Risk-opportunity analyses and production peak forecasting on world conventional oil and gas perspectives

To investigate the situation of conventional oil and gas, this paper examines the global oil and gas discoveries, proved reserves, production, consumption and price. All the influencing factors can be subjected to risk and opportunity analyses, so in the paper, we build upon a risk-opportunity analysis framework, which is a new train of thought. To forecast the peak time of oil and gas production, we used the methods of multi-Hubbert model forecasting and data forecasting. Our results showed that the world oil production will reach a peak between 2010 and 2015 and the gas production will reach a peak around 2030 Oil peak is coming and gas peak is on the way. The main purpose of forecasting oil and gas production peak is give people enough time for preparing mitigation and adaptation plans. This means taking decisive action well before the problem is obvious.

Research on Risks and Forecasting Countermeasures of Hainan Banana Industry

Based on the overviews of the current conditions of Hainan banana industry,the research makes an analysis of the risks faced by Hainan banana industry.They are respectively marketing risks,natural risks,information risks and production risks.In order to promote a sustainable and rapid development of Hainan banana industry,countermeasures are proposed in the research.The first is to strengthen the leading organization of forecasting mechanisms on banana industry.The second is to establish the forecasting mechanisms on banana industry,including four aspects.They are establishing the subordinate forecasting systems on Hainan banana industry;constructing information collecting and checking mechanisms of banana industry;establishing information analysis and decision-making systems and constructing information distribution and information sharing systems.The third is to promote the construction of urgency dealing abilities of banana industry.The fourth is to further perfect the risk-defending and protecting systems of banana industry in Hainan.The fifth is to accelerate the standard generation of banana to improve marketing competence.The sixth is to accelerate the development of intermediate agents to improve the organization degrees.And the last one is to put emphasis on the tech-training courses on banana planting and production to improve the technical quality of banana industry.

Elaborate Forecast about Fire Risk Grade in Forest and Grassland of Inner Mongolia Based on Intelligent Grid

Based on the fire and meteorological data of forest and grassland in Inner Mongolia in recent 30 years,a forest and grassland fire risk grade forecast model is established,and a refined forest and grassland fire risk level forecast system based on smart grid is developed. The results show that predictors are determined about forest and grassland fire risk grade,such as precipitation,minimum relative humidity,maximum temperature,maximum wind speed,number of sunny or rainy days,and forest and grassland combustible stock. According to fire risk division conclusion,forest and grassland areas are divided into 5 forecast areas. By using discriminant analysis and weighted factor overlay method,an elaborate fire risk grade forecast model is established in different forecast areas of Inner Mongolia forest and grassland. By using smart grid forecast field data,an elaborate fire risk grade forecasting system is established for making fire risk grade forecast during 24,48 and 72 h.

Validation of an operational forecasting system of sea dike risk in the southern Zhejiang Province, South China

In this study,an operational forecasting system of sea dike risk in the southern Zhejiang Province,South China was developed based on a coupled storm-surge and wave model.This forecasting system is important because of the high cost of storm-surge damage and the need for rapid emergency planning.A comparison with astronomical tides in 2016 and the validation of storm surges and high water marks of 20 typhoons verified that the forecast system has a good simulation ability.The system can forecast relatively realistic water levels and wave heights as shown under the parametric atmospheric forces simulated in a case study;the sea dikes in credible high risk were mainly located in the estuaries,rivers,and around the islands in the southern Zhejiang.Therefore,the forecast system is applicable in the southern Zhejiang with a support to the effective prevention from typhoon storm-surge damage.

Volatility Forecasting and Volatility Risk Premium

Volatility is an important variable in the financial market. We propose a model-free implied volatility method to measure the volatility and test the volatility risk premium. The model-free implied volatility does not depend on the option pricing model, and extracts information from all the option contracts. We provide empirical evidence from the S & P 500 index option that model-free implied volatility is more accurate to forecast the future volatility and the volatility risk premium does not exist.

