Screening for elevated blood pressure in children and adolescents: a critical appraisal.

Although screening for elevated blood pressure (BP) in adults is beneficial, evidence of its beneficial effects in children is not clear. Elevated BP in children is associated with atherosclerosis early in life and tracks across the life course. However, because of the high variability in BP, tracking is weak, and having an elevated BP in childhood has a low predictive value for having elevated BP later in life. The absolute risk of cardiovascular diseases associated with a given level of BP in childhood and the long-term effect of treatment beginning in childhood are not known. No study has experimentally evaluated the benefits and harm of BP screening in children. One modeling study indicates that BP screen-and-treat strategies in adolescents are moderately cost-effective but less cost-effective than population-wide interventions to decrease BP for the reduction of coronary heart diseases. The US National Heart, Lung, and Blood Institute and the European Society of Hypertension recommend that children 3 years of age and older have their BP measured during every health care visit. According to the US Preventive Services Task Force, there is no sufficient evidence to recommend for or against screening, but their recommendations have to be updated. Whether the benefits of universal BP screening in children outweigh the harm has to be determined. Studies are needed to assess the absolute risk of cardiovascular diseases associated with elevated BP in childhood, to evaluate how to simplify the identification of elevated BP, to evaluate the long-term benefits and harm of treatment beginning in childhood, and to compare universal and targeted screening strategies.

Abrupt decrease in serum testosterone levels after an oral glucose load in men: implications for screening for hypogonadism.

OBJECTIVE: This study examines the physiological impact of a glucose load on serum testosterone (T) levels in men with varying glucose tolerance (GT). DESIGN: Cross-sectional study. PATIENTS AND METHODS: 74 men (19-74 years, mean 51·4 ± 1·4 years) underwent a standard 75-g oral glucose tolerance test with blood sampling at 0, 30, 60, 90 and 120 min. Fasting serum glucose, insulin, total T (and calculated free T), LH, SHBG, leptin and cortisol were measured. RESULTS: 57% of the men had normal GT, 30% had impaired GT and 13% had newly diagnosed type 2 diabetes. Glucose ingestion was associated with a 25% decrease in mean T levels (delta = -4·2 ± 0·3 nm, P < 0·0001). T levels remained suppressed at 120 min compared with baseline (13·7 ± 0·6 vs 16·5 ± 0·7 nm, P < 0·0001) and did not differ across GT or BMI. Of the 66 men with normal T levels at baseline, 10 (15%) had levels that decreased to the hypogonadal range (<9·7 nm) at one or more time points. SHBG, LH and cortisol levels were unchanged. Leptin levels decreased from baseline at all time points (P < 0·0001). CONCLUSIONS: Glucose ingestion induces a significant reduction in total and free T levels in men, which is similar across the spectrum of glucose tolerance. This decrease in T appears to be because of a direct testicular defect, but the absence of compensatory changes in LH suggests an additional central component. Men found to have low nonfasting T levels should be re-evaluated in the fasting state.

Multimodel inference and multimodel averaging in empirical modeling of occupational exposure levels.

Empirical modeling of exposure levels has been popular for identifying exposure determinants in occupational hygiene. Traditional data-driven methods used to choose a model on which to base inferences have typically not accounted for the uncertainty linked to the process of selecting the final model. Several new approaches propose making statistical inferences from a set of plausible models rather than from a single model regarded as 'best'. This paper introduces the multimodel averaging approach described in the monograph by Burnham and Anderson. In their approach, a set of plausible models are defined a priori by taking into account the sample size and previous knowledge of variables influent on exposure levels. The Akaike information criterion is then calculated to evaluate the relative support of the data for each model, expressed as Akaike weight, to be interpreted as the probability of the model being the best approximating model given the model set. The model weights can then be used to rank models, quantify the evidence favoring one over another, perform multimodel prediction, estimate the relative influence of the potential predictors and estimate multimodel-averaged effects of determinants. The whole approach is illustrated with the analysis of a data set of 1500 volatile organic compound exposure levels collected by the Institute for work and health (Lausanne, Switzerland) over 20 years, each concentration having been divided by the relevant Swiss occupational exposure limit and log-transformed before analysis. Multimodel inference represents a promising procedure for modeling exposure levels that incorporates the notion that several models can be supported by the data and permits to evaluate to a certain extent model selection uncertainty, which is seldom mentioned in current practice.

Age-related normograms of serum antimüllerian hormone levels in a population of infertile women: a multicenter study.

Objective: To produce age-related normograms for serum antimullerian hormone (AMH) level in infertile women without polycystic ovaries (non-PCO).Design: Retrospective cohort analysis.Setting: Fifteen academic reproductive centers.Patient(s): A total of 3,871 infertile women.Intervention(s): Blood sampling for AMH level.Main Outcome Measure(s): Serum AMH levels and correlation between age and different percentiles of AMH.Result(s): Age-related normograms for the 3rd, 10th, 25th, 50th, 75th, 90th, and 97th percentiles of AMH were produced. We found that the curves of AMH by age for the 3rd to 50th percentiles fit the model and appearance of linear relation, whereas the curves of >75th percentiles fit cubic relation. There were significant differences in AMH and FSH levels and in antral follicle count (AFC) among women aged 24-33 years, 34-38 years, and >= 39 years. Multivariate stepwise linear regression analysis of FSH, age, AFC, and the type of AMH kit as predictors of AMH level shows that all variables are independently associated with AMH level, in the following order: AFC, FSH, type of AMH kit, and age.Conclusion(s): Age-related normograms in non-PCO infertile women for the 3rd to 97th percentiles were produced. These normograms could provide a reference guide for the clinician to consult women with infertility. However, future validation with longitudinal data is still needed. (Fertil Steril (R) 2011; 95: 2359-63. (C) 2011 by American Society for Reproductive Medicine.)