Validation of nutritional risk index method against patientgenerated subjective global assessment in screening malnutrition in colorectal cancer patients

Objective：To validate malnutrition screening tool of nutrition risk index （NRI） against patent-generated subjective global assessment （PG-SGA） as a gold standard tool in colorectal cancer patients before radiotherapy.Methods：Nutritional status of 52 volunteer colorectal cancer patients with a mean age of 54.1±16.8 years who referred to radiotherapy center were assessed by PG-SGA （gold standard method） and NRI.Serum albumin levels of patients were determined by colorimetric method.A contingency table was used to determine the sensitivity,specificity,and predictive value of the NRI in screening patients at risk of malnutrition,in comparison with the PG-SGA in patients before radiotherapy.Results：The findings of PG-SGA and NRI showed that 52％ and 45％ of patients in our study were moderately or severely malnourished respectively.The NRI had a sensitivity of 66％ and a specificity of 60％ against PG-SGA.The positive predictive value was 64％ and the negative predicative value was 62％.The agreement between NRI and PG-SGA was statistically insignificant （kappa =0.267; P＞0.05）.Conclusions：The findings of present study showed that the prevalence of malnutrition was high in patients with colorectal cancer.Moreover,NRI method had low sensitivity and specificity in assessing nutritional status of patients with cancer.It seems that the combination of anthropometric,laboratory parameters and a subjective scoring system may be helpful tools in screening of malnutrition in cancer patients.

Risk of colon cancer in hereditary non-polyposis colorectal cancer patients as predicted by fuzzy modeling:Influence of smoking

AIM： To investigate whether a fuzzy logic model could predict colorectal cancer （CRC） risk engendered by smoking in hereditary non-polyposis colorectal cancer （HNPCC） patients. METHODS： Three hundred and forty HNPCC mismatch repair （MMR） mutation carriers from the Creighton University Hereditary Cancer Institute Registry were selected for modeling. Age-dependent curves were generated to elucidate the joint effects between gene mutation （hMLH1 or hMSH2）, gender, and smoking status on the probability of developing CRC. RESULTS： Smoking significantly increased CRC risk in male hMSH2 mutation carriers （P 〈 0.05）. hMLH1 mutations augmented CRC risk relative to hMSH2 mutation carriers for males （P 〈 0.05）. Males had a significantly higher risk of CRC than females for hMLH1 non smokers （P 〈 0.05）, hMLH1 smokers （P 〈 0.1） and hMSH2 smokers （P 〈 0.1）. Smoking promoted CRC in a dose-dependent manner in hMSH2 in males （P 〈 0.05）. Females with hMSH2 mutations and both sexes with the hMLH1 groups only demonstrated a smoking effect after an extensive smoking history （P 〈 0.05）. CONCLUSION： CRC promotion by smoking in HNPCC patients is dependent on gene mutation, gender and age. These data demonstrate that fuzzy modeling may enable formulation of clinical risk scores, thereby allowing individualization of CRC prevention strategies.

The Role of the PNI and NLR in Nutritional Risk Screening and Assessment of Gastric Cancer Patients

Background The use of nutritional risk screening and assessment is becoming increasingly common in cancer patients.The Nutritional Risk Screening 2002(NRS 2002)is a nutritional risk screening programe with good utility.The patient generated-subjective global assessment(PG-SGA)is a method used to assess the nutritional status of cancer patients.The prognostic nutritional index(PNI)and neutrophil to lymphocyte ratio(NLR)are considered to be predictors of the prognosis following treatment for patients with a variety of cancers.However,the relationship between the PNI and NLR in the nutritional screening and assessment in patients with gastric cancer is unknown.Methods A retrospective analysis was performed on 378 patients with gastric cancer who underwent surgery at the First Affiliated Hospital of Guangxi Medical University from August 2019 to December 2020.NRS 2002 and PG-SGA were performed within 24 hours of admission,and indicators such as the serum albumin level,body mass index(BMI),PNI and NLR were measured.Results In the grouping based on the NRS2002,patients in the positive group(NRS 2002≥3)had a higher platelet value,a higher median NLR,and a lower PNI than those in the negative group(NRS 2002<3)(295.50±118.49×10^(9)/L vs.269.36±93.52×10^(9)/L,2.38 vs.1.77,42.36±5.96 vs.46.64±4.29).Based on the PG-SGA grouping,the serum albumin level and lymphocyte count were highest in the mild group(PG-SGA:score 2-3),(36.94±3.51 g/L and 1.91±0.7610^(9)/L)and lowest within the severe group(PG SGA score≥9)(34.09±4.18 g/L and 1.51±0.6410^(9)/L).The BMI was highest in the mild group(23.35±3.00 kg/m^(2))and lowest in the severe group(20.63±2.97 kg/m^(2)),and the PNI was also highest in the mild group(46.50±5.17)and lowest in the severe group(41.64±5.53).However,the NLR was lowest in the mild group(median 1.91)and highest in the severe group(median 2.44).Conclusion The PNI and NLR in gastric cancer patients are closely related to the results of the nutritional risk screening and assessment,suggesting that they may be useful to guide the nutritional interventions for gastric cancer patients.

