Country-based modelling of COVID-19 case fatality rate:A multiple regression analysis

BACKGROUND The spread of the severe acute respiratory syndrome coronavirus 2 outbreak worldwide has caused concern regarding the mortality rate caused by the infection.The determinants of mortality on a global scale cannot be fully understood due to lack of information.AIM To identify key factors that may explain the variability in case lethality across countries.METHODS We identified 21 Potential risk factors for coronavirus disease 2019(COVID-19)case fatality rate for all the countries with available data.We examined univariate relationships of each variable with case fatality rate(CFR),and all independent variables to identify candidate variables for our final multiple model.Multiple regression analysis technique was used to assess the strength of relationship.RESULTS The mean of COVID-19 mortality was 1.52±1.72%.There was a statistically significant inverse correlation between health expenditure,and number of computed tomography scanners per 1 million with CFR,and significant direct correlation was found between literacy,and air pollution with CFR.This final model can predict approximately 97%of the changes in CFR.CONCLUSION The current study recommends some new predictors explaining affect mortality rate.Thus,it could help decision-makers develop health policies to fight COVID-19.

干酪乳杆菌(Lactobacillus casei)FV006对发酵食品中生物胺的降解性能

为验证干酪乳杆菌(Lactobacillus casei)对生物胺的降解性能及潜在应用价值。本研究利用高效液相色谱法,探究该菌在液态培养条件下的降胺性能和应用于贵州6种市售发酵食品中的降胺效果。结果表明,在液态培养试验中该菌对组胺、亚精胺、苯乙胺、腐胺、尸胺、酪胺和色胺的降胺率分别为9.44%、23.39%、16.27%、13.68%、19.14%、18.16%和12.45%。此外,研究发现该菌对道菜中色胺的降胺率为56.68%;对豆瓣酱中尸胺、组胺和亚精胺的降胺率分别为68.06%、74.52%和85.82%;对酱油中色胺和尸胺的降胺率为66.75%%、81.53%;对泡菜中色胺的降胺率为45.74%;对鱼罐头中色胺、尸胺、组胺和亚精胺的降胺率分别为55.66%、63.92%、45.96%、52.62%;对香肠中色胺、组胺和亚精胺的降胺率分别为71.15%、56.26%、75.54%。研究还发现该菌既具有产生物胺的能力,也具有降解生物胺的能力,且对不同食品中同一种生物胺的降解具有差异性。本研究为干酪乳杆菌(Lactobacillus casei)在低胺发酵食品中的应用提供理论依据。

SEIHCRD Model for COVID-19 Spread Scenarios,Disease Predictions and Estimates the Basic Reproduction Number,Case Fatality Rate,Hospital,and ICU Beds Requirement

We have proposed a new mathematical method,the SEIHCRD model,which has an excellent potential to predict the incidence of COVID-19 diseases.Our proposed SEIHCRD model is an extension of the SEIR model.Three-compartments have added death,hospitalized,and critical,which improves the basic understanding of disease spread and results.We have studiedCOVID-19 cases of six countries,where the impact of this disease in the highest are Brazil,India,Italy,Spain,the United Kingdom,and the United States.After estimating model parameters based on available clinical data,the modelwill propagate and forecast dynamic evolution.Themodel calculates the Basic reproduction number over time using logistic regression and the Case fatality rate based on the selected countries’age-category scenario.Themodel calculates two types of Case fatality rate one is CFR daily,and the other is total CFR.The proposed model estimates the approximate time when the disease is at its peak and the approximate time when death cases rarely occur and calculate how much hospital beds and ICU beds will be needed in the peak days of infection.The SEIHCRD model outperforms the classic ARXmodel and the ARIMA model.RMSE,MAPE,andRsquaredmatrices are used to evaluate results and are graphically represented using Taylor and Target diagrams.The result shows RMSE has improved by 56%–74%,and MAPE has a 53%–89%improvement in prediction accuracy.

Case Fatality Rate of Severe Acute Respiratory Syndromes in Beijing

To describe the case fatality rate of SARS in Beijing. Methods Data of SARS cases notified from Beijing Center for Disease Control and Prevention （BCDC） and supplemented by other channels were collected. The data were analyzed by rate calculation. Results The case fatality rate of SARS in Beijing was 7.66%, and had an ascending trend while the age of cases was getting older, and a descending trend while the epidemic developmem. The case fatality rate in Beijing was lower than that in other main epidemic countries or regions. Conclusions The risk of death increases with the increment of age of SARS patients. Beijing is successful in controlling and treating SARS.

