The authors have examined prospectively whether the combined approach of establishing tolerance intervals for the circadian variability of blood pressure (BP) as a function of gestational age, and then computing the hyperbaric index (HBI) by comparison of any patient's BP profile (obtained by ambulatory BP monitoring, ABPM) with those intervals, provides a new high sensitivity test for the early detection of pregnant women who subsequently will develop gestational hypertension or preeclampsia. The authors analyzed 503 BP series from 71 women with healthy pregnancies, and 256 series from 42 complicated pregnancies. BP was sampled for about 48 hours once every 4 weeks from the first visit to the hospital to delivery. 90% tolerance limits were computed for each trimester of gestation from 497 series previously obtained from a reference group of 189 normotensive pregnant women. The HBI was then computed for each individual BP series in the validation sample. Sensitivity of this tolerance-hyperbaric test was 90% in the first trimester, and increased up to 99% in the third trimester. The positive predictive value was above 97% in all trimesters, providing, on the average, an early identification of gestational hypertension or preeclampsia 23 weeks prior to the clinical confirmation of the disease. The approach presented here, now validated prospectively, represents a simple, reproducible, noninvasive, and high sensitivity test for the very early identification of gestational hypertension and preeclampsia.
Hermida, R. C.1; Ayala, D. E.1; Calvo, C.2; Mojon, A.1; Fernandez, J. R.1; Alonso, I.1; Dominguez, M. J.2; Covelo, M.2; Lopez, J. E.2 Author Information
Model selection is a topic of special relevance in molecular phylogenetics that affects many, if not all, stages of phylogenetic inference. Here we discuss some fundamental concepts and techniques of model selection in the context of phylogenetics. We start by reviewing different aspects of the selection of substitution models in phylogenetics from a theoretical, philosophical and practical point of view, and summarize this comparison in table format. We argue that the most commonly implemented model selection approach, the hierarchical likelihood ratio test, is not the optimal strategy for model selection in phylogenetics, and that approaches like the Akaike Information Criterion (AIC) and Bayesian methods offer important advantages. In particular, the latter two methods are able to simultaneously compare multiple nested or nonnested models, assess model selection uncertainty, and allow for the estimation of phylogenies and model parameters using all available models (model-averaged inference or multimodel inference). We also describe how the relative importance of the different parameters included in substitution models can be depicted. To illustrate some of these points, we have applied AIC-based model averaging to 37 mitochondrial DNA sequences from the subgenus Ohomopterus(genus Carabus) ground beetles described by Sota and Vogler (2001).