Effect of Nursing Intervention Based on Caprini Risk Assessment Scale for Venous Thromboembolism in Perioperative Patients with Liver Cancer

Objective:To explore the effect of nursing intervention based on Caprini risk assessment scale for venous thromboembolism(VTE)in perioperative patients with liver cancer.Methods:A total of 128 hepatocellular cancer(HCC)patients who were hospitalized in our department from January 2021 to March 2022 and met the research criteria were selected.According to odd and even numbers in the order of inclusion,64 cases were divided into two groups:a control group and an observation group.The control group received routine nursing intervention during perioperative period,while the observation group received nursing intervention based on Caprini risk assessment scale for VTE.The incidence of VTE and complications were compared between the two groups.Results:The incidence of VTE and postoperative complications in the observation group were lower than those in the control group(P<0.05).Conclusion:Nursing intervention based on Caprini risk assessment scale for VTE can reduce the incidence of perioperative deep vein thrombosis and complications in patients with liver cancer;thus,it is worthy of clinical application.

Risk Assessment of Unmanned Aerial Vehicle Flight Based on Kmeans Clustering Algorithm

To quantify unmanned aerial vehicle(UAV)flight risks in low-altitude airspace,we analyze the factors of UAV flight risks from three aspects:flight conflict,flight environment,and traffic characteristics.The aerial risk index and ground risk index of the UAV are constructed,the index screening model and the UAV flight risk assessment model are established,and a UAV flight risk assessment model based on K-means clustering has been proposed.Meanwhile,numerical simulations show the proposed method can not only evaluate the UAV flight risks effectively,but also provide technical support for UAV risk management and control.

TyG指数与老年急性冠脉综合征患者院内主要不良心血管事件相关性及预测价值研究

目的探究甘油三酯葡萄糖(TyG)指数与老年急性冠脉综合征(ACS)患者发生院内主要不良心血管事件(MACE)的相关性及预测价值。方法回顾性分析2015年1月至2020年12月就诊于首都医科大学附属北京安贞医院急诊危重症中心的460例老年ACS患者的病历资料。按照是否发生院内MACE将患者分为MACE组和非MACE组。采用二元logistic回归模型及限制性立方样条图分析老年ACS患者TyG指数与院内MACE发生风险的相关性;多因素logistic回归分析筛选危险因素并构建多因素联合预测模型;受试者操作特征曲线评估TyG指数及多因素联合预测模型对老年ACS患者发生院内MACE的预测价值。结果59例老年ACS患者发生院内MACE,发生率为12.83%。两组糖尿病、脑血管病、心率(HR)、低密度脂蛋白胆固醇(LDL-C)、高密度脂蛋白固醇、甘油三酯、空腹血糖、糖化血红蛋白、肌酸激酶同工酶、肌钙蛋白T、肌红蛋白、N-末端B型脑钠肽前体、TyG指数、左室射血分数、心功能Killip分级比较,差异有统计学意义(P<0.05)。二元logistic回归分析结果显示,TyG指数升高增加院内MACE的发生风险(OR=2.87,P<0.01),调整混杂因素后仍有意义。调整协变量后,TyG指数升高与院内MACE结局呈线性相关(P_(非线性)=0.176)。脑血管病(OR=3.18)、HR(OR=1.04)、LDL-C(OR=1.81)、TyG指数(OR=3.29)是老年ACS患者发生院内MACE的独立危险因素(P<0.05)。多因素联合预测模型为Logit(P)=0.323×脑血管病+0.017×HR+0.48×LDL-C+1.15×TyG指数-15.09。TyG指数和多因素联合预测模型预测老年ACS患者发生院内MACE的曲线下面积分别为0.780、0.855。结论在老年ACS患者中,TyG指数是院内MACE发生的独立危险因素,二者呈线性相关,TyG指数及多因素联合预测模型对老年ACS患者院内MACE的发生具有一定的预测价值。

