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At least 433 records · Page 24Linked to original sources
PubMed1999

Coronary calcium does not accurately predict near-term future coronary events in high-risk adults.

BACKGROUND: Prognostic risk models have had limited success in predicting coronary events in subjects with multiple risk factors. We and others have proposed an alternative approach using radiographically detectable coronary calcium. We evaluated and compared the predictive value of these 2 approaches for determining coronary event risk in asymptomatic adults with multiple coronary risk factors. In addition, we assessed the predictive value of a risk model that included calcium score and cardiac risk-factor data. METHODS AND RESULTS: We recruited 1196 asymptomatic high-coronary-risk subjects who then underwent risk-factor assessment and cardiac electron-beam CT (EBCT) scanning and were followed up for 41 months with a 99% success rate. We applied the Framingham model and our data-derived risk model to determine the 3-year likelihood of a coronary event. The mean age of our cohort was 66 years, and mean 3-year Framingham risk was 3.3+/-3.6%. Sixty-eight percent (818 subjects) had detectable coronary calcium. There were 17 coronary deaths (1.4%) and 29 nonfatal infarctions (2. 4%). The receiver operating characteristic (ROC) curve areas calculated from the Framingham model, our data-derived risk model, and the calcium score were 0.69+/-0.05, 0.68+/-0.05, and 0.64+/-0.05, respectively (P=NS). When calcium score was included as a variable in the data-derived model, the ROC area did not change significantly (0.68+/-0.05 to 0.71+/-0.04; P=NS). CONCLUSIONS: Neither risk-factor assessment nor EBCT calcium is an accurate event predictor in high-risk asymptomatic adults. EBCT calcium score does not add significant incremental information to risk factors, and its use in clinical screening is not justified at this time.

Aged↗
PubMed1991

A model standardized risk assessment protocol for use with hazardous waste sites.

This paper presents a model standardized risk assessment protocol (SRAP) for use with hazardous waste sites. The proposed SRAP focuses on the degree and patterns of evidence that exist for a significant risk to human populations from exposure to a hazardous waste site. The SRAP was designed with at least four specific goals in mind: to organize the available scientific data on a specific site and to highlight important gaps in this knowledge; to facilitate rational, cost-effective decision making about the best distribution of available manpower and resources; to systematically classify sites roughly according to the level of risk they pose to surrounding human populations; and to promote an improved level of communication among professionals working in the area of waste site management and between decision makers and the local population.

Algorithms↗
PubMed2001

Radiation carcinogenesis modelling for risk of treatment-related second tumours following radiotherapy.

Radiobiological modelling of the risk of radiation-induced tumours following high dose radiation implies a general form for the dose-response relationship. Generally, risk will rise with radiation dose at low doses, reach a maximum value and then decline with further increase in dose. The magnitude of risk and the dose at which this risk is maximum are strongly dependent on the kinetics of repopulation by surviving normal and mutant cells and on genetic factors likely to differ between tissues and between individuals. The most reliable way to reduce the risk of second tumours is to reduce radiation dose further at sites where the dose is already low. These sites are usually distant from the primary treatment volume. For illustrative purposes, we have compared the predicted relative risks of second tumours at "distant sites" for treatment plans giving similar dose distributions (dose volume histograms) at the primary site. We suggest that dose reduction to distant sites could be of significant benefit in reducing the risk of second tumours. Further improvement will require more detailed knowledge of the radiation sensitivities and mutagenicities, together with the repopulation kinetics of the various cell lineages within the treatment volume.

Cell Death↗
PubMed2003

Validation of Mayo Clinic risk adjustment model for in-hospital complications after percutaneous coronary interventions, using the National Heart, Lung, and Blood Institute dynamic registry.

OBJECTIVES: We sought to validate the recently proposed Mayo Clinic risk score model for complications after percutaneous coronary interventions (PCI), using an independent data set. BACKGROUND: The Mayo Clinic risk score has eight simple clinical and angiographic variables for the prediction of complications defined as either death, Q-wave myocardial infarction, emergent or urgent coronary artery bypass graft surgery, or cerebrovascular accident after PCI. External validation using an independent data set is lacking. METHODS: A total of 3,264 patients undergoing PCI at each of the 17 sites in the National Heart, Lung, and Blood Institute's Dynamic Registry during two enrollment periods (July 1997 to February 1998 and February to June 1999) were studied. Logistic regression was used to model the calculated risk score and major procedural complications. The expected number of complications, with 95% confidence bounds (CBs), was also calculated. RESULTS: There were 96 (2.94%) observed procedural complications, and the Mayo Clinic risk score predicted 93.5 events (2.86%; 95% CB 2.32% to 3.41%; p = NS). The Hosmer-Lemeshow goodness-of-fit p value was 0.28, and the area under the receiver operating curve was 0.76, indicating excellent overall discrimination. There were no statistical differences between observed and predicted procedural complications using the Mayo Clinic risk score among the most selected high- and low-risk subgroups. CONCLUSIONS: Eight variables were combined into a convenient risk scoring system that accurately predicts cardiovascular complications after PCI. The Mayo clinic predictive model for procedural complications yielded excellent results when applied to a multi-center external data set.

