• 1 While antiretroviral therapy (ART) has reduced morbidity and mortality in people living with HIV (PLHIV), 2 complications associated with ageing such as cardiovascular disease (CVD), cancer, osteoporosis, and other end-organ diseases are increasing. (sajhivmed.org.za)
  • Background: Prediction of absolute risk of cardiovascular diseases (CVDs) has important clinical and public health significance, but the predictive ability of the available tools has not yet been tested in the rural Bangladeshi population. (edu.au)
  • Cardiovascular diseases are the leading cause of death worldwide except Africa. (wikipedia.org)
  • There are many cardiovascular diseases involving the blood vessels. (wikipedia.org)
  • There are also many cardiovascular diseases that involve the heart. (wikipedia.org)
  • citation needed] Coronary artery disease (also known as coronary heart disease and ischemic heart disease) Peripheral arterial disease - disease of blood vessels that supply blood to the arms and legs Cerebrovascular disease - disease of blood vessels that supply blood to the brain (includes stroke) Renal artery stenosis Aortic aneurysm There are also many cardiovascular diseases that involve the heart. (wikipedia.org)
  • Compared to the general population, individuals with depression have an increased risk for cardiovascular diseases. (frontiersin.org)
  • Projections assume that depression will be the leading cause of disability worldwide by 2030 ( 9 ), which might be partly due to the high comorbidity with cardiovascular diseases (CVDs) ( 10 , 11 ). (frontiersin.org)
  • These new risk charts, specifically calibrated for each country, remove major obstacles in applying risk-based strategies to prevent cardiovascular diseases," said Goodarz Danaei , assistant professor of global health at Harvard Chan School and senior author of the paper. (harvard.edu)
  • Cardiovascular diseases are the leading cause of death and disability worldwide, and more than three-quarters of CVD-related deaths occur in low- and middle-income countries. (harvard.edu)
  • Mount Sinai Heart is dedicated to evaluating, counseling, and treating patients and families with genetic-based cardiovascular diseases. (mountsinai.org)
  • However, targeting oral microbiome might still provide preventive and therapeutic insights on cardiovascular diseases. (degruyter.com)
  • Oral dysbiosis, which potentially causes periodontitis to subsequently promote systemic inflammation and local vascular inflammation, increases the risks of cardiovascular diseases (CVDs). (degruyter.com)
  • Cardiovascular diseases are one of the major problems in medicine today and the number of patients increases worldwide. (kobv.de)
  • Mathematical modeling is a powerful tool for prediction and investigation of cardiovascular diseases. (kobv.de)
  • 2030. Modelled figures suggest that cancer incidence an epidemiological transition from communicable and deaths will almost double, with 555 000 new cases of diseases to NCDs such as cardiovascular diseases, cancer in 2012, compared to a prediction of 961 000 new diabetes and cancer ( 3 ). (who.int)
  • Field synopsis of sex in clinical prediction models for cardiovascular disease. (tufts.edu)
  • OBJECTIVES: We sought to critically analyze the routine use of conventional coronary angiography (CCA) before noncoronary cardiac surgery and to assess clinical prediction models that might allow more selective use of CCA in this setting. (who.int)
  • A study reinforces the usefulness of ACC/AHA CVD Pooled Cohort risk equations and the importance of efforts to implement the current guidelines to prevent atherosclerotic cardiovascular disease in African Americans. (acpinternist.org)
  • With the increase in aging and cardiovascular risk factors, the morbidity and mortality of atherosclerotic cardiovascular disease (ASCVD), represented by ischemic heart disease and stroke, continue to rise in China. (biomedcentral.com)
  • Atherosclerotic cardiovascular disease (ASCVD), which mostly involves heart attacks and strokes caused by atherosclerosis, is one of the main causes of death worldwide [ 1 ]. (biomedcentral.com)
  • Cardiovascular disease risk was estimated by Framingham Cardiovascular and Heart Disease (FHS-CVD, FHS-CHD), Atherosclerotic Cardiovascular Disease (ASCVD) and D:A:D 2010 and 2016 risk prediction models for HIV-infected participants of the Ndlovu Cohort Study, Limpopo, rural South Africa. (sajhivmed.org.za)
  • These properties also offer the allure of quantifying change in atherosclerosis to better pinpoint and personalize atherosclerotic cardiovascular disease (ASCVD) risk estimates. (medscape.com)
