1401例超长住院日患者分布与影响因素分析

目的分析超长住院患者分布及影响因素,探讨减少超长住院日的措施。方法从江苏省某三甲医院病案管理系统中调取2020年1月1日-2020年12月31日134016例出院患者的住院病案首页资料,对住院时间≥30天的1401例超长住院患者的分布特征进行统计描述,采用Logistic回归模型分析超长住院日的影响因素。结果2020年全院平均住院日为7.13天,其中超长住院患者平均住院日为41.85天。超长住院患者以60岁以上年龄组最多(39.61%);出院科室主要分布在血液科(42.18%)、普通外科(11.85%)、骨科(7.49%)等;疾病类别主要为肿瘤(47.32%)、影响健康状态和与保健机构接触的因素(10.56%)、循环系统疾病(7.07%)等;多因素Logistic回归结果显示,男性(OR=1.188)、离院方式为非医嘱离院或其他(OR=2.046)和死亡病例(OR=3.362)是超长住院的危险因素。结论控制超长住院日对平均住院日影响显著,医院应加强重点人群、重点科室和重点病种管理提高诊疗管理水平,缩短平均住院日。     

Utility of Differential White Cell Count and Cell Population Data for Ruling Out COVID-19 Infection in Patients With Community-Acquired Pneumonia

IntroductionThe main aim of this study was to assess the utility of differential white cell count and cell population data (CPD) for the detection of COVID-19 in patients admitted for community-acquired pneumonia (CAP) of different etiologies.MethodsThis was a multicenter, observational, prospective study of adults aged ≥18 years admitted to three teaching hospitals in Spain from November 2019 to November 2021 with a diagnosis of CAP. At baseline, a Sysmex XN-20 analyzer was used to obtain detailed information related to the activation status and functional activity of white cells.ResultsThe sample was split into derivation and validation cohorts of 1065 and 717 patients, respectively. In the derivation cohort, COVID-19 was confirmed in 791 patients and ruled out in 274 patients, with mean ages of 62.13 (14.37) and 65.42 (16.62) years, respectively (p < 0.001). There were significant differences in all CPD parameters except MO-Y. The multivariate prediction model showed that lower NE-X, NE-WY, LY-Z, LY-WY, MO-WX, MO-WY, and MO-Z values and neutrophil-to-lymphocyte ratio were related to COVID-19 etiology with an AUC of 0.819 (0.790, 0.846). No significant differences were found comparing this model to another including biomarkers (p = 0.18).ConclusionsAbnormalities in white blood cell morphology based on a few cell population data values as well as NLR were able to accurately identify COVID-19 etiology. Moreover, systemic inflammation biomarkers currently used were unable to improve the predictive ability. We conclude that new peripheral blood biomarkers can help determine the etiology of CAP fast and inexpensively.     

红外光谱数据融合对栽培滇重楼产地鉴别*

目的 多样的环境因素使得不同产地栽培滇重楼的化学成分也丰富多样，不同居群栽培滇重楼的甾体皂苷类成分具有很大的差异，多源数据融合分析能更全面的表征药材化学信息，建立一个高效而准确的产地鉴别模型，为其资源合理开发利用提供依据。方法 以来自云南和四川的8个产地（保山、楚雄、大理、红河、丽江、成都、文山、玉溪）共366份栽培滇重楼根茎为实验材料，采集其傅里叶变换近红外光谱（FT-NIR）和衰减全反射-傅里叶变换中红外光谱（ATR-FTMIR）数据。采用Kennard-Stone算法将不同产地的样品分为2/3的训练集和1/3的预测集，基于4种特征变量提取方法（CARS、VIP、SPA、SO-Covsel）结合2种数据融合策略（低级数据融合和中级数据融合），建立偏最小二乘产地判别分析模型。根据模型参数交叉验证均方根误差（RMSECV）和预测均方根误差（RMSEP）评估模型的稳定性，模型训练集和预测集准确率（ACC）评估模型分类性能。结果 近红外光谱和中红外光谱均能反应不同产地栽培滇重楼的化学成分差异，在中级数据融合中，基于VIP和SPA提取的特征变量建立的模型正确率均大于94%。相较于中级数据融合，低级数据融合模型得到了最为满意的结果，其预测集分类正确率达到100%。结论 根据近红外和中红外数据建立的低级数据融合PLS-DA模型，能够用于栽培滇重楼的产地鉴别分析。     

会所康复模式在女性精神分裂症恢复期病人中的应用

目的:探讨会所康复模式在女性精神分裂症恢复期病人中的应用效果。方法:选取2019年2月—2020年3月精神科收治的100例女性精神分裂恢复期病人作为研究对象,按随机数字表法分为对照组、观察组各50例,对照组采取常规康复治疗,观察组在常规康复治疗基础上应用会所多维度康复治疗模式。采用阳性和阴性症状量表(PANSS)、疾病家庭负担量表(FBS)、日常生活能力量表(ADL)、生活满意度指数B量表(LSIB)评价两组病人干预前、干预3个月、干预6个月精神症状、家庭负担、日常生活能力、生活自理能力。结果:两组病人干预3个月、干预6个月PANSS、FBS、ADL及LSIB评分比较差异有统计学意义(P<0.05);两组组内干预前后PANSS、FBS、ADL及LSIB评分比较差异有统计学意义(P<0.05)。结论:女性精神分裂症病人在恢复阶段应用会所康复模式进行干预可改善其精神症状,缓解其家庭负担,调节其日常生活能力和生活自理能力,提升其生活满意度。     

