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Sepsis is the most common cause of in-hospital deaths, especially from low-income and lower-middle-income countries (LMICs). This study aimed to investigate the mortality rate and associated factors from sepsis in intensive care units (ICUs) in an LMIC. We did a multicenter cross-sectional study of septic patients presenting to 15 adult ICUs throughout Vietnam on the 4 days representing the different seasons of 2019. Of 252 patients, 40.1% died in hospital and 33.3% died in ICU. ICUs with accredited training programs (odds ratio, OR: 0.309; 95% confidence interval, CI 0.122–0.783) and completion of the 3-h sepsis bundle (OR: 0.294; 95% CI 0.083–1.048) were associated with decreased hospital mortality. ICUs with intensivist-to-patient ratio of 1:6 to 8 (OR: 4.533; 95% CI 1.621–12.677), mechanical ventilation (OR: 3.890; 95% CI 1.445–10.474) and renal replacement therapy (OR: 2.816; 95% CI 1.318–6.016) were associated with increased ICU mortality, in contrast to non-surgical source control (OR: 0.292; 95% CI 0.126–0.678) which was associated with decreased ICU mortality. Improvements are needed in the management of sepsis in Vietnam such as increasing resources in critical care settings, making accredited training programs more available, improving compliance with sepsis bundles of care, and treating underlying illness and shock optimally in septic patients.

ObjectivesTo compare the accuracy of the SOFA and APACHE II scores in predicting mortality among ICU patients with sepsis in an LMIC.DesignA multicentre, cross-sectional study.SettingA total of 15 adult ICUs throughout Vietnam.ParticipantsWe included all patients aged ≥ 18 years who were admitted to ICUs for sepsis and who were still in ICUs from 00:00 hour to 23:59 hour of the specified study days (i.e., 9thJanuary, 3rdApril, 3rdJuly, and 9thOctober of the year 2019).Primary and secondary outcome measuresThe primary outcome was hospital all-cause mortality (hospital mortality). We also defined the secondary outcome as all-cause deaths in the ICU (ICU mortality).ResultsOf 252 patients, 40.1% died in hospitals, and 33.3% died in ICUs. SOFA (AUROC: 0.688 [95% CI: 0.618-0.758]; cut-off value ≥ 7.5; PAUROCAUROCAUROCAUROCConclusionsIn this study, SOFA and APACHE II scores were worthwhile in predicting mortality among ICU patients with sepsis. However, due to better discrimination for predicting ICU mortality, the SOFA was preferable to the APACHE II score in predicting mortality.Clinical trials registry – India: CTRI/2019/01/016898Strengths and limitations of this studyAn advantage of the present study was data from multi centres, which had little missing data.Due to the absence of a national registry of intensive care units (ICUs) to allow systematic recruitment of units, we used a snowball method to identify suitable units, which might have led to the selection of centres with a greater interest in sepsis management.Due to the study’s real-world nature, we did not make a protocol for microbiological investigations. Moreover, we mainly evaluated resources utilized in ICUs; therefore, the data detailing the point-of-care testing and life-sustaining treatments were not available. Additionally, to improve the feasibility of conducting the study in busy ICUs, we opted not to collect data on antibiotic resistance and appropriateness.Due to our independent variables (e.g., SOFA score that was greater than or equal to the cut-off value) that might be associated with primary outcome only measured upon ICU admission, the mixed-effects logistic regression model could not be used to predict discrete outcome variables measured at two different times, i.e., inside and outside the ICU settings.Although the sample size was large enough, the confidence interval was slightly wide (±6.03%), which might influence the normal distribution of the sample.

Most popular network simulation tools share some common limitations, including their execution time being too long that undermines performance of network topologies, routing algorithms and related issues. This paper proposes a reduction model for simulating packet transfer process in large-scale interconnection networks. Our proposed simulation framework relies on the reduction of packet transfer process, deterministic finite automata for formal specification and flexible architecture for implementation. Our reduction model supports scalability for large-scale interconnection network and its evaluation highlights the advantages of network design.

As oil and gas production has been going on over a few decades, conventional plays such as pre-Tertiary fractured basement highs and Cenozoic structural traps become more and more exhausted, and the remaining targets of the same type do not have sufficient reserves for development and production. Exploration activities in Cuu Long basin, therefore, are shifting towards more complicating types of plays which are stratigraphic traps and combination traps. Several researches were conducted in southeastern marginal slope and indicated the possibility of stratigraphic pinch-out traps with insufficient petroleum system and low hydrocarbon potential. In spite of many researches, there are still difficulties in defining the distribution and in evaluating hydrocarbon potential of these traps, so seismic stratigraphy analysis in accompanied with interpretation of seismic attribute and well logs is very necessary to support this problem. Seismic stratigraphic analysis on seismic sections, in agreement with seismic attributes’ and log analysis’ findings, show that the stratigraphic/combination traps in Oligocene C and D were formed during lowstand system tract as sigmoid-oblique clinoforms downlapping onto underlying strata in distributary mouths/delta settings. The integration of seismic attribute analysis and well log interpretation has further defined the fan-shaped distribution of these traps. Thus, using various methods, the stratigraphic traps can be better revealed. Further studies, however, need to be carried out to fully evaluate hydrocarbon potential of these stratigraphic/ combination traps, and minimize risks in exploration drilling.