Prediction of petroleum exploration risk and subterranean spatial distribution of hydrocarbon accumulations

Investigation of spatial distribution of oil and gas resource and accurate prediction of the geographic location of its undiscovered resource is significant for reducing exploration risk and improving exploration benefit.A new method for predicting spatial distribution of oil resource is discussed in this paper.It consists of prediction of risk probability in petroleum exploration and simulation of hydrocarbon abundance. Exploration risk probability is predicted by multivariate statistics,fuzzy mathematics and information processing techniques.A spatial attribute database for sample wells was set up and the Mahalanobis distance and Fuzzy value of given samples were obtained.Then,the Bayesian formula was used to calculate the hydrocarbon-bearing probability at the area of exploration wells.Finally,a hydrocarbon probability template is formed and used to forecast the probability of the unknown area. The hydrocarbon abundance is simulated based on Fourier integrals,frequency spectrum synthesis and fractal theory.Firstly,the fast Fourier transformation（FFT） is used to transform the known hydrocarbon abundance from the spatial domain to the frequency domain,then,frequency spectrum synthesis is used to produce the fractal frequency spectrum,and FFT is applied to get the phase information of hydrocarbon-bearing probability.Finally,the frequency spectrum simulation is used to calculate the renewed hydrocarbon abundance in the play. This method is used to predict the abundance and possible locations of the undiscovered petroleum accumulations in the Nanpu Sag of the Bohai Bay Basin,China.The prediction results for the well-explored onshore area of the northern Nanpu Sag agree well with the actual situations.For the less-explored offshore areas in the southern Nanpu Sag,the prediction results suggest high hydrocarbon abundance in Nanpu-1 and Nanpu-2,providing a useful guiding for future exploration.

An Artificial Neural Network Approach for Credit Risk Management

The objective of the research is to analyze the ability of the artificial neural network model developed to forecast the credit risk of a panel of Italian manufacturing companies. In a theoretical point of view, this paper introduces a litera-ture review on the application of artificial intelligence systems for credit risk management. In an empirical point of view, this research compares the architecture of the artificial neural network model developed in this research to an-other one, built for a research conducted in 2004 with a similar panel of companies, showing the differences between the two neural network models.

Assessing the Risk Situation of Network Security for Active Defense

The risk situation assessment and forecast technique of network security is a basic method of active defense techniques. In order to assess the risk of network security two methods were used to define the index of risk and forecast index in time series, they were analytical hierarchy process （AHP） and support vector regression （SVR）. The module framework applied the methods above was also discussed. Experiment results showed the forecast values were so close to actual values and so it proved the approach is correct.

