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Objective: To introduce the competing risk model into outcome prediction of mild cognitive impairment (MCI) of seniors and to explore influencing factors for the prognosis of MCI to Alzheimer's disease (AD)., Methods: Data were collected from six follow-up visits to 600 seniors from communities in Taiyuan city, which were conducted at an interval of six months from October 2010 to May 2013. MCI state was defined as the transient state, AD and death before AD as two absorbing states (death before AD in which was regarded as a competing risk event), building the competing risk model to identify the model parameters, and to explore influencing factors on MCI prognosis to AD. In the meantime, the 3-year MCI-AD transition probability was estimated based on the multi-state Markov model., Results: Based on screening with the multivariate competing risk model analysis, factors such as higher age (estimate HR = 1.56, 95% CI: 1.01-2.39), female gender (HR = 1.72, 95% CI: 1.02-2.92), higher education (HR = 0.64, 95% CI: 0.41-1.00), reading frequently (HR = 0.57, 95% CI: 0.32-0.99), hypertension (HR = 3.43, 95% CI: 1.08-10.85) and high SBP (HR = 1.67, 95% CI: 1.04-2.66), were statistically significant for transition from MCI to AD in three years. 3-year MCI-AD transition probability was 10.7% (95% CI: 8.6%-13.2%)., Conclusion: Age, gender, education, reading and blood pressure were the influencing factors for the prognosis of MCI to AD. Competing risk model was advantageous in studying longitudinal data with multiple potential outcomes.

Objective. To study the probability or risk of decompression sickness in high altitude flight and to establish a probability model. Method. Survival analysis technique was used in the analysis of the information about altitude decompression sickness. Result. It was found that the risk of decompression sickness initially increases up to a certain time point, and then decreases because of denitrogenation. The hazard function may describe the characteristics of this pattern in changes of risk. The parameters of probability models for altitude decompression sickness can be estimated by using the maximum likelihood method. Conclusion. Prediction with the survival models based on the logistic distribution is good.

Winter injury is one of the main meteorological disasters that affect apple’s growing distribution and quality. Existing research mainly studies the injuries caused by extremely low temperatures during deep dormancy of apples, mostly using the mean temperature of the coldest month, the frequency of extreme minimum temperatures as indicators to assess the risk and divide the boundaries of apple’s distribution. However, cold resistance of fruit trees is different during different dormant phases, and is closely related with the cold- resistance exercises in fall. The probabilistic forecasting models of early winter injury and extreme winter cold injury are established with the binary Logistic regression, on basis of the data of 2 084 meteorological stations and the winter injuries happened during 1981- 2010. The space is divided into five risk’s degrees as very low, low, moderate, high and very high. The classification standard of the probability of winter injury was referred from the classification criteria in the IPCC report. The results show that: the probabilistic forecasting models of early winter injury and extreme winter cold injury passed the Hosmer-Losmer test, and the prediction accuracies of independent samples reached 83.6% and 91.4% respectively. Early winter injury depends mainly on time of the first frost day and the time interval between the first frost day and the first day that the lowest temperature is lower than - 15 ℃ . The extreme winter cold injury is affected by the average temperature of the coldest month and the cold accumulated temperature when the daily minimum temperature is lower than - 20 ℃ . The freezing injury caused by short- term extreme low temperature is of small occurrence probability and limited influence scope. The extreme low-temperature injury in winter is mainly caused by continuous intimidation of strong and low temperature. Early winter injury is the main freezing injury in apple-producing regions of China, which happens in most apple-producing regions except the ancient Yellow River region and Yunnan producing region. But extreme winter cold injuries mainly happen in high latitude or high altitude regions, including the northern Bohai Gulf, the northwest of the Loess Plateau and Northern Xinjiang. High risk areas of early winter injury and extreme winter cold injury are almost equal. Gansu is the province that has the largest area of risks with moderate degree and above, followed by Liaoning, Hebei and Shanxi. On the other hand, there are low risks of winter injury, especially for extreme winter cold injury, in Shaanxi and Shandong where there are the largest planting areas of apple. [ABSTRACT FROM AUTHOR]