Aged↗
PubMed2004

Flexible dose-response models for Japanese atomic bomb survivor data: Bayesian estimation and prediction of cancer risk.

Generalised absolute risk models were fitted to the latest Japanese atomic bomb survivor cancer incidence data using Bayesian Markov Chain Monte Carlo methods, taking account of random errors in the DS86 dose estimates. The resulting uncertainty distributions in the relative risk model parameters were used to derive uncertainties in population cancer risks for a current UK population. Because of evidence for irregularities in the low-dose dose response, flexible dose-response models were used, consisting of a linear-quadratic-exponential model, used to model the high-dose part of the dose response, together with piecewise-linear adjustments for the two lowest dose groups. Following an assumed administered dose of 0.001 Sv, lifetime leukaemia radiation-induced incidence risks were estimated to be 1.11 x 10(-2) Sv(-1) (95% Bayesian CI -0.61, 2.38) using this model. Following an assumed administered dose of 0.001 Sv, lifetime solid cancer radiation-induced incidence risks were calculated to be 7.28 x 10(-2) Sv(-1) (95% Bayesian CI -10.63, 22.10) using this model. Overall, cancer incidence risks predicted by Bayesian Markov Chain Monte Carlo methods are similar to those derived by classical likelihood-based methods and which form the basis of established estimates of radiation-induced cancer risk.

Algorithms↗
PubMed2006

Modelling suicide risk in later life.

Affective disorder is generally regarded as the prominent risk factor for suicide in the old age population. Despite the large number of empirical studies available in the literature, there is no attempt in modelling the dynamics of an individual's level of suicide risk theoretically yet. In particular, a dynamic model which can simulate the time evolution of an individual's level of risk for suicide and provide quantitative estimates of the probability of suicide risk is still lacking. In the present study we apply the contingent claims analysis of credit risk modelling in the field of quantitative finance to derive a theoretical stochastic model for estimation of the probability of suicide risk in later life in terms of a signalling index of affective disorder. Our model is based upon the hypothesis that the current state of affective disorder of a patient can be represented by a signalling index and exhibits stochastic movement and that a threshold of affective disorder, which signifies the occurrence of suicide, exists. According to the numerical results, the implications of our model are consistent with the clinical findings. Hence, we believe that such a dynamic model will be essential to the design of effective suicide prevention strategies in the target population of older adults, especially in the primary care setting.

Aged↗
PubMed1996

The challenge of mechanism-based modeling in risk assessment for neurobehavioral end points.

The mathematical form for a dose-time-response model is ideally not just a convenience for summarizing or fitting a particular data set--it represents a hypothesis. The more this hypothesis reflects a mechanistically sophisticated view of the likely reality, the more it can lead to potentially informative validating or invalidating types of predictions about the results of real experiments and (in the long run) reasonably credible predictions outside the range of direct observations. This paper first reviews some distinctive features of the nervous system and neurotoxic responses and theoretically explores some basic quantitative implications of these features. Relationships are derived for how dose-response relationships for the inhibition of function should depend on the numbers of neurons in series or redundant parallel arrangements that are required or capable of performing the function. Previous work is reviewed in which some less nervous-system-specific features were the foci of quantitative risk-assessment modeling for specific neurotoxic end points. These include a) rates of repair of putatively reversible damage in the case of acrylamide; b) human interindividual variability in susceptibility to fetal/developmental effects in the case of methylmercury; and c) opportunities to use intermediate biomarkers to assist in integrated animal toxicological and epidemiologic investigations of the chronic cumulative risks posed by agents that contribute to neuronal loss with increasing age and pathology.

Behavior↗
PubMed2003

Modeling and risk prediction in the current era of interventional cardiology: a report from the National Heart, Lung, and Blood Institute Dynamic Registry.

