It can be seen from the average return of the stocks that it has positive value and is statistically identical with the LQ 45 index return. This result is in line with the investors’ opinion that LQ 45 stocks are profitable. The second result shows that most of LQ 45 stocks are profitable and give high return. But, this result is also contrary to the opinion of investors towards traditional finance paradigm that investors still believe “high risk – high return, low risk – low return”. Although most of LQ 45 stocks are considered as low risk stocks, many investors prefer to choose LQ 45 stocks. It means that the traditional finance paradigm has weakness. It is proven that investors sometimes act irrationally.The third and fourth stages of the study are aimed to analyze the relationship between feeling and belief towards frequency of transaction each day based on the questionnaire using regression analysis. The result shows that there is significant relationship between feeling and frequency of transaction each day.


2021 ◽  
Author(s):  
Fei Li ◽  
Dongcen Ge ◽  
Shu-lan Sun

Abstract Background. Ferroptosis is a newly discovered form of cell death characterized by iron-dependent lipid peroxidation. The aim of this study is to investigate the relationship between ferroptosis and the prognosis of lung adenocarcinoma (LUAD).Methods. RNA-seq data was collected from the LUAD dataset of The Cancer Genome Altas (TCGA) database. We used ferroptosis-related genes as the basis, and identify the differential expression genes (DEGs) between cancer and paracancer. The univariate Cox regression analysis were used to screen the prognostic-related genes. We divided the patients into training and validation sets. Then, we screened out key genes and built a 5 genes prognostic prediction model by the applications of the least absolute shrinkage and selection operator (LASSO) 10-fold cross-validation and the multi-variate Cox regression analysis. We divided the cases by the median value of risk score and validated this model in the validation set. Meanwhile, we analyzed the somatic mutations, and estimated the score of immune infiltration in the high- and low-risk groups, as well as performed functional enrichment analysis of DEGs.Results. The result revealed that the high-risk score triggered the worse prognosis. The maximum area under curve (AUC) of the training set and the validation set of in this study was 0.7 and 0.69. Moreover, we integrated the age, gender, and tumor stage to construct the composite nomogram. The charts indicated that the AUC of cases with survival time of 1, 3 and 5 years are 0.698, 0.71 and 0.73. In addition, the mutation frequency of patients in the high-risk group was higher than that in the low-risk group. Simultaneously, DEGs were mainly enriched in ferroptosis-related pathways by analyzing the functional results.Conclusion. This study constructed a novel LUAD prognosis prediction model base on 5 ferroptosis-related genes, which can provide a prognostic evaluation tool for the clinical therapeutic decision.


Author(s):  
Javier Bueno-Antequera ◽  
Carmen Mayolas-Pi ◽  
Joaquin Reverter-Masià ◽  
Isaac López-Laval ◽  
Miguel Ángel Oviedo-Caro ◽  
...  

We studied the prevalence and possible association between exercise addiction and health in indoor cycling practitioners. In 1014 (492 women) adult indoor cyclists and 926 (597 women) controls with low levels of physical activity according to the short form of the International Physical Activity Questionnaire, we examined the risk of exercise addiction according to the Exercise Addiction Inventory and several health outcomes through a web-based experiment. The prevalence of a high risk of exercise addiction in cyclists was 13.3%, and it was higher in men than in women (16.5% vs. 10.0%, p = 0.002). Women cyclists with a high risk of exercise addiction had higher levels of physical activity (p < 0.001; effect size = −0.62, 95% CI: (−0.91, −0.32)) and anxiety symptom severity (p = 0.001; Effect Size (ES) = −0.59 (−0.89, −0.30)) than those with a low risk. For both sexes, cyclists with a low risk of exercise addiction had better social function, emotional role, and anxiety symptom severity compared with the controls (all p < 0.002; ES ranged from 0.25 to 0.47). Higher anxiety symptom severity and cardiorespiratory fitness were the main determinants of exercise addiction in cyclists (both p < 0.001). Our data suggest the importance of considering exercise addiction in indoor cyclists.


Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 195-195
Author(s):  
Frits van Rhee ◽  
Sarah Waheed ◽  
Saad Z Usmani ◽  
Joshua Epstein ◽  
Adam Rosenthal ◽  
...  

Abstract Abstract 195 GEP analysis is a robust method to distinguish low- and high-risk multiple myeloma (MM), pertaining to 85% and 15% of newly diagnosed patients, respectively (Shaughnessy et al., Blood, 2007; 109:2276–84). As developed in TT2 and validated in TT3A and TT3B, we are now examining, similar to previous work in high-risk MM, whether we can define outliers among low-risk MM, i.e., patients not living up to the low-risk prediction model. Toward this end, we scrutinized early relapses in TT3A and TT3B within three years of protocol entry. Using logistic regression analysis, we identified baseline parameters including GEP, en route for distinguishing this high-risk subset among low-risk MM. Also examined was whether a new model could be built within low-risk disease that allowed for the identification of a high-risk subset. Our database was interrogated for patients known to have GEP-defined low-risk in the GEP-70 model. Table 1 summarizes the 3-year events among GEP-70 low-risk subjects per protocol. An optimal cut-point at +0.146 distinguished, among the combined TT2 and TT3 patients, inferior progression-free survival (PFS) and overall survival (OS) (Figure 1a). Next, we examined outcomes among all TT2 and TT3 patients with GEP data, including those with traditionally-defined high-risk (>=0.66). Here, we were able to distinguish three subgroups with distinctly different PFS and OS (Figure 1b). Utilizing logistic regression analysis, limited to traditionally-defined GEP-70 low-risk MM (=<0.66), three-year progression events during the this period were adversely dominated by the following: GEP-70 scores >0.146 (HR=2.61, p=0.0005), the presence of cytogenetic abnormalities (CA) (HR=1.93, p=0.018), B2M >5.5mg/L (HR=1.95, p=0.04) and LDH >190U/L (HR=1.93, 0.02). These are all reported in Table 2. In conclusion, we have identified, within GEP-70 low-risk patients, a new cut-point. This allows a better categorization of patients having truly low risk disease. Also, above which a prognosis intermediate to the traditional high-risk prognostic group (>=0.66) could be identified. GEP >0.146 dominated a multivariate logistic regression model. Further efforts will be presented on unique genes characterizing this intermediate risk group in relationship to low and high-risk subsets. Table 1. Three-year Events Among GEP-70 Subjects Per Protocol Protocol Total with GEP GEP-70 low-risk GEP-70 low-risk, event within first 3 years TT2 - thalidomide 176 156 55 TT2 + thalidomide 175 149 36 TT3A 275 235 39 TT3B 166 129 23 Table 2. Logistic Regression for 3-year Event Factors, TT2+3 GEP-70 Low-Risk (<0.66) Event in first three years on protocol Variable N With Factor Without Factor OR (95% CI) P - value Multivariate B2M > 5.5 mg/L 666 24/69 (35%) 59/328 (18%) 1.95 (1.03, 3.69) 0.0401 LDH >= 190 U/L 668 33/99 (33%) 50/298 (17%) 1.93 (1.10, 3.40) 0.0229 Cytogenetic abnormalities 665 35/116 (30%) 48/281 (17%) 1.93 (1.12, 3.32) 0.0182 GEP-70 score > 0.146 669 37/104 (36%) 46/293 (16%) 2.61 (1.52, 4.47) 0.0005 OR - Odds Ratio, 95% CI - 95% Confidence Interval, P - value from Wald Chi - Square Test in Logistic Regression. NS2 - Multivariate results not statistically significant at 0.05 level. Univariate p - values reported regardless of significance. Multivariate model uses stepwise selection with entry level 0.1 and variable remains if meets the 0.05 level. A multivariate p - value greater than 0.05 indicates variable forced into model with significant variables chosen using stepwise selection. Disclosures: No relevant conflicts of interest to declare.


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