老年髋部骨折手术延迟的影响因素分析及风险预测模型构建

目的:探讨老年髋部骨折手术延迟的影响因素,构建老年髋部骨折手术延迟风险预测模型。方法:选取2019年11月至2022年11月采用手术治疗的老年髋部骨折患者的病例资料进行研究,将纳入研究的患者按照2∶1的比例随机分为训练集(用于模型构建)和验证集(用于模型验证)。从病历系统中提取纳入患者的信息,包括年龄、性别、体质量指数、骨折类型、美国麻醉医师协会(American Society of Anesthesiologists, ASA)分级、伤前日常活动能力(activities of daily living, ADL)、是否服用影响凝血功能的药物、入院至手术时间、手术方式,是否合并精神障碍、高血压、糖尿病、呼吸系统疾病、心功能不全、肝功能不全、肾功能不全、电解质紊乱、尿酮体异常、下肢静脉血栓、凝血功能异常,以及入院后血清肿瘤坏死因子-α、C反应蛋白水平等。将训练集中的患者根据入院至手术时间分为早期手术组(入院至手术时间<48 h)和延迟手术组(入院至手术时间≥48 h)。先对2组患者的相关信息进行单因素对比分析,再对单因素分析中组间差异有统计学意义的因素进行多因素Logistic回归分析及多重共线性诊断;采用R软件基于贝叶斯网络模型构建老年髋部骨折手术延迟风险预测模型,并采用Netica软件进行贝叶斯网络模型推理。采用受试者操作特征(receiver operating characteristic, ROC)曲线评价老年髋部骨折手术延迟风险预测模型的区分度,采用校准曲线评价老年髋部骨折手术延迟风险预测模型的校准度。结果:(1)分组结果。共纳入老年髋部骨折患者318例,训练集212例、验证集106例。根据入院至手术时间,训练集中早期手术组78例、延迟手术组134例。(2)老年髋部骨折手术延迟影响因素的单因素分析结果。2组患者ASA分级、是否服用影响凝血功能的药物及是否合并精神障碍、高血压、糖尿病、呼吸系统疾病、心功能不全、电解质紊乱、凝血功能异常的比较,组间差异均有统计学意义(χ~2=3.862,P=0.049;χ~2=26.806,P=0.000;χ~2=29.852,P=0.000;χ~2=21.743,P=0.000;χ~2=25.226,P=0.000;χ~2=5.415,P=0.020;χ~2=11.683,P=0.001;χ~2=14.686,P=0.000;χ~2=6.057,P=0.014)。(3)老年髋部骨折手术延迟影响因素的多因素分析及多重共线性诊断结果。多因素Logistic回归分析结果显示,服用影响凝血功能的药物及合并精神障碍、高血压、糖尿病、呼吸系统疾病、心功能不全、电解质紊乱、凝血功能异常均是老年髋部骨折手术延迟的影响因素[β=0.328,P=0.000,OR=5.112,95%CI(2.686,9.728);β=0.322,P=0.000,OR=5.425,95%CI(2.884,10.203);β=0.302,P=0.000,OR=3.956,95%CI(2.189,7.148);β=0.312,P=0.000,OR=4.560,95%CI(2.476,8.398);β=0.291,P=0.021,OR=1.962,95%CI(1.108,3.474);β=0.296,P=0.001,OR=2.713,95%CI(1.520,4.844);β=0.303,P=0.000,OR=3.133,95%CI(1.729,5.679);β=0.296,P=0.015,OR=2.061,95%CI(1.154,3.680)];多重共线性诊断结果显示,上述影响因素均不存在共线性(VIF=1.134,VIF=1.266,VIF=1.465,VIF=1.389,VIF=1.342,VIF=1.183,VIF=1.346,VIF=1.259)。(4)基于贝叶斯网络模型的老年髋部骨折手术延迟风险预测模型的构建与推理结果。基于贝叶斯网络模型构建的老年髋部骨折手术延迟风险预测模型包括8个节点、8条有向边。模型显示,服用影响凝血功能的药物及合并精神障碍、呼吸系统疾病、电解质紊乱、凝血功能异常直接影响手术延迟的发生,合并心功能不全、高血压、糖尿病间接影响手术延迟的发生;推理结果显示,患者合并心功能不全、凝血功能异常及精神障碍时,手术延迟发生率为64.1%。(5)老年髋部骨折手术延迟风险预测模型的评价结果。采用训练集数据进行老年髋部骨折手术延迟风险预测模型评价,ROC曲线下面积为0.861[P=0.000,95%CI(0.810,0.912)],灵敏度为91.29%,特异度为93.35%;校准曲线显示其一致性指数为0.866[P=0.000,95%CI(0.702,0.943)];采用验证集数据进行老年髋部骨折手术延迟风险预测模型评价,ROC曲线下面积为0.848[P=0.000,95%CI(0.795,0.901)],灵敏度为91.62%,特异度为92.46%;校准曲线显示其一致性指数为0.879[P=0.000,95%CI(0.723,0.981)]。结论:服用影响凝血功能的药物以及合并精神障碍、高血压、糖尿病、呼吸系统疾病、心功能不全、电解质紊乱、凝血功能异常均为老年髋部骨折手术延迟的影响因素,基于上述因素构建的老年髋部骨折手术延迟风险预测模型具有较高的应用价值。

全身麻醉患者术毕至转运病房期间低血压危险因素分析

目的分析全身麻醉患者术毕至转运病房期间发生术后低血压(PSH)的危险因素,探讨其对患者预测价值。方法募集231例全麻手术患者,观察手术结束、过床后1、3、5、10 min及入复苏室时、出复苏室时、回病房时是否出现PSH,分析性别、年龄、体重、BMI、基础疾病、麻醉方式、手术方式、术中出入量、BP、HR、RR、SpO 2等因素是否为PSH发生的危险因素。结果与入手术室时相比,手术结束后1、3、5、10 min,入复苏室时、出手术室时和进入病房时各时间点低血压患者发生率分别为29.44%、25.54%、20.35%、17.75%、16.45%、20.35%及22.94%例;与入手术室时相比,入复苏室时PSH组与非PSH组患者的体重、BMI、SBP及DBP有差异(P<0.05);与入手术室时相比,进入病房时PSH组与非PSH组患者的出血量、SBP、DBP及SpO 2有差异(P<0.05);多元线性回归分析显示,SBP为入复苏室时PSH发生的危险因素;出血量及SBP为进入病房时PSH发生的危险因素;ROC曲线分析结果显示,SBP对入复苏室时患者发生PSH具有较好的预测价值,预测值为89.5 mmHg;出血量及SBP对患者进入病房后发生PSH具有较好的预测价值。结论全身麻醉患者术前SBP及术中出血量为术毕PSH发生的危险因素,并对患者术毕返回病房后发生PSH具有良好的预测价值,预测值分别为150 mmHg和126.5 mmHg。