BACKGROUND: Validation of in-hospital mortality models after percutaneous coronary interventions using multicenter data remains limited. METHODS AND RESULTS: This study evaluated whether multivariable mortality models developed during the pre-stent era by New York State, American College of Cardiology (ACC)-National Cardiovascular Data Registry, Northern New England Cooperative Group, Cleveland Clinic Foundation, and the University of Michigan are relevant in patients undergoing percutaneous coronary intervention in the 1997 to 1999 National Heart, Lung, and Blood Institute Dynamic Registry. Of 4448 Dynamic Registry patients, 73% received > or =1 stent and 28% received a IIB/IIIA receptor inhibitor. In-hospital mortality occurred in 64 patients (1.4%). The New York state model predicted mortality in 69 patients (1.5%; 95% confidence bounds [CI], 0.89% to 1.70%); Northern New England predicted mortality in 60 patients (1.3%; 95% CI, 1.0% to 1.7%); and Cleveland Clinic predicted mortality in 76 patients (1.7%; 95% CI, 1.3% to 2.1%). Among high-risk subgroups, with these 3 models, observed and predicted in-hospital mortality rates in general were not different. The other 2 models yielded different results. The University of Michigan predicted fewer deaths (n=47; 1.1%; 95% CI, 0.7% to 1.3%), and the ACC Registry model predicted 603 deaths (13.5%; 95% CI, 12.6% to 14.4%). Using the ACC Registry model, predicted mortality was higher than observed in each subgroup. CONCLUSIONS: Application of 5 mortality risk models developed from different data sets to patients undergoing percutaneous coronary intervention in the Dynamic Registry predicted, in 3 models, mortality rates that were not significantly different than those observed. In both high and low risk subgroups, the University of Michigan slightly underpredicted mortality, and the ACC Registry predicted significantly higher mortality than that observed.

Angioplasty, Balloon, Coronary↗
PubMed1988

Extrapolation of the relative risk of radiogenic neoplasms across mouse strains and to man.

We have examined two interrelated questions: is the susceptibility for radiogenic cancer related to the natural incidence, and are the responses of cancer induction by radiation described better by an absolute or a relative risk model. Also, we have examined whether it is possible to extrapolate relative risk estimates across species, from mice to humans. The answers to these questions were obtained from determinations of risk estimates for nine neoplasms in female and male C3Hf/Bd and C57BL/6 Bd mice and from data obtained from previous experiments with female BALB/c Bd and RFM mice. The mice were exposed to 137Cs gamma rays at 0.4 Gy/min to doses of 0, 0.5, 1.0, or 2.0 Gy. When tumors that were considered the cause of death were examined, both the control and induced mortality rates for the various tumors varied considerably among sexes and strains. The results suggest that in general susceptibility is determined by the control incidence. The relative risk model was significantly superior in five of the tumor types: lung, breast, liver, ovary, and adrenal. Both models appeared to fit myeloid leukemia and Harderian gland tumors, and neither provided good fits for thymic lymphoma and reticulum cell sarcoma. When risk estimates of radiation-induced tumors in humans and mice were compared, it was found that the relative risk estimates for lung, breast, and leukemia were not significantly different between humans and mice. In the case of liver tumors, mice had a higher risk than humans. These results indicate that the relative risk model is the appropriate approach for risk estimation for a number of tumors. The apparent concordance of relative risk estimates between humans and mice for the small number of cancers examined encourages us to undertake further studies.

Animals↗
PubMed1993

A proposal for improving the role of exposure modeling in risk assessment.

This paper explores the adequacy of using currently available exposure assessment models for indoor air inhalation exposures in the context of the uncertainty that exists in both the dose-response assessment and the exposure assessment. A tiered system is proposed for implementing exposure assessments. Each tier involves additional research, but also would lead to reductions in uncertainty. The authors discuss a possible comprehensive research program that will permit the building of well-validated models for indoor air inhalation exposures among classes of chemicals, building types, and exposure scenarios. The authors believe that until such a research program is undertaken, modeling of exposures (and therefore risks) using the current, unvalidated modeling approaches provides little more than worst-case estimates that are useful primarily for making screening decisions about risks.

Air Pollution, Indoor↗
PubMed2004

A quantitative risk assessment model for Salmonella and whole chickens.

