COX MULTIVARIATE REGRESSION ANALYSIS OF RECURRENCE FACTORS FOR COLONIC CARCINOMA

Objective: To determine the independent prognostic factors in the recurrence of colonic carcinoma after curative resection. Methods: Two hundred and one patients undergoing curative resections for colonic carcinoma were investigated by univariate and Cox multivariate regression analyses. Ten factors contributed to the rate were analyzed. Results: Dukes stages, obstruction, postoperative chemotherapy as well as the growth manner of the tumor were significantly associated with the recurrence rate of colonic carcinoma (P<0.05) by univariate analysis, while Dukes stages, obstruction, and postoperative chemotherapy were significant factors by the multivariate analysis. Conclusion: Dukes stages, obstruction, and postoperative chemotherapy are independent prognostic factors in the recurrence of colonic carcinoma.

Risk factors and care of early surgical site infection after primary posterior lumbar interbody fusion

Objectives:To explore the risk factors and nursing measures of early surgical site infection(SSI)after posterior lumbar interbody fusion(PLIF).Methods:A total of 468 patients who received PLIF in our hospital from January 2017 to June 2020 were enrolled into this study.According to the occurrence of early SSI,the patients were divided into two groups,and the general data were analyzed by univariate analysis.Multivariate logistic regression analysis was conducted with the dichotomous variable of whether early SSI occurred and other factors as independent variables to identify the risk factors of early SSI and put forward targeted prevention and nursing measures.Results:Among 468 patients with PLIF,18 patients developed early SSI(3.85%).The proportion of female,age,diabetes mellitus and urinary tract infection(UTI),operation segment,operation time,post-operative drainage volume,and drainage time were significantly higher than those in the uninfected group,with statistical significance(P<0.05),whereas the preoperative albumin and hemoglobin in the infected group were significantly lower than those in the uninfected group,with statistical significance(P<0.05).There was no significant difference between the two groups in the American Society of Anesthesiologists(ASA)grading,body mass index(BMI),complications including cardiovascular and cerebrovascular diseases or hypertension(P>0.05).Logistic regression analysis showed that preoperative diabetes mellitus(OR=2.109,P=0.012)/UTI(OR=1.526,P=0.035),prolonged drainage time(OR=1.639,P=0.029)were risk factors for early SSI.Men(OR=0.736,P=0.027)and albumin level(OR=0.526,P=0.004)were protective factors in reducing early SSI.Conclusions:Women,preoperative diabetes/UTI,hypoproteinemia,and prolonged drainage time are risk factors for early SSI after PLIF.Clinical effective preventive measures should be taken in combination with targeted nursing intervention to reduce the risk of early SSI.

Prediction of pre-oxidation efficiency of refractory gold concentrate by ozone in ferric sulfate solution using artificial neural networks

An artificial neural network model was developed to predict the oxidation of refractory gold concentrate （RGC） by ozone and ferric ions. The concentration of ozone and ferric ions, pulp density, oxygen amount, leaching time and temperature were employed as inputs to the network; the output of the network was the percentage of the ferric extraction iron from RGC. The multilayered feed-forward networks were trained by 33 sets of input-output patterns using a back propagation algorithm; a three-layer network with 8 neurons in the hidden layer gave optimal results. The model gave good predictions of high correlation coefficient （R2=0.966）. The predictions by ANN are more accurate when compared with conventional multivariate regression analysis （MVRA）. In addition, calculation with ANN model indicates that temperature is the predominant parameter and ozone concentration is the lesser influential parameter in the pre-oxidation process of refractory gold ore. The ANN neural network model accurately estimates the ferric extraction during pretreatment process of RGC in gold smelter plants and can be used to optimize the process parameters.

Kinetics of thermal decomposition of lanthanum oxalate hydrate

Lanthanum oxalate hydrate La2（C2O4）3·10H2O,the precursor of La2O3 ultrafine powders,was prepared by impinging stream reactor method with PEG 20000 as surfactant.Thermal decomposition of La2（C2O4）3·10H2O from room temperature to 900 °C was investigated and intermediates and final solid products were characterized by FTIR and DSC-TG.Results show that the thermal decomposition process consists of five consecutive stage reactions.Flynn-Wall-Ozawa（FWO） and Kissinger-Akahira-Sunose（KAS） methods were implemented for the calculation of energy of activation（E）,and the results show that E depends on α,demonstrating that the decomposition reaction process of the lanthanum oxalate is of a complex kinetic mechanism.The most probable mechanistic function,G（α）=[1-（1＋α）1/3]2,and the kinetic parameters were obtained by multivariate non-linear regression analysis method.The average E-value that is compatible with the kinetic model is close to value which was obtained by FWO and KAS methods.The fitting curve matches the original TG curve very well.