Study of Volatility Stochastic Processes in the Context of Solvency Forecasting for Sri Lankan Life Insurers

The main business of Life Insurers is Long Term contractual obligations with a typical lifetime of 20 - 40 years. Therefore, the Solvency metric is defined by the adequacy of capital to service the cash flow requirements arising from the said obligations. The main component inducing volatility in Capital is market sensitive Assets, such as Bonds and Equity. Bond and Equity prices in Sri Lanka are highly sensitive to macro-economic elements such as investor sentiment, political stability, policy environment, economic growth, fiscal stimulus, utility environment and in the case of Equity, societal sentiment on certain companies and industries. Therefore, if an entity is to accurately forecast the impact on solvency through asset valuation, the impact of macro-economic variables on asset pricing must be modelled mathematically. This paper explores mathematical, actuarial and statistical concepts such as Brownian motion, Markov Processes, Derivation and Integration as well as Probability theorems such as the Probability Density Function in determining the optimum mathematical model which depicts the accurate relationship between macro-economic variables and asset pricing.

Risk Assessment and Prediction of Construction Project Based on 1D-CNN-Attention-BP

In order to solve the problem of low accuracy of construction project duration prediction, this paper proposes a CNN attention BP combination model project risk prediction model based on attention mechanism, one-dimensional convolutional neural network (1d-cnn) and BP neural network. Firstly, the literature analysis method is used to select the risk evaluation index value of construction project, and the attention mechanism is used to determine the weight of risk factors on construction period prediction;then, BP neural network is used to predict the project duration, and accuracy, cross entropy loss function and F1 score are selected to comprehensively evaluate the performance of 1d-cnn-attention-bp combined model. The experimental results show that the duration risk prediction accuracy of the risk prediction model proposed in this paper is more than 90%, which can meet the risk prediction of construction projects with high accuracy.

冠心病病人PCI术后1年出血危险因素的模型构建和验证

目的:基于LASSO-Logistic回归分析冠心病病人经皮冠状动脉介入(PCI)术后1年出血的危险因素,并建立Nomogram预测模型,以便临床采取及时、有效的干预方案。方法:选取2021年1月—12月在我院行PCI术的226例冠心病病人为研究对象,依据PCI术后1年是否出血分为出血组、未出血组。采用LASSO-Logistic回归筛选PCI术后1年出血的危险因素,进一步构建Nomogram预测模型。利用受试者工作特征(ROC)曲线、校准曲线验证Nomogram预测模型的价值。结果:PCI术后1年226例冠心病病人出血发生率为11.95%;年龄≥60岁、有消化道病史、慢性肾功能不全、使用血管闭合器、球囊扩张次数、支架术后抗血小板药物停药模式(PARIS)评分、支架术后双重抗血小板治疗病人出血并发症预测(PRECISE-DAPT)评分为PCI术后1年出血的危险因素(P<0.05);Nomogram预测模型预测PCI术后1年出血的ROC曲线下面积为0.959。结论:年龄≥60岁、有消化道病史、慢性肾功能不全、使用血管闭合器、球囊扩张次数、PARIS评分、PRECISE-DAPT评分为冠心病病人PCI术后1年出血的危险因素,基于LASSO-Logistic回归分析建立的Nomogram预测模型对PCI术后1年出血具有一定预测价值,临床应筛查高危人群并实施严格观察,制定合理治疗措施,以降低出血风险。

