Both thrombocytopenia and microangiopathic hemolytic anemia (TMA) are seen in thrombotic thrombocytopenic purpura (TTP) and HELLP syndrome among other disorders during pregnancy. Although both share backgrounds of endothelial injury and microvascular thrombi and some clinical features, yet, they have different etiologies and courses. In late pregnancy, differentiating between these two pathologies can be extremely difficult due to the immense overlap in clinical and laboratory manifestations and this becomes only possible with the use of specific markers as ADAMTS-13, when available. Hereby, we describe three cases that may exemplify the complex association between PE/HELLP syndrome and TTP. The first case presented with PE/HELLP syndrome and deteriorated postpartum to improve on plasmapheresis. The second case was a known TTP patient who developed superimposed PE/HELLP at 27 weeks gestation which necessitated emergent delivery. The third was a case of preeclampsia that progressed to HELLP syndrome on day 2 postpartum but 3 days later was complicated by TTP. HELLP syndrome and TTP can co-exist, but can also complicate one another. In the absence of instantaneous results of ADAMTS-13 and when diagnosis with clinical judgement alone cannot be done with certainty, a short trial-plasmapheresis could be attempted with close observation of the immediate response. This stepwise approach might prove to be a valuable tool when integrated in the usual workup of clinical and laboratory evaluation both before and after delivery.
Software development projects still of high failure rates. Different risk management approaches are recommended by researchers and followed by organizations in order to control this failure rate. Current research is focused towards preventive risk management approach that improves the development process. In this study, we introduce a framework that enhances this approach. This framework describes a systematic method towards enhancing preventive risk management throughout the software development process. In this study, we devised sets of risk management strategies and controls that aim at mitigating each of the identified risks in the adapted list. These strategies besides the identified risk factors are utilized and embedded in the right corresponding Software Development Life Cycle phase to construct our preventive framework.
System analysis and requirements definition is a risky phase. It is susceptible to different types of risk factors from the initial preliminary investigation till the final delivery of the requirements document. Risks reside in this phase are considered the ones with the highest severity among other phases. Being the first phase in the development process, the occurrence of risks in this phase negatively influences subsequent phases, affects project progress, and has a negative impact on the project outcomes. Thus, managing probable risks in this phase deadly helps project managers control the majority of risks that might arise later in the subsequent phase. In order to manage risks properly, probable risks need to be identified early, then, risk management strategies have to be proposed and followed in order to avoid and mitigate their occurrence. In this paper, a total number of 28 risk factors have been introduced. For each risk factor, a set of management strategies is proposed. The identified factors and strategies were the harvest of brainstorming sessions with senior software practitioners, comprehensive literature survey, plus ready-made checklist and taxonomies. In order to validate our results, correlation analysis had been conducted through a web-based survey. The results confirmed our assumptions in that all of the identified risk factors have positive correlation with project failure.
The main aim of this paper is to identify critical success factors (CSFs) and investigate whether they are the same or not across different project organization structures. The organization structures under the study are: functional, project, and matrix. The study is based on a survey that was conducted on a large number of software projects in Jordan. To rank success factors (SFs) and identify critical ones, we use the importance index of SFs, which is calculated based on the likelihood and impact across different structures. For deeper analysis, we carry out statistical experiments with an ANOVA test and Spearman’s rank correlation test. Analysis results of an ANOVA test partially indicates that the values of the SF importance index are slightly different across the three organization structures. Moreover, the Spearman’s rank correlation test results show a high degree of correlation of the SF importance index between the function and project organization structures and a low degree of correlation between the function and matrix organization structures.
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