Existing data and predictive models were used to define the input settings of a previously developed but modified quantitative risk assessment model (QRAM) for Salmonella and whole chickens. The QRAM was constructed in an Excel spreadsheet and was simulated using @Risk. The retail-to-table pathway was modeled as a series of unit operations and associated pathogen events that included initial contamination at retail, growth during consumer transport, thermal inactivation during cooking, cross-contamination during serving, and dose response after consumption. Published data as well as predictive models for growth and thermal inactivation of Salmonella were used to establish input settings. Noncontaminated chickens were simulated so that the QRAM could predict changes in the incidence of Salmonella contamination. The incidence of Salmonella contamination changed from 30% at retail to 0.16% after cooking to 4% at consumption. Salmonella growth on chickens during consumer transport was the only pathogen event that did not impact the risk of salmonellosis. For the scenario simulated, the QRAM predicted 0.44 cases of salmonellosis per 100,000 consumers, which was consistent with recent epidemiological data that indicate a rate of 0.66-0.88 cases of salmonellosis per 100,000 consumers of chicken. Although the QRAM was in agreement with the epidemiological data, surrogate data and models were used, assumptions were made, and potentially important unit operations and pathogen events were not included because of data gaps and thus, further refinement of the QRAM is needed.

Animals↗
PubMed2005

Benzodiazepines and injury: a risk adjusted model.

BACKGROUND: Benzodiazepines (BZD) are one class of medications that are generally acknowledged to be a risk factor for injuries. OBJECTIVE: Our objective was to link outpatient prescription data with clinical data in order to develop a risk adjusted binary model that associates BZD usage with the risk for a healthcare encounter for an injury. METHODS: In total, 3 years of outpatient BZD prescription data, totaling 133 872 outpatient BZD prescriptions for 13 745 patients for a VA medical center, were combined with data from inpatient and outpatient administrative databases. The model incorporated Elixhauser comorbidity measures with 1-year look back period, along with hospital discharges, marital status, age, mean arterial pressure and body mass index. The model also included the dose of the drug, converted to valium equivalents and its duration. The model was analyzed using generalized estimation equations (GEE). RESULTS: Dose, duration, discharges and various comorbidities were associated with an increased risk for injury, while being married reduced the risk. Increased body mass was associated with increased injury risk. Increased mean arterial pressure was associated with decreased risk. CONCLUSIONS: These findings offer guidance on how specific combinations of risk factors and potential protective effects may impact accidental injury risk. Clinicians prescribing or adjusting BZDs can use these results to more accurately tailor medication regimens for a patient. Our findings suggest that clinicians should also consider the nature of the social support system available to the patient in assessing total injury risk.

Age Factors↗
PubMed2002

Inaccuracy of four coronary surgery risk-adjusted models to predict mortality in individual patients.

OBJECTIVES: This study was undertaken to evaluate the accuracy of four different risk-adjusted models in predicting mortality in individual patients who are undergoing coronary artery by-pass graft surgery. In the last decade several models to stratify patients before open heart surgery, according to factors affecting mortality, were developed with the aim of retrospectively comparing outcomes of open heart surgery, based on reliable stratification of case-mix, and of prospectively identifying high risk patients as a basis for a meaningful informed consent for patients counseling. METHODS: The pre-operative risk of death was calculated with four different models in 418 consecutive patients who underwent coronary artery by-pass surgery and then compared with the actual outcome. To discriminate patients with favorable and unfavorable outcome, the logistic regression analysis and the areas under the receiver-operating-characteristic curves were applied. The accuracy score was used to evaluate the reliability of each score to predict the individual outcome. RESULTS: Seven deaths (1.7%) were observed within 30 days from the operation, and the overall incidence was similar to that predicted by all models. Only the NBI score was not able to discriminate survivors from patients who will die, and the areas under the curves were 0.596 for the Parsonnet score, 0.861 for the Cleveland Clinic Foundation score, 0.823 for the French score, and 0.806 for the EuroSCORE. The four models were highly accurate (between 0.97 and 0.98) to predict the overall mortality. In seven patients who died the mean predictive scores were very low and ranged between 2.1 and 4.6, but were significantly higher than those of patients who survived (between 1.1 and 2.2). CONCLUSIONS: The four pre-surgical predictive models were similarly able to discriminate favorable vs. unfavorable outcomes and highly accurate to predict overall mortality, but very inaccurate to predict mortality in individual patients.

Adult↗
PubMed2001

The stratified-population-at-risk (SPAR) model for psychogeriatric nursing: a paradigm for the third millennium?

There is warning of a coming epidemic of older people with psychiatric problems. However, there are already too few specialist nurses to ensure that all older people receive care concordant with accepted professional standards. This problem is an obstacle to the World Health Organization health for all by 2000 objective. The Stratified Population at Risk (SPAR) model is a proactive paradigm for planning psychogeriatric nursing services that includes mental health promotion. The SPAR model assumes that-under certain conditions-all people are vulnerable to psychiatric problems, but differ in their level of risk. The model includes an innovative role for psychogeriatric nurse specialists.

Aged↗
PubMed2002

A risk-factor model of epistatic interaction, focusing on autism.