开放性手外伤术后感染危险因素及预测分析

目的探讨开放性手外伤术后感染危险因素并进一步分析相关因素风险预测临床效能。方法回顾性纳入2020年6月至2023年6月于本院行手术治疗开放性手外伤患者共106例,根据术后有无感染出现分组,比较感染组和无感染组临床特征资料,采用Logistics回归模型多因素分析评估开放性手外伤术后感染独立危险因素,描绘ROC曲线分析上述独立危险因素用于开放性手外伤术后感染风险预测临床效能。结果本研究纳入于本院行手术治疗开放性手外伤患者106例中出现术后感染11例,发生率为10.38%。单因素分析结果显示,年龄、吸烟、合并糖尿病、有无手术创面污染、受伤至手术时间、ASA评分、手术时间及是否行负压引流均可能与开放性手外伤术后感染发生有关(P<0.05)。Logistic回归模型多因素分析结果显示,年龄≥60岁、合并糖尿病、受伤至手术时间≥6 h、手术创面污染及未行负压引流均是开放性手外伤术后感染发生独立危险因素(P<0.05)。ROC曲线分析结果显示,年龄、是否合并糖尿病、受伤至手术时间、有无手术创面污染及有无行负压引流均可用于开放性手外伤术后感染发生风险预测,且上述指标联合预测效能显著优于单一指标(P<0.05)。结论开放性手外伤术后感染发生与年龄、是否合并糖尿病、受伤至手术时间、有无手术创面污染及有无行负压引流关系密切;而上述指标联合在预测开放性手外伤术后感染发生风险方面显示出更优临床效能。

企业竞争战略与管理层策略性业绩:基于管理层业绩预告的分析

从战略管理理论出发研究竞争战略对管理层盈利预测策略的影响。结果表明,采取差异化战略的企业更可能自愿披露盈利预测信息,然而预测偏差较大并更倾向于披露悲观消息。机制检验表明经营风险在差异化战略影响盈利预测中起中介作用。进一步研究发现,在国有企业和金融化程度较强的样本中,差异化竞争战略和盈利预测偏差的关系被显著弱化。

糖尿病足发病风险预测模型的系统评价

背景糖尿病足是糖尿病患者常见并发症,多数患者病情重,疾病进展快。性能良好的糖尿病足发病风险预测模型可以帮助医务人员识别高危患者,尽早采取干预措施。目的系统评价糖尿病足发病风险预测模型,为模型的构建和优化提供参考。方法检索PubMed、Cochrane Library、Embase、Web of Science、中国知网及万方数据知识服务平台发表的关于糖尿病足风险预测模型的相关文献,检索期限为建库至2023-05-15。由研究者独立筛选文献,并提取文献数据,使用预测模型研究的偏倚风险评估工具(PROBAST)对模型进行质量评价。使用Stata 17.0软件对模型中预测因子进行Meta分析。结果共纳入13篇文献,包含13个模型,其中12个模型的曲线下面积(AUC)>0.7。7个模型进行了模型校准,8个模型进行了验证。PROBAST评估结果显示,纳入的13篇文献中有1篇为低偏倚风险,其余12篇均为高偏倚风险;模型适用性方面,1篇为低适用性。Meta分析结果显示,年龄(OR=1.13,95%CI=1.04~1.24)、糖化血红蛋白(OR=1.56,95%CI=1.26~1.94)、足溃疡史(OR=5.93,95%CI=2.85~12.37)、足截肢史(OR=7.79,95%CI=2.74~22.17)、单丝试验敏感性减弱(OR=1.59,95%CI=1.42~1.78)、足真菌感染(OR=6.14,95%CI=1.71~22.04)、肾病(OR=2.09,95%CI=1.65~2.65)是糖尿病足发病风险的影响因素(P<0.05)。结论糖尿病足风险预测模型仍存在不足,未来风险预测模型的建立可重点关注年龄、糖化血红蛋白水平、足溃疡史、足截肢史、单丝试验敏感性、足真菌感染、肾病等预测因子。

关键审计事项风险信息披露与分析师预测

文章以2017—2021年上市公司审计报告为研究对象,通过统计关键审计事项的风险词频探讨风险信息披露对分析师预测的影响。研究发现:关键审计事项风险信息披露降低了分析师的预测偏误和预测分歧度;进一步研究表明,促进公共信息和私有信息的获取以及较高的文本可读性是提高分析师预测质量的主要路径,且有助于修正分析师乐观预测偏差;在内部控制质量、审计质量、机构投资者持股比例、舆论关注度较高的子样本中,关键审计事项风险信息披露对分析师预测质量的改善作用更加明显。研究结论可为完善关键审计事项风险信息披露和传递机制提供实践经验和理论依据。

基于危险天气不确定性的最小风险路径规划方法

为降低飞行过程中遭遇危险天气的概率,同时避免大范围绕飞导致的路径与耗油增加,针对航路中的雷暴、积冰和颠簸天气,使用数值预报和概率预报,面向航前飞行计划,提出一种基于危险天气不确定性的最小风险路径规划方法.首先,基于概率预报数据使用配料法和C-F模型计算雷暴发生概率,基于数值预报数据计算积冰预测指数和颠簸预测指数;然后,融合多类型危险天气,提出一种具备风险标识的栅格化地图;在此基础上,改进传统路径最短的规划算法,构建以风险最小化为目标的Dijkstra和A^(*)算法;最后,使用2023年4月3日华中地区强对流天气预测数据建立风险地图,使用上述改进算法与传统Dijkstra、A^(*)和RRT算法进行路径规划并对比分析.结果表明,传统Dijkstra和A^(*)算法可计算得到最短飞行路径,而改进的A^(*)算法可计算得到总风险最小路径;若综合考虑飞行风险与路径长度,改进的Dijkstra算法最为适合.