  • The study aimed to assess cardiovascular risk classification of common cardiovascular disease (CVD) risk prediction models compared to the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) 2010 and 2016 models in people living with HIV. (sajhivmed.org.za)
  • UH Harrington Heart & Vascular Institute launched a new program in 2016 - ICE (Inflammatory Cardiovascular disease Elimination) Cardiology - that focuses on the prevention of cardiovascular disease in patients with chronic inflammation. (uhhospitals.org)
  • Using data from the Jackson Heart Study (JHS), a community-based study of 5,301 black adults in Jackson, Miss., researchers developed and validated risk prediction models for CVD incidence in black adults, incorporating standard risk factors, biomarkers, and subclinical disease. (acpinternist.org)
  • BACKGROUND: Climate is known to influence the incidence of cardiovascular events. (bvsalud.org)
  • With the exception of the D:A:D model, all other risk prediction models classified fewer people to be at high estimated CVD risk. (sajhivmed.org.za)
  • Model performance was compared with the American College of Cardiology/American Heart Association (ACC/AHA) CVD risk algorithm (Pooled Cohort Equations) and the Framingham Risk Score (FHS) refitted to the JHS data. (acpinternist.org)
  • The Fifth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of nine societies and by invited experts). (acpjournals.org)
  • We therefore applied a machine learning algorithm with a random forest model to predict survival outcomes in 42,257 qualified lung cancer patients. (usda.gov)
  • Biomedical consequences of elevated cholesterol-containing lipoproteins and apolipoproteins on cardiovascular and non-cardiovascular outcomes. (ucl.ac.uk)
  • Questionnaire-based exposome-wide association studies (ExWAS) reveal expected and novel risk factors associated with cardiovascular outcomes in the Personalized Environment and Genes Study. (cdc.gov)
  • Although various measures of CAC progression were independently associated with outcomes, none of the 10 CAC progression algorithms demonstrated an improvement in the C statistic or net reclassification of risk for hard CHD or hard ASCVD compared with models including risk factors and baseline CAC score. (medscape.com)
  • on behalf of the FinnDiane Study Group, Genetic Risk Score Enhances Coronary Artery Disease Risk Prediction in Individuals With Type 1 Diabetes. (diabetesjournals.org)
  • Heterogeneity in the Association Between the Presence of Coronary Artery Calcium and Cardiovascular Events: A Machine Learning Approach in the MESA Study. (cdc.gov)
  • A machine learning model for non-invasive detection of atherosclerotic coronary artery aneurysm. (cdc.gov)
  • Machine Learning Approach for Cardiovascular Risk and Coronary Artery Calcification Score. (cdc.gov)
  • Prediction of 3-year all-cause and cardiovascular cause mortality in a prospective percutaneous coronary intervention registry: Machine learning model outperforms conventional clinical risk scores. (cdc.gov)
  • Performance could be further improved by using summary risk prediction scores such as the EUROSCORE II for coronary artery bypass graft surgery or the GRACE risk score for acute coronary syndrome. (who.int)
  • 2] A prediction model that and transparency of such risk adjustment models, and to widen uses a `history of coronary heart disease' as a risk factor to predict discussion on the strengths and limitations of risk adjustment models death from an acute myocardial infarction (AMI) is always going based on service claims data. (who.int)
  • They evaluated 3281 subjects with paired scans performed over a larger interscan interval, 5.1 years, and with 7.8 years of follow-up after the second scan, resulting in 85 hard coronary, 161 hard cardiovascular, and 241 total cardiovascular events inclusive of revascularization. (medscape.com)
  • Prediction models for cardiovascular disease risk in the general population: systematic review. (nih.gov)
  • SCORE2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in Europe. (umu.se)
  • Random forests (RF) is a widely used machine-learning algorithm, and outperforms many other machine learning algorithms in prediction-accuracy. (usda.gov)
  • Control is achieved by coupling material data streams, acquired through automated and comprehensive in-situ measurements of the hybrid materials' properties, with modelling and control algorithms. (europa.eu)
