838 resultados para Framingham risk score


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The prognostic value of exercise (EXE) and dobutamine echocardiograms (DbE) has been well defined in large studies. However, while risk is determined by both clinical and echo features, no simple means of combining these data has been defined. We sought to combine these data into risk scores. Methods. At 3 expert centers, 7650 pts underwent standard EXE (n=5211) and DbE (w2439) for evaluation of known or suspected CAD and were followed for up to 10 years (mean 5-2) for major events (death or myocardial infarction). A subgroup of 2953 EXE and 1025 DbE pts was randomly selected to develop separate multivariate models for prediction of events. After simplication of each model for clinical use, models were validated in the remaining EXE and DbE pts. ResuI1s. The total number of events was 200 in the EXE and 225 in the DbE pts, of which 58 and 99 events occurred in the respective testing groups. The following regression equations gave equivalent results I” the testing and validation groups for both EXE and DbE; DbE = (Age’O.02) + (DM’l .O) + (Low RPP’0.6) + ([CHF+lschemia+Scar]‘O.7) EXE = ([DM+CHF]‘O.S) + O.S(lschemla #) + l.B(Scar#) - (METS0.19) (where each categorical variable scored 1 when present and 0 when absent, Ischemia# = 1 for l-2 VD. 6 for 3 VD; Scar# = 1 for 1-2 VD, 1.7 for 3 VD). The table summarizes the scores and equivalent outcomes for EXE and DbE. Conclusions. Risk scores based on clinical and EXE or DbE results may be used to quantify the risk of events during follow-up.

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Estimation of absolute risk of cardiovascular disease (CVD), preferably with population-specific risk charts, has become a cornerstone of CVD primary prevention. Regular recalibration of risk charts may be necessary due to decreasing CVD rates and CVD risk factor levels. The SCORE risk charts for fatal CVD risk assessment were first calibrated for Germany with 1998 risk factor level data and 1999 mortality statistics. We present an update of these risk charts based on the SCORE methodology including estimates of relative risks from SCORE, risk factor levels from the German Health Interview and Examination Survey for Adults 2008-11 (DEGS1) and official mortality statistics from 2012. Competing risks methods were applied and estimates were independently validated. Updated risk charts were calculated based on cholesterol, smoking, systolic blood pressure risk factor levels, sex and 5-year age-groups. The absolute 10-year risk estimates of fatal CVD were lower according to the updated risk charts compared to the first calibration for Germany. In a nationwide sample of 3062 adults aged 40-65 years free of major CVD from DEGS1, the mean 10-year risk of fatal CVD estimated by the updated charts was lower by 29% and the estimated proportion of high risk people (10-year risk > = 5%) by 50% compared to the older risk charts. This recalibration shows a need for regular updates of risk charts according to changes in mortality and risk factor levels in order to sustain the identification of people with a high CVD risk.

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Growth-curves are an important tool for evaluating the anthropometric development in pediatrics. The different growth-curves available are based in different populations, what leads to different cut-offs. Pediatric obesity tracks into adulthood and is associated with increased cardiovascular risk. The accurate assessment of a child nutritional status using growth-curves can indicate individuals that are either obese or in risk of becoming obese, allowing an early intervention. Moreover, the association between the data obtained from growth-curves with specific metabolic risk factors further highlights the importance of these charts. This study aimed to evaluate the associations between body mass index z-score (BMIzsc), determined using the growth-curves from the Centre for Disease Control and Prevention (CDC) and from the World Health Organization (WHO), with cardiovascular risk factors, represented here by metabolic syndrome (MS) and insulin resistance (IR) related parameters. The study involved 246 obese adolescents (10-18 years, 122 females). MS was defined according to the International Diabetes Federation. IR was considered for HOMA-IR greater than 2.5.

