Biomedical subjects

Daowen Zhang

Publications and source records attributed to Daowen Zhang.

6 recordsLinked to original sources

PubMed2005

Sarcopenia is related to physical functioning and leg strength in middle-aged women.

BACKGROUND: In the aging process, loss of muscle is relatively continuous, but the initiation, timing, and amount of muscle loss that relate to functional compromise are poorly described. Also poorly understood is whether strength and functioning in aging are related to the amount of lean mass and its change as well as to the amount of fat mass and its change. METHODS: The purpose of the study was to ascertain whether 3-year lean and fat mass change predicted functional status in 712 African American and Caucasian women, aged 34-58 years. Fat and lean mass were assessed with bioelectrical impedance. Lower leg strength (torque) was measured with a portable isometric chair, and two indices of physical functioning, walking velocity and double support (both feet touching the surface while walking), were measured with an instrumented gait mat. RESULTS: Almost 9% of middle-aged women had at least a 6% loss (>2.5 kg) of lean mass over the 3-year observation period. Women who lost at least 2.5 kg of lean mass had slower walking velocity and less leg strength, although women who simultaneously gained more than 2.5 kg of fat mass (at least 7.5%) did not have less leg strength. Age was significantly associated with less velocity, less leg strength, and more time in double support. CONCLUSIONS: Even in middle-aged women, there is loss of lean mass among almost 1 woman in 10, and this loss of lean mass (sarcopenia) is associated with greater compromise in physical functioning.

Adipose Tissue↗

PubMed2004

Generalized linear mixed models with varying coefficients for longitudinal data.

The routinely assumed parametric functional form in the linear predictor of a generalized linear mixed model for longitudinal data may be too restrictive to represent true underlying covariate effects. We relax this assumption by representing these covariate effects by smooth but otherwise arbitrary functions of time, with random effects used to model the correlation induced by among-subject and within-subject variation. Due to the usually intractable integration involved in evaluating the quasi-likelihood function, the double penalized quasi-likelihood (DPQL) approach of Lin and Zhang (1999, Journal of the Royal Statistical Society, Series B61, 381-400) is used to estimate the varying coefficients and the variance components simultaneously by representing a nonparametric function by a linear combination of fixed effects and random effects. A scaled chi-squared test based on the mixed model representation of the proposed model is developed to test whether an underlying varying coefficient is a polynomial of certain degree. We evaluate the performance of the procedures through simulation studies and illustrate their application with Indonesian children infectious disease data.

Biometry↗

PubMed2004

Conditional estimation for generalized linear models when covariates are subject-specific parameters in a mixed model for longitudinal measurements.

The relationship between a primary endpoint and features of longitudinal profiles of a continuous response is often of interest, and a relevant framework is that of a generalized linear model with covariates that are subject-specific random effects in a linear mixed model for the longitudinal measurements. Naive implementation by imputing subject-specific effects from individual regression fits yields biased inference, and several methods for reducing this bias have been proposed. These require a parametric (normality) assumption on the random effects, which may be unrealistic. Adapting a strategy of Stefanski and Carroll (1987, Biometrika74, 703-716), we propose estimators for the generalized linear model parameters that require no assumptions on the random effects and yield consistent inference regardless of the true distribution. The methods are illustrated via simulation and by application to a study of bone mineral density in women transitioning to menopause.

Biometry↗

PubMed2003

Hypothesis testing in semiparametric additive mixed models.

We consider testing whether the nonparametric function in a semiparametric additive mixed model is a simple fixed degree polynomial, for example, a simple linear function. This test provides a goodness-of-fit test for checking parametric models against nonparametric models. It is based on the mixed-model representation of the smoothing spline estimator of the nonparametric function and the variance component score test by treating the inverse of the smoothing parameter as an extra variance component. We also consider testing the equivalence of two nonparametric functions in semiparametric additive mixed models for two groups, such as treatment and placebo groups. The proposed tests are applied to data from an epidemiological study and a clinical trial and their performance is evaluated through simulations.

Anticonvulsants↗

PubMed2002

Randomized COMparison of platelet inhibition with abciximab, tiRofiban and eptifibatide during percutaneous coronary intervention in acute coronary syndromes: the COMPARE trial. Comparison Of Measurements of Platelet aggregation with Aggrastat, Reopro, and Eptifibatide.

BACKGROUND: The relative anti-aggregatory effects of currently prescribed platelet glycoprotein IIb/IIIa receptor antagonists during and after percutaneous coronary intervention for acute coronary syndromes have not been established. METHODS AND RESULTS: We randomized 70 acute coronary syndrome patients undergoing percutaneous coronary intervention to receive abciximab, eptifibatide, or tirofiban at doses used in the Evaluation of Platelet IIb/IIIa Inhibitor for STENTing (EPISTENT), Platelet glycoprotein IIb/IIIa in Unstable angina Receptor Suppression Using Integrilin Therapy (PURSUIT), and Platelet Receptor Inhibition in ischemic Syndrome Management in Patients Limited by Unstable Signs and symptoms (PRISM-PLUS)/Randomized Efficacy Study of Tirofiban for Outcomes and Restenosis (RESTORE) trials, respectively. Platelet aggregation (PA) in response to 20 micro mol/L of adenosine diphosphate was measured with turbidimetric aggregometry in both D-phenylalanyl-L-prolyl-L-arginine chloromethylketone and citrate-anticoagulated blood early (15 and 30 minutes) and late (4, 12, and 18 to 24 hours) after drug initiation. At 15 and 30 minutes, PA was significantly less inhibited by the tirofiban-RESTORE regimen compared with abciximab (P=0.028) and eptifibatide regimens (P=0.0001). The abciximab regimen, however, showed increasingly varied anti-aggregatory effects during continued infusion for > or =4 hours. Citrate exaggerated ex vivo platelet inhibition after eptifibatide and tirofiban, but had the opposite effect on abciximab. Of all regimens evaluated, the eptifibatide regimen inhibited PA most consistently throughout both the early and late periods. CONCLUSIONS: Currently recommended drug regimens to inhibit the platelet glycoprotein IIb/IIIa receptor have distinct pharmacodynamic profiles that might affect their relative efficacy in acute coronary syndromes and percutaneous coronary intervention.

Abciximab↗

PubMed2002

A Monte Carlo EM algorithm for generalized linear mixed models with flexible random effects distribution.

A popular way to represent clustered binary, count, or other data is via the generalized linear mixed model framework, which accommodates correlation through incorporation of random effects. A standard assumption is that the random effects follow a parametric family such as the normal distribution; however, this may be unrealistic or too restrictive to represent the data. We relax this assumption and require only that the distribution of random effects belong to a class of 'smooth' densities and approximate the density by the seminonparametric (SNP) approach of Gallant and Nychka (1987). This representation allows the density to be skewed, multi-modal, fat- or thin-tailed relative to the normal and includes the normal as a special case. Because an efficient algorithm to sample from an SNP density is available, we propose a Monte Carlo EM algorithm using a rejection sampling scheme to estimate the fixed parameters of the linear predictor, variance components and the SNP density. The approach is illustrated by application to a data set and via simulation.

Journal Article↗