Predicting Survival for Chimeric Antigen Receptor T-Cell Therapy: A Validation of Survival Models Using Follow-Up Data From ZUMA-1

ObjectivesSurvival extrapolation for chimeric antigen receptor T-cell therapies is challenging, owing to their unique mechanistic properties that translate to complex hazard functions. Axicabtagene ciloleucel is indicated for the treatment of relapse or refractory diffuse large B-cell lymphoma after 2 or more lines of therapy based on the ZUMA-1 trial. Four data snapshots are available, with minimum follow-up of 12, 24, 36, and 48 months. This analysis explores how survival extrapolations for axicabtagene ciloleucel using ZUMA-1 data can be validated and compared.MethodsThree different parametric modeling approaches were applied: standard parametric, spline-based, and cure-based models. Models were compared using a range of metrics, across the 4 data snapshot, including visual fit, plausibility of long-term estimates, statistical goodness of fit, inspection of hazard plots, point-estimate accuracy, and conditional survival estimates.ResultsStandard and spline-based parametric extrapolations were generally incapable of fitting the ZUMA-1 data well. Cure-based models provided the best fit based on the earliest data snapshot, with extrapolations remaining consistent as data matured. At 48 months, the maximum survival overestimate was 8.3% (Gompertz mixture-cure model) versus the maximum underestimate of 33.5% (Weibull standard parametric model).ConclusionsWhere a plateau in the survival curve is clinically plausible, cure-based models may be helpful in making accurate predictions based on immature data. The ability to reliably extrapolate from maturing data may reduce delays in patient access to potentially lifesaving treatments. Additional research is required to understand how models compare in broader contexts, including different treatments and therapeutic areas.     

我国家庭医生签约服务政策执行的制约因素与优化路径：基于史密斯政策执行过程模型

深化家庭医生签约服务是深化医药卫生体制改革、强化基层医疗卫生服务、实现"健康中国"战略目标的重要选择，也是当前更好维护人民群众健康的重要途径。为有效推进签约服务工作，国家陆续推出各项政策，全国各地也在积极进行实践探索，成效明显。但是，签约服务仍面临诸多问题，其中"执行难"是签约服务深度推进的一大困境。通过史密斯政策执行过程模型，结合签约服务政策执行过程，发现签约服务仍存在法治性不足、政策执行人员水平不高、激励不足、政策环境影响等诸多制约因素。因此，需要从法律和制度方面进行顶层设计、提升执行人员素质和职业认同、建立医患互信、优化政策执行环境等角度进行政策创新，探索家庭医生签约服务可持续发展的路径。     

我国老年人认知水平变化轨迹及其分化

目的 探究影响我国老年人认知水平的变化趋势，分离出年龄、队列效应。方法 基于CLHLS（2002—2018）多重队列追踪数据，以Stata16.0软件为工具，运用分层生长曲线模型进行统计分析。结果 本研究发现，个体行为生活方式、社会经济地位、性别、慢性病数量对认知水平均具有统计学意义；年龄、队列对认知水平的变化具有独立效应；随着年龄的增长，我国老年人认知水平下降，认知水平的城乡、性别差异明显；较年轻出生队列的老年人认知水平较好，认知水平的城乡差异随着队列的年轻化而变大，性别差异在较年轻队列有略微缩小的趋势。结论 影响认知水平因素复杂，认知障碍会增加医疗成本及照护负担，因此需准确把握老年认知水平的变化规律与作用路径，从而为卫生服务、养老保障、长期医疗照护的资源配置提供科学依据。     

Deepm5C: A deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy

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Parks/sports facilities in local communities and the onset of functional disability among older adults in Japan: The J-shaped spatial spillover effects

We examined the associations between parks/sports facilities in local communities and the onset of functional disability among Japanese older adults. We further investigated the spatial spillover effects of parks/sports facilities in 1st-, 2nd-, and 3rd-degree neighboring communities. Data on the onset of functional disability, including date of onset, sex, age, and address (school district) of all older adults aged 65 years and older living in Kobe City were obtained from the public long-term care insurance database (163,348 men [190,831 person-year] and 200,443 women [230,464 person-year]). Multilevel proportional hazard regression analyses showed that the number of parks and sports facilities were negatively associated with the onset of functional disability among men. In particular, these associations were stronger for the adjacent district than for individuals’ living districts. Our results imply that involving multiple neighboring communities as the intervention unit is effective when utilizing community built environments for long-term care prevention in men.