Association of Multimodal Pain Control with Patient-Reported Outcomes in Children Undergoing Surgery

IntroductionOur aim was to describe practices in multimodal pain management at US children's hospitals and evaluate the association between non-opioid pain management strategies and pediatric patient-reported outcomes (PROs).MethodsData were collected as part of the 18-hospital ENhanced Recovery In CHildren Undergoing Surgery (ENRICH-US) clinical trial. Non-opioid pain management strategies included use of preoperative and postoperative non-opioid analgesics, regional anesthetic blocks, and a biobehavioral intervention. PROs included perioperative nervousness, pain-related functional disability, health-related quality of life (HRQoL). Associations were analyzed using multinomial logistic regression models.ResultsAmong 186 patients, 62 (33%) received preoperative analgesics, 186 (100%) postoperative analgesics, 81 (44%) regional anesthetic block, and 135 (73%) used a biobehavioral intervention. Patients were less likely to report worsened as compared to stable nervousness following regional anesthetic block (relative risk ratio [RRR]:0.31, 95% confidence interval [CI]:0.11–0.85), use of a biobehavioral technique (RRR:0.26, 95% CI:0.10–0.70), and both in combination (RRR:0.08, 95% CI:0.02–0.34). There were no associations of non-opioid pain control modalities with pain-related functional disability or HRQoL.ConclusionUse of postoperative non-opioid analgesics have been largely adopted, while preoperative non-opioid analgesics and regional anesthetic blocks are used less frequently. Regional anesthetic blocks and biobehavioral interventions may mitigate postoperative nervousness in children.Level of evidenceIII.     

The American Association for Thoracic Surgery (AATS) 2022 Expert Consensus Document: The use of mechanical circulatory support in lung transplantation

ObjectiveThe use of mechanical circulatory support (MCS) in lung transplantation has been steadily increasing over the prior decade, with evolving strategies for incorporating support in the preoperative, intraoperative, and postoperative settings. There is significant practice variability in the use of these techniques, however, and relatively limited data to help establish institutional protocols. The objective of the AATS Clinical Practice Standards Committee (CPSC) expert panel was to review the existing literature and establish recommendations about the use of MCS before, during, and after lung transplantation.MethodsThe AATS CPSC assembled an expert panel of 16 lung transplantation physicians who developed a consensus document of recommendations. The panel was broken into subgroups focused on preoperative, intraoperative, and postoperative support, and each subgroup performed a focused literature review. These subgroups formulated recommendation statements for each subtopic, which were evaluated by the entire group. The statements were then developed via discussion among the panel and refined until consensus was achieved on each statement.ResultsThe expert panel achieved consensus on 36 recommendations for how and when to use MCS in lung transplantation. These recommendations included the use of veno-venous extracorporeal membrane oxygenation (ECMO) as a bridging strategy in the preoperative setting, a preference for central veno-arterial ECMO over traditional cardiopulmonary bypass during the transplantation procedure, and the benefit of supporting selected patients with MCS postoperatively.ConclusionsAchieving optimal results in lung transplantation requires the use of a wide range of strategies. MCS provides an important mechanism for helping these critically ill patients through the peritransplantation period. Despite the complex nature of the decision making process in the treatment of these patients, the expert panel was able to achieve consensus on 36 recommendations. These recommendations should provide guidance for professionals involved in the care of end-stage lung disease patients considered for transplantation.     

