The influence of corticosteroid treatment on the outcome of influenza A(H1N1pdm09)-related critical illness.

The influence of corticosteroid treatment on the outcome of influenza A(H1N1pdm09)-related critical illness.
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皮质类固醇治疗对流感A(H1N1PDM09)相关的重症疾病结果的影响。

DOI:
10.1186/s13054-016-1230-8
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发表时间:
2016-03-30
期刊:
Critical care (London, England)
影响因子:
--
通讯作者:
Canadian Critical Care Trials Group H1N1 Collaborative
Canadian Critical Care Trials Group H1N1 Collaborative
中科院分区:
其他
文献类型:
--
作者:
Delaney JW;Pinto R;Long J;Lamontagne F;Adhikari NK;Kumar A;Marshall JC;Cook DJ;Jouvet P;Ferguson ND;Griesdale D;Burry LD;Burns KE;Hutchison J;Mehta S;Menon K;Fowler RA;Canadian Critical Care Trials Group H1N1 Collaborative

文献摘要

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2009年甲型流感大流行(H1N1pdm09)相关危重疾病的患者经常接受全身皮质类固醇治疗。虽然观察性研究报告了在对是否接受皮质类固醇治疗的患者的基线差异进行调整后与皮质类固醇相关的显著死亡率,但在随后的流感暴发中,包括甲型禽流感(H7N9),皮质类固醇仍然是一种常见的治疗方法。我们的目标是描述在这些患者中使用皮质类固醇的情况,并调查类固醇处方和临床结果的预测因素,调整基线和时间依赖因素。在对来自51个加拿大ICU的患有H1N1pdm09相关危重疾病的成年人进行的观察性队列研究中,我们调查了类固醇治疗的预测因素以及接受和未接受皮质类固醇治疗的患者的结果。我们使用多变量Logistic回归和倾向分数分析调整了潜在的基线混杂,并使用边际结构模型调整了潜在的时间相关混杂。在607名患者中,280名患者(46.1%)服用了皮质类固醇,每天的中位数剂量为227(四分位数范围,154-443)毫克氢化可的松当量,中位数为7.0(4.0-13.0)天。与未接受激素治疗的患者相比,接受激素治疗的患者在28天的住院粗死亡率(25.5%比16.4%,p = 0.007)更高,无呼吸机天数更少(12.5 ± 10.7vs15.7 ± 10.1,p < 0.001)。经多因素Logistic回归分析,激素使用与住院死亡率的比值比从1.85(95%可信区间1.12~3.04,p = 0.02)降至调整使用激素倾向得分后的1.71(1.05~2.78,p = 0.03),经病例匹配后降至1.52(0.90~2.58,p = 0.12),经病例匹配后降至0.96(0.28~3.28,P = 0.95)使用边际结构模型对随时间变化的组间差异进行调整。皮质类固醇通常用于H1N1pdm09相关危重疾病的处方。仅对基线组间差异进行调整表明,与皮质类固醇相关的死亡风险显著增加。然而,在调整了与时间相关的差异后,我们发现皮质类固醇和死亡率之间没有显著的相关性。这些发现突显了在使用观察性研究评估治疗的临床效果时,调整基线和时间相关混杂因素的挑战和重要性。本文的在线版本(doi:10.1186/s13054-016-1230-8)包含补充材料,授权用户可以使用。
Patients with 2009 pandemic influenza A(H1N1pdm09)-related critical illness were frequently treated with systemic corticosteroids. While observational studies have reported significant corticosteroid-associated mortality after adjusting for baseline differences in patients treated with corticosteroids or not, corticosteroids have remained a common treatment in subsequent influenza outbreaks, including avian influenza A(H7N9). Our objective was to describe the use of corticosteroids in these patients and investigate predictors of steroid prescription and clinical outcomes, adjusting for both baseline and time-dependent factors. In an observational cohort study of adults with H1N1pdm09-related critical illness from 51 Canadian ICUs, we investigated predictors of steroid administration and outcomes of patients who received and those who did not receive corticosteroids. We adjusted for potential baseline confounding using multivariate logistic regression and propensity score analysis and adjusted for potential time-dependent confounding using marginal structural models. Among 607 patients, corticosteroids were administered to 280 patients (46.1 %) at a median daily dose of 227 (interquartile range, 154–443) mg of hydrocortisone equivalents for a median of 7.0 (4.0–13.0) days. Compared with patients who did not receive corticosteroids, patients who received corticosteroids had higher hospital crude mortality (25.5 % vs 16.4 %, p = 0.007) and fewer ventilator-free days at 28 days (12.5 ± 10.7 vs 15.7 ± 10.1, p < 0.001). The odds ratio association between corticosteroid use and hospital mortality decreased from 1.85 (95 % confidence interval 1.12–3.04, p = 0.02) with multivariate logistic regression, to 1.71 (1.05–2.78, p = 0.03) after adjustment for propensity score to receive corticosteroids, to 1.52 (0.90–2.58, p = 0.12) after case-matching on propensity score, and to 0.96 (0.28–3.28, p = 0.95) using marginal structural modeling to adjust for time-dependent between-group differences. Corticosteroids were commonly prescribed for H1N1pdm09-related critical illness. Adjusting for only baseline between-group differences suggested a significant increased risk of death associated with corticosteroids. However, after adjusting for time-dependent differences, we found no significant association between corticosteroids and mortality. These findings highlight the challenges and importance in adjusting for baseline and time-dependent confounders when estimating clinical effects of treatments using observational studies. The online version of this article (doi:10.1186/s13054-016-1230-8) contains supplementary material, which is available to authorized users.