An advanced machine learning method for simultaneous breast cancer risk prediction and risk ranking in Chinese population:A prospective cohort and modeling study

Background:Breast cancer(BC)risk-stratification tools for Asian women that are highly accurate and can provide improved interpretation ability are lacking.We aimed to develop risk-stratification models to predict long-and short-term BC risk among Chinese women and to simultaneously rank potential non-experimental risk factors.Methods:The Breast Cancer Cohort Study in Chinese Women,a large ongoing prospective dynamic cohort study,includes 122,058 women aged 25-70 years old from the eastern part of China.We developed multiple machine-learning risk prediction models using parametric models(penalized logistic regression,bootstrap,and ensemble learning),which were the short-term ensemble penalized logistic regression(EPLR)risk prediction model and the ensemble penalized long-term(EPLT)risk prediction model to estimate BC risk.The models were assessed based on calibration and discrimination,and following this assessment,they were externally validated in new study participants from 2017 to 2020.Results:The AUC values of the short-term EPLR risk prediction model were 0.800 for the internal validation and 0.751 for the external validation set.For the long-term EPLT risk prediction model,the area under the receiver operating characteristic curve was 0.692 and 0.760 in internal and external validations,respectively.The net reclassification improvement index of the EPLT relative to the Gail and the Han Chinese Breast Cancer Prediction Model(HCBCP)models for external validation was 0.193 and 0.233,respectively,indicating that the EPLT model has higher classification accuracy.Conclusions:We developed the EPLR and EPLT models to screen populations with a high risk of developing BC.These can serve as useful tools to aid in risk-stratified screening and BC prevention.

细胞学指标与宫颈癌HPV亚型的相关性研究

目的探讨宫颈癌相关人乳头瘤病毒(HPV)亚型与细胞学指标变化的关联性,为宫颈癌的早期诊断和防治提供更精准依据。方法选取2021年1月至2023年12月期间于南京市高淳人民医院收治的宫颈癌患者为研究对象。采用聚合酶链反应(PCR)技术对患者进行HPV亚型检测,确定高危型(包括HPV16、18、31、33等)和低危型(包括HPV6、11等)HPV感染情况。同时,进行细胞学检查,观察细胞形态(包括细胞核直径、形状等)、染色质分布(通过均匀度评分进行评估)以及细胞异型性(以异型性指数衡量)等细胞学指标变化。运用Spearman方法分析HPV亚型与细胞核形态、染色质分布、细胞异型性的相关性。对HPV亚型、患者年龄、生育史等因素进行Logistic多因素回归分析以确定影响因素。结果高危型HPV感染患者细胞核平均直径13.5μm,70%形状不规则;染色质分布均匀度3.5分,85%不均;细胞异型性指数1.9。低危型细胞核直径9.2μm,40%稍不规则;均匀度6.8分;异型性指数1.3。正常细胞相应指标则更优。Spearman相关性分析显示,高危型HPV感染与细胞核形态异常、染色质分布不均匀度、细胞异型性指数升高呈显著正相关(r=0.82、0.76、0.85,P<0.05)。Logistic多因素回归分析表明,高危型HPV感染是影响细胞学指标异常的重要因素之一(OR=1.46~1.73,P<0.05)。结论高危型HPV感染与细胞学异常密切相关,特定的HPV亚型可能预示着特定的细胞学改变。通过对HPV亚型和细胞学指标的联合检测,可以提高宫颈癌的早期诊断准确性,为宫颈癌的防治提供重要参考。

Ultrasound Features Improve Diagnostic Performance of Ovarian Cancer Predictors in Distinguishing Benign and Malignant Ovarian Tumors

