Mortonmagnusson8284

Multiple organ failure (MOF) may lead to an increased mortality rate of moderately severe (MSAP) or severe acute pancreatitis (SAP). This study is aimed to use machine learning to predict the risk of MOF in the course of disease.

Clinical and laboratory features with significant differences between patients with and without MOF were screened out by univariate analysis. Prediction models were developed for selected features through six machine learning methods. The models were internally validated with a five-fold cross-validation, and a series of optimal feature subsets were generated in corresponding models. A test set was used to evaluate the predictive performance of the six models.

305 (68%) of 455 patients with MSAP or SAP developed MOF. Eighteen features with significant differences between the group with MOF and without it in the training and validation set were used for modeling. Interleukin-6 levels, creatinine levels, and the kinetic time were the three most important features in the optimal feature subsets selected by K-fold cross-validation. The adaptive boosting algorithm (AdaBoost) showed the best predictive performance with the highest AUC value (0.826; 95% confidence interval 0.740 to 0.888). The sensitivity of AdaBoost (80.49%) and specificity of logistic regression analysis (93.33%) were the best scores among the six models in the test set.

A predictive model of MOF complicated by MSAP or SAP was successfully developed based on machine learning. The predictive performance was evaluated by a test set, for which AdaBoost showed a satisfactory predictive performance. The study is registered with the China Clinical Trial Registry (Identifier ChiCTR1800016079).

A predictive model of MOF complicated by MSAP or SAP was successfully developed based on machine learning. The predictive performance was evaluated by a test set, for which AdaBoost showed a satisfactory predictive performance. The study is registered with the China Clinical Trial Registry (Identifier ChiCTR1800016079).

South Korea has one of the lowest fertility rates in the world, reaching a record low of 0.98 in 2018. Understanding socioeconomic differentials in fertility in South Korea has become an important social and policy issue.

This study examines socioeconomic differentials in first and second childbirths among married women using various indicators of socioeconomic status at the individual and household level.

Using the Korean Labor and Income Panel Study (1998-2017), discrete-time hazard models are used to evaluate the relationships between multiple indicators of socioeconomic status and the transition to first and second births.

Higher socioeconomic status (e.g., husband's college education and standard employment, homeownership) is conducive to a transition to parenthood and second births. However, the wife's employment - standard employment in particular - is negatively associated with both first and second childbirth. Bafilomycin A1 in vivo Among the indicators of socioeconomic resources, stable housing arrangements and the husband's employment security appear to be the most important factors for a married couple's fertility decisions.

Socioeconomically disadvantaged married couples tend to delay their transition to parenthood. In addition, those with high SES are more likely than their counterparts with low SES to have second births. If these patterns persist, they have important implications for the demographic process and social stratification.

The findings of this study contribute to a comprehensive understanding of socioeconomic differentials in fertility in South Korea and therefore have important policy implications. These findings will also prove useful to other societies with very low fertility rates.

The findings of this study contribute to a comprehensive understanding of socioeconomic differentials in fertility in South Korea and therefore have important policy implications. These findings will also prove useful to other societies with very low fertility rates.

Geographic proximity between parents and children is increasingly recognized as an alternative measure to coresidence as a gauge for intergenerational support in China. The quality of intergenerational relationships is another important dimension of intergenerational ties that is often underexplored.

We examine the association between parent-child proximity and life satisfaction of older adults and how it interacts with the quality of intergenerational relationships, particularly for vulnerable subpopulations.

We use data from the China Longitudinal Aging Social Survey (CLASS 2014). We use ordered logit models to predict life satisfaction scores (ranged 1 to 4).

Our analyses show that parent-child relationship quality is strongly associated with life satisfaction, regardless of living proximity, in our full sample analysis. For those who have a lower-quality relationship with their children, coresidence or close-distance living does not enhance life satisfaction and they indeed have lower life satisfaond the boundary of the household and of paying close attention to the affective dimension of intergenerational ties.

How children spend their day is closely linked to their social and developmental outcomes. Children's time use is associated with their parents' educational and economic capital, making time use a potential reproduction channel for socioeconomic inequalities.

We evaluate the correlation of natal-family economic resources, parents' education, and children's daily time use in Japan.

Analysing data from a 2006 Japanese time use survey, we use natal-family income, parental education, and the interaction between them to predict in-school and afterschool study time, leisure time, and sleep time for children aged 10-18.

Children from families with higher incomes and more-educated parents spend a longer time studying after school and less time on sleep and leisure. Parental income and mothers' and fathers' education are all independently associated with children's daily patterns.

Our findings suggest that available resources and parental education are important in shaping children's daily routines and, through these routines, their eventual socioeconomic outcomes.