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Biomedical subjects

L Gatewood

Publications and source records attributed to L Gatewood.

17 recordsLinked to original sources
PubMed1999

PREDICT: A simple risk score for clinical severity and long-term prognosis after hospitalization for acute myocardial infarction or unstable angina: the Minnesota heart survey.

BACKGROUND: We evaluated short- and long-term mortality risks in 30- to 74-year-old patients hospitalized for acute myocardial infarction or unstable angina and developed a new score called PREDICT. METHODS AND RESULTS: PREDICT was based on information routinely collected in hospital. Predictors abstracted from hospital record items pertaining to the admission day, including shock, heart failure, ECG findings, cardiovascular disease history, kidney function, and age. Comorbidity was assessed from discharge diagnoses, and mortality was determined from death certificates. For 1985 and 1990 hospitalizations, the 6-year death rate in 6134 patients with 0 to 1 score points was 4%, increasing stepwise to 89% for >/=16 points. Score validity was established by only slightly attenuated mortality prediction in 3570 admissions in 1970 and 1980. When case severity was controlled for, 6-year risk declined 32% between 1970 and 1990. When PREDICT was held constant, 24% of those treated with thrombolysis died in 6 years compared with 31% of those not treated. CONCLUSIONS: The simple PREDICT risk score was a powerful prognosticator of 6-year mortality after hospitalization.

Adult↗
PubMed1997

A decentralized, community-based design for statewide immunization registries in Minnesota.

Incomplete immunization records and an increasingly complex immunization schedule make it difficult for parents and providers to know what shots their children or clients need. Complete and accurate immunization records are needed for day care, sports, camp, and school, but this is difficult--especially when previous immunizations have been received at different clinics. Population-based immunization registries help make complete and accurate records more easily available to parents and health care providers. Registries foster the timely sending of reminder notices for children who are due for immunizations and make it possible for providers to quickly assess immunization rates in their clinic. Public health officials use registries to determine immunization rates, to identify pockets of need where immunization rates are low and to target resources. In Minnesota, over 85% of immunizations are delivered in the private sector. Minnesota is also extensively covered by managed care organizations with an estimated 75% of the total population enrolled in some type of managed care. Strong local community public health agencies in each county also drive local solutions to community needs. These factors and others led to a de-centralized approach to the implementation of registries. The "Minnesota Model" is based on the development of community-based registries which link together local clinics, hospitals, health plans, public health departments, and schools in each region. Each community-based registry is designed to link to a state hub. This decentralized open architecture design is based on standards for data, not hardware or software. The building begins, not by implementing a state registry into which all immunizations are entered, but at the community level. Currently, 38% of Minnesota counties (representing 52% of statewide births) are involved in implementing a community-based registry, and 53% (representing 43% of statewide births) have initiated discussions with private providers. Only 9% of counties (5% of statewide births) have no current registry activity. This paper describes the steps which have been taken towards developing a decentralized statewide immunization information system for Minnesota, based on recommendations put forth by The State Immunization Practices Task Force Work Group on Immunization Registries.

Child↗
PubMed1995

Simulation of stochastic micropopulation models--IV. SNAPPERS: model implementation for genetic traits.

The current paper concerning stochastic micropopulation simulations describes SNAPPERS, which serves as a framework for simulation models of the genetic transmission of disease. The versions described are implemented using the simulation shell, SUMMERS, which includes the generic commonalities of several micropopulation models. Population members in SNAPPERS move through states related to the individual's status relative to the genotype (phenotype). Features of the model include one or two major loci, polygenic and common familial contribution to the phenotype, assortative mating, and flexibility in defining gene action. The user can select from multiple ascertainment strategies for analysis of simulated families.

Chromosome Mapping↗
PubMed1993

Simulation of stochastic micropopulation models--I. The SUMMERS simulation shell.