  • The unique contributions of this article beyond the longer interscan and follow-up periods include the assessment of 10 different proposed algorithms to quantify CAC progression and the inclusion of rigorous statistical metrics to interrogate the incremental value of CAC progression to outcome prediction. (medscape.com)
  • However, the reclassification improvement was not substantially different between model 6 and the ACC/AHA CVD Pooled Cohort risk equations or between model 6 and the FHS. (acpinternist.org)
  • Methods: Data from a case-cohort study (52989 cohort and 439 sub-cohort participants), conducted on a rural Bangladeshi population, were analysed using modified Cox PH model with a maximum follow-up of 2.5 years. (edu.au)
  • Cox proportional hazards models in the derivation cohort to derive risk equations accounting for competing risks. (bmj.com)
  • Of the 10% of patients in the validation cohort classified at highest risk with either the lifetime risk model or the 10 year risk model, only 18 385(14.5%) were at high risk on both measures. (bmj.com)
  • However, since these conventional models were developed for a specific cohort with a unique risk profile and further these models do not consider atherosclerotic plaque-based phenotypes, therefore, such models can either underestimate or overestimate the risk of CVD events. (minervamedica.it)
  • The thesis includes four studies, starting with the development of the statistical framework for the natural history model and then its application on a Swedish mammography screening cohort in study I-II. (ki.se)
  • After the prediction model was derived in an international cohort of patients with ALI, it was validated in two independent samples of patients enrolled in a clinical trial involving 17 academic centers and a North American population-based cohort. (nih.gov)
  • In the derivation cohort, a model based on age, oxygenation index on day 3, and cardiovascular failure on day 3 predicted death and/or ventilator dependence. (nih.gov)
  • The prediction model performed better in the clinical trial validation cohort (area under the receiver operating curve 0.81, 95% confidence interval 0.77 to 0.84) than in the population-based validation cohort (0.71, 95% confidence interval 0.65 to 0.76). (nih.gov)
  • Trajectories of cardiac troponin in the decades before cardiovascular death: a longitudinal cohort study. (ucl.ac.uk)
  • Patients with rheumatoid arthritis (RA) and other inflammatory joint disorders (IJD) have increased cardiovascular disease (CVD) risk compared with the general population. (bmj.com)
  • Patients with depression and healthy controls differ in several cardiovascular risk markers, putting patients at increased risk for CVDs. (frontiersin.org)
  • The guidelines that cover the screening of patients for elevated serum lipid levels, and the treatment of patients with lipid abnormalities, rest on calculations of individual patients' risk for a future cardiovascular event. (medscape.com)
  • But identifying those at high risk of having a future cardiovascular event can be difficult in many countries because there are no reliable risk charts, and because calculating risk typically relies on measurements of blood sugar and lipids-which, in resource-poor settings, can make the assessment too costly or impractical. (harvard.edu)
  • The main objective was to develop and validate a risk model for prediction of short-term mortality due to PGF after heart transplantation using the ISHLT Heart Transplant Registry. (lu.se)
  • Identification of physical activity and sedentary behaviour dimensions that predict mortality risk in older adults: Development of a machine learning model in the Whitehall II accelerometer sub-study and external validation in the CoLaus study. (ucl.ac.uk)
  • Machine learning improves mortality prediction in three-vessel disease. (cdc.gov)
  • Machine Learning-Based Models Incorporating Social Determinants of Health vs Traditional Models for Predicting In-Hospital Mortality in Patients With Heart Failure. (cdc.gov)
  • In 2019, Discovery Health published a risk adjustment model to determine standardised mortality rates across South African private hospital systems, with the aim of contributing towards quality improvement in the private healthcare sector. (who.int)
  • Miami Project researchers recently published a manuscript titled, Cardiometabolic risks and atherosclerotic disease in ApoE knockout mice: Effect of spinal cord injury and Salsalate anti-inflammatory pharmacotherapy in the journal PLOS ONE that demonstrates positive results in treating some of the secondary cardiovascular complications following spinal cord injury (SCI). (themiamiproject.org)