To determine whether ultrasound features can improve the diagnostic performance of tumor markers in distinguishing ovarian tumors,we enrolled 719 patients diagnosed as having ovarian tumors at Nanfang Hospital from September 2014 to November 2016.Age,menopausal status,histopathology,the International Federation of Gynecology and Obstetrics(FIGO)stages,tumor biomarker levels,and detailed ultrasound reports of patients were collected.The area under the curve(AUC),sensitivity,and specificity of the bellow-mentioned predictors were analyzed using the receiver operating characteristic curve.Of the 719 patients,531 had benign lesions,119 had epithelial ovarian cancers(EOC),44 had borderline ovarian tumors(BOT),and 25 had non-EOC.AUCs and the sensitivity of cancer antigen 125(CAI25),human epididymis-specific protein 4(HE4),Risk of Ovarian Malignancy Algorithm(ROMA),Risk of Malignancy Index(RMI1),HE4 model,and Rajavithi-Ovarian Cancer Predictive Score(R-OPS)in the overall population were 0.792,0.854,0.856,0.872,0.893,0.852,and 70.2%,56.9%,69.1%,60.6%,77.1%,71.3%,respectively.For distinguishing EOC from benign tumors,the AUCs and sensitivity of the above mentioned predictors were 0.888,0.946,0.947,0.949,0.967,0.966,and 84.0%,79.8%,87.4%,84.9%,90.8%,89.1%,respectively.Their specificity in predicting benign diseases was 72.9%,94.4%,87.6%,95.9%,86.3%,90.8%,respectively.Therefore,we consider biomarkers in combination with ultrasound features may improve the diagnostic performance in distinguishing malignant from benign ovarian tumors.

The Volatilization of Pollutants from Soil and Groundwater: Its Importance in Assessing Risk for Human Health for a Real Contaminated Site

Pollution of different elements (air, water, soil and subsoil) resulting both from accidental events and from ordinary industrial and civil activities causes negative effects on the human health and on the environment. The present paper examines the analysis of a contaminated site, focusing the attention on the negative effects for receptors exposed to soil and groundwater contamination caused by industrial activities. The case study investigated is a contaminated area located in the industrial district of Trento North once occupied by the Italian Carbochimica plant. Pollution in that area is mainly due to contamination of soil and groundwater with polycyclic aromatic hydrocarbons. The methodology applied is the risk evaluation for human health, in terms of individual cancer risk and hazard index. In particular the attention has been focused on a specific migration way: if pollutants in the soil or in the groundwater undergo a phase change, they spread and get to the soil surface, causing a dispersion of vapors in the atmosphere. In this case risk assessment calls for the evaluation of volatilization factor. Among the different models dealing with the estimation of volatilization factor, those mostly known and used in the national and international field of Human Health Risk Assessment were chosen: Jury’s and Farmer’s models. A sensitivity analysis of models was performed, in order to identify the most significant parameters to estimate the volatilization factors among the wide range of input parameters for the application of models. Performing an accurate selection and data processing of the contaminated site, models for the volatilization factors calculation are applied, thus evaluating air concentrations and Human Health Risk. The analysis of the resulting estimates is an excellent aid to draw interesting conclusions and to verify if the soil and groundwater pollutants volatilization affects the human health considerably.

中国农田磷流失风险评价及其关键驱动因素

农田面源磷流失是农业面源污染的重要原因之一,识别流域内农田磷流失风险的关键源区及其影响因子是面源污染控制的重要手段。基于磷指数模型开展2000—2020年中国农田磷流失风险评估,选取土壤有效磷含量、磷肥施用量为源因子,土壤侵蚀模数、年径流深、农田和水体间归一化距离指数为迁移因子,结合GIS技术评估了中国农田磷流失的关键源区;在此基础上,利用随机森林法分析影响中国农田磷流失的关键因子,并通过结构方程模型揭示了农田磷流失风险指数与各因子的关系。结果表明:1)2000—2020年中国农田的磷流失的低、中、高、极高风险面积分别占农田总面积的43.8%、40.5%、13.4%、2.4%。2)中国农田磷流失在2000、2005、2010、2015、2020年高风险和极高风险总面积的年平均占比从大到小依次为:淮河流域、长江流域、珠江流域、东南诸河流域、松辽河流域、西南诸河流域、黄河流域、内陆河流域、海河流域。3)影响农田磷流失风险的关键源因子和迁移因子分别为土壤有效磷含量和归一化距离指数,其重要性特征值分别为129.53和65.12,土壤有效磷含量是农田磷流失最主要影响因子。4)磷流失风险指数与源因子指数、迁移因子指数呈极显著正相关,选取的14个指标对磷指数的解释度达0.62,其中源因子和迁移因子对磷指数的贡献率分别为0.77、0.19(P <0.001)。研究结果可为中国农田磷流失风险评估提供科学参考,对中国农业面源污染的宏观防控及战略决策具有重要意义。