A generic, abstract model and the simulation shell based on it, both called SUMMERS, are used as a framework for the implementation of stochastic micropopulation models; in these, each individual is followed separately while moving through a sequence of states. The shell supports groups of interacting members, individual characteristics and multiple simultaneous activities. Stochastic decisions may be made using Monte Carlo rules. Keywords control the simulations and the reports generated. A sensitivity analysis utility allows assessment of the dependency of outcomes on model features. Extensive use has been made of software engineering techniques. Specializations of SUMMERS are described in subsequent papers.

Data Collection↗
PubMed1993

Simulation of stochastic micropopulation models--II. VESPERS: epidemiological model implementations for spread of viral infections.

This second paper concerning stochastic micropopulation simulations describes VESPERS, which can serve as a framework for simulation models of the epidemic spread of infection. The versions described are implemented using the simulation shell, SUMMERS, which includes the generic commonalities of several micropopulation models. Population members in VESPERS move through states related to the individual's status relative to the infective agent. Features of the models include mixing groups, member demographics, susceptibility and infectiousness, and co-circulation of infectious agents. The sensitivity of the simulation outcomes to quantitative features of the model has been analyzed. The user can select reports of desired distributions and averages of simulation outcomes.

Demography↗
PubMed1993

Simulation of stochastic micropopulation models--III. COGNET: an artificial neural network for visual recognition.

COGNET, based on a neural network first described by Fukushima, demonstrates the relationship between connectionist and other micropopulation models. Its success and physiological orientation led to an implementation using the SUMMERS simulation shell. After self-supervised learning, COGNET uses forward and backward propagation of signals to recognize partial and noisy patterns, and to reconstruct the originals. Stochastic features include variable thresholds for neuronal firing and occasional cell death. The successful implementation of COGNET demonstrates the generality of the concepts embodied in SUMMERS, which in turn promotes the reusability of software and facilitates the extension of computational models in biomedical research. COGNET itself forms a framework for building other physiologically oriented neural network models.

Computer Simulation↗
PubMed1991

Polychotomous multivariate models for coronary heart disease simulation. I. Tests of a logistic model.

Stochastic compartmental modeling techniques have been employed to simulate coronary heart disease morbidity and mortality. In the current paper, polychotomous logistic models are used to describe the relationship between risk of disease and multiple risk factors, effect modification and confounding variables. The process of estimating the parameters for two risk factors and three types of outcomes is described for a population followed for five years. A Statistical Analysis System (SAS) procedure was used to estimate risk factor coefficients based on two partial periods and on the entire five year epoch. Most of the estimated coefficients were found to be statistically significant. The model performance was evaluated by comparing the observational data with simulated outcomes using a micropopulation and Monte Carlo techniques. Two different tests of goodness of fit were used. Satisfactory fits were obtained both for the risk coefficients based on two partial periods and those based on the entire epoch. This indicates that the model is suitable for simulation of the effects of intervention strategies. The use of the entire epoch involved estimates of one half as many parameters as did the use of two partial periods. Accordingly, it is concluded that only the entire epoch need be considered for future studies of this population.

Adult↗
PubMed1991

An expert system for simulation of coronary heart disease risk factor interventions.

The feasibility of using an expert system to support intervention studies within CRISPERS was investigated. A prototype expert system named CRISPERT was designed to accept user inputs, adjust the values to CRISPERS requirements, start a sequence of simulations, and analyze and interpret the results. The rule-based system was implemented using the expert system development language OPS5 combined with FORTRAN, as well as SAS procedures and DEC VMS system service routines. Results of initial tests suggest that using an expert system as an interface between users and CRISPERS is a viable approach. The development of CRISPERT facilitates the usability of CRISPERS for intervention studies of coronary heart disease.

Computer Simulation↗
PubMed1990

Monte Carlo simulation of HIV infection in an intravenous drug user community.

Intravenous drug users are crucial to the understanding and control of human immunodeficiency virus (HIV) transmission. We have developed a population-based simulation of a community of intravenous drug users. This model was implemented using Monte Carlo techniques, which permit great flexibility in creating realistic social structures, to describe the needle-sharing network of drug users. We present the baseline behavior of this model in a generic community and demonstrate the model's utility for assessing public health interventions. Our early results demonstrate the powerful effects of social networks on HIV transmission and the importance of prevalence levels in assessing the effectiveness of interventions in the drug-injecting community.