  • These widely reported AD risk factors after SCI raise a fundamental question whether-or to what extent-SCI alters the trajectory of these cardiovascular complications. (themiamiproject.org)
  • We and others have previously developed and validated HIV risk prediction models to identify PrEP candidates using electronic health records data. (cdc.gov)
  • We showed that random forest model outperforms the standard multinomial logistic regression model in prediction accuracy. (usda.gov)
  • The DNN model was superior in predicting HR-AHF days compared with the logistic regression model [c-statistics: 0.888 (95%CI: 0.818-0.958) vs. 0.827 (95%CI: 0.745-0.910): p=0.0013]. (bvsalud.org)
  • Methods: We developed a non-linear artificial neural networks (ANN) model to evaluate the association between recipient-donor variables and post-transplant PGF. (lu.se)
  • For better prevention and intervention, relevant guidelines recommend using predictive models for early detection of ASCVD high-risk groups. (biomedcentral.com)
  • Therefore, this study aims to establish a population ASCVD prediction model in rural areas of Xinjiang using survival analysis. (biomedcentral.com)
  • Traditional ASCVD prediction models (Framingham and China-PAR models) were constructed in the test set. (biomedcentral.com)
  • Different models' discrimination and calibration degrees were compared to find the optimal prediction model for this population according to different genders and further analyze the risk factors of ASCVD. (biomedcentral.com)
  • The performance of the ASCVD prediction model based on the RSF algorithm is better than that based on Cox regression, Lasso-Cox, and the traditional ASCVD prediction model in the rural population of Xinjiang. (biomedcentral.com)
  • Currently, the most commonly used survival analysis method is the Cox proportional hazards model, and most traditional ASCVD prediction models are constructed based on this model. (biomedcentral.com)
  • Kappa statistics ranged from 0.34 for ASCVD to 0.60 for FHS-CVD as compared to the D:A:D 2010 risk prediction model. (sajhivmed.org.za)
  • Statistical analysis included the C statistic, a measure used to estimate the probability that a model is able to predict an outcome, with values ranging from 0.5, indicating that the outcome is no different than chance, to 1.0, in which the model predicts the outcome perfectly. (acpinternist.org)
  • Conclusion: An ANN model to predict primary graft dysfunction was derived and independently validated. (lu.se)
  • Boston, MA - A new study led by Harvard T.H. Chan School of Public Health researchers provides powerful new tools to help clinicians around the globe predict their patients' 10-year risk of cardiovascular disease (CVD) . (harvard.edu)
  • These up-to-date charts will be useful everywhere, but particularly in low- and middle-income countries that lack locally-developed models to predict CVD risk, and in places where access to labs that can perform bloodwork is limited. (harvard.edu)
  • National and international guidelines recommend that physicians use risk prediction equations, usually in the form of risk charts, to predict which of their patients are at high risk for heart disease and stroke, and to suggest lifestyle modification or prescribe medication to lower their risk. (harvard.edu)
  • With natural history models we can learn more about the progression of the disease, study the effects of breast cancer screening, and predict a woman's future risk of breast cancer. (ki.se)
  • A model based on age and cardiopulmonary function three days after the intubation is able to predict, moderately well, a combined end-point of death and/or prolonged mechanical ventilation in patients with ALI. (nih.gov)
  • The best model to predict CV death included low blood pressure, estimated glomerular filtration rate ≤ 60 mL/min, peripheral oedema, previous HF hospitalization, ischaemic HF, chronic obstructive pulmonary disease, elevated N‐terminal pro‐B‐type natriuretic peptide (NT‐proBNP), and troponin (c‐index = 0.73). (gla.ac.uk)
  • The era of big data has enabled sophisticated models to predict air pollution concentrations over space and time. (biomedcentral.com)
  • Home blood pressure monitoring has previously been shown to be a useful adjunct to team-based care for hypertension, and home BP readings can predict cardiovascular risk more accurately than office BP measurements. (bmj.com)
  • The models use demographics (e.g., race, primary language), diagnoses (e.g., prior syphilis or HIV counseling), laboratory tests (e.g., positive gonorrhea tests), and prescriptions (e.g., treatments for opioid addiction or syphilis) to predict HIV risk. (cdc.gov)