端粒长度与认知障碍及其中药治疗的研究现况

认知障碍是指记忆、语言、理解和判断等一个或多个方面的功能障碍,包括轻度认知障碍和各种类型的痴呆症。痴呆症是认知障碍最严重的表现,是一种导致患者日常生活、社会交往和工作能力发生显著变化的综合征。阿尔茨海默病(AD)是最常见的痴呆症类型,其次是血管性痴呆(VD)和其他神经退行性痴呆[1]。已知年龄与认知功能的退化密切相关。     

基于文本挖掘和生物医学数据库的新型冠状病毒肺炎药物发现

目的 基于文本挖掘技术和生物医学数据库对新型冠状病毒肺炎（COVID-19）相关文献进行数据挖掘分析，探究COVID-19及其主要症状发热、咳嗽、呼吸障碍相关基因靶点，筛选潜在有效的化学药和中药。方法 使用GenCLiP 3网站获取COVID-19和其主要症状咳嗽、发热、呼吸障碍共4个关键词的共有靶点，在METASCAPE数据库中对其进行基因本体（GO）和通路富集分析，再利用String数据库和Cytoscape软件构建共有靶点的蛋白质相互作用网络，筛选获得核心基因，运用DGIdb数据库、SymMap数据库针对核心基因进行中西医治疗药物预测。结果 获得COVID-19及其主要症状共有基因靶点28个，其中有IL2、IL1B、CCL2等核心基因16个，使用DGIdb数据库筛选获得与16个关键靶点相互作用的化学药包括沙利度胺、来氟米特、环孢素等28种，中药包括虎杖、黄芪、芦荟等70味。结论 COVID-19及其主要症状的病理机制可能和CD4、KNG1、VEGFA等28个共有基因相关，可能通过介导TNF、IL-17等信号通路参与COVID-19病理过程。潜在有效药物可能通过作用相关靶点通路起到治疗COVID-19的作用。     

Out of the boxes,out of the silos: The need of interdisciplinary collaboration to reduce poor-quality medical products in the supply chain

In this paper, we argue that understanding and addressing the problem of poor-quality medical products requires a more interdisciplinary approach than has been evident to date. While prospective studies based on rigorous standardized methodologies are the gold standard for measuring the prevalence of poor-quality medical products and understanding their distribution nationally and internationally, they should be complemented by social science research to unpack the complex set of social, economic, and governance factors that underlie these patterns. In the following sections, we discuss specific examples of prospective quality surveys and of social science studies, highlighting the value of cross-sector partnerships in driving high-quality, policy-relevant research in this area.     

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。     

基于标准化患者法评价四川农村基层医生两种慢性病诊断准确性及其影响因素

目的 运用标准化患者法评估四川农村地区基层医生不稳定型心绞痛和2型糖尿病两种慢性病诊断准确性现状,探讨基层医生两种慢性病诊断准确性的主要影响因素,为提升基层医生两种慢性病诊断准确性提供科学依据。方法 采用多阶段随机整群抽样方法,抽取四川省自贡市5个区/县50个乡镇100个村为研究现场,以调查当日在岗的全科及内科医生作为研究对象。共进行两轮数据采集,第1轮采集样本乡镇卫生院和村卫生室医生的基本信息;第1轮调查完成1个月后,运用标准化患者法开展第2轮调查,收集农村基层医生对不稳定型心绞痛和2型糖尿病诊断结果信息。运用Logistic回归分析农村基层医生不稳定型心绞痛和2型糖尿病诊断准确性的影响因素。结果 共纳入172名农村基层医生,完成186次标准化患者访问,正确诊断率为48.39%。其中不稳定型心绞痛的正确诊断率为18.68%(17/91),2型糖尿病的正确诊断率为76.84%(73/95)。Logistic回归分析显示,具有执业医师资质的农村基层医生更有可能做出正确诊断(OR=4.857,95%CI=1.076~21.933,P=0.040)。农村基层医生在诊断过程中涉及的必要问诊和检查条目越多,做出正确诊断的概率越高(OR=1.627,95%CI=1.065~2.485,P=0.024)。与不稳定型心绞痛相比,农村基层医生对2型糖尿病做出正确诊断的可能性更高(OR=6.306,95%CI=3.611~11.013,P<0.001)。结论 四川农村基层医生不稳定型心绞痛和2型糖尿病诊断准确性整体较差,建议以基层医生慢性病诊断过程质量改善为突破口,提升基层医生执业水平,进而提高慢性病诊断准确性。