A Study on the Global Scenario of COVID-19 Related Case Fatality Rate, Recovery Rate and Prevalence Rate and Its Implications for India—A Record Based Retrospective Cohort Study

Importance: Corona virus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pandemic claiming millions of lives since the first outbreak was reported in Wuhan, China during December 2019. It is thus important to make cross-country comparison of the relevant rates and understand the socio-demographic risk factors. Methods: This is a record based retrospective cohort study. Table 1 was extracted from https://www.worldometers.info/coronavirus/ and from the Corona virus resource center (Table 2, Figures 1-3), Johns Hopkins University. Data for Table 1 includes all countries which reported >1000 cases and Table 2 includes 20 countries reporting the largest number of deaths. The estimation of CFR, RR and PR of the infection, and disease pattern across geographical clusters in the world is presented. Results: From Table 1, we could infer that as on 4th May 2020, COVID-19 has rapidly spread world-wide with total infections of 3,566,423 and mortality of 248,291. The maximum morbidity is in USA with 1,188,122 cases and 68,598 deaths (CFR 5.77%, RR 15% and PR 16.51%), while Spain is at the second position with 247,122 cases and 25,264 deaths (CFR 13.71%, RR 38.75%, PR 9.78%). Table 2 depicts the scenario as on 8th October 2020, where-in the highest number of confirmed cases occurred in US followed by India and Brazil (cases per million population: 23,080, 5007 & 23,872 respectively). For deaths per million population: US recorded 647, while India and Brazil recorded 77 and 708 respectively. Conclusion: Studying the distribution of relevant rates across different geographical clusters plays a major role for measuring the disease burden, which in-turn enables implementation of appropriate public healthcare measures.

儿童急性坏死性脑病26例临床特征及预后分析

目的总结儿童急性坏死性脑病(ANEC)的临床特征、治疗过程和预后。方法回顾性分析2016年6月至2022年12月确诊ANEC患儿的临床资料。对存活患儿进行电话随访,应用儿童整体表现分类量表(POPC)评估患儿生存质量。结果共纳入26例ANEC患儿,男女比例为1.6∶1,中位年龄36.0(23.0~69.0)个月。发病季节以夏季常见(42.3%),其次为冬季(34.6%);前驱感染以流感病毒感染多见(34.6%),其次为人类疱疹病毒6B型及新型冠状病毒。所有患儿均有发热伴不同程度意识障碍,24例出现惊厥。神经影像学以对称性丘脑受累(100%)为典型改变,多伴有基底节区(50.0%)、脑干(61.5%)、小脑(26.9%)等部位受累。23例患儿接受甲基泼尼松龙激素冲击治疗,住院病死率为23.1%(6/26),出院6个月后累积病死率为30.7%(8/26)。6个月后随访到14例存活患儿,11例接受康复治疗,其中POPC评估2分1例,3分4例,4分6例,5分1例,6分2例。3例新型冠状病毒感染后ANEC患儿3个月随访POPC评估结果为2分2例,6分1例。结论华南地区ANEC于夏季和冬季高发,新型冠状病毒感染可诱发ANEC;临床表现为发热、抽搐、意识障碍三联征,典型影像学改变为双侧丘脑受累。早期免疫治疗及综合康复训练有助于减少神经系统后遗症的严重程度。

A New Method to Predict Erythrocyte Sedimentation Rate with Natural Geographical Factors and Location by Case-based Reasoning: A Case Study of China

Reference values of erythrocyte sedimentation rate(ESR)are the key to interpret ESR blood test in clinic.The common local reference ESR values are more accuracy in blood test that are established with natural geographical factors by using the multiple linear regression(MLR)model and the artificial neural network(ANN).These knowledge-based methods have limitations since the knowledge domains of ESR and natural geographical factors are limited.This paper presents a new cases-depended model to establish reference ESR values with natural geographical factors and location using case-based reasoning(CBR)since knowledge domain of ESR and geographical factors is weak.Overall 224 local normal ESR values of China that calculated from 13623 samples were obtained,and the corresponding natural geographical factors and location that include altitude,sunshine hours,relative humidity,temperature,precipitation,annual temperature range and annual average wind speed were obtained from the National Geomatics Center of China.CBR was used to predict the unseen local reference ESR values with cases.The average absolute deviation(AAD),mean square error(MSE),prediction accuracy(PA),and Pearson correlation coefficient(r)between the observed and estimated data of proposed model is 33.07%,9.02,66.93% and 0.78,which are better than those of ANN and MLR model.The results show that the proposed model provides higher prediction accuracy than those of the artificial neural network and multiple linear regression models.The predicted values are very close to the observed values.Model results show significant agreement of cases data.Consequently,the model is used to predict the unseen local reference ESR with natural geographical factors and location.In spatial,the highest ESR reference areas are distributed in the southern-western district of China that includes Sichuan,Chongqing,Guangxi and Guizhou provinces,and the reference ESR values are greater than 23 mm/60 min.The higher ESR reference values are distributed in the middle part and northern-eastern of China which include Hubei,Henan,Shaanxi,Shanxi,Jilin and Heilongjiang provinces,and the reference ESR values are greater than 18 mm/60min.The lowest ESR reference values are distributed in the northern-western of China that includes Tibet and Xinjiang,and the reference ESR values are lower than 5 mm/60min.

