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.     

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。     

医院信息化平台住院陪护人员管理功能的开发与应用

目的 探讨医院信息系统中增加住院陪护管理功能的应用效果。方法 基于互联网医院、智慧医院等信息系统，开发信息化住院陪护管理功能，包括流行病学史调查、免费核酸申请、电子陪护证办理、体温监测登记及上报和统计查询。该功能与医院智慧护理链接后全院应用。比较功能应用前和应用后的遵医嘱一患一陪达标率、有效陪护证达标率、体温监测并登记日上报达标率和陪护证使用追溯率，评价护士和管理者疫情防控管理的人均耗时以及对该管理功能的满意度。结果 应用信息化陪护管理功能后，一患一陪达标率、有效陪护证达标率、体温监测并登记日上报达标率和陪护证使用追溯率显著高于应用前（均P＜0.05）；护士陪护管理人均耗时从（554.13±30.77）s降至（311.67±21.54）s（P＜0.05）；护士和管理者对该信息化陪护管理功能的满意度显著提高（均P＜0.05）。结论 信息化住院陪护管理功能的应用有效提升了疫情期间陪护的管理质量和管理效率，提高了一线护士和管理者的满意度。     

Policy Analysis for Prevention and Control of Influenza in Aged Care

ObjectiveThis study aimed to analyze national influenza infection control policy documents within aged care settings by identifying the consistencies, inconsistencies, and gaps with the current evidence and by evaluating methodological quality. Aged care providers can use these findings to identify their policy documents' strengths and weaknesses.DesignA quality and content analysis of national level policy documents.Setting and ParticipantsAged care settings rely on national agencies' policy recommendations to control and prevent outbreaks. There is limited research on the effectiveness of control measures to prevent and treat influenza within aged care settings. Because of the complexities around aged care governance, the primary responsibility in developing a comprehensive facility-level, infection-prevention policy, falls to the providers.MethodsThe analysis was conducted using the (1) International Appraisal of Guidelines, Research and Evaluation assessment tool, containing 23 items across 6 domains; and the (2) Influenza Related Control Measures in Aged Care settings checklist, developed by the authors, with 82 recommendations covering: medical interventions, nonmedical interventions, and physical layout.ResultsThere were 19 documents from 9 different high-income countries, with a moderately high methodological quality in general. The quality assessment's average score was 40.2% (95% CI 31.9%–44.7%). “Stakeholder involvement” ranked third, and “Editorial independence” and “Rigor of development” had the lowest average scores across all domains. The content analysis' average score was 37.2% (95% CI 10.5%–21.5%). The highest scoring document (59.1%) included term definitions, cited evidence for recommendations, and clear measurable instructions. “Physical Layout” had the least coverage and averaged 21.9% (95% CI 4.2%–37.5%), which shows a substantial gap in built environment recommendations.Conclusions and ImplicationsExisting policy documents vary in their comprehensiveness. The higher scoring documents provide an ideal model for providers. The checklist tools can be used to assess and enhance documents. Further research on document end-user evaluation would be useful, as there is room for improvement in methodological quality and coverage of recommendation coverage, especially related to physical layout.     

The National Home-Based Primary Care Learning Network: A Practice-Based Quality Improvement and Research Network

Home-based primary care (HBPC) provides interdisciplinary, comprehensive care at home for homebound older adults and has been largely excluded from the national conversation on care quality and quality improvement. In this Pragmatic Innovations article, we describe the work of the National HBPC Learning Network (LN), which focuses on fostering a continuous learning culture among HBPC practices to improve practice quality, elevate the field of HBPC, and create a community of continuous growth and quality of care accountability. The LN recruits HBPC practices in waves of 9 to 10 practices. It currently comprises 38 HBPC practices that care for 58,000 patients across 25 states (approximately 26% of all patients receiving HBPC in the United States). In a Kickoff meeting, the HBPC practices in each wave are instructed in the basics of quality improvement, develop project aim statements and their first plan-do-study-act cycle, receive an introduction to the LN quality improvement software platform, and review plans for LN engagement. Each month, practices submit updates and receive real-time feedback on their quality improvement work. Monthly virtual workshops are held with all practices that include sharing results of a “1-minute survey” (a monthly 1-to 3-question survey sent to all LN participants on a topic relevant to HBPC practices), a didactic and discussion related to the 1-minute survey topic, and interactive progress updates from LN participants regarding their quality improvement work. Each wave ends with “Moving-up Day,” where practices report on their overall project and reflect on how their practice has changed as a result of the LN. LN practices have addressed and improved performance in multiple HBPC-related quality areas including assessment of functional status and cognitive impairment, falls prevention, advanced care planning, COVID-19 vaccination, and others. We present case studies of 3 LN practices and how LN participation strengthened their practices.     

地方医学院校课程质量监控体系的构建探索

基于国家深化高等院校课程建设的新时代视域，提升课程质量成为高校教育教学发展的重要任务。地方医学院校作为基层卫生人才的培养摇篮，构建科学合理的课程质量监控体系愈发迫切。本文分析了我国高等院校课程质量监控体系存在的问题，结合地方医学院校办学特点和广州医科大学工作实践，探索构建了集“多样化监控方法、全维度监控指标、闭环式反馈机制、多层级文化建设”为一体的课程质量监控体系，为同类院校提供实际参考。     

多元化联合教学模式在超声引导下疼痛介入治疗中的应用

目的探讨多元化联合教学模式在超声引导下疼痛介入治疗教学中的应用效果。方法选择2018年1月至2020年12月在北京大学第三医院疼痛科进修的30名医师作为研究对象,将其分为对照组与观察组;对照组采用常规教学模式;观察组采用多元化联合教学模式,比较两组医师技能考核成绩、教学质量评分和满意度评分。结果观察组医师技能考核成绩优良率为93.3%,高于对照组的73.3%(P<0.05);观察组医师对基础理论知识掌握、临床思维能力的提高、学习兴趣的激发、疾病诊治能力的提高4个方面的评分均高于对照组(P<0.01)。结论多元化联合教学模式可促进超声引导下疼痛介入治疗技能的提高,有利于提高学员的综合临床能力。