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Introducción: Entre las diferentes herramientas clínicas para evaluar la presencia de enfermedad coronaria mediante puntajes, la más usada es la Escala de Riesgo cardiovascular de Framingham. Desde hace unos años, se creó el puntaje de calcio coronario el cual mide el riesgo cardiovascular según la presencia de placas ateromatosas vistas por tomografía computarizada. Se evaluó la asociación entre la escala de Framigham y el puntaje de calcio coronario en una población de sujetos sanos asintomáticos. Metodología: Se realizó un estudio transversal para evaluar la asociación entre el puntaje de calcio coronario y la escala de Framingham en sujetos asintomáticos que se practicaron exámen médico preventivo en la Fundación Cardioinfantil- Instituto de Cardiología (FCI-IC) en el periodo comprendido entre 1 de Julio 2011 hasta el 31 de octubre de 2015. Resultados: Se evaluaron 262 pacientes en total. La prevalencia de riesgo cardiovascular fue bajo en un 77.86% de la población, medio en 18.70% y alto en 3.44%, según la escala de Framingham. El riesgo cardiovascular según el puntaje de Calcio coronario fue nulo 70.99%, bajo en 21.75%, medio en 4.19%, severo en 3.05%. Se encontró una asociación entre ambos puntajes para riesgo estadísticamente significativa (p0,00001) Discusión: El riesgo cardiovascular establecido por escala de Framingham se relaciona de forma significativa con la presencia de placas aterioscleróticas. El estudio demostró que en una muestra de sujetos asintomáticos, hay una alteración estructural coronaria temprana.

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Background: The Malnutrition Screening Tool (MST) is a valid nutrition screening tool in the acute hospital setting but has not been assessed in residential aged care facilities. The aim of this secondary analysis was to determine whether the MST could be a useful nutrition screening tool when compared with a full nutrition assessment by Subjective Global Assessment (SGA) in the residential aged care setting. ----- Methods: Two hundred and eighty-five residents (29% male; mean age: 84 ± 9 years) from eight residential aged care facilities in Australia participated. A secondary analysis of data collected during a nutrition intervention study was conducted. The MST consists of two questions related to recent weight loss and appetite. While the MST was not specifically applied, weight loss and appetite information was available and an estimated MST score (0-5) calculated. Nutritional status was assessed by a research assistant trained in using SGA. ----- Results: Malnutrition prevalence was 42.8% (122 malnourished out of 285 residents). Compared to the SGA, the MST was an effective predictor of nutritional risk (sensitivity = 83.6%, specificity = 65.6%, positive predictive value = 0.65, negative predictive value =0.84). ----- Conclusions: The components of the MST have acceptable sensitivity and specificity suggesting it can play a valuable role in quickly identifying malnutrition risk in the residential aged care setting. Further prospective research using the MST tool against a broader array of objective and subjective nutritional parameters is required to confirm its validity as a screening tool in aged care settings.

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The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