  • data to study the association between cardiovascular fitness and other health conditions and risk factors, such as obesity, cardiovascular disease, diabetes, hypertension, and activity and dietary patterns. (cdc.gov)
  • obesity and cardiovascular disease, decreasing variation and inappropriate cardiac utilization. (acc.org)
  • Valentin Fuster, MD, PhD, will transition to president of Mount Sinai Heart, one of the world's leading centers for cardiovascular care, cardiac surgery, and advanced research. (mountsinai.org)
  • The integration of these inflammatory biomarkers into traditional lipid prediction models may improve the forecasting of future AD. (themiamiproject.org)
  • NME) comprises three highly integrated may be considered as the traditional pathways common to cancer, diabetes, groups: the Biomarkers Group (BMA), the domains of nutrition in cancer research and cardiovascular disease. (who.int)
  • Cardiovascular/Stroke Risk Stratification in Parkinson's Disease Patients Using Atherosclerosis Pathway and Artificial Intelligence Paradigm: A Systematic Review. (cdc.gov)
  • N-terminal B-type natriuretic peptide or troponin elevations, or the Background use of inotropes during admission, are much more powerful and Risk stratification and prediction is an integral part of clinical accurate predictors than admission to hospital alone. (who.int)
  • A 10-year CVD risk model based on multiple risk factors (such as age, sex, body mass index (BMI), hypertension, systolic blood pressure (SBP), cigarettes per day, pulse rate, and diabetes) was developed in which heart rate was identified as one of the novel risk factors. (aut.ac.nz)
  • European Guidelines on cardiovascular disease prevention in clinical practice (version 2012). (acpjournals.org)
  • The primary prevention of cardiovascular disease involves classifying individuals according to their global cardiovascular risk. (bmj.com)
  • In recent years an increasing emphasis has been placed on the need for improved primary prevention of cardiovascular disease. (bmj.com)
  • End-stage renal disease and concomitant cardiovascular disease. (acc.org)
  • The 2008 adaption included additional cardiovascular events (ie, stroke, transient ischemic attack) that had not previously been assessed. (medscape.com)
  • Predictive Accuracy of Stroke Risk Prediction Models Across Black and White Race, Sex, and Age Groups. (cdc.gov)
  • CV Risk in IBD Patients Receiving Small Molecule Drugs Does treatment with small molecule drugs such as JAK inhibitors and S1P modulators increase the risk of cardiovascular events in patients with inflammatory bowel disease? (medscape.com)
  • Individuals with rheumatologic (systemic lupus erythematosus, rheumatoid arthritis, ankylosing spondylitis, scleroderma), inflammatory bowel (ulcerative colitis, Crohn's disease), and skin (psoriasis) disease are known to be at increased risk of cardiovascular disease. (uhhospitals.org)
  • Altogether, the altered immune and inflammatory responses, and endotoxemia contribute to the dysfunction and stress in cardiovascular cells (e.g . endothelial cells, vascular smooth muscle cells and cardiomyocytes), increasing cardiovascular risks. (degruyter.com)
  • Historically these models have been evaluated using overall metrics that measure how close predictions are to monitoring data. (biomedcentral.com)
  • However, no data were provided regarding the incremental value of CAC progression to baseline CAC regarding metrics such as improvement in the C statistic of the model or net reclassification improvement. (medscape.com)
  • A clinical trial assessed cardiovascular and pulmonary responses in those who vaped or smoked cigarettes vs those who did not via a 15-minute product-use challenge. (clinicaladvisor.com)
  • CNT/F produces pulmonary, cardiovascular, and other toxic effects in animals along with a significant release of bioactive peptides into the circulation, the augmented serum peptidome. (cdc.gov)
  • In general, CVD risk assessments are performed using conventional risk prediction models. (minervamedica.it)
  • In this thesis, we developed risk predictions which can incorporate the effects of screening directly---something that the conventional risk prediction models can't do. (ki.se)
  • The model parameters were determined by cross-validation and parameter tuning and then verified in the training set. (biomedcentral.com)
  • Honda T, Yoshida D, Hata J, Hirakawa Y, Ishida Y, Shibata M, Sakata S, Kitazono T, Ninomiya T. Development and validation of modified risk prediction models for cardiovascular disease and its subtypes: The Hisayama Study. (healthdata.org)
