Evaluation of a fast-and-frugal clinical decision algorithm ('pathways') on clinical outcomes in hospitalised patients with COVID-19 treated with anticoagulants.

Evaluation of a fast-and-frugal clinical decision algorithm ('pathways') on clinical outcomes in hospitalised patients with COVID-19 treated with anticoagulants.
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DOI:
10.1111/jep.13780
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发表时间:
2023-03
影响因子:
2.4
通讯作者:
Guyatt, Gordon
Guyatt, Gordon
中科院分区:
医学4区
文献类型:
--
作者:
Djulbegovic, Benjamin;Hozo, Iztok;Lizarraga, David;Thomas, Joseph;Barbee, Michael;Shah, Nupur;Rubeor, Tyler;Dale, Jordan;Reiser, Jochen;Guyatt, Gordon

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批评者指责循证医学(EBM)过分强调算法规则而不是非结构化的临床经验和直觉,但结构化决策支持系统在改善健康结果方面的作用仍然不确定。我们的目的是评估根据基于循证临床实践指南(CPG)的算法,与个别执业医师自行决定给予的抗凝治疗相比,对住院的 COVID-19 患者进行抗凝预防是否可以改善临床结果。一项观察性设计,包括对 2020 年 3 月 10 日至 2022 年 1 月 11 日期间入住美国学术中心的所有确诊为 COVID-19 的连续急性患者 (n = 1783) 进行分析。美国血液学会针对住院的 COVID-19 患者进行抗凝预防的 CPG 已转化为临床路径,并转化为快速节俭决策 (FFT) 树(“算法”)。我们比较了根据 FFT 算法对住院的 COVID-19 患者进行抗凝预防治疗与根据个体执业医师酌情给予的抗凝治疗。在一项调整分析中,结合使用 Lasso(最小绝对收缩和选择算子)和基于倾向评分的加权 [增强逆概率加权] 统计技术来控制聚类数据,该算法并没有减少死亡、静脉血栓栓塞或大出血,但有助于避免更长的住院时间 [需要治疗的患者数量 (NNT) = 40 (95% CI: 23–143),表明对于每个40 名患者 (23–143) 采用 FFT 算法进行管理,其中一名患者避免住院超过 10 天],并避免住进重症监护病房 (ICU) [NNT = 19 (95% CI: 13–40)]。所有模型选择的协变量都得到了很好的平衡。结果对于用于测试结果稳定性的敏感性分析仍然稳健。当使用结构化 FFT 算法进行分娩时,CPG 缩短了住院时间并有助于避免入住 ICU,但它并没有影响其他相关结果。
Critics have charged that evidence‐based medicine (EBM) overemphasises algorithmic rules over unstructured clinical experience and intuition, but the role of structured decision support systems in improving health outcomes remains uncertain. We aim to assess if delivery of anticoagulant prophylaxis in hospitalised patients with COVID‐19 according to an algorithm based on evidence‐based clinical practice guideline (CPG) improved clinical outcomes compared with administration of anticoagulant treatment given at individual practitioners' discretion. An observational design consisting of the analysis of all acutely ill, consecutive patients (n = 1783) with confirmed COVID‐19 diagnosis admitted between 10 March 2020 to 11 January 2022 to an US academic center. American Society of Haematology CPG for anticoagulant prophylaxis in hospitalised patients with COVID‐19 was converted into a clinical pathway and translated into fast‐and‐frugal decision (FFT) tree (‘algorithm’). We compared delivery of anticoagulant prophylaxis in hospitalised patients with COVID‐19 according to the FFT algorithm with administration of anticoagulant treatment given at individual practitioners' discretion. In an adjusted analysis, using combination of Lasso (least absolute shrinkage and selection operator) and propensity score based weighting [augmented inverse‐probability weighting] statistical techniques controlling for cluster data, the algorithm did not reduce death, venous thromboembolism, or major bleeding, but helped avoid longer hospital stay [number of patients needed to be treated (NNT) = 40 (95% CI: 23–143), indicating that for every 40 patients (23–143) managed on FFT algorithm, one avoided staying in hospital longer than 10 days] and averted admission to intensive‐care unit (ICU) [NNT = 19 (95% CI: 13–40)]. All model's selected covariates were well balanced. The results remained robust to sensitivity analyses used to test the stability of the findings. When delivered using a structured FFT algorithm, CPG shortened the hospital stay and help avoided admission to ICU, but it did not affect other relevant outcomes.
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