Human coronary artery remodeling, beginning and end of the atherosclerotic process.
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BACKGROUND, AIMS OF THE STUDY: The objective of the study was to relate the progress of coronary artery remodeling to the earliest stages of the atherosclerotic process. For this purpose, a mathematical model for description of dimensional change of the coronary artery wall and its constituent components was developed and applied. MATERIALS AND METHODS: The study used coronary artery samples randomly taken from each of 83 consecutive, unselected postmortems. All samples were routinely fixed and processed to paraffin for the preparation of right-angled, 5-micron sections, routinely stained and mounted for subsequent analysis. Computer assisted image analysis, using 32 systematic random, radial sampling lines, was used for interactive measurements of distance from centre of lumen to points defining intima, media and adventitia thickness along the radial intercept, which were subsequently tabled for analysis of variance, calculations of (group-vessel) means, and related to stage of pathology. RESULTS: Pre-atherosclerotic changes, before any localised changes in especially intima dimensions, are found, consisting of a process of gradual vascular widening, associated with temporally at least partly dissociated increases in width, which as a fraction of total vessel radius show a phased process. In these, the intima first increases, subsequently remains stable, and finally reduces in width proportionally to the increasing diameter. The media shows a similar initial increase, on average stabilising in the third phase after reaching a plateau value in the second. The adventitia, already increasing in phase 1, continues to increase in phase 2, accelerating in phase 3. The complex process, as found, occurs systematically in all vessels, is distributed circumferentially, and precedes the development of localised lesions of the intima. CONCLUSIONS: The findings suggest the existence of a diffuse complex of changes, consisting of a gradual vascular widening followed by narrowing, with associated mural changes reflecting the atherosclerotic process. (+info)
Empirical efficiency maximization: improved locally efficient covariate adjustment in randomized experiments and survival analysis.
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It has long been recognized that covariate adjustment can increase precision in randomized experiments, even when it is not strictly necessary. Adjustment is often straightforward when a discrete covariate partitions the sample into a handful of strata, but becomes more involved with even a single continuous covariate such as age. As randomized experiments remain a gold standard for scientific inquiry, and the information age facilitates a massive collection of baseline information, the longstanding problem of if and how to adjust for covariates is likely to engage investigators for the foreseeable future. In the locally efficient estimation approach introduced for general coarsened data structures by James Robins and collaborators, one first fits a relatively small working model, often with maximum likelihood, giving a nuisance parameter fit in an estimating equation for the parameter of interest. The usual advertisement is that the estimator will be asymptotically efficient if the working model is correct, but otherwise will still be consistent and asymptotically Gaussian. However, by applying standard likelihood-based fits to misspecified working models in covariate adjustment problems, one can poorly estimate the parameter of interest. We propose a new method, empirical efficiency maximization, to optimize the working model fit for the resulting parameter estimate. In addition to the randomized experiment setting, we show how our covariate adjustment procedure can be used in survival analysis applications. Numerical asymptotic efficiency calculations demonstrate gains relative to standard locally efficient estimators (+info)
Empirical vs natural weighting in random effects meta-analysis.
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Estimation and inference for case-control studies with multiple non-gold standard exposure assessments: with an occupational health application.
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Rank-based estimation in the {ell}1-regularized partly linear model for censored outcomes with application to integrated analyses of clinical predictors and gene expression data.
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