  • The proposed model achieved a good discrimination and calibration ability with C-index (receiver operating characteristic (ROC)) being 0.71 in the validation dataset. (aut.ac.nz)
  • We validated the model via statistical and empirical validation. (aut.ac.nz)
  • Subjects Patients aged 30-84 years who were free of cardiovascular disease and not taking statins between 1 January 1994 and 30 April 2010: 2 343 759 in the derivation dataset, and 1 267 159 in the validation dataset. (bmj.com)
  • Development and validation of explainable machine-learning models for carotid atherosclerosis early screening. (cdc.gov)
  • Prediction models containing several features to estimate the risk of patients with confirmed infection could help clinicians give appropriate treatment when health care resources are limited. (signavitae.com)
  • This review highlights the link between eGFR reduction and that of atherosclerosis progression, which increases the risk of adverse cardiovascular events. (minervamedica.it)
  • Aims Heart failure (HF) patients are at high‐risk of cardiovascular (CV) events, including CV death. (gla.ac.uk)
  • Risk prediction models are widely used in primary care to identify and initiate therapy in those at risk for future cardiovascular events. (bmj.com)
  • However, the contribution of CAC change to the prediction of these events was again modest when compared with the information contained in the baseline CAC score. (medscape.com)
  • The predictive power of the models was assessed by calculating C-statistics and generating ROC curves with other measures of diagnostic tests. (edu.au)
  • Further extensive efforts are needed to deepen our understanding on oral-cardiovascular connection in the context of diagnostic and therapeutic perspectives. (degruyter.com)
  • In this paper, we have applied parametric local sensitivity analysis (LSA) to a linear elastic model of the arm arteries, to find and rank sensitive param- eters that may be helpful in clinical diagnosis. (kobv.de)
  • In general, model reporting should conform to published reporting standards, and attempts should be made to test model validity by using sensitivity analyses. (who.int)
  • Our structural heart disease patients are treated through a team of general cardiologists, interventional cardiologists, and cardiovascular surgeons. (mountsinai.org)
  • Preventive cardiologists continue to refine their risk prediction models, striving for the "perfect formula" for predicting a heart attack or other cardiovascular event. (uhhospitals.org)
  • We compared the prediction accuracy of the tuned RF and multinomial logistic regression (MLR) models. (usda.gov)
  • The tuned RF model with 300 iterations and 10 variables outperformed the MLR model (accuracy =69.8% vs 64.6%, 1:1 sample-split), while 4:1 sample-split produced lower prediction-accuracy than 1:1 sample-split. (usda.gov)
  • Comparing Prognostic Accuracy of Delirium Prediction Models This study compares three prediction models for ICU delirium. (medscape.com)
  • The top-five peptide model offered ideal prediction with high accuracy (Q2 = 0.99916). (cdc.gov)
  • reactions to having their medical records searched, harms from potential breaches in confidentiality, and the accuracy of model predictions. (cdc.gov)
  • Identifying patients at higher risk for each individual event may help selecting patients for clinical trials and tailoring cardiovascular therapies. (gla.ac.uk)
  • The extremely popular engineering field of drug-eluting biodegradable scaffolds for regenerative medicine, cancer treatment and cardiovascular therapies has largely failed to ensure therapy at the right place, at the right time and with the right dose. (europa.eu)
  • Chronic SCI results in a greater prevalence of risk factors for cardiovascular disease (CVD) and atherosclerotic disease (AD) - plaque buildup in a person's arteries - when compared to the able-bodied population. (themiamiproject.org)
  • This study explores the use of a genetic risk score (GRS) for CAD risk prediction, compares it to established clinical markers, and investigates its performance according to the age and pharmacological treatment. (diabetesjournals.org)
  • Lifestyle interventions targeting healthy diet and/or physical activity are recommended as a physically active and healthy lifestyle contributes equally to patients' mental well-being and cardiovascular health. (frontiersin.org)