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Background and significance: Older adults with chronic diseases are at increasing risk of hospital admission and readmission. Approximately 75% of adults have at least one chronic condition, and the odds of developing a chronic condition increases with age. Chronic diseases consume about 70% of the total Australian health expenditure, and about 59% of hospital events for chronic conditions are potentially preventable. These figures have brought to light the importance of the management of chronic disease among the growing older population. Many studies have endeavoured to develop effective chronic disease management programs by applying social cognitive theory. However, limited studies have focused on chronic disease self-management in older adults at high risk of hospital readmission. Moreover, although the majority of studies have covered wide and valuable outcome measures, there is scant evidence on examining the fundamental health outcomes such as nutritional status, functional status and health-related quality of life. Aim: The aim of this research was to test social cognitive theory in relation to self-efficacy in managing chronic disease and three health outcomes, namely nutritional status, functional status, and health-related quality of life, in older adults at high risk of hospital readmission. Methods: A cross-sectional study design was employed for this research. Three studies were undertaken. Study One examined the nutritional status and validation of a nutritional screening tool; Study Two explored the relationships between participants. characteristics, self-efficacy beliefs, and health outcomes based on the study.s hypothesized model; Study Three tested a theoretical model based on social cognitive theory, which examines potential mechanisms of the mediation effects of social support and self-efficacy beliefs. One hundred and fifty-seven patients aged 65 years and older with a medical admission and at least one risk factor for readmission were recruited. Data were collected from medical records on demographics, medical history, and from self-report questionnaires. The nutrition data were collected by two registered nurses. For Study One, a contingency table and the kappa statistic was used to determine the validity of the Malnutrition Screening Tool. In Study Two, standard multiple regression, hierarchical multiple regression and logistic regression were undertaken to determine the significant influential predictors for the three health outcome measures. For Study Three, a structural equation modelling approach was taken to test the hypothesized self-efficacy model. Results: The findings of Study One suggested that a high prevalence of malnutrition continues to be a concern in older adults as the prevalence of malnutrition was 20.6% according to the Subjective Global Assessment. Additionally, the findings confirmed that the Malnutrition Screening Tool is a valid nutritional screening tool for hospitalized older adults at risk of readmission when compared to the Subjective Global Assessment with high sensitivity (94%), and specificity (89%) and substantial agreement between these two methods (k = .74, p < .001; 95% CI .62-.86). Analysis data for Study Two found that depressive symptoms and perceived social support were the two strongest influential factors for self-efficacy in managing chronic disease in a hierarchical multiple regression. Results of multivariable regression models suggested advancing age, depressive symptoms and less tangible support were three important predictors for malnutrition. In terms of functional status, a standard regression model found that social support was the strongest predictor for the Instrumental Activities of Daily Living, followed by self-efficacy in managing chronic disease. The results of standard multiple regression revealed that the number of hospital readmission risk factors adversely affected the physical component score, while depressive symptoms and self-efficacy beliefs were two significant predictors for the mental component score. In Study Three, the results of the structural equation modelling found that self-efficacy partially mediated the effect of health characteristics and depression on health-related quality of life. The health characteristics had strong direct effects on functional status and body mass index. The results also indicated that social support partially mediated the relationship between health characteristics and functional status. With regard to the joint effects of social support and self-efficacy, social support fully mediated the effect of health characteristics on self-efficacy, and self-efficacy partially mediated the effect of social support on functional status and health-related quality of life. The results also demonstrated that the models fitted the data well with relative high variance explained by the models, implying the hypothesized constructs under discussion were highly relevant, and hence the application for social cognitive theory in this context was supported. Conclusion: This thesis highlights the applicability of social cognitive theory on chronic disease self-management in older adults at risk of hospital readmission. Further studies are recommended to validate and continue to extend the development of social cognitive theory on chronic disease self-management in older adults to improve their nutritional and functional status, and health-related quality of life.

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While extensive research efforts have been devoted to improve the motorcycle safety, the relationship between the rider behavior and the crash risk is still not well understood.The objective of this study is to evaluate how behavioral factors influence crash risk and to identify the most vulnerable group of motorcyclists. To explore the rider behavior, a questionnaire containing 61-items of impulsive sensation seeking, aggression, and risk-taking behavior was developed. By clustering the crash risk using the medoid portioning algorithm, the log-linear model relating the rider behavior to crash risk has been developed. Results show that crash-involved motorcyclists score higher in all three behavioral traits. Aggressive and high risk-taking motorcyclists are more likely to fall under the high vulnerable group while impulsive sensation seeking is not found to be significant. Defining personality types from aggression and risk-taking behavior, “Extrovert” and “Follower” personality type of motorcyclists are more prone to crashes. The findings of this study will be useful for road safety campaign planners to be more focused in the target group as well as those who employ motorcyclists for their delivery business