基于二维云模型的深基坑施工风险评价方法

为兼顾深基坑施工风险评估中涉及的模糊和随机不确定性,提出了基于二维云模型和3En规则的深基坑施工风险评价方法.首先,辨识了深基坑施工风险源,建立了多因素施工风险评价指标体系;其次,根据工程情况采用德尔菲法初步判定评价指标重要性,采用层次分析法和熵权法确定评价指标的主客观权重,获得综合权重;然后,根据风险评价准则和正向云发生器生成二维标准云和综合云;最后,利用云模型的3En规则和综合云云滴分布概率,快速判断风险等级的隶属度.运用提出的风险评价方法预测了南宁市某深基坑工程施工风险等级,与传统模糊综合风险评价方法对比,该评价方法具有可靠性.

Caprini风险评估模型对乳腺癌化疗患者输液港相关静脉血栓形成的预测效果分析

目的探究基于Caprini风险评估模型对乳腺癌化疗患者输液港相关静脉血栓形成的预测效果。方法选取2018年5月—2022年5月医院收治的输液港化疗乳腺癌患者300例为调查对象,将确诊已发生输液港相关静脉血栓的乳腺癌患者60例作为发生组,未发生输液港相关静脉血栓的乳腺癌患者240例为未发生组,收集所有患者一般资料,采用Caprini风险评估模型对两组患者进行风险评分及危险度分级,通过多因素Logistic回归模型分析乳腺癌化疗患者输液港相关静脉血栓形成影响因素,探讨Caprini风险评估模型预测乳腺癌化疗患者输液港相关静脉血栓形成价值。结果二元Logistic多因素回归分析结果显示,年龄、长期卧床、输液港留置时间、既往静脉血栓病史、远处转移、合并症、下肢水肿、穿刺前D-D水平、穿刺前CRP水平、Caprini风险评估模型评分及其危险度分级为乳腺癌化疗患者输液港相关静脉血栓形成影响因素(P<0.05),其中,年龄≥60岁、长期卧床、输液港留置时间≥1年、既往静脉血栓病史、远处转移、合并症、下肢水肿、穿刺前高D-D水平、穿刺前高CRP水平、Caprini风险评估模型评分>9.5分的乳腺癌化疗患者更容易发生输液港相关静脉血栓。ROC曲线分析显示,Caprini风险评估模型评分预测乳腺癌化疗患者输液港相关静脉血栓形成的AUC分别为0.807,cut-off值为9.5分,敏感度与特异性分别为55.0%、92.1%。结论年龄、长期卧床、输液港留置时间、既往静脉血栓病史、远处转移、合并症、下肢水肿、穿刺前D-D水平、穿刺前CRP水平、Caprini风险评估模型评分为乳腺癌化疗患者输液港相关静脉血栓形成影响因素。通过Caprini风险评估模型预测乳腺癌化疗患者输液港相关静脉血栓形成具有较好价值。

基于改进AHP-灰云模型的模块栈桥加工制造安全风险评价

为了对新型模块式钢栈桥加工安全风险进行客观评价,保障生产顺利进行,采用改进AHP-灰云模型对某模块栈桥加工制造过程进行安全风险评价。从人、机械、物料、环境和管理5个方面开展系统研究,建立了包括9项二级指标和28项三级指标的安全风险评价指标体系。采用改进的层次分析法确定指标权重值,将现场安全风险评估值输入灰云模型,进行风险等级的确定。研究结果表明该方法适用于模块栈桥加工制造安全风险评价,经分析吊车与地面作业交叉情况、机械设备的检查维修、噪声的影响三项指标风险值较高,并提出相应的风险防范措施。