全球COVID-19疫情主要预测模型比较分析

目的新冠感染病死率预测对于深入理解新冠病毒严重性、合理配置医疗资源及开展针对性防疫策略有重大意义。方法本研究依据新冠病毒变异优势株,将疫情发展划分四个时期,选取美国、印度、巴西、墨西哥、秘鲁、中国六个国家以及全球平均水平的病死率为研究对象。运用灰色模型、指数平滑模型、ARIMA模型、支持向量机、Prophet和LSTM模型六个模型进行拟合预测,探讨各模型的优缺点和适用性,选取效果最优的模型对全球和重点国家的病死率进行预测。结果模型比较显示多种模型各有优缺点,经预测,多数国家的累计确诊人数和累计死亡人数增长速度减缓,发展趋势逐渐平稳。结论传统时间序列模型适于发展趋势平稳、有限样本的预测;而机器学习模型更适用于波动型变化数据,可进行大样本预测,进一步外推,运用到其他卫生领域的研究。

某三级专科医院DRG分组高倍率病例费用影响因素比较分析

[目的]基于天津市某三级专科医院DRG分组数据探讨专科医院DRG组高倍率病例影响因素,为医院进行有针对性的成本控制提供参考。[方法]收集某专科医院2022年10月1日-2023年9月30日上传的医保患者医保结算清单经分组器分组后正常入组数据,按照进入天津市医保局DRG分组器分组后的全市付费次均费用、平均住院天数计算入组病例费用的倍率,应用logistic回归分析高倍率病例的影响因素,采用灰色关联分析法分析高倍率病例各分项费用与住院总费用的关联度。[结果]入组病例总数为7829例,其中高倍率病例673例,占8.60%。Logistic回归结果显示,DRG合并并发症、15~60岁、非医嘱离院、实际住院天数长是高倍率病例产生的影响因素(P<0.05)。灰色关联结果显示,在10个高倍率的DRG组里,有5个DRG组的诊断费与其呈现最强的相关性,有3个DRG组的药品费与其呈现最强的相关性,有2个DRG组的综合服务费与其呈现最强的相关性。[结论]药品费、诊断费、综合服务费、合并并发症、15~60岁及住院天数长与高倍率住院费用的产生显著相关,是医院进行有指向性成本控制的重要因素。

Subgroup comparison of COVID-19 case and mortality with associated factors in Mississippi: findings from analysis of the first four months of public data

We compared subgroup differences in COVID-19 case and mortality and investigated factors associated with case and mortality rate(MR)measured at the county level in Mississippi.Findings were based on data published by the Mississippi State Department of Health between March 11 and July 16,2020.The COVID-19 case rate and case fatality rate(CFR)differed by gender and race,while MR only differed by race.Residents aged 80 years or older and those who live in a non-metro area had a higher case rate,CFR,and MR.After controlling for selected factors,researchers found that the percent of residents who are obese,low income,or with certain chronic conditions were associated with the county COVID-19 case rate,CFR,and/or MR,though some were negatively related.The findings may help the state to identify counties with higher COVID-19 case rate,CFR,and MR based on county demographics and the degree of its chronic conditions.

2018—2022年某综合性三甲医院住院死亡病例分析

目的 分析2018—2022年某综合性三甲医院住院患者死亡病例特征,为科学合理配置医疗资源,加强医疗质量管理提供参考。方法 从该院病案信息系统中提取2018年1月1日至2022年12月31日的所有出院患者信息,对出院患者和死亡病例总数、年龄、性别分布以及疾病诊断等,采用Excel 2007和SPSS 18.0软件进行数据整理和统计分析。结果 675例死亡病例中,男性病例443例(65.63%),女性232例(34.37%),住院患者病死率0.64%;死亡原因居前3位的疾病为循环系统疾病、呼吸系统疾病、肿瘤,分别占总死亡病例数的28.44%、28.30%和27.56%;死亡病例男女性别比1.91∶1,病死率男性高于女性,差异有统计学意义(χ2=46.068,P<0.001)。年龄越大,病死率越高,50岁以上病死率迅速上升。结论 医院住院患者病死率总体较低,老年人是该院的死亡高危人群,循环系统疾病、恶性肿瘤和呼吸系统疾病是最主要的死亡原因。在医疗工作中,应根据患者年龄、性别、死亡高发病种等特点,科学合理配置医疗资源,降低住院患者病死率。