Research to date on the genetics of autism has not uncovered a major susceptibility locus and indications are that a number of genes, perhaps as many as 15-20, may play detectable but minor roles in the etiology of the condition. To cope with this situation, a risk-factor model based on standard epidemiologic designs is proposed. The model supposes that adding a factor to a fixed set of existing factors always increases the total risk. Thus, according to the model genetic contributions cumulate but are not necessarily additive. A threshold, hence, epistasis is required. The model is applied to several conditions in which the risk of autism is elevated, some genetic (fragile X, tuberous sclerosis) and some exogenous (rubella and thalidomide embryopathies). Male gender is discussed as a risk factor. This approach is contrasted primarily with Gillberg and Coleman's view of autism as "a syndrome or series of syndromes caused by many different separate individual diseases." The principal point of difference is whether the effects of different causes cumulate or do not cumulate. In the present approach they do, in Gillberg and Coleman's they do not.

Autistic Disorder↗
PubMed1999

Applying risk assessment models in non-surgical patients: overview of our clinical experience.

Many venous thromboembolic events occur in non-surgical patients. Prophylaxis is recommended in consensus statements but is not uniformly applied in clinical practice. Medical conditions such as stroke, cancer, and myocardial infarction are associated with thromboembolism. Patients' overall risk is affected by pharmacotherapies (e.g., cancer chemotherapy), mechanical interventions (e.g., central venous catheterization), and by intrinsic patient factors such as age, obesity and coagulation disorders, both inherited and acquired. Few large clinical trials in well-defined medical patient subgroups have been performed. Due to the perceived lower incidence of thromboembolism in non-surgical patients compared to patients undergoing high-risk surgery (e.g., hip replacement), the value of thromboprophylaxis in medical patients has been questioned. Prophylaxis may have a significant impact on the frequency of non-fatal thromboembolic events, thereby reducing short- and long-term morbidity. Due to the complexity of overall thromboembolic risk assessment in medical patients and the paucity of convincing studies at present, prospectively validated evidence-based risk assessment models for determining thrombosis risk would be useful. Further clinical research is needed to help develop accurate methods of risk stratification and to clarify the benefits of thromboprophylaxis in medical patients.

Humans↗
PubMed2004

Hormesis: from marginalization to mainstream: a case for hormesis as the default dose-response model in risk assessment.

The paper provides an account of how the hormetic dose response has emerged in recent years as a serious dose-response model in toxicology and risk assessment after decades of extreme marginalization. In addition to providing the toxicological basis of this dose-response revival, the paper reexamines the concept of a default dose model in toxicology and risk assessment and makes the argument that the hormetic model satisfies criteria (e.g., generalizability, frequency, application to risk assessment endpoints, false positive/negative potential, requirements for hazard assessment, reliability of estimating risks, capacity for validation of risk estimates, public health implications of risk estimates) for such a default model better than its chief competitors, the threshold and linear at low dose models. The selection of the hormetic model as the default model in risk assessment for noncarcinogens and specifically for carcinogens would have a profound impact on the practice of risk assessment and its societal implications.

Animals↗
PubMed1993

A risk-assessment model for toxic exposure of small mammalian carnivores to cadmium in contaminated natural environments.

A model is presented to assess the risk of cadmium toxicity in mammalian wildlife in contaminated environments. The target-organ load was used as a hazard indicator and animals were considered to be at risk when a critical value, i.e. the lowest-observed-adverse-effect level (LOAEL), was attained or exceeded. The model was developed for Sorex araneus, a small mammalian predator with a high potential of attaining the critical target-organ load. Model parameter values were estimated from both explicit analysis of original field data and from theoretical considerations. A submodel was derived from linear regression of data concerning 36 field sites to predict the bioconcentration of cadmium in earthworms, an important food item of small mammalian carnivores. In addition to soil cadmium concentration several soil factors affecting cadmium bioavailability were included in the submodel. A second submodel was developed to predict target-organ load from a non-linear age-dependent regression of data on 63 predators from two different field sites. A separate theoretical model was constructed for the prediction of target-organ load as a function of pollutant ingestion, assimilation rates, and internal partitioning. The risk of cadmium exposure was assessed by estimating the EC50 value, the environmental effect concentration of a toxic substance in soil at which 50% of an adult population of predators would attain a target-organ load equal to or higher than the LOAEL. The model allows one to establish availability-differentiated soil quality standards with regard to cadmium pollution in natural environments. It predicts an exponential increase of the risk of hazardous exposure of terrestrial wildlife in areas sensitive to increasing levels of soil acidification ('chemical time bomb effect').

Animals↗