Maternal risk factors for low birth weight for term births in a developed region in China:a hospital-based study of 55,633 pregnancies

Low birth weight （LBW） is an important risk factor for neonatal and infant mortality and morbidity in adults.. How- ever, no large scale study on the prevalence of LBW and related maternal risk factors in China has been published. To explore the effects of maternal factors on LBW for term birth in China, we conducted a hospital-based retrospective study of 55, 633 Chinese pregnancy cases between 2001 and 2008. Maternal sociodemographic data, history of infer- tility and contraceptive use were obtained. Their medical status and diseases during pre-pregnancy were examined by physical examination at the first antenatal care visit. Maternal medical status before childbirth and pregnancy outcomes, including body weight, infant gender, multiple pregnancy and congenital anomalies, were recorded. Univariate and multivariate logistic regression, and linear regression were used to investigate the relationship be- tween maternal factors and term LBW. The general incidence of term LBW was 1.70% in the developed area of China. After preliminary analysis using the univariate model, low primary education, anemia, hypertensive disor- ders, placental previa, oligohydramnios and premature rupture of membrane were predicted as independent factors of term LBW in the multivariate model. Furthermore, the decrease in annual frquencies of these risk factors were major causes of gradual decline in the incidence of LBW （from 2.43% in 2001 to 1.21% in 2008）. The study dem- onstrated that among maternal factors, primary education, anemia and hypertensive disorders could contribute to LBW for term birth even in the most developed area of China.

Modified shock index and mortality rate of emergency patients

BACKGROUND:This study aimed to determine whether modified shock index(MSI)is associated with mortality that is superior to heart rate,blood pressure,or the shock index(SI).in emergency patients.METHODS:A retrospective database review was performed on 22 161 patients who presented to Peking Union Medical College Hospital Emergency Department and received intravenous fluids from January 1 to December 31,2009.We gathered data of the patients on age,gender,vital signs,levels of consciousness,presenting complaints,and SI and MSI were calculated for all patients.RESULTS:Multivariate regression analysis was performed to determine the correlation between risk factors and outcome.There is a significant correlation between emergency patient mortality rate and patient's vital signs obtained at the triage desk(HR>120 beats/min,systolic BP<90 mmHg,diastolic BP<60 mmHg).MSI is a stronger predictor of emergency patient mortality compared to heart rate and blood pressure alone,whereas SI does not have a significant correlation with emergency patient mortality rate.CONCLUSION:MSI is a clinically significant predictor of mortality in emergency patients.It may be better than using heart rate and blood pressure alone.SI is not significantly correlated with the mortality rate of the emergency patient.

Three Practical Methods for Analyzing Slope Stability

Since the environmental capacity and the arable as well as the inhabitant lands have actually reached a full balance, the slopes are becoming the more and more important options for various engineering constructions. Because of the geological complexity of the slope, the design and the decision-making of a slope-based engineering is still not practical to rely solely on the theoretical analysis and numerical calculation, but mainly on the experience of the experts. Therefore, it has important practical significance to turn some successful experience into mathematic equations. Based upon the abundant typical slope engineering construction cases in Yunnan, Southwestern China, 3 methods for analyzing the slope stability have been developed in this paper. First of all, the corresponded analogous mathematic equation for analyzing slope stability has been established through case studies. Then, artificial neural network and multivariate regression analysis have also been set up when 7 main influencing factors are adopted.

Dyslipidemia and Outcome in Patients with Acute Ischemic Stroke

Objective To study the relationship between dyslipidemia and outcome in patients with acute ischemic stroke. Methods Data about 2 568 patients with acute ischemic stroke were collected from 4 hospitals in Shandong Province from January 2006 to December 2008. National Institute of Health Stroke Scale （NIHSS） 〉10 at discharge or death was defined as the outcome. Effect of dyslipidemia on outcome in patients with acute ischemic stroke was analyzed by multivariate logistic regression analysis and propensity score-adjusted analysis, respectively. Results The serum levels of TC, LDL-C, and HDL-C were significantly associated with the outcome in patients with acute ischemic stroke. Multivariate logistic regression analysis and propensity score-adjusted analysis showed that the ORs and 95% CIs were 3.013 （1.259, 7.214）/2.655 （1.298, 5.43）, 3.157 （1.306, 7.631）/3.405 （1.621, 7.154）, and 0.482 （0.245, 0.946）/0.51 （0.282, O.921）, respectively, for patients with acute ischemic stroke. Hosmer-Lemeshow goodness-of-fit test showed no significant difference in observed and predicted risk in patients with acute ischemic stroke （chi-square=8.235, P=0.411）. Conclusion Serum levels of TC, LDL-C, and HDL-C are positively related with the outcome in patients with acute ischemic stroke.