高精度综合景观格局的中国人口暴露风险评价

基于PM2.5、人口格网数据,采用暴露风险评价模型,在高精度时空分辨率下,研究中国2000—2020年PM2.5人口暴露风险的时空演变,对中国的PM2.5人口暴露风险进行评价。并结合土地利用数据,在最佳移动窗口的基础上测算景观格局指数,以皮尔逊相关性分析揭示景观格局对PM2.5浓度及其人口暴露风险关系。中国PM2.5人口暴露风险趋势为先增加后减少,胡焕庸线东西侧PM2.5人口暴露风险值相差较大。从空间变化上看,中国PM2.5人口暴露风险高污染聚集区域主要分布在京津冀、长三角以及中原地区。研究发现,边缘密度(ED)、形状指数(LSI)有利于缓和PM2.5人口暴露风险等问题。边缘密度、形状指数和边缘形状复杂度降低可以有效地减少PM2.5人口暴露风险,而高破碎度的景观类型会导致削减PM2.5人口暴露风险作用进一步弱化。

胃癌术后炎性并发症的危险因素分析及列线图预测模型构建

目的探讨胃癌根治性切除术后炎性并发症的危险因素,并构建风险预测列线图模型。方法回顾性分析402例接受胃癌根治性切除术治疗的原发性胃癌患者的临床资料,患者术前均接受营养风险筛查2002(NRS2002)评分、患者主观整体评估(PG-SGA)分级、第3腰椎骨骼肌质量指数(L3-SMI)评估及血清学指标检测。采用单因素分析筛选胃癌术后炎性并发症的影响因素,并采用多因素Logistic回归分析确定胃癌术后炎性并发症的独立危险因素。基于多因素Logistic回归分析结果构建预测胃癌根治性切除术后炎性并发症的列线图模型,并通过受试者工作特征(ROC)曲线、校准曲线评价模型的预测效能。结果单因素分析结果显示,年龄、TNM分期、体质量指数、术前血红蛋白、术前白蛋白、术前球蛋白、NRS2002评分、PG-SGA分级、L3-SMI是胃癌根治性切除术后患者发生炎性并发症的影响因素(P<0.05)。多因素Logistic回归分析结果显示,年龄≤60岁、术前血红蛋白≤130 g/L(男)或115 g/L(女)、TNM分期为Ⅳ期、NRS2002评分≥3分、L3-SMI≤52.4 cm^(2)/m^(2)(男)或38.5 cm^(2)/m^(2)(女)是胃癌患者术后发生炎性并发症的独立危险因素(P<0.05)。基于年龄、术前血红蛋白、TNM分期、NRS2002评分构建列线图模型,ROC曲线显示列线图模型的曲线下面积为0.930,敏感度和特异度分别为93.2%和89.2%,校准曲线显示列线图预测的炎性并发症发生概率与实际结果具有良好的一致性。结论年龄≤60岁、术前低血红蛋白、TNM分期为Ⅳ期、NRS2002评分≥3分、低L3-SMI是胃癌患者术后发生炎性并发症的独立危险因素,基于年龄、术前血红蛋白、TNM分期、NRS2002评分构建的列线图模型能够精准预测胃癌术后炎性并发症。

江西丘陵山区公路地质灾害危险性评价多耦合模型对比研究

山区公路沿线地质灾害发育,影响山区城镇居民交通出行和生命财产安全。危险性评价可以综合分析地质灾害孕灾环境和致灾因子的贡献特征,对于公路防灾减灾具有重要的指导作用。以江西省S223省道竹头坑子—渠坎下段为例,基于频率比(frequency ratio,FR),耦合熵指数(entropy index,EI)、层次分析法(analytic hierarchy process,AHP)及二者组合权(EI-AHP),构建4种地质灾害危险性评价模型;针对公路沿线地质环境与地质灾害发育特征,选取自然坡度、坡向、地形起伏度、坡面形态、切坡高度、切坡坡度、地层岩性、断层与斜坡的关系等8个评价因子作为危险性评价指标,以斜坡单元作为评价单元,采用FR量化评价因子,结合AHP、EI计算评价因子的主客观权重,依托ArcGIS平台得到基于FR的多耦合模型,绘制不同评价模型的公路沿线地质灾害危险性分区图。结果表明:FR、EI-FR、AHP-FR及EI-AHP-FR 4个评价模型的AUC值分别为0.746,0.811,0.836,0.833,表明AHP-FR评价模型的预测精度最高,能有效对公路沿线地质灾害进行危险性评价;最终划分江西省S223省道竹头坑子—渠坎下段高危险区、较高危险区、中危险区、较低危险区、低危险区的面积依次为0.295,0.570,1.509,0.354,1.732 km^(2),分别占全区总面积的6.66%、12.79%、33.86%、7.97%、38.71%。研究结果可为公路的安全建设和正常运营提供科学的地质参考依据。