1990-2019年中国心血管疾病流行现状、疾病负担及发病预测分析

背景心血管疾病是严重危害人类健康的重大慢病,且仍是我国乃至全球一个亟待解决的公共卫生问题。目的探讨1990—2019年中国心血管疾病流行特征和疾病负担情况,预测2020—2050年中国心血管疾病发病情况,为心血管疾病相关防治策略的制订提供参考。方法检索2019年全球疾病负担研究(GBD 2019)数据库,提取1990—2019年中国及全球心血管疾病负担及危险因素的相关数据并进行分析,使用基于GBD 2019数据库可公开的发病率、患病率、死亡率以及对应的年龄标准化(简称标化)率来量化心血管疾病的疾病流行情况,使用伤残损失寿命年(YLD)、早死损失寿命年(YLL)、伤残调整寿命年(DALY)量化疾病负担情况,构建ARIMA模型预测2020—2050年中国心血管疾病的发病情况。结果1990—2019年中国心血管疾病的发病率、患病率及死亡率呈逐年上升趋势,其中发病率、患病率及死亡率分别增长了93.75%、99.75%、57.39%。女性的标化发病率、标化患病率均高于男性,标化死亡率低于男性(P<0.05)。从2019年数据上看,中国心血管疾病总体发病率随着年龄升高呈上升趋势,在95岁及以上年龄组达到最高值。男性和女性的发病率趋势与总体趋势相似,但略有差异。总体患病率随着年龄升高呈上升趋势,女性高于男性。在45岁以后心血管疾病的死亡率呈现上升趋势,男性的死亡率在各个年龄段均高于女性。1990—2019年男性YLL率、YLD率、DALY率增长了36.99%、102.42%、40.78%,女性增长了2.79%、107.13%、11.50%。从2019年数据来看,中国总人群心血管疾病的YLL率、YLD率、DALY率总体随着年龄的增加呈上升趋势,尚无拐点出现。男性YLL率、DALY率随人口老龄化进展逐渐升高并远高过女性,女性YLD率在55~59岁年龄组后逐渐升高并远高过男性。1990—2019年,全球心血管疾病的标化发病率、标化患病率及标化死亡率呈逐年下降趋势,而中国的标化发病率和标化患病率仍有所增加,标化死亡率虽有所降低,但仍高于全球范围。从全球整体水平上看,中国心血管疾病的标化YLL率、标化DALY率虽同全球一样呈下降趋势,但2000年以后中国心血管疾病的疾病负担高于全球整体水平,且标化YLD率逐年增加。与心血管疾病死亡相关的危险因素主要是吸烟、吸二手烟、饮酒、体力活动少、高空腹血糖、高收缩压、高BMI、高低密度脂蛋白胆固醇以及肾功能不全。从中国及全球相关数据来看,高收缩压(高血压)依然是造成心血管疾病死亡的首要危险因素,且死亡人数逐年增加。高低密度脂蛋白胆固醇(高脂血症)是全球及近年来中国心血管疾病死亡的第二因素。2020—2050年中国心血管疾病标化发病率仍呈上升趋势,预计到2050年心血管疾病的标化发病率将达到663.618/10万。结论1990—2019年我国心血管疾病的发病率、患病率及死亡率呈逐年上升趋势,因心血管疾病导致的疾病负担较重,在未来50年尚无拐点出现,疾病流行及负担情况均高于全球范围。预计到2050年心血管疾病的标化发病率将达到663.618/10万。

