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1.
《Archivos de bronconeumología》2022,58(12):802-808
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. 相似文献
2.
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。 相似文献
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5.
《Value in health》2022,25(3):350-358
ObjectivesWe propose a framework of health outcomes modeling with dynamic decision making and real-world data (RWD) to evaluate the potential utility of novel risk prediction models in clinical practice. Lung transplant (LTx) referral decisions in cystic fibrosis offer a complex case study.MethodsWe used longitudinal RWD for a cohort of adults (n = 4247) from the Cystic Fibrosis Foundation Patient Registry to compare outcomes of an LTx referral policy based on machine learning (ML) mortality risk predictions to referral based on (1) forced expiratory volume in 1 second (FEV1) alone and (2) heterogenous usual care (UC). We then developed a patient-level simulation model to project number of patients referred for LTx and 5-year survival, accounting for transplant availability, organ allocation policy, and heterogenous treatment effects.ResultsOnly 12% of patients (95% confidence interval 11%-13%) were referred for LTx over 5 years under UC, compared with 19% (18%-20%) under FEV1 and 20% (19%-22%) under ML. Of 309 patients who died before LTx referral under UC, 31% (27%-36%) would have been referred under FEV1 and 40% (35%-45%) would have been referred under ML. Given a fixed supply of organs, differences in referral time did not lead to significant differences in transplants, pretransplant or post-transplant deaths, or overall survival in 5 years.ConclusionsHealth outcomes modeling with RWD may help to identify novel ML risk prediction models with high potential real-world clinical utility and rule out further investment in models that are unlikely to offer meaningful real-world benefits. 相似文献
6.
目的:探索何晓晖教授治疗慢性胃炎并发胃黏膜肠上皮化生及异型增生的用药规律。方法:收集何晓晖教授治疗慢性胃炎并发胃黏膜肠上皮化生及异型增生的中药处方117张,将数据输入古今医案云平台(V2.3.9),经标准化后创建一个新医案库。结果:117张处方中,高频药物为蒲公英、黄连、海螵蛸等;高频药物类别以补虚药、活血化瘀药、清热药的使用最多;药性以寒(寒与微寒)、温(温与微温)为主,药味以苦、甘为多,药物多归脾、胃经;聚类分析显示有4个组别;复杂网络分析得到11味核心药物。结论:何教授治疗慢性胃炎并发胃黏膜肠上皮化生及异型增生以“衡”为法,从虚、毒、瘀、痰论治,通过健脾益胃、燮理纳运、清热燥湿解毒、活血化瘀消癥、化痰散结等标本兼顾,最终逆转胃黏膜上皮肠化与异型增生的病理改变,疗效肯定。 相似文献
7.
随着人类基因组测序、生物大数据信息分析、分子病理检测和人工智能辅助病理诊断等技术进步及其应用, 临床医学发展迈向精准诊疗时代。这一时代背景下, 传统诊断病理学迎来前所未有的历史机遇, 正在向"下一代诊断病理学(next-generation diagnostic pathology)"迈进。下一代诊断病理学以病理形态和临床信息为诊断基础, 以分子检测与生物信息分析、智慧制样与流程质控、智能诊断与远程会诊、病灶活体可视化与"无创"病理诊断等创新前沿交叉技术为主要特征, 以多组学和跨尺度整合诊断为病理报告内容, 实现对疾病的"最后诊断", 并预测疾病演进和结局、建议治疗方案和评估治疗反应, 形成新的疾病诊断"金标准"。未来, 需要激发病理学科创新活力, 加快下一代诊断病理学成熟和应用, 重塑病理学科理论和技术体系, 发挥诊断病理学在疾病"防、诊、治、养"等过程中的重要作用, 促进临床医学进一步发展, 服务健康中国战略。 相似文献
8.
Objective
The aim of the study was to estimate the effect of the state-based reinsurance programs through the section 1332 State Innovation Waivers on health insurance marketplace premiums and insurer participation.Data Source
2015 to 2022 Robert Wood Johnson Foundation Health Insurance Exchange Compare Datasets.Study Design
An event study difference-in-differences (DD) model separately for each year of implementation and a synthetic control method (SCM) are used to estimate year-by-year effects following program implementation.Data Collection/Extraction Methods
Not applicable.Principal Findings
Reinsurance programs were associated with a decline in premiums in the first year of implementation by 10%–13%, 5%–19%, and 11%–17% for bronze, silver, and gold plans (p < 0.05). There is a trend of sustained declines especially for states that implemented their programs in 2019 and 2020. The SCM analyses suggest some effect heterogeneity across states but also premium declines across most states. There is no evidence that reinsurance programs affected insurer participation.Conclusion
State-based reinsurance programs have the potential to improve the affordability of health insurance coverage. However, reinsurance programs do not appear to have had an effect on insurer participation, highlighting the need for policy makers to consider complementary strategies to encourage insurer participation. 相似文献9.
10.
[目的] 探讨鲁科达教授治疗肾性蛋白尿的用药规律,归纳总结其组方经验,以供临床参考。[方法] 收集2018年1月至2020年12月鲁教授中医门诊的肾性蛋白尿医案,以Microsoft Excel 2019软件将处方信息转化为可分析的结构化数据,并建立相关数据库,利用频次统计分析、关联规则分析、聚类分析对高频药物、四气五味归经、高频药对、核心组方进行数据挖掘。[结果] 共纳入肾性蛋白尿病例691则,处方3 750首,共涉及中药261味,将使用频次前34味的药物作为高频药物,如黄芪、党参、白术、山药、茯苓、山茱萸、甘草、薏苡仁、地黄、川牛膝、青风藤、地龙等。利用关联规则分析得到高频药对20组,通过聚类分析演化得到4个核心组方。[结论] 鲁教授治疗肾性蛋白尿以补肾健脾、清热利湿、消瘀泄浊为主。 相似文献