2009-2023年天津市某儿童医院住院儿童死亡病例分析

目的分析2009—2023年天津市某儿科医院住院儿童死亡病例特点。方法收集天津市某儿童医院2009—2023年住院儿童的病案首页信息,分析2009—2013年、2014—2018年、2019—2023年三个时间段死亡病例的性别、年龄、疾病系统及死亡病种情况。结果2009—2023年,住院患儿共678145例,其中876例死亡,死亡率为0.13%;三个时间段的死亡率分别为0.28%、0.16%、0.06%,整体呈递减趋势(χ^(2)=383.962,P<0.01)。男性儿童死亡率(0.12%)显著低于女性儿童死亡率(0.15%)(χ^(2)=303.785,P<0.01)。婴儿期死亡人数最多(263例),青春期死亡人数最少(61例)。死亡疾病系统顺位在三个时间段的变化方面,循环系统疾病从第六位上升至第三位,肿瘤从第九位上升至第六位,先天性畸形、变形和染色体异常从第三位降至第八位。前十位死亡病种中,重症肺炎在三个时间段中均排名第一;急性淋巴细胞白血病顺位由2009—2013年的第九位上升至2019—2023年的第三位。新生儿期排名第一的死亡病种为新生儿呼吸衰竭,婴儿期、幼儿期、学龄前期及学龄期排名第一的死亡病种均为重症肺炎,青春期排名第一的死亡病种为海绵窦脓肿。结论2009—2023年间天津市住院儿童死亡率明显下降,儿科临床和预防工作应继续重点关注婴儿期的重症肺炎、脓毒血症患儿,以及海绵窦脓肿等病种,同时应加强对循环系统、某些传染病和寄生虫病、意外伤害、恶性肿瘤的预防和控制,以有效降低住院患儿死亡率。

DRGs付费下高倍率病例影响因素分析——以精神专科病组为例

[目的]分析精神专科高倍率的住院病例的影响因素。[方法]对某精神专科医院2022年1-12月出院病例通过CHS-DRG(1.1)分组器反馈的高倍率病例进行统计分析,并组织专家对问题病例进行讨论。[结果]2022年的12,382例精神科病例中有229例高倍率病例,其中:电休克MECT未细分组49例(21.40%)、青少年多手段治疗11例(4.80%)、老年患者治疗严重并发症和合并症6例(2.62%)、住院时长超60天64例(27.95%)、共病患者联合治疗15例(6.55%)、分组方案不合理82例(35.81%)、编码导致入组错误2例(0.87%)。[结论]精神专科高倍率病例影响因素主要为:测算存在来源失真、精神专科的合并症未得到体现、MECT组亏损大、儿童及青少年精神障碍治疗难度与成年期有显著差异、部分病组分组不合理和编码质量等。

影响热射病患者90 d预后的危险因素分析

目的探讨热射病患者90 d预后的危险因素。方法回顾性分析2018年6月至2022年8月该院重症医学科收治的热射病患者89例,根据90 d死亡情况分为存活组(62例)和死亡组(27例),比较2组患者年龄、入院时体温及心率、降温时间、炎症及器官功能障碍的实验室数据、急性生理和慢性健康状况Ⅱ评分、序贯器官衰竭估计(SOFA)评分、格拉斯哥昏迷评分法评分等。结果89例患者中90 d内死亡27例(30.3%)。降温时间、入院时心率、SOFA评分是影响患者生存的独立危险因素(风险比=6.230、1.738、1.042,95%可信区间:2.561~14.521、1.026~2.114、1.011~1.427,P=0.004、0.002、0.023)。降温时间、入院时心率、SOFA评分联合预测热射病患者90 d病死率的受试者工作特征曲线下面积为0.993(95%可信区间:0.976~1.000,P<0.001),灵敏度为1.000,特异度为0.933。结论降温时间、入院时心率、SOFA评分是影响热射病患者90 d生存的因素,3个指标可联合使用预测患者90 d病死率和不良预后。

