Methods: This is a cohort study where prevalent ESRD patients' details were recorded between May 2012 and October 2012. Their records were matched with national death record at the end of year 2015 to identify the deceased patients within three years. Four models were formulated with two models were based on logistic regression models but with different number of predictors and two models were developed based on risk scoring technique. The preferred models were validated by using sensitivity and specificity analysis.
Results: A total of 1332 patients were included in the study. Majority succumbed due to cardiovascular disease (48.3%) and sepsis (41.3%). The identified risk factors were mode of dialysis (P < 0.001), diabetes mellitus (P < 0.001), chronic heart disease (P < 0.001) and leg amputation (P = 0.016). The accuracy of four models was almost similar with AUC between 0.680 and 0.711. The predictive models from logistic regression model and risk scoring model were selected as the preferred models based on both accuracy and simplicity. Besides the mode of dialysis, diabetes mellitus and its complications are the important predictors for early mortality among prevalent ESRD patients.
Conclusions: The models either based on logistic regression or risk scoring model can be used to screen high risk prevalent ESRD patients.
RESULTS: We propose a succinct representation of the distance matrices which tremendously reduces the space requirement. We give a complete solution, called SuperRec, for the inference of chromosomal structures from Hi-C data, through iterative solving the large-scale weighted multidimensional scaling problem.
CONCLUSIONS: SuperRec runs faster than earlier systems without compromising on result accuracy. The SuperRec package can be obtained from http://www.cs.cityu.edu.hk/~shuaicli/SuperRec .
OBJECTIVES: This paper discusses RISAPI of our original work in the field, which shows how probabilistic planning and system theory algorithms in workplace robotic systems that work with people can allow for that reasoning using a security robot system. The problem is a general way as an incomplete knowledge 2-player game.
RESULTS: In this general framework, the various hypotheses and these contribute to thrilling and complex robot behavior through real-time interaction, which transforms actual human subjects into a spectrum of production systems, robots, and care facilities.
CONCLUSION: The models of the internal human situation, in which robots can be designed efficiently, are limited, and achieve optimal computational intractability in large, high-dimensional spaces. To achieve this, versatile, lightweight portrayals of the human inner state and modern algorithms offer great hope for reasoning.
METHODS: Perioperative data from 3008 adult patients undergoing elective cardiac surgery from 2008 to 2011 at the two main heart centers in Singapore was analyzed prospectively, and confirmatory analysis was conducted with the generalized structural equation model.
RESULTS: Diabetes was significantly associated with postoperative acute kidney injury (AKI) and postoperative hyperglycemia. Postoperative AKI, Malay ethnicity, and blood transfusion were associated with postoperative dialysis. Postoperative AKI and blood transfusion were also associated with postoperative arrhythmias. In turn, postoperative dialysis and arrhythmias increased the odds of 30-day mortality by 7.7- and 18-fold, respectively.
CONCLUSIONS: This study identified that diabetes is directly associated with postoperative hyperglycemia and AKI, and indirectly associated with arrhythmias and 30-day mortality. Further, we showed that ethnicity not only affects the prevalence of diabetes, but also postoperative diabetes-related outcomes.