Equipment Contamination↗
PubMed1976

An influenza simulation model for immunization studies.

A stochastic simulation epidemic model based on discrete time intervals and appropriate for any infectious agent spread by person-to-person contacts is presented. The population is highly structured, allowing for five age groups and for subgrouping mixing in families, neighborhoods, schools, and preschool playgroups as well as total community mixing. With proper choice of relative susceptibility by age, length of latency and infectivity periods, pathogenicity and withdrawal patterns, and the relative infectiousness of silent infections, the model becomes highly agent-specific. The model includes flexible immunization routines and variable vaccine response patterns. The model is applied to the 1957 Asian and 1968 Hong Kong pandemic strains of influenza A. The results of several schedules of immunization of school children are presented and compared for the two strains.

Adolescent↗
PubMedDate not supplied

Polychotomous multivariate models for coronary heart disease simulation. II. Comparisons of risk functions.

This is the second in a series of papers dealing with models of coronary heart disease. Three different types of statistical models are considered as risk functions: the multivariate logistic model, the Cox proportional hazard model and the Neyman exponential risk avoidance model. The types of models differ in the form hypothesized for the probability of occurrence of coronary heart disease outcomes: incident myocardial infarct, cardiac death, and death from other causes. Although the three risk functions are strikingly different, they can all be tested using the CRISPERS chronic disease simulation system. Simulations were performed using data from North Karelia, Finland. The polychotomous multivariate logistic risk function is convenient for studies involving increasing numbers of risk factors. The Cox proportional hazard regression model is shown to be unsuitable for the cohort dataset used as well as for some of the intended uses of the simulation models. The Neyman exponential risk avoidance model involves time in a quite different fashion. It has the inherent advantage of being easier to relate to underlying biological mechanisms because it is the integral of first order rate equations. It is concluded that more than one risk function should be evaluated for simulations of coronary heart disease.

Adult↗
PubMedDate not supplied

Polychotomous multivariate models for coronary heart disease simulation. III. Model sensitivities and risk factor interventions.

This is the third in a series of papers dealing with models of coronary heart disease. Sensitivity analyses of the logistic risk function and the Neyman risk function are reported. The resulting response surfaces are also used to investigate the optimality of the set of values for the risk coefficients. It is shown that the coefficients estimated by maximum likelihood are preferable to the sets from an optimisation procedure. Two different sets of risk coefficients estimated using short periods and entire epochs for the logistic risk function are shown to lead to similar conclusions concerning simulated primary intervention strategies. However, the corresponding risk factor reductions using the Neyman risk function lead to somewhat different effects. Additional information is needed to distinguish between these two assumptions of the risk function used to model coronary heart disease. This underscores the need to understand the effects of the underlying risk function assumed when interpreting simulated outcomes of intervention strategies.

Computer Simulation↗
PubMedDate not supplied

Polychotomous multivariate models for coronary heart disease simulation. IV. The impact of physiological aging.

This is an extension of a series of papers dealing with certain models used in the simulation of coronary heart disease. The current study investigates implications of including age as a risk factor in the models discussed in the preceding papers. The effects of using age as a risk factor were investigated in two ways. In one of these, age is interpreted as age of entry into the study; it is similar to the other risk factors in that it is assumed to be constant throughout the study. In the other, age is interpreted as the actual age; thus it increases during the course of simulations. Two polychotomous, multivariate risk functions developed in previous studies, the logistic risk and the Neyman exponential risk, were used to explore the effects of including age as a risk factor. The estimated risk coefficient for age was found to be statistically significant for both functions. The model performance was evaluated by comparing the observational data with outcomes simulated using Monte Carlo techniques. It was found that the logistic risk function failed to describe the observations either with age as a constant or with aging during the simulations. The models including the Neyman exponential risk avoidance fit the data well. The evaluation of the results indicates that aging during the simulations is better than using only the age as the constant value at entry to the study.

Adult↗