高龄膝骨关节炎患者跌倒的危险因素分析及风险预测模型建立

目的:分析高龄膝骨关节炎患者跌倒的危险因素,建立跌倒风险预测模型。方法:以2020年1月至2022年4月在遂宁市中心医院就诊的年龄≥65岁的膝骨关节炎患者为研究对象。根据6个月内是否有排除外力因素的跌倒史进行分组,有跌倒史者归入跌倒组,无跌倒史者归入未跌倒组。收集2组患者的年龄、性别、病程、体质量指数(body mass index,BMI)、患病侧别、其他部位疼痛情况、合并其他慢性病情况、其他部位关节置换史、经常爬楼梯史、膝关节外伤史、Kellgren-Lawrence分级等一般资料。采用西安大略和麦克马斯特大学骨关节炎指数(Western Ontario and McMaster Universities osteoarthritis index,WOMAC)评价患膝疼痛、僵硬和功能受限程度,采用Lysholm膝关节评分评价膝关节功能。进行下肢三维运动学和动力学测试,收集包括时空参数、运动学参数和动力学参数在内的各项数据。比较2组患者的一般资料、临床评价结果及下肢各项力学参数,进行单因素分析。根据单因素分析结果采用Logistic回归分析高龄膝骨关节炎患者跌倒的危险因素,构建跌倒风险预测模型,并对模型进行评价。结果:①单因素分析结果。共纳入140例患者,跌倒组78例,未跌倒组62例。2组患者病程、其他部位疼痛情况、其他部位关节置换史、经常爬楼梯史、膝关节外伤史、Kellgren-Lawrence分级的组间比较,差异均有统计学意义。跌倒组患者WOMAC评分中疼痛、僵硬、功能障碍评分均高于未跌倒组,对侧腿离地期、步时长于未跌倒组,步长短于未跌倒组,步速慢于未跌倒组,足跟着地期踝背伸角、支撑期最大踝跖屈角、最大踝背伸角、最大踝跖屈角、足跟着地期膝伸角、支撑期最大膝伸角均大于未跌倒组,支撑期最大膝屈角、最大膝屈角、最大髋伸角、髋屈力矩峰值、髋伸力矩峰值、膝屈力矩峰值、膝伸力矩峰值、踝跖屈力矩峰值均小于未跌倒组。②高龄膝骨关节炎患者跌倒的危险因素分析及风险预测模型评价结果。Logistic回归分析结果显示,病程长、经常爬楼梯、疼痛重、足跟着地期踝背伸角增大、足跟着地期膝伸角增大、最大膝屈角减小、膝屈力矩峰值减小、踝跖屈力矩峰值减小均为高龄膝骨关节炎患者跌倒的独立危险因素[OR=5.230,95%CI(3.232,7.021),P=0.004;OR=4.367,95%CI(2.648,5.953),P=0.003;OR=4.252,95%CI(2.159,6.231),P=0.003;OR=3.473,95%CI(2.982,4.028),P=0.021;OR=6.977,95%CI(3.667,8.964),P=0.001;OR=3.989,95%CI(1.667,5.264),P=0.010;OR=7.051,95%CI(4.267,8.164),P=0.001;OR=4.675,95%CI(2.563,6.798),P=0.008]。跌倒风险预测列线图模型显示,病程>6年、经常爬楼梯、WOMAC疼痛评分>48分、足跟着地期踝背伸角>9.25°、足跟着地期膝伸角>2.35°、最大膝屈角<45°、膝屈力矩峰值<0.65 N·m·kg^(-1)、踝跖屈力矩峰值<0.90 N·m·kg^(-1)时,高龄膝骨关节炎患者跌倒风险的预测值总分为409分,患者发生跌倒的概率为71.90%。受试者操作特征(receiver operating characteristics,ROC)曲线分析结果显示,预测模型区分度较高,训练集ROC曲线下面积为0.698(P=0.000),灵敏性71.43%,特异性65.89%;验证集ROC曲线下面积为0.699(P=0.000),灵敏性78.26%,特异性63.18%。Hosmer-Lemeshow拟合优度检验结果显示,预测模型拟合优度好(训练集:χ^(2)=0.748,P=0.504;验证集:χ^(2)=1.328,P=0.263)。临床决策曲线分析结果显示,训练集阈概率在9%~88%时净获益率高;验证集阈概率在11%~92%时净获益率高。结论:病程长、经常爬楼梯、疼痛重、足跟着地期踝背伸角增大、足跟着地期膝伸角增大、最大膝屈角减小、膝屈力矩峰值减小、踝跖屈力矩峰值减小均为高龄膝骨关节炎患者跌倒的独立危险因素;根据这些危险因素建立的跌倒风险预测模型,对于高龄膝骨关节炎患者的跌倒风险具有一定的预测价值。