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.     

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。     

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.     

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。     

女性压力性尿失禁风险预测的研究进展

综述女性压力性尿失禁(stress urinary incontinence,SUI)风险预测的研究进展。指出女性SUI风险预测相关文献普遍存在风险预测工具和指标缺乏临床大样本验证,指标、纳入人群不统一的现象,风险预测模型存在构建过程未按报告规范进行,未进行完整的模型验证以及模型性能评价指标不规范的情况。未来研究可以在现有风险预测工具或模型的基础上进行改进、完善,以期为女性SUI风险预测提供参考。     

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.