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Background: Kallikrein 15 (KLK15)/Prostinogen is a plausible candidate for prostate cancer susceptibility. Elevated KLK15 expression has been reported in prostate cancer and it has been described as an unfavorable prognostic marker for the disease. Objectives: We performed a comprehensive analysis of association of variants in the KLK15 gene with prostate cancer risk and aggressiveness by genotyping tagSNPs, as well as putative functional SNPs identified by extensive bioinformatics analysis. Methods and Data Sources: Twelve out of 22 SNPs, selected on the basis of linkage disequilibrium pattern, were analyzed in an Australian sample of 1,011 histologically verified prostate cancer cases and 1,405 ethnically matched controls. Replication was sought from two existing genome wide association studies (GWAS): the Cancer Genetic Markers of Susceptibility (CGEMS) project and a UK GWAS study. Results: Two KLK15 SNPs, rs2659053 and rs3745522, showed evidence of association (p, 0.05) but were not present on the GWAS platforms. KLK15 SNP rs2659056 was found to be associated with prostate cancer aggressiveness and showed evidence of association in a replication cohort of 5,051 patients from the UK, Australia, and the CGEMS dataset of US samples. A highly significant association with Gleason score was observed when the data was combined from these three studies with an Odds Ratio (OR) of 0.85 (95% CI = 0.77-0.93; p = 2.7610 24). The rs2659056 SNP is predicted to alter binding of the RORalpha transcription factor, which has a role in the control of cell growth and differentiation and has been suggested to control the metastatic behavior of prostate cancer cells. Conclusions: Our findings suggest a role for KLK15 genetic variation in the etiology of prostate cancer among men of European ancestry, although further studies in very large sample sets are necessary to confirm effect sizes.

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Academic pressure among adolescents is a major risk factor for poor mental health and suicide and other harmful behaviours. While this is a worldwide phenomenon, it appears to be especially pronounced in China and other East Asian countries. Despite a growing body of research into adolescent mental health in recent years, the multiple constructs within the ‘educational stress’ phenomenon have not been clearly articulated in Chinese contexts. Further, the individual, family, school and peer influencing factors for educational stress and its associations with adolescent mental health are not well understood. An in-depth investigation may provide important information for the ongoing educational reform in Mainland China with a special focus on students’ mental health and wellbeing. The primary goal of this study was to examine the relative contribution of educational stress to poor mental health, in comparison to other well-known individual, family, school and peer factors. Another important task was to identify significant risk factors for educational stress. In addition, due to the lack of a culturally suitable instrument for educational stress in this population, a new tool – the Educational Stress Scale for Adolescents (ESSA) was initially developed in this study and tested for reliability and validity. A self-administered questionnaire was used to collect information from convenient samples of secondary school students in Shandong, China. The pilot survey was conducted with 347 students (grades 8 and 11) to test the psychometric properties of the ESSA and other scales or questions in the questionnaire. Based on factor analysis and reliability and validity testing, the 16-item scale (the ESSA) with five factors showed adequate to good internal consistency, 2-week test-retest reliability, and satisfactory concurrent and predictive validity. Its factor structure was further demonstrated in the main survey with a confirmatory factor analysis illustrating a good fit of the proposed model based on a confirmatory factor analysis. The reliabilities of other scales and questions were also adequate to be used in this study. The main survey was subsequently conducted with a sample of 1627 secondary school (grades 7-12) students to examine the influencing factors of educational stress and its associations with mental health outcomes, including depression, happiness and suicidal behaviours. A wide range of individual, family, school and peer factors were found to have a significant association with the total ESSA and subscale scores. Most of the strong factors for academic stress were school or study-related, including rural school location, low school connectedness, perceived poor academic grades and frequent emotional conflicts with teachers and peers. Unexpectedly, family and parental factors, such as parental bonding, family connectedness and conflicts with parents were found to have little or no association with educational stress. Educational stress was the most predictive variable for depression, but was not strongly associated with happiness. It had a strong association with suicide ideation but not with suicide attempts. Among five subscales of the ESSA, ‘Study despondency’ score had the strongest associations with these mental health measures. Surprising, two subscales, ‘Self-expectation’ and ‘Worry about grades’ showed a protective effect on suicidal behaviours. An additional analysis revealed that although academic pressure was the most commonly reported reason for suicidal thinking, the occurrence of problems in peer relationships such as peer teasing and bullying, and romantic problems had a much stronger relationship with actual attempts. This study provides some insights into the nature and health implications of educational stress among Chinese adolescents. Findings in this study suggest that interventions on educational stress should focus on school environment and academic factors. Intervention programs focused on educational stress may have a high impact on the prevalence of common mental disorders such as depression. Efforts to increase perceived happiness however should cover a wider range of individual, family and school factors. The importance of healthy peer relationships should be adequately emphasised in suicide prevention. In addition, the newly developed scale (the ESSA) demonstrates sound psychometric properties and is expected to be used in future research into academic-related stress among secondary school adolescents.