Statistical approach to determination of overhaul and maintenance cost of loading equipment in surface mining

The purpose of this research was to develop a new approach in determination of overhaul and maintenance cost of loading equipment in surface mining. Two statistical models including univariate exponential regression (UER) and multivariate linear regression (MLR) were used in this study. Loading equipment parameters such as bucket capacity, machine weight, engine power, boom length, digging depth, and dumping height were considered as variables. The results obtained by models and mean absolute error rate indicate that these models can be applied as the useful tool in determination of overhaul and maintenance cost of loading equipment. The results of this study can be used by the decision-makers for the specific surface mining operations.

Discovering optimal weights in weighted‑scoring stock‑picking models: a mixture design approach

Certain literature that constructs a multifactor stock selection model adopted a weighted-scoring approach despite its three shortcomings.First,it cannot effectively identify the connection between the weights of stock-picking concepts and portfolio performances.Second,it cannot provide stock-picking concepts’optimal combination of weights.Third,it cannot meet various investor preferences.Thus,this study employs a mixture experimental design to determine the weights of stock-picking concepts,collect portfolio performance data,and construct performance prediction models based on the weights of stock-picking concepts.Furthermore,these performance prediction models and optimization techniques are employed to discover stock-picking concepts’optimal combination of weights that meet investor preferences.The samples consist of stocks listed on the Taiwan stock market.The modeling and testing periods were 1997–2008 and 2009–2015,respectively.Empirical evidence showed(1)that our methodology is robust in predicting performance accurately,(2)that it can identify significant interactions between stock-picking concepts’weights,and(3)that which their optimal combination should be.This combination of weights can form stock portfolios with the best performances that can meet investor preferences.Thus,our methodology can fill the three drawbacks of the classical weighted-scoring approach.

A Hybrid Dynamical-Statistical Approach for Predicting Winter Precipitation over Eastern China

Correlation analysis revealed that winter precipitation in six regions of eastern China is closely related not only to preceding climate signals but also to synchronous atmospheric general circulation fields. It is therefore necessary to use a method that combines both dynamical and statistical predictions of winter precipitation over eastern China （hereinafter called the hybrid approach）, in this connection, seasonal real-time prediction models for winter precipitation were established for the six regions. The models use both the preceding observations and synchronous numerical predictions through a multivariate linear regression analysis. To improve the prediction accuracy, the systematic error between the original regression model result and the corresponding observation was corrected. Cross-validation analysis and real-time prediction experiments indicate that the prediction models using the hybrid approach can reliably predict the trend, sign, and interannual variation of regionally averaged winter precipitation in the six regions of concern. Averaged over the six target regions, the anomaly correlation coefficient and the rate with the same sign of anomaly between the cross-validation analysis and observation during 1982-2008 are 0.69 and 78%, respectively. This indicates that the hybrid prediction approach adopted in this study is applicable in operational practice.

Effects of topography on structuring species assemblages in a subtropical forest

Aims Topography has long been recognized as an important factor in shaping species distributions.Many studies revealed that species may show species-habitat associations.However,few studies inves-tigate how species assemblages are associated with local habitats,and it still remains unclear how the community-habitat associa-tions vary with species abundance class and life stage.In this study,we analyzed the community-habitat associations in a subtropical montane forest.Methods The fully mapped 25-ha(500×500 m)forest plot is located in Badagongshan Nature Reserve in Hunan Province,Central China.It was divided into 625(20×20 m)quadrats.Habitat types were classified by multivariate regression tree analyses that cluster areas with similar species composition according to the topographic characteristics.Indicator species analysis was used to identify the most important species for structuring species assemblages.We also compared the community-habitat associations for two levels of species abundances(i.e.abundant and rare)and three different life stages(i.e.saplings,juveniles and adults),while accounting for sample size effects.Important Findings The Badagongshan plot was divided into five distinct habitat types,which explained 34.7%of the variance in tree species composi-tion.Even with sample size taken into account,community-habi-tat associations for rare species were much weaker than those for abundant species.Also when accounting for sample size,very small differences were found in the variance explained by topography for the three life stages.Indicator species of habitat types were mainly abundant species,and nearly all adult stage indicator species were also indicators in juvenile and sapling stages.Our study manifested that topographical habitat filtering was important in shaping over-all local species compositions.However,habitat filtering was not important in shaping rare species’distributions in this forest.The community-habitat association patterns in this forest were mainly shaped by abundant species.In addition,during the transitions from saplings to juveniles,and from juveniles to adults,the relative importance of habitat filtering was very weak.