  • Detailed descriptions of the protocol are provided in the NHANES Cardiovascular Fitness Procedure Manual (National Center for Health Statistics, 2004). (cdc.gov)
  • CDC pooled results for those years to cardiovascular health of this population ( 5 ). (cdc.gov)
  • Now, a new report from the Women's Health Study and the Physician's Health Study II suggests that adding HbA1c measurements to the model can improve risk prediction and lead to downward classification of some diabetics. (jwatch.org)
  • Oral dysbiosis refers to the imbalance between symbionts and pathobionts in the oral cavity, posing potential threats to host cardiovascular health. (degruyter.com)
  • We introduce frequency band model performance, which quantifies health estimation capacity of air quality prediction models for time series studies of air pollution and health. (biomedcentral.com)
  • Further, frequency band model performance is more strongly associated ( R 2 = 0.95) with health association bias compared to overall approaches ( R 2 = 0.57). (biomedcentral.com)
  • For PM 2.5 predictions in Salt Lake City, UT, frequency band model performance better identifies acute error that may impact estimated short-term health associations. (biomedcentral.com)
  • For epidemiologic studies, frequency band model performance provides an improvement over existing approaches because it evaluates models at the timescale of interest and is more strongly associated with bias in estimated health associations. (biomedcentral.com)
  • Evaluating prediction models at timescales relevant for health studies is critical to determining whether model error will impact estimated health associations. (biomedcentral.com)
  • Our objective was to estimate the future direct health care costs due to diabetes for a 10-year period in Canada using national survey data, a validated diabetes risk prediction tool and individual-level attributable cost estimates. (canada.ca)
  • Six models composed of different risk variables were constructed and externally validated using 2 independent black adult data sets from the Atherosclerosis Risk in Communities (ARIC) study and the Multi-Ethnic Study of Atherosclerosis (MESA). (acpinternist.org)
  • The models discriminated reasonably well in the ARIC and Multi-Ethnic Study of Atherosclerosis data (C statistic range, 0.70 to 0.77). (acpinternist.org)
  • In a new thesis, Rickard Strandberg, PhD student at the Department of Medical Epidemiology and Biostatistics, lays the foundations for a new natural history model for breast cancer. (ki.se)
  • In Study IV, the model is used to study the effect that certain acquisition parameters used in mammography have on the detectability of breast cancer tumors. (ki.se)
  • As always, there are areas where the breast cancer modelling can be improved. (ki.se)
  • For this model specifically, the most important areas are metastasis and breast cancer sub-types. (ki.se)
  • This systematic review compared different types of models for predicting the prognosis of influenza infection, informing us of risk factors for the predictive model in predicting the prognosis of influenza in the early stage. (signavitae.com)
  • The models have high predictive performance and can be used to alert clinicians about patients who merit clinical evaluations for PrEP. (cdc.gov)
  • Although these interactions remain to be further examined in humans, the physiological functions of taurine appear to be inconsistent with the adverse cardiovascular symptoms associated with excessive consumption of caffeine-taurine containing beverages. (researchgate.net)
  • iii) assess the models' performance to differentiate CV from non‐CV death. (gla.ac.uk)
  • Competing‐risk models were used to assess the best combination of variables associated with each cause‐specific death. (gla.ac.uk)
  • Therefore, purpose of this study was to assess acute electrophysiologic effects of caffeine and taurine, two of the main ingredients of energy drinks, in an experimental whole-heart model. (researchgate.net)
  • A unique cardiovascular disease (CVD) risk calculator for black adults may not be necessary, a study found, despite that fact that current prediction models were developed with predominantly white populations. (acpinternist.org)
  • The study found that, between 85% and 99% of the time, the office-based risk prediction model worked as well as the laboratory-based model in characterizing CVD risk. (harvard.edu)
  • In study III, Rickard Strandberg focuses on risk prediction with a modification of the natural history model to incorporate risk factors separately in each of the four components of the model. (ki.se)
