Cytogenetic diagnoses after chorionic villus sampling are less reliable in very-high- or very-low-risk pregnancies

An increasing number of cytogenetic prenatal diagnoses are performed on chorionic villus samplings. The accuracy of this method is influenced by chromosomal mosaicism, mostly confined to direct preparation methods. Especially those investigators who have experienced false-negative and false-positive findings propagate the combined use of direct and culture methods. Yet large collaborative studies have shown that in approximately two-thirds of diagnostic cases only one procedure is applied. Moreover, the accuracy of a cytogenetic investigation depends not only on the ontogenetic origin of the tissues investigated, but also on interacting factors such as the ‘a priori risk’ and the ‘predictive value of a cytogenetic finding’. On this basis a differentiated prenatal diagnostic procedure is discussed, including either sole short-term culture (STC), combined STC and long-term culture (LTC), primary amniocentesis (AC), or primary percutaneous umbilical blood sampling (PUBS). The predictive value of the cytogenetic diagnosis from CVS varies significantly dependent on the a priori risk of a chromosome aberration and, in the case of an abnormal karyotype, on the specific chromosome involved. A non-mosaic and ‘non-lethal’ trisomy detected in STC is highly representative of the embryo/fetus, but there are exceptions of limited predictive value, e.g., trisomy 18. Guided by the strategy of an optional follow-up by LTC, AC, or PUBS in 1317 successive CV samplings, we are not aware of a false-negative diagnosis, but probably had one false-positive diagnosis: 47,XXY after STC; 46,XY after LTC. When referring to the rate of fetuses with an unbalanced karyotype expected in the different indication groups, a relative increase of false-positive findings in the very-low-risk group (maternal age ⩽35 years of age) and of false-negative findings in the very-high-risk group (abnormal ultrasonographic findings) of pregnant women when only performing CVS becomes obvious. Because of this dilemma, AC or—especially in the latter group—PUBS might be primarily offered to these indication groups instead of CVS.     

A new method for analysing socio-ecological patterns of vulnerability

This paper presents a method for the analysis of socio-ecological patterns of vulnerability of people being at risk of losing their livelihoods as a consequence of global environmental change. This method fills a gap in methodologies for vulnerability analysis by providing generalizations of the factors that shape vulnerability in specific socio-ecological systems and showing their spatial occurrence. The proposed method consists of four steps that include both quantitative and qualitative analyses. To start, the socio-ecological system exposed to global environmental changes that will be studied needs to be determined. This could, for example, be farmers in drylands, urban populations in coastal areas and forest-dependent people in the tropics. Next, the core dimensions that shape vulnerability in the socio-ecological system of interest need to be defined. Subsequently, a set of spatially explicit indicators that reflect these core dimensions is selected. Cluster analysis is used for grouping the indicator data. The clusters found, referred to as vulnerability profiles, describe different typical groupings of conditions and processes that create vulnerability in the socio-ecological system under study, and their spatial distribution is provided. Interpretation and verification of these profiles is the last step in the analysis. We illustrate the application of this method by analysing the patterns of vulnerability of (smallholder) farmers in drylands. We identify eight distinct vulnerability profiles in drylands that together provide a global overview of different processes taking place and sub-national detail of their distribution. By overlaying the spatial distribution of these profiles with specific outcome indicators such as conflict occurrence or migration, the method can also be used to understand these phenomena better. Analysis of vulnerability profiles will in a next step be used as a basis for identifying responses to reduce vulnerability, for example, to facilitate the transfer of best practices to reduce vulnerability between different places.