网络安全风险评估方法研究综述

网络安全风险评估是构建网络空间安全体系的重要环节,可以有效保护个人和组织机构避免受到网络安全攻击。文中简要概述了网络安全风险评估理论,重点介绍了目前主流的网络安全风险评估方法,并根据不同的方法性质对现有方法进行分类和对比,分析了各方法的优缺点以及适用范围。在此基础上,文中归纳提取出对网络安全评估结果产生影响的因素并对网络安全评估领域未来的研究重点进行提议。分析结果表明,关联性和评估指标的不确定性以及评估过程的实时性这3个因素是影响风险评估效果的主要因素,并给未来的风险评估方法研究提供了参考依据。

基于隐马尔可夫模型的火灾风险评估研究

近年来全球气候变化越来越复杂,自然灾害频发,森林防火形式日益严峻,森林火灾风险评估工作越来越重要。为此,基于隐马尔可夫模型(Hidden Markov Model, HMM)提出一种森林火险评估模型。首先构建森林火灾风险指标体系,将其分为气象条件、森林特征以及防火意识和能力3类12个指标,并根据层次分析法计算指标权重。同时,针对HMM模型求解过程中Baum-Welch算法对初始值有较强的依赖性且容易陷入局部最优的问题,提出通过粒子群优化算法搜索全局最优解作为HMM初始值,再使用Baum-Welch算法进行局部校正,使其快速收敛到全局最优解。利用优化前后的2个模型分别对重庆市森林火灾风险数据开展评估,验证优化后的模型能够有效地评估森林火灾风险,并且与改进前相比更精确,可为区域森林防火工作提供有效指导。

老年脓毒症患者住院期间死亡风险预测模型的建立与验证

目的建立并验证可预测老年脓毒症患者住院死亡风险的模型。方法回顾性纳入2019年1月—2022年12月哈尔滨医科大学附属第一医院重症医学科住院治疗的238例脓毒症患者,以住院期间转归情况为主要结局指标,分为死亡组68例(28.57%)和生存组170例(71.43%)。采用多因素Logistic回归法筛选脓毒症患者住院死亡的独立危险因素,并根据影响因素构建预测脓毒症患者住院死亡风险的模型。采用受试者工作特征(ROC)曲线对预测模型的性能进行评定,结果以曲线下面积(AUC)表示;基于2016年1月—2018年12月的176例脓毒症患者的临床资料进行外部验证。结果单因素分析显示,与生存组比较,死亡组年龄>70岁的比率、急性肾损伤(AKI)Ⅲ期比率及红细胞分布宽度(RDW)、纤维蛋白原、乳酸、血肌酐、英国早期预警评分(NEWS)、快速序贯器官衰竭评分(qSOFA)升高,氧合指数、白蛋白降低,差异均有统计学意义(P<0.05)。多因素Logistic回归分析结果显示,年龄>70岁(OR=1.426,95%CI:1.055~1.928)、乳酸>6 mmol/L(OR=1.436,95%CI:1.105~1.867)、RDW>16%(OR=1.354,95%CI:1.080~1.698)、AKIⅢ期(OR=1.982,95%CI:1.407~2.791)、qSOFA>2分(OR=1.853,95%CI:1.255~2.738)是脓毒症患者住院期间死亡的独立危险因素(P<0.05)。根据回归分析结果,建立脓毒症患者死亡风险方程,一致性指数(Cindex)=-1.694+0.355×年龄+0.303×RDW+0.362×乳酸+0.684×AKIⅢ期+0.617×qSOFA。ROC曲线显示,内部验证时Cindex预测脓毒症患者住院期间死亡的AUC为0.882(95%CI:0.834~0.929),灵敏度为83.82%,特异度为77.06%;外部验证时Cindex预测脓毒症患者住院期间死亡的AUC为0.823(95%CI:0.757~0.889),灵敏度为74.13%,特异度为81.36%。结论年龄、乳酸、RDW、AKI分期、qSOFA与老年脓毒症死亡风险具有相关性,基于这些参数构建的模型可能有助于预测老年脓毒症住院期间全因死亡风险。