propensity score weighting

倾向得分加权
  • 文章类型: Journal Article
    医疗保险和医疗补助服务中心严重败血症和败血症休克管理捆绑(SEP-1)评估抗生素管理,乳酸测量,严重脓毒症发病3小时内血培养采集。SEP-13小时束在严重脓毒症患者中的影响尚未广泛描述。本研究旨在描述3小时集束化依从性对严重脓毒症患者28天住院死亡率的影响。
    这是一个回顾,倾向调整,巢式病例对照研究评估严重脓毒症患者3小时脓毒症集束化依从性的影响.
    这项研究是在很大程度上进行的,学术,底特律三级医疗中心,密歇根州从2017年7月1日到2019年12月31日。
    病例定义为28天住院死亡率。对照定义为在28天存活或出院的那些。根据3小时集束化依从性或不依从性将患者分开。评估嵌套和总体队列。手动验证严重脓毒症时间零点。休克患者,在时间零点的8小时内需要血管升压药,或不符合SEP-1纳入标准的患者被排除.
    主要结果是3小时集束化依从性患者与不依从性患者中28天住院死亡率的倾向调整几率。次要结果包括个体束元素依从性的死亡率,进展为感染性休克,和根据逻辑回归的死亡率预测因素。
    共纳入了325例依从性和325例非依从性患者。每组的中位序贯器官衰竭评估(SOFA)评分为3分。在3小时集束疗法(比值比[OR]1.039;95%CI:0.721-1.497;p=0.838)或个别集束疗法中,依从者与不依从者的倾向调整死亡率差异无统计学意义。SOFA评分和女性性别是死亡率的预测因素。
    严重脓毒症患者3小时集束化依从性不影响28天住院死亡率。需要进一步的研究来了解3小时集束化依从性对严重脓毒症死亡率的影响。
    The Centers for Medicare and Medicaid Services Severe Sepsis and Septic Shock Management Bundle (SEP-1) assesses antibiotic administration, lactate measurement, and blood culture collection within 3 h of severe sepsis onset. The impact of the SEP-1 3-hour bundle among patients with severe sepsis is not extensively described. This investigation aimed to describe the impact of 3-hour bundle compliance on 28-day in-hospital mortality in patients with severe sepsis.
    This was a retrospective, propensity adjusted, nested case-control study assessing the impact of compliance with a 3-hour sepsis bundle among patients with severe sepsis.
    This study was conducted at a large, academic, tertiary care medical center in Detroit, Michigan from July 1, 2017 to December 31, 2019.
    Cases were defined as those suffering 28-day in-hospital mortality. Controls were defined as those surviving at or discharged by 28 days. Patients were separated based on 3-hour bundle compliance or noncompliance. Nested and overall cohorts were assessed. Severe sepsis time zero was manually validated. Patients with shock, requiring vasopressors within 8 h of time zero, or those not meeting SEP-1 inclusion criteria were excluded.
    The primary outcome was the propensity adjusted odds of 28-day in-hospital mortality among 3-hour bundle compliant versus noncompliant patients. Secondary outcomes included mortality for individual bundle element compliance, progression to septic shock, and predictors of mortality according to logistic regression.
    A total of 325 compliant and 325 noncompliant patients were included. The median Sequential Organ Failure Assessment (SOFA) score was three in each group. There was no difference in propensity adjusted odds of mortality among those compliant versus noncompliant with the 3-hour bundle (odds-ratio [OR] 1.039; 95% CI: 0.721-1.497; p = 0.838) or with individual bundle elements. SOFA score and female sex were predictors of mortality.
    Three-hour bundle compliance did not impact 28-day in-hospital mortality in patients with severe sepsis. Further research is needed to understand the impact of 3-hour bundle compliance on mortality in severe sepsis.
    导出

    更多引用

    收藏

    翻译标题摘要

    我要上传

    求助全文

  • 文章类型: Journal Article
    Propensity score methods are increasingly being used in the infectious diseases literature to estimate causal effects from observational data. However, there remains a general gap in understanding among clinicians on how to critically review observational studies that have incorporated these analytic techniques.
    Using a cohort of 4967 unique patients with Enterobacterales bloodstream infections, we sought to answer the question \"Does transitioning patients with gram-negative bloodstream infections from intravenous to oral therapy impact 30-day mortality?\" We conducted separate analyses using traditional multivariable logistic regression, propensity score matching, propensity score inverse probability of treatment weighting, and propensity score stratification using this clinical question as a case study to guide the reader through (1) the pros and cons of each approach, (2) the general steps of each approach, and (3) the interpretation of the results of each approach.
    2161 patients met eligibility criteria with 876 (41%) transitioned to oral therapy while 1285 (59%) remained on intravenous therapy. After repeating the analysis using the 4 aforementioned methods, we found that the odds ratios were broadly similar, ranging from 0.84-0.95. However, there were some relevant differences between the interpretations of the findings of each approach.
    Propensity score analysis is overall a more favorable approach than traditional regression analysis when estimating causal effects using observational data. However, as with all analytic methods using observational data, residual confounding will remain; only variables that are measured can be accounted for. Moreover, propensity score analysis does not compensate for poor study design or questionable data accuracy.
    导出

    更多引用

    收藏

    翻译标题摘要

    我要上传

       PDF(Sci-hub)

       PDF(Pubmed)

公众号