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Aims: To identify risk factors for major Adverse Events (AEs) and to develop a nomogram to predict the probability of such AEs in individual patients who have surgery for apparent early stage endometrial cancer. Methods: We used data from 753 patients who were randomized to either total laparoscopic hysterectomy or total abdominal hysterectomy in the LACE trial. Serious adverse events that prolonged hospital stay or postoperative adverse events (using common terminology criteria 3+, CTCAE V3) were considered major AEs. We analyzed pre-surgical characteristics that were associated with the risk of developing major AEs by multivariate logistic regression. We identified a parsimonious model by backward stepwise logistic regression. The six most significant or clinically important variables were included in the nomogram to predict the risk of major AEs within 6 weeks of surgery and the nomogram was internally validated. Results: Overall, 132 (17.5%) patients had at least one major AE. An open surgical approach (laparotomy), higher Charlson’s medical co-morbidities score, moderately differentiated tumours on curettings, higher baseline ECOG score, higher body mass index and low haemoglobin levels were associated with AE and were used in the nomogram. The bootstrap corrected concordance index of the nomogram was 0.63 and it showed good calibration. Conclusions: Six pre-surgical factors independently predicted the risk of major AEs. This research might form the basis to develop risk reduction strategies to minimize the risk of AEs among patients undergoing surgery for apparent early stage endometrial cancer.

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The Kallikrein-related peptidase, KLK4, has been shown to be significantly overexpressed in prostate tumours in numerous studies and is suggested to be a potential biomarker for prostate cancer. KLK4 may also play a role in prostate cancer progression through its involvement in epithelial-mesenchymal transition, a more aggressive phenotype, and metastases to bone. It is well known that genetic variation has the potential to affect gene expression and/or various protein characteristics and hence we sought to investigate the possible role of single nucleotide polymorphisms (SNPs) in the KLK4 gene in prostate cancer. Assessment of 61 SNPs in the KLK4 locus (±10 kb) in approximately 1300 prostate cancer cases and 1300 male controls for associations with prostate cancer risk and/or prostate tumour aggressiveness (Gleason score <7 versus ≥7) revealed 7 SNPs to be associated with a decreased risk of prostate cancer at the Ptrend<0.05 significance level. Three of these SNPs, rs268923, rs56112930 and the HapMap tagSNP rs7248321, are located several kb upstream of KLK4; rs1654551 encodes a non-synonymous serine to alanine substitution at position 22 of the long isoform of the KLK4 protein, and the remaining 3 risk-associated SNPs, rs1701927, rs1090649 and rs806019, are located downstream of KLK4 and are in high linkage disequilibrium with each other (r2≥0.98). Our findings provide suggestive evidence of a role for genetic variation in the KLK4 locus in prostate cancer predisposition.

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There is increasing concern about the impact of employees’ alcohol and other drug (AOD) consumption on workplace safety, particularly within the construction industry. No known study has scientifically evaluated the relationship between the use of drugs and alcohol and safety impacts in construction, and there has been only limited adoption of nationally coordinated strategies, supported by employers and employees to render it socially unacceptable to arrive at a construction workplace with impaired judgment from AODs. This research aims to scientifically evaluate the use of AODs within the Australian construction industry in order to reduce the potential resulting safety and performance impacts and engender a cultural change in the workforce. Using the Alcohol Use Disorders Identification Test (AUDIT), the study will adopt both quantitative and qualitative methods to evaluate the extent of general AOD use in the industry. Results indicate that a proportion of the construction sector may be at risk of hazardous alcohol consumption. A total of 286 respondents (58%) scored above the cut-off score for risky alcohol use with 43 respondents (15%) scoring in the significantly ‘at risk’ category. Other drug use was also identified as a major issue that must be addressed. Results support the need for evidence-based, preventative educational initiatives that are tailored specifically to the construction industry.