DRG高倍率病例费用结构分析及相关影响因素研究

目的分析疾病诊断相关分组(diagnosis related groups,DRG)高倍率病例费用结构,研究影响住院费用的相关因素,合理利用DRG评价指标,为公立医院精细化管理和高质量发展提供参考。方法以2021年1月—2022年6月广西某三甲医院为样本,描述分析高倍率病例特征,运用SPSS 26.0统计学分析各因素对费用的影响。结果数据来源为从医保平台选取2021年1月—2022年6月DRG终审数据,高倍率病例6217例,占比5.76%,内科组与外科组在高倍率病例占比比较,差异无统计学意义(P>0.05)。在单因素分析中,权重、科室类别对高倍率病例住院费用有显著影响(P<0.05),而医保类别与高倍率费用无关(P>0.05)。结论权重递增结合费用倍数递减的方式制定高倍率病例认定标准是相对科学合理的,但同时应加大对违规入组病例审核力度,重视目前实际付费阶段存在的问题,转变传统医保按项目付费观念,多种付费方式相结合,合理利用DRG评价指标,以更好适应DRG支付方式改革。

核电仪控系统测试用例优先级技术研究

冗余通道设计是反应堆安全级仪控系统提高可靠性的一种常用技术手段。在安全级仪控系统测试工作中,测试阶段通常面临着交货节点的压力,会导致测试时间十分紧迫。为提升测试效率,提出了一种测试执行优化方案,建立了以异常检测率、严重异常检测能力和代码覆盖率为影响因素的优先级计算方法,根据不同测试目标调整各影响因素权重。以缺陷检测加权百分比(APFD)这一测试指标定量描述测试执行效果,验证了测试用例优先级方法的有效性。所述方案在回归测试以及仪控系统冗余通道测试中具有良好的应用前景。

中国建立技术类知识产权上诉案件强制调解制度之质疑——基于美国联邦巡回上诉法院相关经验的检视

中国最高人民法院集中审理技术类知识产权上诉案件后,“案多人少”困境逐步显现,参照美国经验建立强制调解制度的对策受到立法机关、学界关注。美国联邦巡回上诉法院建立强制调解制度曾面临重大争议,该院所披露调解率因统计口径偏差具有误导性。依照中国常用统计口径重新统计的结果表明,该院知识产权上诉案件强制调解情况较差且逐年恶化,显著低于中国现有制度成效。随着中国知识产权诉讼环境逐年改善,上诉案件中当事人调解动机难以增强,实施强制调解很难取得良好实效。以美国“自由裁量型”强制调解制度为蓝本的制度构建方案,缺乏明确的案件筛选标准,有悖于中国沿袭的“规范出发型”大陆法系民事诉讼立法传统,不契合目前中国民事调解制度发展阶段,故现阶段中国不宜建立技术类知识产权上诉案件强制调解制度。

以苏州为例的公交专用道评价方法研究

公共汽电车交通(简称公交)以其灵活、大运量以及广泛布设的特征,成为公共交通的重要组成部分。但是,在日益拥堵的城市环境中,公交面临日趋严峻的效率和可靠性挑战。设置公交专用道是保障公交优先、提高公交服务品质的关键措施,为公交车减少不必要的延误。如何准确评价公交专用道的效率、保障其适用性,成为公交专用道发展中的重要问题。从公交专用道的利用率与公交运行速度提升率两个角度,建立公交专用道的评价指标,评价公交专用道的布设效果。研究可为规范公交专用道的设计方法和精准量化公交专用道的布设效果,提供理论与方法依据。

解冻卵裂期胚胎养成囊胚行植入前遗传学检测二次冷冻复苏移植后临床结局

目的 回顾性评估解冻卵裂期胚胎养成囊胚后进行活检,再次冷冻移植后临床及新生儿结局,以期为临床医生和患者提供参考数据。方法 收集2017年1月至2022年10月于西北妇女儿童医院生殖中心接受解冻卵裂期胚胎养成囊胚后进行活检,再次解冻移植治疗的患者的冻融胚胎移植周期为实验组(n=13),并将女方新鲜周期取卵时年龄、移植囊胚级别、胚胎植入前遗传学诊断的指证以及分类作为匹配因素,按照1∶3配对,选取同周期新鲜囊胚活检、解冻后移植的患者作为对照组(n=39)。比较两组患者的临床基线资料、妊娠结局以及新生儿结局。结果 两组患者临床基本资料、妊娠率以及活产率均无统计学差异(P>0.05),两组产科及新生儿结局亦无显著性差异(P>0.05)。两组患者均未报道重大产科并发症和新生儿畸形。结论 将冻存的卵裂期胚胎解冻后培养至囊胚期进行活检,行胚胎植入前遗传学检测,冷冻后再次复苏行冻融移植周期的妊娠率、活产率及新生儿结局与新鲜囊胚活检后进行冻融移植无明显差异,可以为患者提供更多的选择。