  • Validating the model against data from other study populations is also an important step. (ki.se)
  • Professor, Departments of Neurological Surgery, Physical Medicine & Medicine and Physical Therapy, Co-Director, DHHS-NIDILRR South Florida SCI Model System, and led by Gregory Bigford, Ph.D., Assistant Scientist , discovered these findings in their pre-clinical work, and hope that further study will lead to effective clinical interventions for those living with SCI. (themiamiproject.org)
  • Without information about study-specific context, it is impossible to provide an unqualified assessment of a model that is informative about the specific application. (biomedcentral.com)
  • A computational model for end-to-side anastomosis (superior ulnar collateral anastomosis with posterior ulnar recurrent, SUC-PUR) is carried out to study the effects of some clinically relevant haemodynamic parameters like blood flow resistance and terminal re- sistance on pressure and flow at different locations of the arm artery. (kobv.de)
  • 2 Therefore, the purpose of this study was to elucidate the impact of caffeine and taurine on arrhythmogenesis in a sensitive whole-heart model. (researchgate.net)
  • In the current study, we convened focus groups with PCPs to elicit their perspectives on using prediction models to identify PrEP candidates in clinical practice. (cdc.gov)
  • In preparation for implementation in clinical settings, we conducted a qualitative study with PCPs to learn their perspectives on using HIV risk prediction models to identify PrEP candidates in primary care. (cdc.gov)
  • 1 National policies now support targeting of interventions to reduce risk of cardiovascular disease among high risk patients. (bmj.com)
  • Therefore, we examined whether common physiological cardiovascular risk factors differ between patients with depression and healthy (non-depressed) controls, whether patients and controls differ in CRF, and whether higher CRF is associated with a lower cardiovascular risk in both patients and healthy controls. (frontiersin.org)
  • Additionally, we examined whether within the patient sample, cardiovascular risk factors differ between patients with mild, moderate and severe depression, and whether the relationship between symptom severity and cardiovascular risk is moderated by patients' CRF levels. (frontiersin.org)
  • Compared to healthy controls, patients with depression had a higher cardiovascular risk as evident from about half of the examined indicators. (frontiersin.org)
  • In contrast, people with good CRF show more favourable cardiovascular risk scores, a relationship which was observed in both healthy controls and patients with depression. (frontiersin.org)
  • However, among diabetes patients, the office-based model underestimated the risk noticeably. (harvard.edu)
  • yet these models allowed the identification of patients in whom absolute CV death rates clearly outweigh non‐CV death ones. (gla.ac.uk)
  • Conclusions Risk models for predicting CV and non‐CV death allowed the identification of patients at higher absolute risk of dying from CV causes (vs. non‐CV ones). (gla.ac.uk)
  • PCPs believed that models could facilitate patient-provider communication about HIV risk, destigmatize and standardize HIV risk assessments, help patients accurately perceive their risk, and identify PrEP candidates who might otherwise be missed. (cdc.gov)
  • The net reclassification improvement (NRI) is an increasingly popular measure for evaluating improvements in risk predictions. (acpjournals.org)
  • However, their prediction with traditional statistical models remain imprecise. (bvsalud.org)
  • Conclusions: Existing CVD risk prediction tools may identify future CHD cases with fairly good confidence on a short-term basis. (edu.au)
  • CONCLUSIONS: The DNN model had good prediction ability for incident AHF using climate information. (bvsalud.org)
  • Hopefully, we have communicated that these types of modelling approaches are useful for a wide array of applications. (ki.se)
  • In simulations, frequency band model performance rates predictions better (lower RMSE, higher correlation) when there is no error at a particular timescale (e.g., acute) and worse when error is added to that timescale, compared to overall approaches. (biomedcentral.com)
  • Because time is an explicit parameter incorporated in species-specific constants such as mu- cociliary clearance rates used in the models, the impact of the application of optimal model structures to refine adjustments and assumptions used in default risk assessment approaches to address exposure duration are discussed. (cdc.gov)